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18 results on '"Atmospheric and Environmental Research, Inc. (AER)"'

1. Impact of Continental Freshwater Runoff on Coastal Sea Level

Author: Rui M. Ponte, Christopher G. Piecuch, Jamal Uddin Khan, Sherin V. Raju, Fabrice Papa, Fabien Durand, Melanie Becker, 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-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), Woods Hole Oceanographic Institution (WHOI), LIttoral ENvironnement et Sociétés - UMRi 7266 (LIENSs), Université de La Rochelle (ULR)-Centre National de la Recherche Scientifique (CNRS), Indo-French Cell for Water Sciences (IFCWS), Indian Institute of Science [Bangalore] (IISc Bangalore), Institute of Water and Flood Management, Bangladesh University of Engineering and Technology, Atmospheric and Environmental Research, Inc. (AER), ANR-17-CE03-0001,DELTA,Les deltas sous l'impact du changement global(2017), 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), LIttoral ENvironnement et Sociétés (LIENSs), and La Rochelle Université (ULR)-Centre National de la Recherche Scientifique (CNRS)
Subjects: 010504 meteorology & atmospheric sciences, [SDE.MCG]Environmental Sciences/Global Changes, Baroclinity, Observational techniques, Forcing (mathematics), 010502 geochemistry & geophysics, 01 natural sciences, Current (stream), Geophysics, Oceanography, 13. Climate action, Geochemistry and Petrology, Others, Barotropic fluid, Environmental science, 14. Life underwater, Temporal scales, Surface runoff, Sea level, 0105 earth and related environmental sciences
Abstract: International audience; Freshwater discharge to the coastal ocean is a fundamental component of the global water cycle. It can impact coastal sea level over a broad range of spatial and temporal scales. Here we review the status of the current knowledge based on observational and modeling approaches. The main limitation in studies of the influence of rivers on coastal sea level has been the lack of consolidated discharge databases. We first provide an inventory of the main data sources currently available. We then review the existing knowledge about the runoff forcing of coastal sea level, differentiating between the mass and steric height contributions. Both mechanisms are important for coastal sea level budget, although they act on different scales. The mass contribution is related to a global ocean response that is established on relatively short timescales through barotropic processes while the steric contribution is associated with more of a regional adjustment that takes place on longer timescales by means of baroclinic dynamics. While numerical models required to simulate the runoff impact on coastal sea level variability have been improving over the past decades , a similar evolution is awaited for observational techniques, both for in situ observation and for remote sensing.
Published: 2019
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2. Atmospheric ammonia variability and link with particulate matter formation: a case study over the Paris area

Author: C. Viatte, T. Wang, M. Van Damme, E. Dammers, F. Meleux, L. Clarisse, M. W. Shephard, S. Whitburn, P. F. Coheur, K. E. Cady-Pereira, C. Clerbaux, TROPO - LATMOS, Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS), Sorbonne Université (SU)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS), Sorbonne Université (SU)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS), Spectroscopy, Quantum Chemistry and Atmospheric Remote Sensing (SQUARES), Université libre de Bruxelles (ULB), Environment and Climate Change Canada, Institut National de l'Environnement Industriel et des Risques (INERIS), and Atmospheric and Environmental Research, Inc. (AER)
Subjects: Pollution, Atmospheric Science, 010504 meteorology & atmospheric sciences, media_common.quotation_subject, Atmospheric model, 010501 environmental sciences, Infrared atmospheric sounding interferometer, Atmospheric sciences, 01 natural sciences, lcsh:Chemistry, medicine, Precipitation, 0105 earth and related environmental sciences, media_common, [PHYS.PHYS.PHYS-AO-PH]Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph], [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, Particulates, Seasonality, medicine.disease, lcsh:QC1-999, lcsh:QD1-999, 13. Climate action, HYSPLIT, Environmental science, Spatial variability, lcsh:Physics, Sciences exactes et naturelles
