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1. Black carbon and dust alter the response of mountain snow cover under climate change

Author: Marion Réveillet, Marie Dumont, Simon Gascoin, Matthieu Lafaysse, Pierre Nabat, Aurélien Ribes, Rafife Nheili, Francois Tuzet, Martin Ménégoz, Samuel Morin, Ghislain Picard, and Paul Ginoux
Subjects: Science
Abstract: Black carbon and dust deposition advanced the end of the snow season by 17 days on average over the last 40 years in the French Alps and the Pyrenees. The warming-induced snow cover decline was partly offset by decreases in black carbon deposition observed since the 1980s.
Published: 2022
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2. Sensitivity of Glaciers in the European Alps to Anthropogenic Atmospheric Forcings: Case Study of the Argentière Glacier

Author: Léo Clauzel, Martin Ménégoz, Adrien Gilbert, Olivier Gagliardini, Delphine Six, Guillaume Gastineau, and Christian Vincent
Subjects: glacier modeling, climate forcings, detection‐attribution, time of emergence, statistical adjustment, Geophysics. Cosmic physics, QC801-809
Abstract: Abstract This study aims to quantify the contribution of anthropogenic forcings on the retreat of the Argentière Glacier (European Alps). The glacier evolution is simulated over 1850–2014 following retrospective scenarios produced with the IPSL‐CM6‐LR climate model, with and without natural and anthropogenic forcings. The scenarios used to force an ice flow model are statistically downscaled, preserving the long‐term trends and the physical consistency between precipitation and temperature. Since the late 19th century, the regional aerosol cooling has partially counteracted the greenhouse gas‐induced warming, delaying the time of emergence of the anthropogenic signal. The anthropogenic signal emerged from natural variability in 1979 for temperature and surface melting, and in 2008 for the glacier mass, whereas its snout position in 2014 remains compatible with natural variability. From the total mass loss between 1850 and 2014, 66% [21%–111%] is attributed to anthropogenic activities.
Published: 2023
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3. Reanalysing the 2007–19 glaciological mass-balance series of Mera Glacier, Nepal, Central Himalaya, using geodetic mass balance

Author: Patrick Wagnon, Fanny Brun, Arbindra Khadka, Etienne Berthier, Dibas Shrestha, Christian Vincent, Yves Arnaud, Delphine Six, Amaury Dehecq, Martin Ménégoz, and Vincent Jomelli
Subjects: Glacier mass balance, glacier monitoring, mountain glaciers, Environmental sciences, GE1-350, Meteorology. Climatology, QC851-999
Abstract: The 2007–19 glaciological mass-balance series of Mera Glacier in the Everest Region, East Nepal, is reanalysed using the geodetic mass balance assessed by differencing two DEMs obtained from Pléiades stereo-images acquired in November 2012 and in October 2018. The glaciological glacier-wide annual mass balance of Mera Glacier has to be systematically decreased by 0.11 m w.e. a−1 to match the geodetic mass balance. We attribute part of the positive bias of the glaciological mass balance to an over-estimation of the accumulation above 5520 m a.s.l., likely due to a measurement network unable to capture its spatial variability. Over the period 2007–19, Mera Glacier has lost mass at a rate of −0.41 ± 0.20 m w.e. a−1, in general agreement with regional averages for the central Himalaya. We observe a succession of negative mass-balance years since 2013.
Published: 2021
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4. Improved Near‐Surface Continental Climate in IPSL‐CM6A‐LR by Combined Evolutions of Atmospheric and Land Surface Physics

Author: Frédérique Cheruy, Agnès Ducharne, Frédéric Hourdin, Ionela Musat, Étienne Vignon, Guillaume Gastineau, Vladislav Bastrikov, Nicolas Vuichard, Binta Diallo, Jean‐Louis Dufresne, Josefine Ghattas, Jean‐Yves Grandpeix, Abderrahmane Idelkadi, Lidia Mellul, Fabienne Maignan, Martin Ménégoz, Catherine Ottlé, Philippe Peylin, Jérôme Servonnat, Fuxing Wang, and Yanfeng Zhao
Subjects: climate modelling, atmosphere‐land surface interactions, stable boundary layer, hydrology, soil moisture, temperature bias, Physical geography, GB3-5030, Oceanography, GC1-1581
Abstract: Abstract This work is motivated by the identification of the land‐atmosphere interactions as one of the key sources of uncertainty in climate change simulations. It documents new developments in related processes, namely, boundary layer/convection/clouds parameterizations and land surface parameterization in the Earth System Model of the Institut Pierre Simon Laplace (IPSL). Simulations forced by prescribed oceanic conditions are produced with different combinations of atmospheric and land surface parameterizations. They are used to explore the sensitivity to the atmospheric physics and/or soil physics of major biases in the near surface variables over continents, the energy and moisture coupling established at the soil/atmosphere interface in not too wet (energy limited) and not too dry (moisture limited) soil moisture regions also known as transition or “hot‐spot” regions, the river runoff at the outlet of major rivers. The package implemented in the IPSL‐Climate Model for the Phase 6 of the Coupled Models Intercomparison Project (CMIP6) allows us to reduce several biases in the surface albedo, the snow cover, and the continental surface air temperature in summer as well as in the temperature profile in the surface layer of the polar regions. The interactions between soil moisture and atmosphere in hotspot regions are in better agreement with the observations. Rainfall is also significantly improved in volume and seasonality in several major river basins leading to an overall improvement in river discharge. However, the lack of consideration of floodplains and human influences in the model, for example, dams and irrigation, impacts the realism of simulated discharge.
Published: 2020
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5. On the observed connection between Arctic sea ice and Eurasian snow in relation to the winter North Atlantic Oscillation

Author: María Santolaria-Otín, Javier García-Serrano, Martin Ménégoz, and Joan Bech
Subjects: North Atlantic Oscillation, teleconnection, sea ice, snow cover, Environmental technology. Sanitary engineering, TD1-1066, Environmental sciences, GE1-350, Science, Physics, QC1-999
Abstract: Sea ice concentration (SIC) in the eastern Arctic and snow cover extent (SCE) over central Eurasia in late autumn have been proposed as potential predictors of the winter North Atlantic Oscillation (NAO). Here, maximum covariance analysis is used to further investigate the links between autumn SIC in the Barents-Kara Seas (BK) and SCE over Eurasia (EUR) with winter sea level pressure (SLP) in the North Atlantic-European region over 1979-2019. As shown by previous studies, the most significant covariability mode of SIC/BK is found for November. Similarly, the covariability with SCE/EUR is only statistically significant for November, not for October. Changes in temperature, specific humidity, SIC/BK and SCE/EUR in November are associated with a circulation anomaly over the Ural-Siberian region that appears as a precursor of the winter NAO; where the advection of climatological temperature/humidity by the anomalous flow is related to SCE/EUR and SIC/BK anomalies.
Published: 2021
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6. An R package for climate forecast verification.

Author: Nicolau Manubens, Louis-Philippe Caron, Alasdair Hunter, Omar Bellprat, Eleftheria Exarchou, Neven S. Fuckar, Javier Garcia-Serrano, François Massonnet, Martin Ménégoz, Valentina Sicardi, Lauriane Batté, Chloé Prodhomme, Verónica Torralba, Nicola Cortesi, Oriol Mula-Valls, Kim Serradell, Virginie Guemas, and Francisco J. Doblas-Reyes
Published: 2018
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7. Supplementary material to 'Simulating one century (1902–2009) of river discharges, low flow sequences and flood events of an alpine river from large-scale atmospheric information'

Author: Caroline Legrand, Benoît Hingray, Bruno Wilhelm, and Martin Ménégoz
Published: 2023

8. Sensitivity of Alpine glaciers to anthropogenic atmospheric forcings: case study of the Argentière glacier

Author: Clauzel, Léo, Gilbert, Adrien, Martin, Ménégoz, Gagliardini, Olivier, Six, Delphine, Gastineau, Guillaume, Institut des Géosciences de l’Environnement (IGE), Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), Océan et variabilité du climat (VARCLIM), Laboratoire d'Océanographie et du Climat : Expérimentations et Approches Numériques (LOCEAN), Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité)-Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), ANR-18-CE01-0015,SAUSSURE,Glissement des glaciers et pression hydrologique sous glaciaire en relat(2018), Menegoz, Martin, and APPEL À PROJETS GÉNÉRIQUE 2018 - Glissement des glaciers et pression hydrologique sous glaciaire en relat - - SAUSSURE2018 - ANR-18-CE01-0015 - AAPG2018 - VALID
Subjects: [SDE] Environmental Sciences, [SDE]Environmental Sciences
Abstract: This study aims at quantifying the contribution of external climate forcings on the retreat of the Argentière glacier (Mont-Blanc area). Its evolution is simulated over 1850-2014 following retrospective scenarios produced with the IPSL-CM6-LR climate model, excluding and including natural and anthropogenic forcings. These scenarios are statistically adjusted at the local scale, ensuring a preservation of the long-term trends and a physical consistency between precipitation and temperature, to finally force an ice flow model coupled with a surface mass balance scheme. The regional aerosol cooling partly counteracted the greenhouse gases warming, delaying the time of emergence of anthropogenic signals: The anthropogenic influences emerged from the natural variability in 1979 for temperature and in 2008 for the mass of the glacier, whereas its snout position in 2014 remains compatible with natural variability. We found that 66% [20-112%] of the total mass loss in 2014 since 1850 can be attributed to anthropogenic activities.
Published: 2022

9. Impact of climate change on wintertime persistent inversions in the Grenoble valley during the 21st century

Author: Sara Bacer, Julien Beaumet, Enzo Le Bouëdec, Martin Ménégoz, Hubert Gallée, and Chantal Staquet
Abstract: When anticyclonic conditions persist over mountainous regions, inversion layers can develop in the valleys and persist from a few days to a few weeks, especially in winter. During inversion episodes, the atmosphere inside the valley is stable and vertical mixing is prevented, promoting the accumulation of pollutants below the inversion layer and affecting the air quality of the valley.Mountainous areas are experiencing a warming rate twice stronger than the global atmospheric temperature, thus, they are particularly sensitive to climate change. In the 21st century, the valley circulation will undergo unknown modifications due to climate change, and this concerns also the fate of wintertime persistent inversions, which could be reinforced or weakened with consequences on pollutant trapping.This work addresses the issue of climate change impact on persistent inversions in the Grenoble valley, which is the most populated city in the Alps. The long-term projections of the regional climate model MAR (Modéle Atmosphérique Régional) forced by the global climate model MPI (developed by the Max Planck Institute) are first used to perform a statistical study of the inversions over the 21st century. The main characteristics of the inversions, e.g. duration, frequency, intensity, and their trends, are investigated for two different scenarios (SSP2-4.5 and SSP5-8.5). The intensity and the frequency of the inversions show a statistically significant decreasing trend in the 21st century for the worst-case scenario.The detailed structure of the inversion (atmospheric circulation, vertical temperature profiles, and inversion top) is next investigated by comparing two persistent episodes in the past and around 2050. For this purpose, the WRF (Weather Research and Forecasting) model, forced by MAR, is used at high resolution (111 m). In order to perform a fair comparison of the episodes, and given the influence of the orography on the valley circulation, the episodes are selected in such a way to satisfy common large-scale characteristics of a wintertime anticyclonic regime over Grenoble.
Published: 2022

10. Contrasting seasonal changes in total and intense precipitation in the European Alps from 1903 to 2010

Author: Juliette Blanchet, Samuel Morin, Julien Beaumet, Sandrine Anquetin, Nicolas C. Jourdain, Evgenia Valla, Hubert Gallée, Xavier Fettweis, Martin Ménégoz, Bruno Wilhelm, Institut des Géosciences de l’Environnement (IGE), Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), and Université Grenoble Alpes (UGA)
Subjects: 010504 meteorology & atmospheric sciences, 0208 environmental biotechnology, High resolution, 02 engineering and technology, Forcing (mathematics), 01 natural sciences, lcsh:Technology, lcsh:TD1-1066, Vertical gradient, Precipitation, lcsh:Environmental technology. Sanitary engineering, lcsh:Environmental sciences, 0105 earth and related environmental sciences, lcsh:GE1-350, lcsh:T, lcsh:Geography. Anthropology. Recreation, 020801 environmental engineering, lcsh:G, 13. Climate action, Climatology, [SDE]Environmental Sciences, Period (geology), Environmental science, Spatial variability, Climate model, Seasonal cycle
Abstract: Changes in precipitation over the European Alps are investigated with the regional climate model MAR (Modèle Atmosphérique Régional) applied with a 7 km resolution over the period 1903–2010 using the reanalysis ERA-20C as forcing. A comparison with several observational datasets demonstrates that the model is able to reproduce the climatology as well as both the interannual variability and the seasonal cycle of precipitation over the European Alps. The relatively high resolution allows us to estimate precipitation at high elevations. The vertical gradient of precipitation simulated by MAR over the European Alps reaches 33% km−1 (1.21 mm d−1 km−1) in summer and 38 % km−1 (1.15 mm d−1 km−1) in winter, on average, over 1971–2008 and shows a large spatial variability. A significant (p value < 0.05) increase in mean winter precipitation is simulated in the northwestern Alps over 1903–2010, with changes typically reaching 20 % to 40 % per century. This increase is mainly explained by a stronger simple daily intensity index (SDII) and is associated with less-frequent but longer wet spells. A general drying is found in summer over the same period, exceeding 20 % to 30 % per century in the western plains and 40 % to 50 % per century in the southern plains surrounding the Alps but remaining much smaller ( %) and not significant above 1500 m a.s.l. Below this level, the summer drying is explained by a reduction in the number of wet days, reaching 20 % per century over the northwestern part of the Alps and 30 % to 50 % per century in the southern part of the Alps. It is associated with shorter but more-frequent wet spells. The centennial trends are modulated over the last decades, with the drying occurring in the plains in winter also affecting high-altitude areas during this season and with a positive trend of autumn precipitation occurring only over the last decades all over the Alps. Maximum daily precipitation index (Rx1day) takes its highest values in autumn in both the western and the eastern parts of the southern Alps, locally reaching 50 to 70 mm d−1 on average over 1903–2010. Centennial maxima up to 250 to 300 mm d−1 are simulated in the southern Alps, in France and Italy, as well as in the Ticino valley in Switzerland. Over 1903–2010, seasonal Rx1day shows a general and significant increase at the annual timescale and also during the four seasons, reaching local values between 20 % and 40 % per century over large parts of the Alps and the Apennines. Trends of Rx1day are significant (p value < 0.05) only when considering long time series, typically 50 to 80 years depending on the area considered. Some of these trends are nonetheless significant when computed over 1970–2010, suggesting a recent acceleration of the increase in extreme precipitation, whereas earlier periods with strong precipitation also occurred, in particular during the 1950s and 1960s.
Published: 2020