Abstract: The Paris megacity experiences frequent particulate matter (i.e.PM2.5, particulate matterwith a diameter less than 2.5 µm) pollution episodes in spring(March–April). At this time of the year, large numbers of the particlesconsist of ammonium sulfate and nitrate which are formed from ammonia(NH3) released during fertilizer spreading practices and transportedfrom the surrounding areas to Paris. There is still limited knowledge of theemission sources around Paris, their magnitude, and their seasonality. Using space-borne NH3 observation records of 10 years (2008–2017) and5 years (2013–2017) provided by the Infrared Atmospheric SoundingInterferometer (IASI) and the Cross-Track Infrared Sounder (CrIS)instrument, regional patterns of NH3 variabilities (seasonal andinterannual) are derived. Observations reveal identical high seasonalvariability with three major NH3 hotspots found from March to August.The high interannual variability is discussed with respect to atmospherictotal precipitation and temperature. A detailed analysis of the seasonal cycle is performed using both IASI andCrIS instrument data, together with outputs from the CHIMERE atmosphericmodel. For 2014 and 2015, the CHIMERE model shows coefficients ofdetermination of 0.58 and 0.18 when compared to IASI and CrIS,respectively. With respect to spatial variability, the CHIMERE monthlyNH3 concentrations in spring show a slight underrepresentation overBelgium and the United Kingdom and an overrepresentation in agricultural areasin the French Brittany–Pays de la Loire and Plateau du Jura region, as wellas in northern Switzerland. In addition, PM2.5 concentrationsderived from the CHIMERE model have been evaluated against surfacemeasurements from the Airparif network over Paris, with which agreement wasfound (r2 = 0.56) with however an underestimation during springpollution events. Using HYSPLIT cluster analysis of back trajectories, we show that NH3total columns measured in spring over Paris are enhanced when air massesoriginate from the north-east (e.g. the Netherlands and Belgium), highlightingthe importance of long-range transport in the NH3 budget over Paris.Variability in NH3 in the north-east region is likely to impact NH3concentrations in the Parisian region since the cross-correlation functionis above 0.3 (at lag = 0 and 1 d). Finally, we quantify the key meteorological parameters driving the specificconditions important for the formation of PM2.5 from NH3 in theÎle-de-France region in spring. Data-driven results based on surfacePM2.5 measurements from the Airparif network and IASI NH3measurements show that a combination of the factors such as a low boundarylayer of ∼500 m, a relatively low temperature of 5 ∘C, a high relative humidity of 70 %, and wind from the north-eastcontributes to a positive PM2.5 and NH3 correlation., info:eu-repo/semantics/published
Published: 2020
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3. CMIP5 model selection for ISMIP6 ice sheet model forcing: Greenland and Antarctica

Author: Christopher M. Little, Cécile Agosta, Heiko Goelzer, Sophie Nowicki, Helene Seroussi, Thomas J. Bracegirdle, Fiammetta Straneo, Nicolas C. Jourdain, Tore Hattermann, Alice Barthel, Los Alamos National Laboratory (LANL), 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), Glaces et Continents, Climats et Isotopes Stables (GLACCIOS), 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), Atmospheric and Environmental Research, Inc. (AER), Norwegian Polar Institute, 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), Institute for Marine and Atmospheric Research [Utrecht] (IMAU), Utrecht University [Utrecht], NASA Goddard Space Flight Center (GSFC), Jet Propulsion Laboratory (JPL), NASA-California Institute of Technology (CALTECH), Scripps Institution of Oceanography (SIO), University of California [San Diego] (UC San Diego), University of California-University of California, British Antarctic Survey (BAS), Natural Environment Research Council (NERC), ANR-15-CE01-0015,AC-AHC2,Circulation atmosphérique et changement de cycle hydrologique pour l'Arctique(2015), ANR-15-CE01-0005,TROIS-AS,Vers un système de modélisation régionale océan / calotte / atmosphère(2015), 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), 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 ), Scripps Institution of Oceanography (SIO - UC San Diego), University of California (UC)-University of California (UC), Sub Dynamics Meteorology, and Marine and Atmospheric Research
Subjects: 010504 meteorology & atmospheric sciences, 0207 environmental engineering, Forcing (mathematics), 02 engineering and technology, 010502 geochemistry & geophysics, 01 natural sciences, Atmosphere, 020701 environmental engineering, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, lcsh:Environmental sciences, Water Science and Technology, Earth-Surface Processes, 0105 earth and related environmental sciences, VDP::Mathematics and natural science: 400, lcsh:GE1-350, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, geography, geography.geographical_feature_category, Géologie et minéralogie, Continental shelf, Model selection, lcsh:QE1-996.5, VDP::Technology: 500, VDP::Matematikk og Naturvitenskap: 400, Ice-sheet model, lcsh:Geology, Sea surface temperature, VDP::Teknologi: 500, 13. Climate action, Climatology, Environmental science, Climate model, théorie et applications [Econométrie et méthodes statistiques], Ice sheet