11. Sensitivity of Alpine glaciers to anthropogenic atmospheric forcings

Author: Léo Clauzel, Adrien Gilbert, Martin Ménégoz, and Olivier Gagliardini
Abstract: European Alpine glaciers have strongly shrunk over the last 150 years in response to climate warming. Glacier retreat is expected to persist and even intensify in future projections. This work aims at evaluating how much of the glacier retreat can be attributed to anthropogenic atmospheric forcings. For this purpose, we quantify the evolution of the Argentière glacier in the Mont Blanc area under different climate reconstructions over the period 1850-present. The different reconstructions are extracted from 4 ensemble experiments conducted with the IPSL-CM6-LR General Circulation Model (GCM), excluding and including natural and anthropogenic atmospheric forcings. These 6-member experiments are statistically corrected and downscaled with a quantile mapping approach that ensures consistent long term tendencies and precipitation-temperature relationship. These data feed a three-dimensional ice flow model coupled with a surface mass balance model to simulate changes in the glacier geometry over time. Over 1850-2014, historical simulations show a significant warming whereas there is no clear trend of precipitation at the annual scale. The glacier appears to be highly sensitive to individual anthropogenic forcings, with a glacier volume loss around 45% in the greenhouse gases-only experiment and a growth of about 5% in the aerosols-only experiment in 2014 relative to 1850, compared to the 32% volume loss over the same period in the historical experiment. Moreover, the natural-only experiment reveals the great impact of anthropogenic forcings with a much lower volume loss of about 10%. The latter also confirms that the end of the Little Ice Age would have occurred even without human activities. Finally, the simulations highlight a strong influence of natural internal variability and show that Argentiere Glacier definitively left its possible natural pathway only during the last decade.
Published: 2022

12. Replicability of the EC-Earth3 Earth system model under a change in computing environment

Author: Xavier Yepes-Arbós, Martin Ménégoz, Mario Acosta, Eleftheria Exarchou, Francisco J. Doblas-Reyes, François Massonnet, Institut des Géosciences de l’Environnement (IGE), Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), Universitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors, Barcelona Supercomputing Center, and UCL - SST/ELI/ELIC - Earth & Climate
Subjects: Canvis climàtics -- Models matemàtics, 010504 meteorology & atmospheric sciences, Computer science, River runoff, Matemàtiques i estadística::Matemàtica aplicada a les ciències [Àrees temàtiques de la UPC], 02 engineering and technology, 010103 numerical & computational mathematics, Porting, 01 natural sciences, Replicability, 0202 electrical engineering, electronic engineering, information engineering, Earth System Model, Earth system model, 0101 mathematics, Astrophysics::Galaxy Astrophysics, 0105 earth and related environmental sciences, Weather forecasting -- Mathematical models, Desenvolupament humà i sostenible::Degradació ambiental::Canvi climàtic [Àrees temàtiques de la UPC], lcsh:QE1-996.5, Contrast (statistics), 020207 software engineering, Climatic changes -- Mathematical models, Data science, HPC computing, Term (time), Earth system science, lcsh:Geology, Previsió del temps -- Models matemàtics, 13. Climate action, [SDE]Environmental Sciences, High performance computing, Càlcul intensiu (Informàtica)
Abstract: Most Earth system models (ESMs) are running under different high-performance computing (HPC) environments. This has several advantages, from allowing different groups to work with the same tool in parallel to leveraging the burden of ensemble climate simulations, but it also offers alternative solutions in the case of shutdown (expected or not) of any of the environments. However, for obvious scientific reasons, it is critical to ensure that ESMs provide identical results under changes in computing environment. While strict bit-for-bit reproducibility is not always guaranteed with ESMs, it is desirable that results obtained under one computing environment are at least statistically indistinguishable from those obtained under another environment, which we term a “replicability” condition following the metrology nomenclature. Here, we develop a protocol to assess the replicability of the EC-Earth ESM. Using two versions of EC-Earth, we present one case of non-replicability and one case of replicability. The non-replicable case occurs with the older version of the model and likely finds its origin in the treatment of river runoff along Antarctic coasts. By contrast, the more recent version of the model provides replicable results. The methodology presented here has been adopted as a standard test by the EC-Earth consortium (27 institutions in Europe) to evaluate the replicability of any new model version across platforms, including for CMIP6 experiments. To a larger extent, it can be used to assess whether other ESMs can safely be ported from one HPC environment to another for studying climate-related questions. Our results and experience with this work suggest that the default assumption should be that ESMs are not replicable under changes in the HPC environment, until proven otherwise. This research has been supported by the EU Commission – H2020 (grant nos. 727862: APPLICATE, 312979: IS-ENES2, 675191: ESiWACE, and 641727: PRIMAVERA) and the Spanish Ministerio de Economía y Competitividad (MINECO) (grant no. CGL2015-70353-R: HIATUS).
Published: 2020

13. Climate change in the High Mountain Asia in CMIP6

Author: Martin Ménégoz, Gerhard Krinner, Mickaël Lalande, Kathrin Naegeli, Stefan Wunderle, Institut des Géosciences de l’Environnement (IGE), Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Institut de Recherche pour le Développement (IRD)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), Oeschger Centre for Climate Change Research (OCCR), University of Bern, and Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )
Subjects: 010504 meteorology & atmospheric sciences, Science, 0207 environmental engineering, Climate change, QE500-639.5, 02 engineering and technology, Atmospheric sciences, 01 natural sciences, High mountain, Precipitation, 910 Geography & travel, 020701 environmental engineering, 550 Earth sciences & geology, 0105 earth and related environmental sciences, Coupled model intercomparison project, geography, QE1-996.5, Plateau, geography.geographical_feature_category, Elevation, Northern Hemisphere, Cru, Geology, Dynamic and structural geology, 13. Climate action, [SDE]Environmental Sciences, General Earth and Planetary Sciences, Environmental science
Abstract: Climate change over High Mountain Asia (HMA, including the Tibetan Plateau) is investigated over the period 1979–2014 and in future projections following the four Shared Socioeconomic Pathways: SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5. The skill of 26 Coupled Model Intercomparison Project phase 6 (CMIP6) models is estimated for near-surface air temperature, snow cover extent and total precipitation, and 10 of them are used to describe their projections until 2100. Similarly to previous CMIP models, this new generation of general circulation models (GCMs) shows a mean cold bias over this area reaching −1.9 [−8.2 to 2.9] ∘C (90 % confidence interval) in comparison with the Climate Research Unit (CRU) observational dataset, associated with a snow cover mean overestimation of 12 % [−13 % to 43 %], corresponding to a relative bias of 52 % [−53 % to 183 %] in comparison with the NOAA Climate Data Record (CDR) satellite dataset. The temperature and snow cover model biases are more pronounced in winter. Simulated precipitation rates are overestimated by 1.5 [0.3 to 2.9] mm d−1, corresponding to a relative bias of 143 % [31 % to 281 %], but this might be an apparent bias caused by the undercatch of solid precipitation in the APHRODITE (Asian Precipitation-Highly-Resolved Observational Data Integration Towards Evaluation of Water Resources) observational reference. For most models, the cold surface bias is associated with an overestimation of snow cover extent, but this relationship does not hold for all models, suggesting that the processes of the origin of the biases can differ from one model to another. A significant correlation between snow cover bias and surface elevation is found, and to a lesser extent between temperature bias and surface elevation, highlighting the model weaknesses at high elevation. The models with the best performance for temperature are not necessarily the most skillful for the other variables, and there is no clear relationship between model resolution and model skill. This highlights the need for a better understanding of the physical processes driving the climate in this complex topographic area, as well as for further parameterization developments adapted to such areas. A dependency of the simulated past trends on the model biases is found for some variables and seasons; however, some highly biased models fall within the range of observed trends, suggesting that model bias is not a robust criterion to discard models in trend analysis. The HMA median warming simulated over 2081–2100 with respect to 1995–2014 ranges from 1.9 [1.2 to 2.7] ∘C for SSP1-2.6 to 6.5 [4.9 to 9.0] ∘C for SSP5-8.5. This general warming is associated with a relative median snow cover extent decrease from −9.4 % [−16.4 % to −5.0 %] to −32.2 % [−49.1 % to −25.0 %] and a relative median precipitation increase from 8.5 % [4.8 % to 18.2 %] to 24.9 % [14.4 % to 48.1 %] by the end of the century in these respective scenarios. The warming is 11 % higher over HMA than over the other Northern Hemisphere continental surfaces, excluding the Arctic area. Seasonal temperature, snow cover and precipitation changes over HMA show a linear relationship with the global surface air temperature (GSAT), except for summer snow cover which shows a slower decrease at strong levels of GSAT.
Published: 2021

14. Impact of climate change on wintertime European atmospheric blocking

Author: Fatima Jomaa, Martin Ménégoz, Enzo Le Bouëdec, Chantal Staquet, Hubert Gallée, Sara Bacer, Julien Beaumet, Laboratoire des Écoulements Géophysiques et Industriels [Grenoble] (LEGI), Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), Institut des Géosciences de l’Environnement (IGE), and Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )
Subjects: Coupled model intercomparison project, [SDU]Sciences of the Universe [physics], Atmospheric circulation, Climatology, [SDE]Environmental Sciences, Pressure increase, Climate change, Environmental science, Climate model, Blocking (statistics)
Abstract: We study the impact of climate change on wintertime atmospheric blocking over Europe focusing on the frequency, duration, and extension of blocking events. These events are identified via the weather type decomposition (WTD) methodology applied on the output of climate models of the Coupled Model Intercomparison Project phase 6 (CMIP6). Historical simulations as well as two future scenarios, SSP2-4.5 and SSP5-8.5, are considered. The models are evaluated against the reanalysis and only a subset of climate models, which better represent the blocking weather regime in the recent-past climate, is considered for the analysis. We find that frequency and duration of blocking events remain relatively stationary over the 21st century. In order to quantify the extension of blocking events, we define a new methodology which relies on the WTD to identify blocking events. We show that the results are in agreement with previous studies that define blocking events with blocking indexes. We find that blocking extension will increase, especially in the worst-case scenario, due to a pressure increase driven by a thermodynamical warming during blocking events rather than atmospheric circulation changes.
Published: 2021

15. Supplementary material to 'Impact of climate change on wintertime European atmospheric blocking'

Author: Sara Bacer, Fatima Jomaa, Julien Beaumet, Hubert Gallée, Enzo Le Bouëdec, Martin Ménégoz, and Chantal Staquet
Published: 2021

16. Un Institut Environnement - Société à l’UGAVers une pérennisation de la dynamique impulsée autour des études des trajectoires des socio-écosystèmes dans un contexte d’évolution climatique

Author: Anquetin, Sandrine, Buclet, Nicolas, Lavorel, Sandra, Bourdeau, Philippe, Eckert, Nicolas, Dalmasso, Anne, Georges-Marcelpoil, Emmanuelle, Giguet-Covex, Charline, Grosinger, Julia, Haenni, Catherine, Judet, Pierre-Marie, Lachello, Raphaël, Lutoff, Céline, Martin, Ménégoz, Prieur, Clémentine, Spiegelberger, Thomas, Reineking, Björn, Ruin, Isabelle, Thuiller, Wilfried, Ziébelin, Danielle, Institut des Géosciences de l’Environnement (IGE), Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), and Université Grenoble Alpes (UGA)
Subjects: [SDE.ES]Environmental Sciences/Environmental and Society
Abstract: Un Institut Environnement-Société à l'UGA Vers une pérennisation de la dynamique impulsée autour des études des trajectoires des socio-écosystèmes dans un contexte d'évolution climatique Document co-écrit par les membres du Comité de Pilotage du CDP TRAJECTORIES, complété de quelques chercheurs.
Published: 2021

17. Contrasting seasonal changes in temperature, precipitation and snow cover simulated over the European Alps during the twentieth century

Author: Sandrine Anquetin, Martin Ménégoz, Christian Vincent, Julien Beaumet, Juliette Blanchet, Nicolas C. Jourdain, Samuel Morin, Bruno Wilhelm, Xavier Fettweis, Delphine Six, Hubert Gallée, Institut des Géosciences de l’Environnement (IGE), Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), Fonds National de la Recherche Scientifique [Bruxelles] (FNRS), Centre national de recherches météorologiques (CNRM), and Météo France-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)
Subjects: [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology, 13. Climate action, Climatology, Environmental science, Precipitation, ComputingMilieux_MISCELLANEOUS, Snow cover
Abstract: The evolution of temperature, precipitation and snow cover in the European Alps have been simulated with the regional climate model MAR applied with a 7 kilometre horizontal resolution and driven by the ERA-20C (1902-2010) and the ERA5 reanalyses (1981-2018). A comparison with observational datasets, including French and Swiss local meteorological stations, in-situ glacier mass balance measurements and reanalysis product demonstrates high model skill for snow cover duration and snow water equivalent (SWE) as well as for the climatology and the inter-annual variability of both temperature and precipitation. The relatively high resolution allows to estimate the meteorological variables up to 3000m.a.s.l. The vertical gradient of precipitation simulated by MAR over the European Alps reaches 33% km-1 (1.21 mmd-1.km-1) in summer and 38%km-1 (1.15mmd mmd-1.km-1) in winter, on average over 1971–2008 and shows a large spatial variability. This study evidences seasonal and altitudinal contrasts of climate trends over the Alps. A significant (pvalue< 0.05) increase in mean winter precipitation is simulated in the northwestern Alps over 1903–2010, with changes typically reaching 20% to 40% per century, a signal strongly modulated by multi-decadal variability during the second part of the century. A general drying is found in summer over the same period, exceeding 20% to 30% per century in the western plains and 40% to 50% per century in the southern plains surrounding the Alps but remaining smaller ( 2000 m a.s.l) in summer. In spring, warming trends show a maximum at intermediate elevations (1500 m to 1800 m). Our results suggest that higher warming at these elevations is mostly linked with the snow-albedo feedback in spring and summer.
Published: 2021

18. Modulation of the snow cover changes in the French Alps and the Pyrenees by the deposition of light absorbing particles over the last 40 years

Author: Simon Gascoin, Paul Ginoux, Matthieu Lafaysse, Marion Réveillet, François Tuzet, Rafife Nheili, Aurélien Ribes, Marie Dumont, Martin Ménégoz, and Pierre Nabat
Subjects: Modulation, Environmental science, Atmospheric sciences, Deposition (chemistry), Snow cover
Abstract: By darkening the snow surface, mineral dust and black carbon (BC) deposition accelerate snowmelt and triggers numerous feedbacks. Assessments of their long-term impact at the regional scale are still largely missing despite the environmental and socio-economic implications of snow cover changes. Using detailed snowpack simulations, we show that dust and BC deposition advance snowmelt by 17 days on average in the French Alps and the Pyrenees over the 1979-2018 period, with major implications for water availability and ground temperature. The effect of BC compared to dust is generally prevailing except in the Southern Pyrenees more exposed to Saharan dust events. We also quantify a contribution of BC and dust deposition up to 30% to the variance of the snow melt-out date. Lastly, we demonstrate that the decrease in BC deposition since the 80's alleviated the impact of current warming on snow cover decline. Therefore, this study highlights the importance of accounting for the inter-annual fluctuations in light absorbing particles deposition to improve the accuracy of snow cover reanalyses and climate projections.
Published: 2021

19. The EC-Earth3 Earth System Model for the Climate Model Intercomparison Project 6

Author: Raffaele Bernardello, Pablo Ortega, Pirkka Ollinaho, M. Pasha Karami, Federico Serva, Declan O'Donnell, David Wårlind, Matthias Gröger, Torben Koenigk, Paul A. Miller, Franco Catalano, Arthur Ramos, Klaus Wyser, Glenn Carver, Ivana Cvijanovic, Evelien Dekker, Ramon Fuentes-Franco, Xavier Yepes-Arbós, Martin Ménégoz, Marianne Sloth Madsen, Roland Schrödner, Mario Acosta, Shiyu Wang, Louis-Philippe Caron, Qiong Zhang, Eduardo Moreno-Chamarro, Ulrika Willén, Torben Schmith, Philippe Le Sager, Paul Nolan, Lars Nieradzik, Tommi Bergman, Shuting Yang, Jukka-Pekka Keskinen, Andrea Alessandri, Peter Anthoni, Twan van Noije, Yohan Ruprich-Robert, Oriol Tintó Prims, François Massonnet, Clement Rousset, Miguel Castrillo, Souhail Bousetta, Petteri Uotila, David Docquier, Jost von Hardenberg, Risto Makkonen, Valentina Sicardi, Gijs van den Oord, Uwe Fladrich, Francisco J. Doblas-Reyes, Thomas Reerink, Paolo Davini, Martin Vancoppenolle, Jenny Hieronymus, Benjamin Smith, Etienne Tourigny, Almut Arneth, Thomas Arsouze, Ralf Doescher, Tian Tian, Pablo Echevarria, Swedish Meteorological and Hydrological Institute (SMHI), Barcelona Supercomputing Center - Centro Nacional de Supercomputacion (BSC - CNS), CNR Institute of Atmospheric Sciences and Climate (ISAC), Consiglio Nazionale delle Ricerche (CNR), Karlsruhe Institute of Technology (KIT), Royal Netherlands Meteorological Institute (KNMI), European Centre for Medium-Range Weather Forecasts (ECMWF), Italian National Agency for New Technologies, Energy and Sustainable Economic Development (ENEA), Politecnico di Torino = Polytechnic of Turin (Polito), University of Helsinki, Finnish Meteorological Institute (FMI), Université Catholique de Louvain = Catholic University of Louvain (UCL), Institut des Géosciences de l’Environnement (IGE), Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Institut de Recherche pour le Développement (IRD)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), Lund University [Lund], Nucleus for European Modeling of the Ocean (NEMO R&D ), Laboratoire d'Océanographie et du Climat : Expérimentations et Approches Numériques (LOCEAN), Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)-Institut de Recherche pour le Développement (IRD)-Muséum national d'Histoire naturelle (MNHN)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)-Institut de Recherche pour le Développement (IRD)-Muséum national d'Histoire naturelle (MNHN)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU), National Research Council of Italy | Consiglio Nazionale delle Ricerche (CNR), Agenzia Nazionale per le nuove Tecnologie, l’energia e lo sviluppo economico sostenibile = Italian National Agency for New Technologies, Energy and Sustainable Economic Development (ENEA), Helsingin yliopisto = Helsingfors universitet = University of Helsinki, Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité)-Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), and Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité)
Subjects: 0106 biological sciences, 010504 meteorology & atmospheric sciences, European community, Computer science, 010604 marine biology & hydrobiology, Frame (networking), 01 natural sciences, Variety (cybernetics), Coupling (computer programming), [SDE]Environmental Sciences, Systems engineering, Range (statistics), Key (cryptography), Climate model, Earth system model, 0105 earth and related environmental sciences
Abstract: The Earth System Model EC-Earth3 for contributions to CMIP6 is documented here, with its flexible coupling framework, major model configurations, a methodology for ensuring the simulations are comparable across different HPC systems, and with the physical performance of base configurations over the historical period. The variety of possible configurations and sub-models reflects the broad interests in the EC-Earth community. EC-Earth3 key performance metrics demonstrate physical behaviour and biases well within the frame known from recent CMIP models. With improved physical and dynamic features, new ESM components, community tools, and largely improved physical performance compared to the CMIP5 version, EC-Earth3 represents a clear step forward for the only European community ESM. We demonstrate here that EC-Earth3 is suited for a range of tasks in CMIP6 and beyond.
Published: 2021

20. Twentieth century temperature and snow cover changes in the French Alps

Author: C. Vincent, Hubert Gallée, Delphine Six, Samuel Morin, Julien Beaumet, Bruno Wilhelm, Xavier Fettweis, Sandrine Anquetin, Martin Ménégoz, Institut des Géosciences de l’Environnement (IGE), Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), Centre national de recherches météorologiques (CNRM), Institut national des sciences de l'Univers (INSU - CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS), Université de Liège, Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), and Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)
Subjects: 010504 meteorology & atmospheric sciences, 0207 environmental engineering, Climate change, 02 engineering and technology, 01 natural sciences, Regional climate change, Glacier mass balance, Ecosystem, Precipitation, 020701 environmental engineering, 0105 earth and related environmental sciences, Climatic trends, Global and Planetary Change, Elevation, Regional climate modeling, 15. Life on land, Snow, Water resources, 13. Climate action, [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology, [SDE]Environmental Sciences, Environmental science, Climate model, Physical geography, European Alps, High mountain
Abstract: Changes in snow cover associated with the warming of the French Alps greatly influence social-ecological systems through their impact on water resources, mountain ecosystems, economic activities, and glacier mass balance. In this study, we investigated trends in snow cover and temperature over the twentieth century using climate model and reanalysis data. The evolution of temperature, precipitation and snow cover in the European Alps has been simulated with the Modèle Atmospherique Régional (MAR) applied with a 7-km horizontal resolution and driven by ERA-20C (1902-2010) and ERA5 (1981–2018) reanalyses data. Snow cover duration and snow water equivalent (SWE) simulated with MAR are compared to the SAFRAN - SURFEX-ISBA-Crocus - MEPRA meteorological and snow cover reanalysis (S2M) data across the French Alps (1958–2018) and in situ glacier mass balance measurements. MAR outputs provide a realistic distribution of SWE and snow cover duration as a function of elevation in the French Alps. Large disagreements are found between the datasets in terms of absolute warming trends over the second part of the twentieth century. MAR and S2M trends are in relatively good agreement for the decrease in snow cover duration, with higher decreases at low elevation ($\sim $ ∼ 5–10%/decade). Consistent with other studies, the highest warming rates in MAR occur at low elevations (< 1000 m a.s.l) in winter, whereas they are found at high elevations (> 2000 m a.s.l) in summer. In spring, warming trends show a maximum at intermediate elevations (1500 to 1800 m). Our results suggest that higher warming at these elevations is mostly linked to the snow-albedo feedback in spring and summer caused by the disappearance of snow cover at higher elevation during these seasons. This work has evidenced that depending on the season and the period considered, enhanced warming at higher elevations may or may not be found. Additional analysis in a physically comprehensive way and more high-quality dataset, especially at high elevations, are still required to better constrain and quantify climate change impacts in the Alps and its relation to elevation.
Published: 2021

21. Improved Near‐Surface Continental Climate in IPSL‐CM6A‐LR by Combined Evolutions of Atmospheric and Land Surface Physics

Author: Nicolas Vuichard, Catherine Ottlé, Frédéric Hourdin, Ionela Musat, Yanfeng Zhao, Fabienne Maignan, Jérôme Servonnat, Jean-Yves Grandpeix, Agnès Ducharne, Lidia Mellul, Frédérique Cheruy, Abderrahmane Idelkadi, Jean-Louis Dufresne, Guillaume Gastineau, Etienne Vignon, Binta Diallo, Martin Ménégoz, Fuxing Wang, Philippe Peylin, Vladislav Bastrikov, Josefine Ghattas, Laboratoire de Météorologie Dynamique (UMR 8539) (LMD), Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Modélisation des Surfaces et Interfaces Continentales (MOSAIC), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Milieux Environnementaux, Transferts et Interactions dans les hydrosystèmes et les Sols (METIS), École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Ecole Polytechnique Fédérale de Lausanne (EPFL), Océan et variabilité du climat (VARCLIM), Laboratoire d'Océanographie et du Climat : Expérimentations et Approches Numériques (LOCEAN), Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)-Institut de Recherche pour le Développement (IRD)-Muséum national d'Histoire naturelle (MNHN)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)-Institut de Recherche pour le Développement (IRD)-Muséum national d'Histoire naturelle (MNHN)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP), Institut des Géosciences de l’Environnement (IGE), Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Institut de Recherche pour le Développement (IRD)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), Modelling the Earth Response to Multiple Anthropogenic Interactions and Dynamics (MERMAID), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité)-Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), and ANR-17-EURE-0006,IPSL-CGS,IPSL Climate graduate school(2017)
Subjects: Atmospheric physics, Physical geography, 010504 meteorology & atmospheric sciences, 0207 environmental engineering, Climate change, hydrology, 02 engineering and technology, Atmospheric model, GC1-1581, Atmospheric sciences, Oceanography, 01 natural sciences, temperature bias, Hotspot (geology), Environmental Chemistry, [SDU.STU.HY]Sciences of the Universe [physics]/Earth Sciences/Hydrology, 020701 environmental engineering, ComputingMilieux_MISCELLANEOUS, 0105 earth and related environmental sciences, Global and Planetary Change, Discharge, Soil physics, 15. Life on land, climate modelling, atmosphere‐land surface interactions, stable boundary layer, GB3-5030, Boundary layer, 13. Climate action, [SDE]Environmental Sciences, General Earth and Planetary Sciences, Environmental science, Climate model, soil moisture
Abstract: International audience; This work is motivated by the identification of the land-atmosphere interactions as one of the key sources of uncertainty in climate change simulations. It documents new developments in related processes, namely, boundary layer/convection/clouds parameterizations and land surface parameterization in the Earth System Model of the Institut Pierre Simon Laplace (IPSL). Simulations forced by prescribed oceanic conditions are produced with different combinations of atmospheric and land surface parameterizations. They are used to explore the sensitivity to the atmospheric physics and/or soil physics of • major biases in the near surface variables over continents, • the energy and moisture coupling established at the soil/atmosphere interface in not too wet (energy limited) and not too dry (moisture limited) soil moisture regions also known as transition or "hot-spot" regions, • the river runoff at the outlet of major rivers. The package implemented in the IPSL-Climate Model for the Phase 6 of the Coupled Models Intercomparison Project (CMIP6) allows us to reduce several biases in the surface albedo, the snow cover, and the continental surface air temperature in summer as well as in the temperature profile in the surface layer of the polar regions. The interactions between soil moisture and atmosphere in hotspot regions are in better agreement with the observations. Rainfall is also significantly improved in volume and seasonality in several major river basins leading to an overall improvement in river discharge. However, the lack of consideration of floodplains and human influences in the model, for example, dams and irrigation, impacts the realism of simulated discharge. Plain Language Summary Land surface-atmosphere interactions play an essential role in the climate system. They strongly modulate the regional climates and have impacts on the global scale for instance through freshwater release into the oceans. Climate hazards (heat waves, droughts) and their impacts on populations also strongly depend on interactions between land and atmosphere and on their evolution with climate change. Climate models are precious tools to investigate how the Earth climate behaves. The sixth phase of the Climate Model Intercomparison Project (CMIP6) provides important tools to measure the progress and address the remaining open questions regarding the continental climate modeling. The representation of the land-atmosphere coupled system by the IPSL-Climate Model involved in CMIP6 is thoroughly evaluated against observations and compared with simulations using the CMIP5 version. Several biases concerning the temperature over land and over the ice sheets and with the snow cover are significantly reduced. Numerous improvements were made developping advanced parameterizations and tuning of the radiation and of the turbulent mixing in the atmospheric model. The realism of the seasonal
Published: 2020

22. On the observed connection between Arctic sea ice and Eurasian snow in relation to the winter North Atlantic Oscillation

Author: Javier García-Serrano, Martin Ménégoz, Joan Bech, María Santolaria-Otín, Institut des Géosciences de l’Environnement (IGE), Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), and Barcelona Supercomputing Center
Subjects: 010504 meteorology & atmospheric sciences, Sea ice, 010501 environmental sciences, Teleconnection, 01 natural sciences, Atmospheric circulation, Snow cover, 0105 earth and related environmental sciences, General Environmental Science, Climatology, geography, geography.geographical_feature_category, Renewable Energy, Sustainability and the Environment, Sea ice--Arctic regions, Public Health, Environmental and Occupational Health, Snow, Arctic ice pack, Connection (mathematics), Oceanography, 13. Climate action, North Atlantic oscillation, Climatologia, Enginyeria agroalimentària::Ciències de la terra i de la vida [Àrees temàtiques de la UPC], [SDE]Environmental Sciences, North Atlantic Oscillation, Geology
Abstract: Sea ice concentration (SIC) in the eastern Arctic and snow cover extent (SCE) over central Eurasia in late autumn have been proposed as potential predictors of the winter North Atlantic Oscillation (NAO). Here, maximum covariance analysis is used to further investigate the links between autumn SIC in the Barents-Kara Seas (BK) and SCE over Eurasia (EUR) with winter sea level pressure (SLP) in the North Atlantic-European region over 1979-2019. As shown by previous studies, the most significant covariability mode of SIC/BK is found for November. Similarly, the covariability with SCE/EUR is only statistically significant for November, not for October. Changes in temperature, specific humidity, SIC/BK and SCE/EUR in November are associated with a circulation anomaly over the Ural-Siberian region that appears as a precursor of the winter NAO; where the advection of climatological temperature/humidity by the anomalous flow is related to SCE/EUR and SIC/BK anomalies. The research leading to these results has received funding from the European Commissions H2020 projects APPLICATE (GA 727862) and PRIMAVERA (GA 641727), and the ANR Belmont RACE project (ANR-20-AORS-0002). JG-S has been supported by the Ramón y Cajal programme (RYC-2016-21181). MM has been supported by the MINECO project VOLCADEC (CGL201570177-R). JB has been supported by MINECO projects CGL2016-81828-REDT (AEI) and RTI2018-098693-B643-C32 (AEI). The authors thank Hervé Douville (CNRM/Météo-France) and Guillaume Gastineau (LOCEAN/IPSL, France) for useful discussions, and two anonymous reviewers for their valuable insights.
Published: 2020