Abstract: The ice sheet model intercomparison project for CMIP6 (ISMIP6) effort brings together the ice sheet and climate modeling communities to gain understanding of the ice sheet contribution to sea level rise. ISMIP6 conducts stand-alone ice sheet experiments that use space- and time-varying forcing derived from atmosphere-ocean coupled global climate models (AOGCMs) to reflect plausible trajectories for climate projections. The goal of this study is to recommend a subset of CMIP5 AOGCMs (three core and three targeted) to produce forcing for ISMIP6 stand-alone ice sheet simulations, based on (i) their representation of current climate near Antarctica and Greenland relative to observations and (ii) their ability to sample a diversity of projected atmosphere and ocean changes over the 21st century. The selection is performed separately for Greenland and Antarctica. Model evaluation over the historical period focuses on variables used to generate ice sheet forcing. For stage (i), we combine metrics of atmosphere and surface ocean state (annual- and seasonal-mean variables over large spatial domains) with metrics of time-mean subsurface ocean temperature biases averaged over sectors of the continental shelf. For stage (ii), we maximize the diversity of climate projections among the best-performing models. Model selection is also constrained by technical limitations, such as availability of required data from RCP2.6 and RCP8.5 projections. The selected top three CMIP5 climate models are CCSM4, MIROC-ESM-CHEM, and NorESM1-M for Antarctica and HadGEM2-ES, MIROC5, and NorESM1-M for Greenland. This model selection was designed specifically for ISMIP6 but can be adapted for other applications., SCOPUS: ar.j, info:eu-repo/semantics/published
Published: 2020
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4. Towards Comprehensive Observing and Modeling Systems for Monitoring and Predicting Regional to Coastal Sea Level

Author: Rui M. Ponte, Mark Carson, Mauro Cirano, Catia M. Domingues, Svetlana Jevrejeva, Marta Marcos, Gary Mitchum, R. S. W. van de Wal, Philip L. Woodworth, Michaël Ablain, Fabrice Ardhuin, Valérie Ballu, Mélanie Becker, Jérôme Benveniste, Florence Birol, Elizabeth Bradshaw, Anny Cazenave, P. De Mey-Frémaux, Fabien Durand, Tal Ezer, Lee-Lueng Fu, Ichiro Fukumori, Kathy Gordon, Médéric Gravelle, Stephen M. Griffies, Weiqing Han, Angela Hibbert, Chris W. Hughes, Déborah Idier, Villy H. Kourafalou, Christopher M. Little, Andrew Matthews, Angélique Melet, Mark Merrifield, Benoit Meyssignac, Shoshiro Minobe, Thierry Penduff, Nicolas Picot, Christopher Piecuch, Richard D. Ray, Lesley Rickards, Alvaro Santamaría-Gómez, Detlef Stammer, Joanna Staneva, Laurent Testut, Keith Thompson, Philip Thompson, Stefano Vignudelli, Joanne Williams, Simon D. P. Williams, Guy Wöppelmann, Laure Zanna, Xuebin Zhang, Atmospheric and Environmental Research, Inc. (AER), University of Hamburg, Institute for Marine and Antarctic Studies and Centre for Marine Socioecology, University of Tasmania [Hobart, Australia] (UTAS), National Oceanography Centre [Southampton] (NOC), University of Southampton, Institut Mediterrani d'Estudis Avancats (IMEDEA), Consejo Superior de Investigaciones Científicas [Madrid] (CSIC)-Universidad de las Islas Baleares (UIB), Natural Environment Research Council (NERC), Collecte Localisation Satellites (CLS), Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Centre National d'Études Spatiales [Toulouse] (CNES), Division Hydrographie Océanographie et Météorologie Militaire (HOM), Service hydrographique et océanographique de la Marine, LIttoral ENvironnement et Sociétés - UMRi 7266 (LIENSs), Université de La Rochelle (ULR)-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-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), Agence Spatiale Européenne (ESA), European Space Agency (ESA), Echanges Côte-Large (ECOLA), 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), Jet Propulsion Laboratory (JPL), NASA-California Institute of Technology (CALTECH), NOAA Geophysical Fluid Dynamics Laboratory (GFDL), National Oceanic and Atmospheric Administration (NOAA), Department of Atmospheric and Oceanic Sciences [Boulder] (ATOC), University of Colorado [Boulder], Bangor University, Bureau de Recherches Géologiques et Minières (BRGM) (BRGM), Institut des Géosciences de l’Environnement (IGE), Institut de Recherche pour le Développement (IRD)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Centre