23. Response to referee #1

Author: Martin Ménégoz
Published: 2020

24. Response to Frederico Grazzini, acting as the referee#2

Author: Martin Ménégoz
Published: 2020

25. Response to referee #3

Author: Martin Ménégoz
Published: 2020

26. Robust Multiyear Climate Impacts of Volcanic Eruptions in Decadal Prediction Systems

Author: Roberto Bilbao, Doug Smith, Nick Dunstone, Claudia Timmreck, Gary Strand, Jon Robson, Martin Ménégoz, Gokhan Danabasoglu, Holger Pohlmann, Steve G. Yeager, Leon Hermanson, Pablo Ortega, Institut des Géosciences de l’Environnement (IGE), Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), and Barcelona Supercomputing Center
Subjects: Atmospheric Science, 010504 meteorology & atmospheric sciences, Climate prediction, 7. Clean energy, 01 natural sciences, Volcanic aerosols, Earth and Planetary Sciences (miscellaneous), Volcans, Volcanic eruptions, Stratosphere, 0105 earth and related environmental sciences, Desenvolupament humà i sostenible [Àrees temàtiques de la UPC], Mathematical models, geography, Vulcanian eruption, geography.geographical_feature_category, Models matemàtics, Geophysics, El Niño Southern Oscillation, Volcano, Erupcions volcàniques -- Avaluació del risc, 13. Climate action, Space and Planetary Science, North Atlantic oscillation, Climatology, [SDE]Environmental Sciences, Period (geology), Errors-in-variables models, Environmental science, Volcanoes, Decadal prediction systems
Abstract: Major tropical volcanic eruptions have a large impact on climate, but there have only been three major eruptions during the recent relatively well‐observed period. Models are therefore an important tool to understand and predict the impacts of an eruption. This study uses five state‐of‐the‐art decadal prediction systems that have been initialized with the observed state before volcanic aerosols are introduced. The impact of the volcanic aerosols is found by subtracting the results of a reference experiment where the volcanic aerosols are omitted. We look for the robust impact across models and volcanoes by combining all the experiments, which helps reveal a signal even if it is weak in the models. The models used in this study simulate realistic levels of warming in the stratosphere, but zonal winds are weaker than the observations. As a consequence, models can produce a pattern similar to the North Atlantic Oscillation in the first winter following the eruption, but the response and impact on surface temperatures are weaker than in observations. Reproducing the pattern, but not the amplitude, may be related to a known model error. There are also impacts in the Pacific and Atlantic Oceans. This work contributes toward improving the interpretation of decadal predictions in the case of a future large tropical volcanic eruption. We thank the three reviewers for their help in improving this manuscript. The data are available from DOI (10.5281/zenodo.2613699). L. H. was supported by the Climate Resilience Project funded by UKRI. N. D. and D. M. S. were supported by the Met Office Hadley Centre Climate Programme funded by BEIS and Defra. M. M., R. B., and P. O. received funding from the Ministerio de Economia y Competitividad (MINECO) as part of the VOLCADEC (Ref. CGL2015‐70177‐R) and HIATUS (Ref. CGL2015‐70353‐R) projects. H. P. and C. T. were supported by the German Ministry of Education and Research (BMBF) under the project MiKlip (Grants 01LP1519A and 01LP1517B). J. I. R. was supported by the Natural Environmental Research Council (NERC)‐funded SMURPHS project and the ACSIS program. HiGEM‐DP experiments were performed using the ARCHER UK National Supercomputing Service (http://www.archer.ac.uk). The National Center for Atmospheric Research (NCAR) is a major facility sponsored by the U.S. National Science Foundation (NSF) under Cooperative Agreement No. 1852977. G. D. and S. Y. further acknowledge the support of NSF Collaborative Research EaSM2 Grant OCE‐1243015. G. S. was supported by the Regional and Global Climate Modeling Program (RGCM) of the U.S. Department of Energy's, Office of Science (BER), Cooperative Agreement DE‐FC02‐97ER62402.
Published: 2020

27. The importance of modelled processes in the evolution of snow cover versus snow mass

Author: María Santolaria-Otín, Carrie M. Vuyovich, Sujay V. Kumar, Gerhard Krinner, Lawrence Mudryk, Claire Brutel-Vuilmet, Chris Derksen, Rhae Sung Kim, and Martin Ménégoz
Subjects: Environmental science, Snow, Atmospheric sciences, Snow cover
Abstract: Conventional wisdom holds that confidence in future projections of snow cover extent and snow mass requires an understanding of the expected changes in future snow characteristics as a function of modelled snow processes. We will highlight contrasting results which suggest differing importance in the role of sub-grid scale processes on simulations of seasonal snow.The first study is an evaluation of simulated snow cover extent projections from models participating in the 6th phase of the World Climate Research Programme Coupled Model Inter-comparison Project (CMIP-6). We demonstrate a single linear relationship between projected spring snow extent and global surface air temperature (GSAT) changes, which is valid across all future climate scenarios. This finding suggests that Northern Hemisphere spring snow extent will decrease by about 8% relative to the 1995-2014 level per °C of GSAT increase. The sensitivity of snow to temperature forcing largely explains the absence of any climate change pathway dependency, similar to other fast response components of the cryosphere such as sea ice and near surface permafrost.The second study makes use of an ensemble of land surface models, downscaled to 5 km resolution across North America over the 2009-2017 period. In this case, uncertainty in total North American snow mass is dominated by differences among land surface model configurations. While the largest absolute spread in snow mass is found in mountainous regions, heavily vegetated boreal regions have the largest fractional spread compared to climatological values. In particular, differences in rain-snow partitioning and sublimation rates control the largest portions of the total uncertainty. These results suggest that projections of future snow mass depend specifically on how such processes are modelled and parameterized.
Published: 2020

28. Detection of precipitation and snow cover trends in the the European Alps over the last century using model and observational data

Author: Hubert Gallée, Bruno Wilhelm, Martin Ménégoz, Xavier Fettweis, Samuel Morin, Vincent Vionnet, Juliette Blanchet, Nicolas C. Jourdain, Sandrine Anquetin, and Julien Beaumet
Subjects: Climatology, Environmental science, Observational study, Precipitation, Snow cover
Abstract: The European Alps are particularly sensitive to climate change. Compared to temperature, changes in precipitation are more challenging to detect and attribute to ongoing anthropic climate change mainly as a result of large inter-annual variability, lack of reliable measurements at high elevations and opposite signals depending on the season or the elevation considered. However, changes in precipitation and snow cover have significant socio-environmental impact mostly trough water resource availability. These changes are investigated within the framework of the Trajectories initiative (). The variability and changes in precipitation and snow cover in the European Alps has been simulated with the MAR regional climate model at a 7 km horizontal resolution driven by ERA20C (1902-2010) and ERA5 (1979-2018) reanalyses. For precipitation, MAR outputs were compared with EURO-4M, SAFRAN, SPAZM and E-OBS reanalyses as well as in-situ observations. The model was shown to reproduce correctly seasonal and inter-annual variability. The spatial biases of the model have the same order of magnitude as the differences between the three observational data sets. Model experiment has been used to detect precipitation changes over the last century. An increase in winter precipitation is simulated over the North-western part of the Alps at high altitudes (>1500m). Significant decreases in summer precipitation were found in many low elevation areas, especially the Po Plain while no significant trends where found at high elevations. Because of large internal variability, precipitation changes are significant (pvalueSnow depth and water equivalent (SWE) in the French Alps simulated with MAR have been compared to the SAFRAN-Crocus reanalyses and to in-situ observations. MAR was found to simulate a realistic distribution of SWE as function of the elevation in the French Alpine massifs, although it underestimates SWE at low elevations in the Pre-Alps. Snow cover over the whole European Alps is evaluated using MODIS satellite data. Finally, trends in snow cover and snow depth are highlighted as well as their relationships with the precipitation and temperature changes over the last century.
Published: 2020

29. Role of Saharan dust and black carbon deposition on snow cover in the French mountain ranges over the last 39 years

Author: Marie Dumont, Simon Gascoin, Marion Réveillet, Pierre Nabat, Rafife Nheili, François Tuzet, Paul Ginoux, Martin Ménégoz, and Matthieu Lafaysse
Subjects: Environmental science, Carbon black, Mineral dust, Atmospheric sciences, Deposition (chemistry), Snow cover
Abstract: Light absorbing particles such as black carbon(BC) or mineral dust are known to darken the snow surface when deposited on the snow cover and amplify several snow-albedo feedbacks, drastically modifying the snowpack evolution and the snow cover duration. Mineral dust deposition on snow is generally more variablein time than black carbon deposition and can exhibit both a high inter and intra annual variability. In France, the Alps and the Pyrenees mountain ranges are affected by large dust deposition events originating from the Sahara . The aim of this study is to quantify the impact of these impurities on the snow cover variability over the last 39 years (1979-2018).For that purpose, the detailed snowpack model Crocus with an explicit representation of impurities is forced by SAFRAN meteorological reanalysis and a downscaling of the simulated deposition fluxes from a regional climate model (ALADIN-Climate). Different simulations are performed: (i) considering dust and/or BC (i.e. explicit representation), (ii) without impurities and (iii) considering an implicit representation (i.e. empirical parameterization based on a decreasing law of the albebo with snow age).Simulations are compared at point scale to the snow depth measured at more than 200 Meteo-France’s stations in each massif, and spatially evaluated over the 2000-2018 period in comparing thesnow cover area, snow cover duration and the Jacard index to MODIS snow products. Scores are generally better when considering the explicit representation of the impurities than when using the snow age as a proxy for light absorbing particles content.Results indicate that dust and BC have a significant impact on the snow cover duration with strong variations in the magnitude of the impact from one year to another and from one location to another.We also investigate the contribution of light absorbing particles depositionto snow cover inter-annual variability based on statistical approaches.
Published: 2020

30. Historical Northern Hemisphere snow cover trends and projected changes in the CMIP-6 multi-model ensemble

Author: Mike Brady, Claire Brutel-Vuilmet, María Santolaria-Otín, Chris Derksen, Gerhard Krinner, Richard Essery, Lawrence Mudryk, Martin Ménégoz, Institut des Géosciences de l’Environnement (IGE), Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), and Université Grenoble Alpes (UGA)
Subjects: 010504 meteorology & atmospheric sciences, 0207 environmental engineering, Climate change, 02 engineering and technology, Forcing (mathematics), Permafrost, 01 natural sciences, 03 medical and health sciences, 0302 clinical medicine, Sea ice, Cryosphere, 020701 environmental engineering, lcsh:Environmental sciences, 0105 earth and related environmental sciences, Earth-Surface Processes, Water Science and Technology, 030304 developmental biology, lcsh:GE1-350, geography, 0303 health sciences, geography.geographical_feature_category, lcsh:QE1-996.5, Northern Hemisphere, Snow, lcsh:Geology, 13. Climate action, Climatology, [SDE]Environmental Sciences, Environmental science, Snow cover, 030217 neurology & neurosurgery
Abstract: This paper presents an analysis of observed and simulated historical snow cover extent and snow mass, along with future snow cover projections from models participating in the World Climate Research Programme Coupled Model Intercomparison Project Phase 6 (CMIP6). Where appropriate, the CMIP6 output is compared to CMIP5 results in order to assess progress (or absence thereof) between successive model generations. An ensemble of six observation-based products is used to produce a new time series of historical Northern Hemisphere snow extent anomalies and trends; a subset of four of these products is used for snow mass. Trends in snow extent over 1981–2018 are negative in all months and exceed -50×103 km2 yr−1 during November, December, March, and May. Snow mass trends are approximately −5 Gt yr−1 or more for all months from December to May. Overall, the CMIP6 multi-model ensemble better represents the snow extent climatology over the 1981–2014 period for all months, correcting a low bias in CMIP5. Simulated snow extent and snow mass trends over the 1981–2014 period are stronger in CMIP6 than in CMIP5, although large inter-model spread remains in the simulated trends for both variables. There is a single linear relationship between projected spring snow extent and global surface air temperature (GSAT) changes, which is valid across all CMIP6 Shared Socioeconomic Pathways. This finding suggests that Northern Hemisphere spring snow extent will decrease by about 8 % relative to the 1995–2014 level per degree Celsius of GSAT increase. The sensitivity of snow to temperature forcing largely explains the absence of any climate change pathway dependency, similar to other fast-response components of the cryosphere such as sea ice and near-surface permafrost extent.
Published: 2020

31. Supplementary material to 'Historical Northern Hemisphere snow cover trends and projected changes in the CMIP-6 multi-model ensemble'

Author: Lawrence Mudryk, Maria Santolaria-Otín, Gerhard Krinner, Martin Ménégoz, Chris Derksen, Claire Brutel-Vuilmet, Mike Brady, and Richard Essery
Published: 2020

32. Contrasting seasonal changes in total and intense precipitation in the European Alps from 1903 to 2010

Author: Martin Ménégoz, Evgenia Valla, Nicolas C. Jourdain, Juliette Blanchet, Julien Beaumet, Bruno Wilhelm, Hubert Gallée, Xavier Fettweis, Samuel Morin, Sandrine Anquetin, Institut des Géosciences de l’Environnement (IGE), Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), Institut d'Astronomie et de Géophysique Georges Lemaître (UCL-ASTR), Université Catholique de Louvain = Catholic University of Louvain (UCL), Groupe d'étude de l'atmosphère météorologique (CNRM-GAME), and Institut national des sciences de l'Univers (INSU - CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS)
Subjects: [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, 13. Climate action, [SDU]Sciences of the Universe [physics]
Abstract: Changes of precipitation over the European Alps are investigated with the regional climate model MAR applied with a 7-km resolution over the period 1903–2010 using the reanalysis ERA-20C as forcing. A comparison with several observational datasets demonstrates that the model is able to reproduce the climatology as well as both the inter-annual variability and the seasonal cycle of precipitation over the European Alps. The relatively high resolution allows to estimate precipitation at high elevations. The vertical gradient of precipitation simulated by MAR over the European Alps reaches 33 % km−1 (1.21 mm.day−1.km−1) in summer and 38 % km−1 (1.15 mm.day−1.km−1) in winter, on average over 1971–2008 and shows a large spatial variability. A significant (p-value −1 on average over 1903–2010. Centennial maxima up to 250 to 300 mm.day−1 are simulated in the Southern Alps, in France and Italy, as well as in the Ticino valley in Switzerland. Over 1903–2010, seasonal Rx1day shows a general and significant increase at the annual timescale and also during the four seasons, reaching local values between 20 % and 40 % per century over large parts of the Alps and the Apennines. Trends of Rx1day are significant (p-value&thinsp
Published: 2020

33. Supplementary material to 'Contrasting seasonal changes in total and intense precipitation in the European Alps from 1903 to 2010'

Author: Martin Ménégoz, Evgenia Valla, Nicolas C. Jourdain, Juliette Blanchet, Julien Beaumet, Bruno Wilhelm, Hubert Gallée, Xavier Fettweis, Samuel Morin, and Sandrine Anquetin
Published: 2020

34. Detecting Improvements in Forecast Correlation Skill: Statistical Testing and Power Analysis

Author: Stefan Siegert, Martin Ménégoz, Omar Bellprat, David B. Stephenson, and Francisco J. Doblas-Reyes
Subjects: Atmospheric Science, 010504 meteorology & atmospheric sciences, Correlation coefficient, 0208 environmental biotechnology, Forecast skill, Initialization, Weather and climate, 02 engineering and technology, 01 natural sciences, 020801 environmental engineering, Correlation, Model resolution, Power analysis, Statistics, 0105 earth and related environmental sciences, Mathematics, Statistical hypothesis testing
Abstract: The skill of weather and climate forecast systems is often assessed by calculating the correlation coefficient between past forecasts and their verifying observations. Improvements in forecast skill can thus be quantified by correlation differences. The uncertainty in the correlation difference needs to be assessed to judge whether the observed difference constitutes a genuine improvement, or is compatible with random sampling variations. A widely used statistical test for correlation difference is known to be unsuitable, because it assumes that the competing forecasting systems are independent. In this paper, appropriate statistical methods are reviewed to assess correlation differences when the competing forecasting systems are strongly correlated with one another. The methods are used to compare correlation skill between seasonal temperature forecasts that differ in initialization scheme and model resolution. A simple power analysis framework is proposed to estimate the probability of correctly detecting skill improvements, and to determine the minimum number of samples required to reliably detect improvements. The proposed statistical test has a higher power of detecting improvements than the traditional test. The main examples suggest that sample sizes of climate hindcasts should be increased to about 40 years to ensure sufficiently high power. It is found that seasonal temperature forecasts are significantly improved by using realistic land surface initial conditions.
Published: 2017

35. Role of the Atlantic Multidecadal Variability in modulating the climate response to a Pinatubo-like volcanic eruption

Author: Yohan Ruprich-Robert, Pierre-Antoine Bretonnière, Martin Ménégoz, Christophe Cassou, Francisco J. Doblas-Reyes, Didier Swingedouw, and Barcelona Supercomputing Center
Subjects: Atmospheric Science, 010504 meteorology & atmospheric sciences, Atmospheric circulation, 010502 geochemistry & geophysics, Atmospheric sciences, Climate dynamics, Ensemble size, 01 natural sciences, Climate model, Atlantic Equatorial mode, Atlantic multidecadal oscillation, Climate science, Hadley cell, Volcanic eruptions, 0105 earth and related environmental sciences, Vulcanian eruption, Enginyeria biomèdica [Àrees temàtiques de la UPC], 13. Climate action, North Atlantic oscillation, Climatology, Environmental science, North Atlantic Oscillation, Atlantic multidecadal variability, Teleconnection, Clima--Observacions, Canvis climàtics
Abstract: The modulation by the Atlantic multidecadal variability (AMV) of the dynamical climate response to a Pinatubo-like eruption is investigated for the boreal winter season based on a suite of large ensemble experiments using the CNRM-CM5 Coupled Global Circulation Model. The volcanic eruption induces a strong reduction and retraction of the Hadley cell during 2 years following the eruption and independently of the phase of the AMV. The mean extratropical westerly circulation simultaneously weakens throughout the entire atmospheric column, except at polar Northern latitudes where the zonal circulation is slightly strengthened. Yet, there are no significant changes in the modes of variability of the surface atmospheric circulation, such as the North Atlantic Oscillation (NAO), in the first and the second winters after the eruption. Significant modifications over the North Atlantic sector are only found during the third winter. Using clustering techniques, we decompose the atmospheric circulation into weather regimes and provide evidence for inhibition of the occurrence of negative NAO-type circulation in response to volcanic forcing. This forced signal is amplified in cold AMV conditions and is related to sea ice/atmosphere feedbacks in the Arctic and to tropical-extratropical teleconnections. Finally, we demonstrate that large ensembles of simulations are required to make volcanic fingerprints emerge from climate noise at mid-latitudes. Using small size ensemble could easily lead to misleading conclusions especially those related to the extratropical dynamics, and specifically the NAO. This research was carried out within the pro- jects: (i) MORDICUS funded by the French Agence Nationale de la Recherche (ANR-13-SENV-0002-02); (ii) SPECS funded by the European Commission’s Seventh Framework Research Programme under the grant agreement 308378; (iii) VOLCADEC funded by the Spanish program MINECO/FEDER (ref. CGL2015-70177-R). We thank Javier Garcia-Serrano for its comments about the NAO precursors, Omar Bellprat for its suggestions concerning the statistical analysis and François Massonnet for its recommendations in terms of graphical presentation. CC is grateful to Marie-Pierre Moine, Laure Coquart and Isabelle Dast for technical help to run the model. Computer resources have been provided by Cerfacs. We thank the two anonymous referees for their useful comments and suggestions to improve this manuscript.
Published: 2018

36. Forecasting the climate response to volcanic eruptions: prediction skill related to stratospheric aerosol forcing

Author: Virginie Guemas, Omar Bellprat, Martin Ménégoz, Roberto Bilbao, Francisco J. Doblas-Reyes, Barcelona Supercomputing Center, Laboratoire de glaciologie et géophysique de l'environnement (LGGE), Observatoire des Sciences de l'Univers de Grenoble (OSUG ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Centre National de la Recherche Scientifique (CNRS), Barcelona Supercomputing Center - Centro Nacional de Supercomputacion (BSC - CNS), and Institució Catalana de Recerca i Estudis Avançats (ICREA)
Subjects: climate variability, 010504 meteorology & atmospheric sciences, Energies [Àrees temàtiques de la UPC], Forecast skill, Forcing (mathematics), Hiatus, 010502 geochemistry & geophysics, Decadal forecast, 01 natural sciences, Volcanic activity prediction, Activitat volcànica--Previsió, Volcanic aerosols, European commission, Climate variability, 0105 earth and related environmental sciences, General Environmental Science, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, Previsió del temps, geography, geography.geographical_feature_category, Renewable Energy, Sustainability and the Environment, Seasonal climate forecasting, decadal forecast, Public Health, Environmental and Occupational Health, volcanic aerosols, Climatic changes, Skill of forecast systems, Aerosol, R package, Volcano, 13. Climate action, skill of forecast systems, Climatology, Environmental science, Climate response, ENSO, Canvis climàtics
Abstract: The last major volcanic eruptions, the Agung in 1963, El Chichon in 1982 and Pinatubo in 1991, were each associated with a cooling of the troposphere that has been observed over large continental areas and over the Western Pacific, the Indian Ocean and the Southern Atlantic. Simultaneously, Eastern tropical Pacific temperatures increased due to prevailing El Ni?o conditions. Here we show that the pattern of these near-surface temperature anomalies is partly reproduced with decadal simulations of the EC-Earth model initialised with climate observations and forced with an estimate of the observed volcanic aerosol optical thickness. Sensitivity experiments highlight a cooling induced by the volcanic forcing, whereas El Ni?o events following the eruptions would have occurred even without volcanic eruptions. Focusing on the period 1961?2001, the main source of skill of this decadal forecast system during the first 2 years is related to the initialisation of the model. The contribution of the initialisation to the skill becomes smaller than the contribution of the volcanic forcing after two years, the latter being substantial in the Western Pacific, the Indian Ocean and the Western Atlantic. Two simple protocols for real time forecasts are investigated: using the forcing of a past volcanic eruption to simulate the forcing of a new one, and applying a two-year exponential decay to the initial stratospheric aerosol load observed at the beginning of the forecast. This second protocol applied in retrospective forecasts allows a partial reproduction of the skill attained with observed forcing. The research leading to these results has received funding from the Ministerio de Economía y Competitividad (MINECO) as part of the VOLCADEC (ref.CGL2015–70177-R) and HIATUS (ref.CGL2015–70353-R) projects, as well as the program SPECS funded by the European Commission’s Seventh Framework Research Programme under the grant agreement 308378. We thank the Met Office for providing the HadCRTU4 observational dataset. All the analysis and figures have been produced with the s2dverification R package (https://cran.r-project.org/ web/packages/s2dverification/index.html) and the simulations have been launched with the Autosubmit workflow manager (http://autosubmit.readthedocs.io/en/latest/)
Published: 2018

37. An R package for climate forecast verification

Author: Francisco J. Doblas-Reyes, François Massonnet, Eleftheria Exarchou, Martin Ménégoz, Alasdair Hunter, Louis-Philippe Caron, Nicolau Manubens, Neven S. Fučkar, Verónica Torralba, Kim Serradell, Omar Bellprat, Virginie Guemas, Lauriane Batté, Javier García-Serrano, Nicola Cortesi, Oriol Mula-Valls, Valentina Sicardi, Chloé Prodhomme, and UCL - SST/ELI/ELIC - Earth & Climate
Subjects: Environmental Engineering, 010504 meteorology & atmospheric sciences, Computer science, Process (engineering), Ecological Modeling, media_common.quotation_subject, Forecast skill, 010502 geochemistry & geophysics, 01 natural sciences, Industrial engineering, Forecast verification, Visualization, R package, Ecological Modelling, Data retrieval, Climate model, Quality (business), Software, 0105 earth and related environmental sciences, media_common
Abstract: Forecast verification is necessary to determine the skill and quality of a forecasting system, and whether it shows improvement with pre- or post-processing. s2dverification v2.8.0 is an open-source R package for the quality assessment of climate forecasts using state-of-the-art verification scores. The package provides tools for each step of the forecast verification process: data retrieval, processing, calculation of verification measures and visualisation of the results. Examples are provided and explained for each of these stages using climate model output.
Published: 2018

38. Impact of explosive volcanic eruptions on the main climate variability modes

Author: Didier Swingedouw, Myriam Khodri, Martin Ménégoz, Juliette Mignot, Pablo Ortega, Christophe Cassou, Vincent Hanquiez, Environnements et Paléoenvironnements OCéaniques (EPOC), Observatoire aquitain des sciences de l'univers (OASU), Université Sciences et Technologies - Bordeaux 1 (UB)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Sciences et Technologies - Bordeaux 1 (UB)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS), Climate and Environmental Physics [Bern] (CEP), Physikalisches Institut [Bern], Universität Bern [Bern] (UNIBE)-Universität Bern [Bern] (UNIBE), Oeschger Centre for Climate Change Research (OCCR), University of Bern, Processus de la variabilité climatique tropicale et impacts (PARVATI), Laboratoire d'Océanographie et du Climat : Expérimentations et Approches Numériques (LOCEAN), Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), NCAS-Climate [Reading], Department of Meteorology [Reading], University of Reading (UOR)-University of Reading (UOR), Barcelona Supercomputing Center - Centro Nacional de Supercomputacion (BSC - CNS), Centre Européen de Recherche et de Formation Avancée en Calcul Scientifique (CERFACS), Barcelona Supercomputing Center, Université Sciences et Technologies - Bordeaux 1-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Sciences et Technologies - Bordeaux 1-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-École pratique des hautes études (EPHE), Universität Bern [Bern]-Universität Bern [Bern], Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Muséum national d'Histoire naturelle (MNHN)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Muséum national d'Histoire naturelle (MNHN)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), CERFACS [Toulouse], and Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)
Subjects: Desenvolupament humà i sostenible::Medi ambient [Àrees temàtiques de la UPC], 010504 meteorology & atmospheric sciences, Radiative forcing, Climate change, [PHYS.PHYS.PHYS-GEO-PH]Physics [physics]/Physics [physics]/Geophysics [physics.geo-ph], 010502 geochemistry & geophysics, Oceanography, Atmospheric sciences, 01 natural sciences, Climate models, Climate predictability, Atlantic multidecadal oscillation, Erupcions volcàniques, Volcanic eruptions, ComputingMilieux_MISCELLANEOUS, Detectors de radiació, 0105 earth and related environmental sciences, Global and Planetary Change, Explosive eruption, Climate oscillation, 13. Climate action, North Atlantic oscillation, Climatology, Climate model, Climate state, Geology
Abstract: Volcanic eruptions eject largeamounts of materials into the atmosphere, which can have an impact on climate. In particular, the sulphur dioxide gas released in the stratosphere leads to aerosol formation that reflects part of the incoming solar radiation, thereby affecting the climate energy balance. In this review paper, we analyse the regional climate imprints of large tropical volcanic explosive eruptions. For this purpose, we focus on the impact on three major climatic modes, located in the Atlantic (the North Atlantic Oscillation: NAO and the Atlantic Multidecadal Oscillation: AMO) and Pacific (the El Niño Southern Oscillation, ENSO) sectors. We present an overview of the chain of events that contributes to modifying the temporal variability of these modes. Our literature review is complemented by new analyses based on observations of the instrumental era as well as on available proxy records and climate model simulations that cover the last millennium. We show that the impact of volcanic eruptions of the same magnitude or weaker than 1991 Mt. Pinatubo eruption on the NAO and ENSO is hard to detect, due to the noise from natural climate variability. There is however a clear impact of the direct radiative forcing resulting from tropical eruptions on the AMO index both in reconstructions and climate model simulations of the last millennium, while the impact on the ocean circulation remains model-dependent. To increase the signal to noise ratio and better evaluate the climate response to volcanic eruptions, improved reconstructions of these climatic modes and of the radiative effect of volcanic eruptions are required on a longer time frame than the instrumental era. Finally, we evaluate climate models' capabilities to reproduce the observed and anticipated impacts and mechanisms associated with volcanic forcing, and assess their potential for seasonal to decadal prediction. We find a very large spread in the simulated responses across the different climate models. Dedicated experimental designs and analyses are therefore needed to decipher the cause for this large uncertainty. This research was partly funded by the ANR MORDICUS project (ANR-13-SENV-0002-02). It is also funded by the SPECS project funded by the European Commission's Seventh Framework Research Programme under the grant agreement 308378 and by the EMBRACE project with research number 282672. To analyse the CMIP5 data, this study benefited from the IPSL Prodiguer-Ciclad facility, which is supported by CNRS, UPMC, Labex L-IPSL, which is funded by the ANR (grant # ANR-10-LABX-0018) and by the European FP7 IS-ENES2 project (grant # 312979). The research leading to these results has received funding from the Ministerio de Economía y Competitividad (MINECO) as part of the VOLCADEC project CGL2015-70177-R. We also thank Patrick Brockmann for help with the figure design and Eric Guilyardi for useful insights on the section dealing with ENSO. Finally, we acknowledge the comments from two reviewers that helped to clarify our arguments and complete the paper with some useful references.
Published: 2017