National d'Études Spatiales [Toulouse] (CNES), Woods Hole Oceanographic Institution (WHOI), Institute of Marine Sciences, Consiglio Nazionale delle Ricerche [Roma] (CNR), Department of Atmospheric, Oceanic and Planetary Physics [Oxford] (AOPP), University of Oxford [Oxford], CSIRO Marine and Atmospheric Research (CSIRO), Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), Sub Dynamics Meteorology, Marine and Atmospheric Research, LIttoral ENvironnement et Sociétés (LIENSs), La Rochelle Université (ULR)-Centre National de la Recherche Scientifique (CNRS), 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), Agence Spatiale Européenne = European Space Agency (ESA), 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), National Research Council of Italy | Consiglio Nazionale delle Ricerche (CNR), University of Oxford, National Aeronautics and Space Administration (US), Australian Research Council, National Science Foundation (US), Intergovernmental Oceanographic Commission of UNESCO, Natural Environment Research Council (UK), Engineering and Physical Sciences Research Council (UK), Netherlands Organization for Scientific Research, and European Commission
Subjects: 0106 biological sciences, coastal impacts, 010504 meteorology & atmospheric sciences, integrated observing system, lcsh:QH1-199.5, coastal, Ocean Engineering, Aquatic Science, Environmental Science (miscellaneous), lcsh:General. Including nature conservation, geographical distribution, Oceanography, 01 natural sciences, Data assimilation, 14. Life underwater, impacts, lcsh:Science, Sea level, [SDU.STU.OC]Sciences of the Universe [physics]/Earth Sciences/Oceanography, 0105 earth and related environmental sciences, Water Science and Technology, Global and Planetary Change, coastal sea level, business.industry, 010604 marine biology & hydrobiology, Ocean current, Environmental resource management, Geodetic datum, Future sea level, sea-level trends, Current (stream), coastal adaptation, 13. Climate action, observational gaps, coastal ocean modeling, Environmental science, lcsh:Q, Coastal impacts, business, Downscaling
Abstract: A major challenge for managing impacts and implementing effective mitigation measures and adaptation strategies for coastal zones affected by future sea level (SL) rise is our limited capacity to predict SL change at the coast on relevant spatial and temporal scales. Predicting coastal SL requires the ability to monitor and simulate a multitude of physical processes affecting SL, from local effects of wind waves and river runoff to remote influences of the large-scale ocean circulation on the coast. Here we assess our current understanding of the causes of coastal SL variability on monthly to multi-decadal timescales, including geodetic, oceanographic and atmospheric aspects of the problem, and review available observing systems informing on coastal SL. We also review the ability of existing models and data assimilation systems to estimate coastal SL variations and of atmosphere-ocean global coupled models and related regional downscaling efforts to project future SL changes. We discuss (1) observational gaps and uncertainties, and priorities for the development of an optimal and integrated coastal SL observing system, (2) strategies for advancing model capabilities in forecasting short-term processes and projecting long-term changes affecting coastal SL, and (3) possible future developments of sea level services enabling better connection of scientists and user communities and facilitating assessment and decision making for adaptation to future coastal SL change., RP was funded by NASA grant NNH16CT00C. CD was supported by the Australian Research Council (FT130101532 and DP 160103130), the Scientific Committee on Oceanic Research (SCOR) Working Group 148, funded by national SCOR committees and a grant to SCOR from the U.S. National Science Foundation (Grant OCE-1546580), and the Intergovernmental Oceanographic Commission of UNESCO/International Oceanographic Data and Information Exchange (IOC/IODE) IQuOD Steering Group. SJ was supported by the Natural Environmental Research Council under Grant Agreement No. NE/P01517/1 and by the EPSRC NEWTON Fund Sustainable Deltas Programme, Grant Number EP/R024537/1. RvdW received funding from NWO, Grant 866.13.001. WH was supported by NASA (NNX17AI63G and NNX17AH25G). CL was supported by NASA Grant NNH16CT01C. This work is a contribution to the PIRATE project funded by CNES (to TP). PT was supported by the NOAA Research Global Ocean Monitoring and Observing Program through its sponsorship of UHSLC (NA16NMF4320058). JS was supported by EU contract 730030 (call H2020-EO-2016, “CEASELESS”). JW was supported by EU Horizon 2020 Grant 633211, Atlantos.
Published: 2019
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5. Present and future of L-Band radiometry

Author: Rajat Bindlish, Dara Entekhabi, Jean-Pierre Wigneron, Yann Kerr, Nicolas Reut, Gary Lagerloef, Lars Kaleschke, Jacqueline Boutin, Nemesio Rodriguez-Fernandez, Tong Lee, Simon Yueh, Centre d'études spatiales de la biosphère (CESBIO), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), 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), Massachusetts Institute of Technology (MIT), NASA Goddard Space Flight Center (GSFC), Atmospheric and Environmental Research, Inc. (AER), ESR. Station d'Economie et Sociologie rurales, Interactions Sol Plante Atmosphère (UMR ISPA), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro), Processus et interactions de fine échelle océanique (PROTEO), 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), Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER), Université de Hambourg, 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 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 de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), 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: L band, [SDV]Life Sciences [q-bio], 0208 environmental biotechnology, 0211 other engineering and technologies, 02 engineering and technology, 020801 environmental engineering, L band radiometry, [SDE]Environmental Sciences, Environmental science, Radiometry, Satellite, Uniqueness, Orbit (control theory), Microwave radiometry, 021101 geological & geomatics engineering, Remote sensing
Abstract: International audience; After almost 9 years in orbit L band satellite radiometry has demonstrated its impacts and values for a wide range of science and applications. In some cases it has demonstrated its uniqueness for assessing key environmental variables and in many others its high impact.
Published: 2018
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6. Comparison of SMOS and SMAP soil moisture retrieval approaches using tower-based radiometer data over a vineyard field

Author: Ernesto Lopez-Baeza, Yann Kerr, Peggy O'Neill, Ahmad Al Bitar, P. Richaume, Heather Lawrence, Roberto Fernandez Moran, Gabrielle De Lannoy, Jean-Pierre Wigneron, Richard de Jeu, Arnaud Mialon, Simone Bircher, Mike Schwank, Thomas J. Jackson, Maciej Miernecki, University of Hamburg, Interactions Sol Plante Atmosphère (UMR ISPA), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro), Universitat de València (UV), Centre d'études spatiales de la biosphère (CESBIO), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), 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), Vrije universiteit = Free university of Amsterdam [Amsterdam] (VU), Atmospheric and Environmental Research, Inc. (AER), Hydrology and Remote Sensing Laboratory, US Department of Agriculture [Beltsville] (USDA), Gamma Remote Sensing, Swiss Federal Institute for Forest, Snow and Landscape Research WSL, European Centre for Medium-Range Weather Forecasts (ECMWF), VU University Amsterdam, Earth and Climate, and Amsterdam Global Change Institute
Subjects: 010504 meteorology & atmospheric sciences, Mean squared error, Meteorology, [SDE.MCG]Environmental Sciences/Global Changes, 0211 other engineering and technologies, Soil Science, 02 engineering and technology, Astrophysics::Cosmology and Extragalactic Astrophysics, 01 natural sciences, Physics::Geophysics, 14. Life underwater, Computers in Earth Sciences, Time series, 021101 geological & geomatics engineering, 0105 earth and related environmental sciences, Remote sensing, Atmospheric sounding, Valencia Anchor Station, Radiometer, Geology, Inversion (meteorology), SMAP, 15. Life on land, Brightness temperature, Soil water, Environmental science, Radiometry, Soil moisture retrieval, ELBARA, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, SMOS
Abstract: International audience; The objective of this study was to compare several approaches to soil moisture (SM) retrieval using l-band microwave radiometry. The comparison was based on a brightness temperature (TB) data set acquired since 2010 by the L-band radiometer ELBARA-II over a vineyard field at the Valencia Anchor Station (VAS) site. ELBARA-II, provided by the European Space Agency (ESA) within the scientific program of the SMOS (Soil Moisture and Ocean Salinity) mission, measures multiangular TB data at horizontal and vertical polarization for a range of incidence angles (30°–60°). Based on a three year data set (2010–2012), several SM retrieval approaches developed for spaceborne missions including AMSR-E (Advanced Microwave Scanning Radiometer for EOS), SMAP (Soil Moisture Active Passive) and SMOS were compared. The approaches include: the Single Channel Algorithm (SCA) for horizontal (SCA-H) and vertical (SCA-V) polarizations, the Dual Channel