39. Oceanic Forcing of Antarctic Climate Change: A Study Using a Stretched-Grid Atmospheric General Circulation Model

Author: Chloé Largeron, Claire Brutel-Vuilmet, Cécile Agosta, Gerhard Krinner, and Martin Ménégoz
Subjects: Atmospheric Science, Coupled model intercomparison project, Climate oscillation, Climatology, Global warming, Climate commitment, Abrupt climate change, Environmental science, Climate change, Climate model, Climate state, Atmospheric sciences
Abstract: A variable-resolution atmospheric general circulation model (AGCM) is used for climate change projections over the Antarctic. The present-day simulation uses prescribed observed sea surface conditions, while a set of five simulations for the end of the twenty-first century (2070–99) under the Special Report on Emissions Scenarios (SRES) A1B scenario uses sea surface condition anomalies from selected coupled ocean–atmosphere climate models from phase 3 of the Coupled Model Intercomparison Project (CMIP3). Analysis of the results shows that the prescribed sea surface condition anomalies have a very strong influence on the simulated climate change on the Antarctic continent, largely dominating the direct effect of the prescribed greenhouse gas concentration changes in the AGCM simulations. Complementary simulations with idealized forcings confirm these results. An analysis of circulation changes using self-organizing maps shows that the simulated climate change on regional scales is not principally caused by shifts of the frequencies of the dominant circulation patterns, except for precipitation changes in some coastal regions. The study illustrates that in some respects the use of bias-corrected sea surface boundary conditions in climate projections with a variable-resolution atmospheric general circulation model has some distinct advantages over the use of limited-area atmospheric circulation models directly forced by generally biased coupled climate model output.
Published: 2014

40. Seasonal and annual mass balances of Mera and Pokalde glaciers (Nepal Himalaya) since 2007

Author: Martin Ménégoz, Patrick Wagnon, Etienne Berthier, Marie Dumont, E. Vuillermoz, Joseph M. Shea, Christian Vincent, Adrien Gilbert, Bijay K. Pokhrel, Yves Arnaud, S. Gruber, D. Stumm, Laboratoire de glaciologie et géophysique de l'environnement (LGGE), Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), International Centre for Integrated Mountain Development (ICIMOD), Laboratoire d'étude des transferts en hydrologie et environnement (LTHE), Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS), Cryosphère satelittaire (CRYO), Laboratoire d'études en Géophysique et océanographie spatiales (LEGOS), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), Ev-K2-CNR Committee, Écosystémique des communautés récifales et de leurs usages dans le Pacifique insulaire (CoReUS), Centre d'Etudes de la Neige (CEN), Centre national de recherches météorologiques (CNRM), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Grenoble (OSUG ), Institut national des sciences de l'Univers (INSU - CNRS)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Grenoble Alpes (UGA)-Météo-France -Institut national des sciences de l'Univers (INSU - CNRS)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Grenoble Alpes (UGA), Department of Hydrology and Meteorology, Babarmahal, Kathmandu (DHM), Government of Nepal Ministry of Science, Technology & Environment, Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS), Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS), Institut national des sciences de l'Univers (INSU - CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS), International Centre for Integrated Mountain Development, ICIMOD, Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique de Grenoble (INPG)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National d'Études Spatiales [Toulouse] (CNES)-Observatoire Midi-Pyrénées (OMP), Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS), and Météo France-Centre National de la Recherche Scientifique (CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS)
Subjects: 010504 meteorology & atmospheric sciences, 0207 environmental engineering, Energy balance, ALPS, 02 engineering and technology, Atmospheric sciences, CHHOTA SHIGRI GLACIER, 01 natural sciences, REGION, Glacier mass balance, WESTERN HIMALAYA, 020701 environmental engineering, MOUNT EVEREST, SATELLITE, [SDU.STU.OC]Sciences of the Universe [physics]/Earth Sciences/Oceanography, lcsh:Environmental sciences, 0105 earth and related environmental sciences, Earth-Surface Processes, Water Science and Technology, Monsoon of South Asia, lcsh:GE1-350, geography, geography.geographical_feature_category, lcsh:QE1-996.5, Glacier, Snow, lcsh:Geology, 13. Climate action, SNOW, Climatology, PRECIPITATION, Aeolian processes, INDIA, ENERGY-BALANCE, Geology
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Vincent, C. Arnaud, Y. Berthier, E. Vuillermoz, E. Gruber, S. Menegoz, M. Gilbert, A. Dumont, M. Shea, J. M. Stumm, D. Pokhrel, B. K. French Service d'Observation GLACIOCLIM; French National Research Agency [ANR-09-CEP-005-01/PAPRIKA]; Nepal Academy of Science and Technology [Ev-K2-CNR]; Italian National Research Council; Italian Ministry of Education, University and Research; Italian Ministry of Foreign Affairs; CNES through the TOSCA programme; Royal Norwegian Embassy in Kathmandu This work has been supported by the French Service d'Observation GLACIOCLIM and the French National Research Agency through ANR-09-CEP-005-01/PAPRIKA. This study was carried out within the framework of the Ev-K2-CNR Project in collaboration with the Nepal Academy of Science and Technology as foreseen by the Memorandum of Understanding between Nepal and Italy, and thanks to contributions from the Italian National Research Council, the Italian Ministry of Education, University and Research and the Italian Ministry of Foreign Affairs. All people involved in the field or helping for logistical support at the Pyramid, in Kathmandu or in Italy are greatly acknowledged here. We thank J. P. Chazarin, R. Biron and the porters who have been involved in successive field trips, sometimes in harsh conditions. S. Kaspari measured the stakes on 23-25 April 2009, and is greatly acknowledged here. Pleiades-1A images were obtained free of charge in the framework of the "Recette Thematique Utilisateur Pleiades/ORFEO" conducted by the French Space Agency (CNES). The SPOT5 DEM and images were obtained thanks to ISIS proposals #397 and #520. E. Berthier acknowledges support from the CNES through the TOSCA programme. J. Shea and D. Stumm acknowledge institutional support from ICIMOD, and financial support from the Royal Norwegian Embassy in Kathmandu. E. Thibert helped to calculate the mass balance accuracy and is greatly acknowledged here. The authors are sincerely grateful to M. Pelto, T. Molg, P. Lardeux, B. Raup, S. Ommanney and the two referees T. Nuimura and C. Mayer for their valuable comments which greatly helped to improve this paper. 0 COPERNICUS GESELLSCHAFT MBH GOTTINGEN CRYOSPHERE; In the Everest region, Nepal, ground-based monitoring programmes were started on the debris-free Mera Glacier (27.7 degrees N, 86.9 degrees E; 5.1 km(2), 6420 to 4940 m a.s.l.) in 2007 and on the small Pokalde Glacier (27.9 degrees N, 86.8 degrees E; 0.1 km(2), 5690 to 5430 m a.s.l., similar to 25 km north of Mera Glacier) in 2009. These glaciers lie on the southern flank of the central Himalaya under the direct influence of the Indian monsoon and receive more than 80% of their annual precipitation in summer (June to September). Despite a large inter-annual variability with glacier-wide mass balances ranging from -0.67 +/- 0.28 m w.e. in 2011-2012 (Equilibrium-line altitude (ELA) at similar to 5800 m a.s.l.) to +0.46 +/- 0.28 m w.e. in 2010-2011 (ELA at similar to 5340 m a.s.l.), Mera Glacier has been shrinking at a moderate mass balance rate of -0.08 +/- 0.28 m w.e. yr(-1) since 2007. Ice fluxes measured at two distinct transverse cross sections at similar to 5350 m a.s.l. and similar to 5520 m a.s.l. confirm that the mean state of this glacier over the last one or two decades corresponds to a limited mass loss, in agreement with remotely-sensed region-wide mass balances of the Everest area. Seasonal mass balance measurements show that ablation and accumulation are concomitant in summer which in turn is the key season controlling the annual glacier-wide mass balance. Unexpectedly, ablation occurs at all elevations in winter due to wind erosion and sublimation, with remobilised snow potentially being sublimated in the atmosphere. Between 2009 and 2012, the small Pokalde Glacier lost mass more rapidly than Mera Glacier with respective mean glacier-wide mass balances of -0.72 and -0.23 +/- 0.28 m w.e. yr(-1). Low-elevation glaciers, such as Pokalde Glacier, have been usually preferred for in-situ observations in Nepal and more generally in the Himalayas, which may explain why compilations of ground-based mass balances are biased toward negative values compared with the regional mean under the present-day climate.
Published: 2013

41. Estimated range of black carbon dry deposition and the related snow albedo reduction over Himalayan glaciers during dry pre-monsoon periods

Author: K.-M. Lau, Toshihiko Takemura, Angela Marinoni, Qian Tan, Mian Chin, Paolo Laj, Teppei J. Yasunari, Martin Ménégoz, and Paolo Bonasoni
Subjects: Atmospheric Science, geography, geography.geographical_feature_category, Range (biology), Glacier, Carbon black, Albedo, Snow, Deposition (aerosol physics), Climatology, Surface roughness, Environmental science, Biomass burning, General Environmental Science
Abstract: One of the major factors attributed to the accelerated melting of Himalayan glaciers is the snow darkening effect of atmospheric black carbon (BC). The BC is the result of incomplete fossil fuel combustion from sources such as open biomass burning and wood burning cooking stoves. One of the key challenges in determining the darkening effect is the estimation uncertainty of BC deposition (BCD) rate on surface snow cover. Here we analyze the variation of BC dry deposition in seven different estimates based on different dry deposition methods which include different atmospheric forcings (observations and global model outputs) and different spatial resolutions. The seven simulations are used to estimate the uncertainty range of BC dry deposition over the southern Himalayas during pre-monsoon period (March–May) in 2006. Our results show BC dry deposition rates in a wide range of 270–4700 μg m −2 during the period. Two global models generate higher BC dry deposition rates due to modeled stronger surface wind and simplification of complicated sub-grid surface conditions in this region. Using ice surface roughness and observation-based meteorological data, we estimate a better range of BC dry deposition rate of 900–1300 μg m −2 . Under dry and highly polluted conditions, aged snow and sulfate-coated BC are expected to possibly reduce visible albedo by 4.2–5.1%. Our results suggest that for estimating aerosol-induced snow darkening effects of Himalaya snowpacks using global and regional models, realistic physical representation of ice or snow surface roughness and surface wind speed are critical in reducing uncertainties on the estimate of BC deposition over snow surface.
Published: 2013

42. Atmospheric drying as the main driver of dramatic glacier wastage in the southern Indian Ocean

Author: Yoann Malbeteau, Deborah Verfaillie, Vincent Rinterknecht, Jennifer E. Kay, Hubert Gallée, Vincent Jomelli, Etienne Berthier, Martin Ménégoz, Daniel Brunstein, Young-Hyang Park, Vincent Favier, L. Ducret, Laboratoire d'Ingénierie des Matériaux (LIM), Centre National de la Recherche Scientifique (CNRS), Laboratoire de glaciologie et géophysique de l'environnement (LGGE), Observatoire des Sciences de l'Univers de Grenoble [1985-2015] (OSUG [1985-2015]), Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology [2007-2019] (Grenoble INP [2007-2019])-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology [2007-2019] (Grenoble INP [2007-2019])-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'études en Géophysique et océanographie spatiales (LEGOS), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National d'Études Spatiales [Toulouse] (CNES)-Observatoire Midi-Pyrénées (OMP), Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Géographie Physique, LGP, Laboratoire de géographie physique : Environnements Quaternaires et Actuels (LGP), Centre National de la Recherche Scientifique (CNRS)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Université Panthéon-Sorbonne (UP1), Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Département Milieux et Peuplements Aquatiques, Muséum national d'Histoire naturelle (MNHN), SUPA School of Physics and Astronomy [St Andrews], University of St Andrews [Scotland], University of St Andrews. Earth and Environmental Sciences, University of St Andrews. Marine Alliance for Science & Technology Scotland, University of St Andrews. Scottish Oceans Institute, Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS), Barcelona Supercomputing Center - Centro Nacional de Supercomputacion (BSC - CNS), Cooperative Institute for Research in Environmental Sciences (CIRES), University of Colorado [Boulder]-National Oceanic and Atmospheric Administration (NOAA), Université Grenoble Alpes (UGA), Biogéochimie-Traceurs-Paléoclimat (BTP), Laboratoire d'Océanographie et du Climat : Expérimentations et Approches Numériques (LOCEAN), Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Muséum national d'Histoire naturelle (MNHN), Observatoire des Sciences de l'Univers de Grenoble (OSUG ), Institut polytechnique de Grenoble - Grenoble Institute of Technology [2007-2019] (Grenoble INP [2007-2019])-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology [2007-2019] (Grenoble INP [2007-2019])-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Centre National de la Recherche Scientifique (CNRS), Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Université Fédérale Toulouse Midi-Pyrénées-Centre National d'Études Spatiales [Toulouse] (CNES)-Météo France-Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS), Université Panthéon-Sorbonne (UP1)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Centre National de la Recherche Scientifique (CNRS), Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Grenoble (OSUG ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS), Université Paris 1 Panthéon-Sorbonne (UP1)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Centre National de la Recherche Scientifique (CNRS), Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Muséum national d'Histoire naturelle (MNHN)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Muséum national d'Histoire naturelle (MNHN)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), SUPA School of Physics and Astronomy [University of St Andrews], University of St Andrews [Scotland]-Scottish Universities Physics Alliance (SUPA), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), and Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)
Subjects: 010504 meteorology & atmospheric sciences, Atmospheric circulation, [SDE.MCG]Environmental Sciences/Global Changes, 010502 geochemistry & geophysics, 01 natural sciences, Article, Latitude, Glacier mass balance, SDG 13 - Climate Action, Precipitation, General, ComputingMilieux_MISCELLANEOUS, 0105 earth and related environmental sciences, GB, geography, GE, Multidisciplinary, geography.geographical_feature_category, Glacier, 3rd-DAS, Indian ocean, 13. Climate action, Climatology, [SDE]Environmental Sciences, GB Physical geography, Environmental science, Climate model, Storm track, GE Environmental Sciences
Abstract: This study was funded by IPEV-1048 GLACIOCLIM-KESAACO and LEFE-INSU KCRuMBLE programs, and the Agence Nationale de la Recherche through contract ANR-14-CE01-0001-01 (ASUMA). The ongoing retreat of glaciers at southern sub-polar latitudes is particularly rapid and widespread. Akin to northern sub-polar latitudes, this retreat is generally assumed to be linked to warming. However, no long-term and well-constrained glacier modeling has ever been performed to confirm this hypothesis. Here, we model the Cook Ice Cap mass balance on the Kerguelen Islands (Southern Indian Ocean, 49°S) since the 1850s. We show that glacier wastage during the 2000s in the Kerguelen was among the most dramatic on Earth. We attribute 77% of the increasingly negative mass balance since the 1960s to atmospheric drying associated with a poleward shift of the mid-latitude storm track. Because precipitation modeling is very challenging for the current generation of climate models over the study area, models incorrectly simulate the climate drivers behind the recent glacier wastage in the Kerguelen. This suggests that future glacier wastage projections should be considered cautiously where changes in atmospheric circulation are expected. Publisher PDF
Published: 2016

43. Glacier surface mass balance modeling in the inner tropics using a positive degree-day approach

Author: Vincent Jomelli, B. Caceres, L. Maisincho, Martin Ménégoz, L. Mourre, Vincent Favier, Marcos Villacís, Antoine Rabatel, R. Basantes Serrano, Patrick Wagnon, and B. Francou
Subjects: 0106 biological sciences, geography, geography.geographical_feature_category, Glacier, Noon, Snow, 010603 evolutionary biology, 01 natural sciences, Wind speed, Freezing level, 010602 entomology, Glacier mass balance, Climatology, Environmental science, Shortwave radiation, Glacier foreland
Abstract: We present a basic ablation model combining a positive degree-day approach to calculate melting and a simple equation based on wind speed to compute sublimation. The model was calibrated at point scale (4900 m a.s.l.) on Antizana Glacier 15 (0.28 km2; 0°28' S, 78°09' W) with data from March 2002 to August 2003 and validated with data from January to November 2005. Cross validation was performed by interchanging the calibration and validation periods. Optimization of the model based on the calculated surface energy balance allowed degree-day factors to be retrieved for snow and ice, and suggests that melting started when daily air temperature was still below 0 °C, because incoming shortwave radiation was intense around noon and resulted in positive temperatures for a few hours a day. The model was then distributed over the glacier and applied to the 2000–2008 period using meteorological inputs measured on the glacier foreland to assess to what extent this approach is suitable for quantifying glacier surface mass balance in Ecuador. Results showed that a model based on temperature, wind speed, and precipitation is able to reproduce a large part of surface mass-balance variability of Antizana Glacier 15 even though the melting factors for snow and ice may vary with time. The model performed well because temperatures were significantly correlated with albedo and net shortwave radiation. Because this relationship disappeared when strong winds result in mixed air in the surface boundary layer, this model should not be extrapolated to other tropical regions where sublimation increases during a pronounced dry season or where glaciers are located above the mean freezing level.
Published: 2016

44. Equilibrium of sinks and sources of sulphate over Europe: comparison between a six-year simulation and EMEP observations

Author: M. Legrand, D. Salas y Melia, Béatrice Josse, M. Martet, Martin Ménégoz, Vincent-Henri Peuch, I. Dombrowski-Etchevers, Martine Michou, and H. Teyssèdre
Subjects: lcsh:Chemistry, Atmospheric Science, lcsh:QD1-999, Climatology, Sulfur cycle, Precipitation, Chemical scheme, Atmospheric sciences, Annual cycle, Scavenging, lcsh:Physics, lcsh:QC1-999, Aerosol
Abstract: Sulphate distributions were simulated with a global chemistry transport model. A chemical scheme describing the sulphur cycle and the parameterisations of the main sinks for sulphate aerosols were included in the model. A six-year simulation was conducted from the years 2000 to 2005, driven by the ECMWF operational analyses. Emissions come from an inventory representative of the year 2000. This paper focuses on the analysis of the sulphate sinks and sources over Europe for the entire period of simulation. The Sulphate burden shows a marked annual cycle, which is the result of the annual variations of the aqueous and gaseous chemistry. Regionally, the monthly mean aerosol burden can vary by a factor of 2 from one year to another, because of different weather conditions, driving chemistry, transport and wet deposition of sulphate aerosols. Sulphate ground concentrations, scavenging fluxes and precipitation modelled were compared with observations. The model represents quite well sulphate fields over Europe, but has a general tendency to overestimate sulphate ground concentrations, in particular over Northern Europe. We assume that it is linked to the representation of the scavenging fluxes, which are underestimated. We suggest that uncertainties in modelled precipitation explain only partially the underestimation of the scavenging fluxes in the model.
Published: 2009

45. Black carbon in snow in the upper Himalayan Khumbu Valley, Nepal: observations and modeling of the impact on snow albedo, melting, and radiative forcing

Author: P. Laj, S. Lim, Hans-Werner Jacobi, Paolo Stocchi, Paolo Bonasoni, Martin Ménégoz, Yves Arnaud, Patrick Ginot, Angela Marinoni, Laboratoire de glaciologie et géophysique de l'environnement (LGGE), Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS), Institut Català de Ciències del Clima (IC3), CNR Institute of Atmospheric Sciences and Climate (ISAC), Consiglio Nazionale delle Ricerche (CNR), EV-K2-CNR Committee, Bergamo, Italy, Laboratoire d'étude des transferts en hydrologie et environnement (LTHE), Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique de Grenoble (INPG)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA), Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS), Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Grenoble (OSUG), and Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)
Subjects: 010504 meteorology & atmospheric sciences, 0207 environmental engineering, 02 engineering and technology, black carbon, Atmospheric sciences, Monsoon, medicine.disease_cause, 01 natural sciences, Radiative transfer, medicine, 020701 environmental engineering, lcsh:Environmental sciences, climate modeling, 0105 earth and related environmental sciences, Earth-Surface Processes, Water Science and Technology, lcsh:GE1-350, geography, geography.geographical_feature_category, Himalayas, lcsh:QE1-996.5, Snow grains, Glacier, Radiative forcing, Snowpack, Snow, Soot, lcsh:Geology, 13. Climate action, Climatology, [SDE]Environmental Sciences, Environmental science, albedo
Abstract: International audience; Black carbon (BC) in snow in the Himalayas has recently attracted considerable interest due to its impact on snow albedo, snow and glacier melting, regional climate and water resources. A single particle soot photometer (SP2) instrument was used to measure refractory BC (rBC) in a series of surface snow samples collected in the upper Khumbu Valley, Nepal between November 2009 and February 2012. The obtained time series indicates annual cycles with maximum rBC concentrations before the onset of the monsoon season and fast decreases during the monsoon period. Detected concentrations ranged from a few up to 70 ppb with rather large uncertainties due to the handling of the samples. Detailed modeling of the snowpack, including the detected range and an estimated upper limit of BC concentrations, was performed to study the role of BC in the seasonal snowpack. Simulations were performed for three winter seasons with the snowpack model Crocus, including a detailed description of the radiative transfer inside the snowpack. While the standard Crocus model strongly overestimates the height and the duration of the seasonal snowpack, a better calculation of the snow albedo with the new radiative transfer scheme enhanced the representation of the snow. However, the period with snow on the ground without BC in the snow was still overestimated between 37 and 66 days, which was further diminished by 8 to 15 % and more than 40 % in the presence of 100 or 300 ppb of BC. Compared to snow without BC, the albedo is reduced on average by 0.027 and 0.060 in the presence of 100 and 300 ppb BC. While the impact of increasing BC in the snow on the albedo was largest for clean snow, the impact on the local radiative forcing is the opposite. Here, increasing BC caused an even larger impact at higher BC concentrations. This effect is related to an accelerated melting of the snowpack caused by a more efficient meta-morphism of the snow due to an increasing size of the snow grains with increasing BC concentrations. The melting of the winter snowpack was shifted by 3 to 10 and 17 to 27 days during the three winter seasons in the presence of 100 and 300 ppb BC compared to clean snow, while the simulated annual local radiative forcing corresponds to 3 to 4.5 and 10.5 to 13.0 W m −2. An increased sublimation or evaporation of the snow reduces the simulated radiative forcing, leading to a net forcing that is lower by 0.5 to 1.5 W m −2 , while the addition of 10 ppm dust causes an increase of the radiative forcing between 2.5 and 3 W m −2. According to the simula-Published by Copernicus Publications on behalf of the European Geosciences Union. 1686 H.-W. Jacobi et al.: Black carbon in snow in the upper Himalayan Khumbu Valley tions, 7.5 ppm of dust has an effect equivalent to 100 ppb of BC concerning the impact on the melting of the snowpack and the local radiative forcing.
Published: 2015

46. Recent glacier decline in the Kerguelen Islands (49°S, 69°E) derived from modeling, field observations, and satellite data

Author: Yves Frenot, Marie Dumont, Vincent Favier, Vincent Rinterknecht, Daniel Brunstein, Martin Ménégoz, Adrien Gilbert, Hubert Gallée, Deborah Verfaillie, Vincent Jomelli, Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Laboratoire de glaciologie et géophysique de l'environnement (LGGE), Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Météo-France Direction Interrégionale Sud-Est (DIRSE), Météo-France, Laboratoire de géographie physique : Environnements Quaternaires et Actuels (LGP), Université Paris 1 Panthéon-Sorbonne (UP1)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Centre National de la Recherche Scientifique (CNRS), DEES, University of St Andrews [Scotland], Ecosystèmes, biodiversité, évolution [Rennes] (ECOBIO), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut Ecologie et Environnement (INEE), Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Rennes (OSUR), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2), Université de Rennes (UNIV-RENNES)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2), Université de Rennes (UNIV-RENNES)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Centre National de la Recherche Scientifique (CNRS), IPEV program 1048 (GLACIOCLIM-KESAACO), INSU program LEFE-KCRuMBLE, Université de Rennes (UR)-Institut Ecologie et Environnement (INEE), Université de Rennes (UR)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Centre National de la Recherche Scientifique (CNRS), University of St Andrews. Earth and Environmental Sciences, University of St Andrews. Marine Alliance for Science & Technology Scotland, University of St Andrews. Scottish Oceans Institute, Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire des Sciences de l'Univers de Grenoble (OSUG), Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry]), Météo France, Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Rennes (OSUR)-Institut Ecologie et Environnement (INEE), Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES), Université Grenoble Alpes (UGA), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Université Panthéon-Sorbonne (UP1), and Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Rennes (OSUR)-Centre National de la Recherche Scientifique (CNRS)
Subjects: GB, geography, geography.geographical_feature_category, 010504 meteorology & atmospheric sciences, NDAS, Elevation, Glacier, Albedo, 010502 geochemistry & geophysics, Spatial distribution, Snow, 01 natural sciences, QE Geology, Glacier mass balance, Geophysics, 13. Climate action, Climatology, GB Physical geography, [SDE]Environmental Sciences, Snow line, QE, Moderate-resolution imaging spectroradiometer, Geology, 0105 earth and related environmental sciences, Earth-Surface Processes
Abstract: Date of Acceptance: 28/02/2015 The retreat of glaciers in the Kerguelen Islands (49°S, 69°E) and their associated climatic causes have been analyzed using field data and Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images to validate a positive degree-day (PDD) model forced by data from local meteorological stations. Mass balance measurements made during recent field campaigns on the largest glacier of the Cook Ice Cap were compared to data from the early 1970s, providing a 40 year view of the differences in the spatial distribution of surface mass balance (SMB). To obtain additional regional data for the validation of our models, we analyzed MODIS images (2000-2012) to determine if our model was capable of reproducing variations in the transient snow line. The PDD model correctly simulated the variations in the snow line, the spatial variations in the SMB, and its trend with elevation. Yet current SMB values diverge from their classic linear representation with elevation, and stake data at high altitudes now display more negative SMB values than expected. By analyzing MODIS albedo, we observed that these values are caused by the disappearance of snow and associated feedback on melt rates. In addition, certain parts of Ampere Glacier could not be reproduced by the surface energy balance model because of overaccumulation due to wind deposition. Finally, the MODIS data, field data, and our models suggest that the acceleration of glacier wastage in Kerguelen is due to reduced net accumulation and an associated rise in the snow line since the 1970s. Publisher PDF
Published: 2015

47. Precipitation and snow cover in the Himalaya: from reanalysis to regional climate simulations

Author: Hans-Werner Jacobi, Hubert Gallée, and Martin Ménégoz
Subjects: lcsh:GE1-350, geography, Plateau, geography.geographical_feature_category, Rain gauge, lcsh:T, lcsh:Geography. Anthropology. Recreation, Monsoon, Atmospheric sciences, Snow, lcsh:Technology, lcsh:TD1-1066, lcsh:G, Climatology, Dry season, Environmental science, Spatial variability, Climate model, Precipitation, lcsh:Environmental technology. Sanitary engineering, lcsh:Environmental sciences
Abstract: We applied a Regional Climate Model (RCM) to simulate precipitation and snow cover over the Himalaya, between March 2000 and December 2002. Due to its higher resolution, our model simulates a more realistic spatial variability of wind and precipitation than those of the reanalysis of the European Centre of Medium range Weather Forecast (ECMWF) used as lateral boundaries. In this region, we found very large discrepancies between the estimations of precipitation provided by reanalysis, rain gauges networks, satellite observations, and our RCM simulation. Our model clearly underestimates precipitation at the foothills of the Himalaya and in its eastern part. However, our simulation provides a first estimation of liquid and solid precipitation in high altitude areas, where satellite and rain gauge networks are not very reliable. During the two years of simulation, our model resembles the snow cover extent and duration quite accurately in these areas. Both snow accumulation and snow cover duration differ widely along the Himalaya: snowfall can occur during the whole year in western Himalaya, due to both summer monsoon and mid-latitude low pressure systems bringing moisture into this region. In Central Himalaya and on the Tibetan Plateau, a much more marked dry season occurs from October to March. Snow cover does not have a pronounced seasonal cycle in these regions, since it depends both on the quite variable duration of the monsoon and on the rare but possible occurrence of snowfall during the extra-monsoon period.
Published: 2013

48. Current state of glaciers in the tropical Andes: a multi-century perspective on glacier evolution and climate change

Author: Rubén Basantes, Antoine Rabatel, Bernard Francou, J. Gomez, Edson Ramirez, G. Consoli, M. Scheel, Alvaro Soruco, Jorge Luis Ceballos, J. Mendoza, Remigio Galarraga, Pierre Ribstein, B. Caceres, Marcos Villacís, L. Maisincho, Mathias Vuille, Christian Huggel, Vincent Jomelli, Martin Ménégoz, Yves Arnaud, Patrick Wagnon, Wilson Suarez, Yves Lejeune, Manuel Collet, Jean-Emmanuel Sicart, Patrick Ginot, Vincent Favier, Thomas Condom, Laboratoire de glaciologie et géophysique de l'environnement (LGGE), Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), CHYC, Laboratoire d'étude des transferts en hydrologie et environnement (LTHE), Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS), Universidad Mayor de San Andrés (UMSA), ANA, UGRH, INAMHI (INAMHI), Ministerio de Minas y Energia, Meteorología y Estudios Ambientales ? IDEAM, Department of Atmospheric and Environmental Sciences [Albany] (DAES), University at Albany [SUNY], State University of New York (SUNY)-State University of New York (SUNY), Department of Geography [Zürich], Universität Zürich [Zürich] = University of Zurich (UZH), Météo-France Direction Interrégionale Sud-Est (DIRSE), Météo-France, Escuela Politécnica Nacional (EPN), CLIPS, Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Grenoble (OSUG), Laboratoire de géographie physique : Environnements Quaternaires et Actuels (LGP), Université Paris 1 Panthéon-Sorbonne (UP1)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Centre National de la Recherche Scientifique (CNRS), Structure et fonctionnement des systèmes hydriques continentaux (SISYPHE), Université Pierre et Marie Curie - Paris 6 (UPMC)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Mines Paris - PSL (École nationale supérieure des mines de Paris), Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS), SENAMHI, French IRD (Institut de Recherche pour le Developpement) through the Andean part of the French glaciers observatory service: GLACIOCLIM, French IRD (Institut de Recherche pour le Developpement) through the JEAI-IMAGE, Swiss Agency for Development and Cooperation, Swiss Federal Office for the Environment, Servicio Nacional de Meteorologia e Hidrologia del Peru, Helvetas Swiss Intercooperation, US-NSF, US State Department, CARE, CNES/SPOT-Image ISIS program [503], CNRS-INSU, [SENESCYT-EPN-PIC-08-506], Comunidad Andina de Naciones (CAN), World Bank, Inter-American Institute, Observatoire des Sciences de l'Univers de Grenoble [1985-2015] (OSUG [1985-2015]), Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology [2007-2019] (Grenoble INP [2007-2019])-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology [2007-2019] (Grenoble INP [2007-2019])-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS), aucun, IGEMA, Universidad de Extremadura (UEX), Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique de Grenoble (INPG)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire des Sciences de l'Univers de Grenoble [1985-2015] (OSUG [1985-2015]), Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology [2007-2019] (Grenoble INP [2007-2019])-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology [2007-2019] (Grenoble INP [2007-2019])-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique de Grenoble (INPG)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire des Sciences de l'Univers de Grenoble [1985-2015] (OSUG [1985-2015]), Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology [2007-2019] (Grenoble INP [2007-2019])-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology [2007-2019] (Grenoble INP [2007-2019])-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry]), Unité de Recherche Great Ice, Glaciology and Geomorphodynamics Group, Department of geography, Synchrotron SOLEIL, Hydrologie-Hydraulique (UR HHLY), Centre national du machinisme agricole, du génie rural, des eaux et forêts (CEMAGREF), Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology [2007-2019] (Grenoble INP [2007-2019])-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology [2007-2019] (Grenoble INP [2007-2019])-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Grenoble [1985-2015] (OSUG [1985-2015]), Université de Rennes 1 - Faculté de Médecine (UR1 Médecine), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES), Institut des Géosciences de l’Environnement (IGE), Institut de Recherche pour le Développement (IRD)-Institut polytechnique de Grenoble - Grenoble Institute of Technology [2007-2019] (Grenoble INP [2007-2019])-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Laboratoire d'Ingénierie des Matériaux (LIM), Université Panthéon-Sorbonne (UP1)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Centre National de la Recherche Scientifique (CNRS), Institut des Sciences de la Terre [2011-2015] (ISTerre [2011-2015]), Université Joseph Fourier - Grenoble 1 (UJF)-Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-Institut national des sciences de l'Univers (INSU - CNRS)-Institut de recherche pour le développement [IRD] : UR219-PRES Université de Grenoble-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS), Instituto Nacional de Meteorología en Hidrología, inconnu, Inconnu, Milieux Environnementaux, Transferts et Interactions dans les hydrosystèmes et les Sols (METIS), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS), DEPARTMENT OF CIVIL AND ENVIRONMENTAL ENGINEERING NATIONAL POLYTECHNIC SCHOOL QUITO ECU, Partenaires IRSTEA, Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), University of Zurich, Rabatel, A, Centre national de recherches météorologiques (CNRM), Institut national des sciences de l'Univers (INSU - 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CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Laboratoire de géographie physique (LGP), Université Paris 1 Panthéon-Sorbonne (UP1)-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS), Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS), Groupe d'étude de l'atmosphère météorologique (CNRM-GAME), Institut national des sciences de l'Univers (INSU - CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique de Grenoble (INPG)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique de Grenoble (INPG)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA), UMSA, University of Zürich [Zürich] (UZH), Météo France, Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Grenoble (OSUG), Centre National de la Recherche Scientifique (CNRS)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Université Panthéon-Sorbonne (UP1), Université Pierre et Marie Curie - Paris 6 (UPMC)-École pratique des hautes études (EPHE)-MINES ParisTech - École nationale supérieure des mines de Paris-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry]), Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Grenoble (OSUG), Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry]), Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-MINES ParisTech - École nationale supérieure des mines de Paris, and Université Pierre et Marie Curie - Paris 6 (UPMC)-École Pratique des Hautes Études (EPHE)
Subjects: 010504 meteorology & atmospheric sciences, [SDE.MCG]Environmental Sciences/Global Changes, 0207 environmental engineering, 1904 Earth-Surface Processes, Climate change, purl.org/pe-repo/ocde/ford#1.05.10 [https], Context (language use), 02 engineering and technology, 01 natural sciences, Tropósfera, Precipitación, Glacier mass balance, Conservación de glaciares, 2312 Water Science and Technology, Glaciares, Cambio climático, Precipitation, Surge, 910 Geography & travel, [SDU.STU.HY]Sciences of the Universe [physics]/Earth Sciences/Hydrology, 020701 environmental engineering, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, Monitoreo de lagunas y glaciares, lcsh:Environmental sciences, 0105 earth and related environmental sciences, Earth-Surface Processes, Water Science and Technology, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, lcsh:GE1-350, geography, geography.geographical_feature_category, lcsh:QE1-996.5, Accumulation zone, Glacier, Earth, 15. Life on land, [SDE.ES]Environmental Sciences/Environmental and Society, lcsh:Geology, Climatología, 10122 Institute of Geography, Surface Processes, 13. Climate action, purl.org/pe-repo/ocde/ford#1.05.11 [https], [SDU]Sciences of the Universe [physics], [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology, Climatology, [SDE]Environmental Sciences, Period (geology), Geology
Abstract: Original abstract: The aim of this paper is to provide the community with a comprehensive overview of the studies of glaciers in the tropical Andes conducted in recent decades leading to the current status of the glaciers in the context of climate change. In terms of changes in surface area and length, we show that the glacier retreat in the tropical Andes over the last three decades is unprecedented since the maximum extension of the Little Ice Age (LIA, mid-17th–early 18th century). In terms of changes in mass balance, although there have been some sporadic gains on several glaciers, we show that the trend has been quite negative over the past 50 yr, with a mean mass balance deficit for glaciers in the tropical Andes that is slightly more negative than the one computed on a global scale. A break point in the trend appeared in the late 1970s with mean annual mass balance per year decreasing from -0.2 m w.e. in the period 1964–1975 to -0.76 m w.e. in the period 1976–2010. In addition, even if glaciers are currently retreating everywhere in the tropical Andes, it should be noted that this is much more pronounced on small glaciers at low altitudes that do not have a permanent accumulation zone, and which could disappear in the coming years/decades. Monthly mass balance measurements performed in Bolivia, Ecuador and Colombia show that variability of the surface temperature of the Pacific Ocean is the main factor governing variability of the mass balance at the decadal timescale. Precipitation did not display a significant trend in the tropical Andes in the 20th century, and consequently cannot explain the glacier recession. On the other hand, temperature increased at a significant rate of 0.10 °C decade-1 in the last 70 yr. The higher frequency of El Niño events and changes in its spatial and temporal occurrence since the late 1970s together with a warming troposphere over the tropical Andes may thus explain much of the recent dramatic shrinkage of glaciers in this part of the world. Artículo en acceso abierto Proporciona un panorama completo de los estudios de glaciares en los Andes tropicales realizados en las últimas décadas que conduzcan al estado de los glaciares en el contexto del cambio climático. En cuanto a los cambios en la superficie y la longitud, muestra que el retroceso del glaciar en los Andes tropicales en las últimas tres décadas no tiene precedentes desde la extensión máxima de la Pequeña Edad de Hielo (LIA, mediados del siglo XVII a principios del siglo XVIII). Respecto a los cambios en el balance de masas, muestra que la tendencia ha sido negativa en los últimos 50 años.
Published: 2013

49. Boreal and temperate snow cover variations induced by black carbon emissions in the middle of the 21st century

Author: Gerhard Krinner, Anne Cozic, Olivier Boucher, Yves Balkanski, Martin Ménégoz, P. Ciais, Laboratoire de glaciologie et géophysique de l'environnement (LGGE), Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS), Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Modelling the Earth Response to Multiple Anthropogenic Interactions and Dynamics (MERMAID), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Calcul Scientifique (CALCULS), Laboratoire de Météorologie Dynamique (UMR 8539) (LMD), Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-École des Ponts ParisTech (ENPC)-École polytechnique (X)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC), ICOS-ATC (ICOS-ATC), Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS), Université Paris-Saclay-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS Paris)-École normale supérieure - Paris (ENS Paris), Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), and Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)
Subjects: lcsh:GE1-350, 010504 meteorology & atmospheric sciences, lcsh:QE1-996.5, Northern Hemisphere, Climate change, 010501 environmental sciences, 15. Life on land, [SDU.STU.ME]Sciences of the Universe [physics]/Earth Sciences/Meteorology, Atmospheric sciences, Snow, 01 natural sciences, Aerosol, lcsh:Geology, Atmosphere, Deposition (aerosol physics), Arctic, Boreal, 13. Climate action, Climatology, Environmental science, lcsh:Environmental sciences, 0105 earth and related environmental sciences, Earth-Surface Processes, Water Science and Technology
Abstract: International audience; We used a coupled climate-chemistry model to quantify the impacts of aerosols on snow cover north of 30 degrees N both for the present-day and for the middle of the 21st century. Black carbon (BC) deposition over continents induces a reduction in the mean number of days with snow at the surface (MNDWS) that ranges from 0 to 10 days over large areas of Eurasia and Northern America for the present-day relative to the pre-industrial period. This is mainly due to BC deposition during the spring, a period of the year when the remaining of snow accumulated during the winter is exposed to both strong solar radiation and a large amount of aerosol deposition induced themselves by a high level of transport of particles from polluted areas. North of 30 degrees N, this deposition flux represents 222 Gg BC month(-1) on average from April to June in our simulation. A large reduction in BC emissions is expected in the future in all of the Representative Concentration Pathway (RCP) scenarios. In particular, considering the RCP8.5 in our simulation leads to a decrease in the spring BC deposition down to 110 Gg month-1 in the 2050s. However, despite the reduction of the aerosol impact on snow, the MNDWS is strongly reduced by 2050, with a decrease ranging from 10 to 100 days from present-day values over large parts of the Northern Hemisphere. This reduction is essentially due to temperature increase, which is quite strong in the RCP8.5 scenario in the absence of climate mitigation policies. Moreover, the projected sea-ice retreat in the next decades will open new routes for shipping in the Arctic. However, a large increase in shipping emissions in the Arctic by the mid-21st century does not lead to significant changes of BC deposition over snow-covered areas in our simulation. Therefore, the MNDWS is clearly not affected through snow darkening effects associated with these Arctic ship emissions. In an experiment without nudging toward atmospheric reanalyses, we simulated however some changes of the MNDWS considering such aerosol ship emissions. These changes are generally not statistically significant in boreal continents, except in Quebec and in the West Siberian plains, where they range between -5 and -10 days. They are induced both by radiative forcings of the aerosols when they are in the snow and in the atmosphere, and by all the atmospheric feedbacks. These experiments do not take into account the feedbacks induced by the interactions between ocean and atmosphere as they were conducted with prescribed sea surface temperatures. Climate change by the mid-21st century could also cause biomass burning activity (forest fires) to become more intense and occur earlier in the season. In an idealised scenario in which forest fires are 50% stronger and occur 2 weeks earlier and later than at present, we simulated an increase in spring BC deposition of 21 Gg BC month(-1) over continents located north of 30 degrees N. This BC deposition does not impact directly the snow cover through snow darkening effects. However, in an experiment considering all the aerosol forcings and atmospheric feedbacks, except those induced by the ocean-atmosphere interactions, enhanced fire activity induces a significant decrease of the MNDWS reaching a dozen of days in Quebec and in Eastern Siberia.
Published: 2013

50. Boreal snow cover variations induced by aerosol emissions in the middle of the 21st century

Author: A. Cozic, P. Ciais, Martin Ménégoz, Olivier Boucher, Gerhard Krinner, and Y. Balkanski
Subjects: Boreal, Climatology, Environmental science, Atmospheric sciences, Snow cover, Aerosol
Abstract: We used a coupled climate-chemistry model to quantify the impacts of aerosols on snow cover both for the present-day and for the middle of the 21st century. Black carbon (BC) deposition over continents induces a reduction in the Mean Number of Days With Snow at the Surface (MNDWS) that ranges from 0 to 10 days over large areas of Eurasia and Northern America for the present-day relative to the pre-industrial period. This is mainly due to BC deposition during the spring, a period of the year when the remaining of snow accumulated during the winter is exposed to both strong solar radiation and large amount of aerosol deposition induced themselves by a high level of transport of particles from polluted areas. North of 30° N, this deposition flux represents 222 Gg BC month−1 on average from April to June in our simulation. A large reduction in BC emissions is expected in the future in the Radiative Concentration Pathway (RCP) scenarios. Considering this scenario in our simulation leads to a decrease in the spring BC deposition down to 110 Gg month−1 in the 2050s in the RCP8.5 scenario. However, despite the reduction of the aerosol impact on snow, the MNDWS is strongly reduced by 2050, with a decrease ranging from 10 to 100 days from pre-industrial values over large parts of the Northern Hemisphere. This reduction is essentially due to temperature increase, which is quite strong in the RCP8.5 scenario in the absence of climate mitigation policies. Moreover, the projected sea-ice retreat in the next decades will open new routes for shipping in the Arctic. However, a large increase in shipping emissions in the Arctic by the mid 21st century does not lead to significant changes of BC deposition over snow-covered areas in our simulation. Therefore, the MNDWS is clearly not affected through snow darkening effects associated to these Arctic ship emissions. In an experiment without nudging toward atmospheric reanalyses, we simulated however some changes of the MNDWS considering such aerosol ship emissions. These changes are generally not statistically significant in boreal continents, except in the Quebec and in the West Siberian plains, where they range between −5 and −10 days. They are induced both by radiative forcings of the aerosols when they are in the atmosphere, and by all the atmospheric feedbacks. Climate change by the mid 21st century could also cause biomass burning activity (forest fires) to become more intense and occur earlier in the season. In an idealized scenario in which forest fires are 50% stronger and occur 2 weeks earlier than at present, we simulated an increase in spring BC deposition of 21 Gg BC month−1 over continents located north of 30° N. This BC deposition does not impact directly the snow cover through snow darkening effects. However, in an experiment considering all the aerosol forcings and atmospheric feedbacks, enhanced fire activity induces a significant decrease of the MNDWS reaching a dozen of days in Quebec and in Eastern Siberia.
Published: 2012

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