Algorithm (DCA), the Land Parameter Retrieval Model (LPRM) and two simplified approaches based on statistical regressions (referred to as ‘Mattar’ and ‘Saleh’). Time series of vegetation indices required for three of the algorithms (SCA-H, SCA-V and ‘Mattar’) were obtained from MODIS observations. The SM retrievals were evaluated against reference SM values estimated from a multiangular 2-Parameter inversion approach. As no in situ SM data was used, the evaluation made here is relative to the use of this specific reference data set. The results obtained with the current base line algorithms developed for SMAP (SCA-H and -V) are in very good agreement with the ‘reference’ SM data set derived from the multi-angular observations (R2 ≈ 0.90, RMSE varying between 0.035 and 0.056 m3/m3 for several retrieval configurations). This result showed that, provided the relationship between vegetation optical depth and a remotely-sensed vegetation index can be calibrated, the SCA algorithms can provide results very close to those obtained from multi-angular observations in this study area. The approaches based on statistical regressions provided similar results and the best accuracy was obtained with the ‘Saleh’ methods based on either bi-angular or bipolarization observations (R2 ≈ 0.93, RMSE ≈ 0.035 m3/m3). The LPRM and DCA algorithms were found to be slightly less successful in retrieving the ‘reference’ SM time series (R2 ≈ 0.75, RMSE ≈ 0.055 m3/m3). However, the two above approaches have the great advantage of not requiring any model calibrations previous to the SM retrievals.
Published: 2014
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7. Use of atmospheric angular momentum forecasts for UT1 predictions: analyses over CONT08

Author: D.A. Salstein, D. Gambis, Sébastien Lambert, Systèmes de Référence Temps Espace (SYRTE), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS), Rotation de la Terre et géodésie spatiale, Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Systèmes de référence célestes, and Atmospheric and Environmental Research, Inc. (AER)
Subjects: Angular momentum, Meteorology, Atmospheric circulation, International Earth Rotation and Reference Systems Service, Ranging, law.invention, Geophysics, Geochemistry and Petrology, law, Universal Time, Environmental science, Computers in Earth Sciences, [PHYS.ASTR]Physics [physics]/Astrophysics [astro-ph], Interplanetary spaceflight, Orbit determination, Reference frame
Abstract: International audience; Real-time orbit determination and interplanetary navigation require accurate predictions of the orientation of the Earth in the celestial reference frame and in particular that for Universal Time UT1. Much of the UT1 variations over periods ranging from hours to a couple of years are due to the global atmospheric circulation. Therefore, the axial atmospheric angular momentum (AAM) forecast series may be used as a proxy index to predict UT1. Our approach taking advantage of this fact is based on an adaptive procedure. It involves incorporating integrations of AAM estimates into UT1 series. The procedure runs on a routine basis using AAM forecasts that are based on the two meteorological series, from the US National Centers for Environmental Prediction and the Japan Meteorological Agency. It is pertinent to test the prediction method for the period that includes the special CONT08 campaign over which we expect a significant improvement in UT1 accuracy. The studies we carried out were aimed both to compare atmospheric forecasts and analyses, as well as to compare the skills of the UT1 forecasts based on the method with atmospheric forecasts and that using current statistical processes, as applied to the C04 Earth orientation parameters series derived by the International Earth rotation and Reference Systems service (IERS). Here we neglect the oceanic sub-diurnal and diurnal variations, as these signals are expected to be smaller than the UT1-equivalent of 100 mu s, when averaged over a few days. The prediction performances for a 2-day forecast are similar, but at a forecast horizon of a week, the AAM-based forecast is roughly twice as skillful as the statistically based one.
Published: 2011
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8. Satellite and In Situ Salinity: Understanding Near-Surface Stratification and Subfootprint Variability

Author: Ludovic Brucker, Andrea Santos-Garcia, Tong Lee, Jacqueline Boutin, Alexander Soloviev, Emmanuel P. Dinnat, Brian Ward, Wenqing Tang, Nicolas Reul, William E. Asher, Nadya T. Vinogradova, Nicolas Kolodziejczyk, Julian Schanze, Kyla Drushka, Jessica Anderson, Thomas Meissner, Yi Chao, Christophe Maes, Thierry Delcroix, W.L. Jones, R. Drucker, Lisan Yu, Gilles Reverdin, Interactions et Processus au sein de la couche de Surface Océanique (IPSO), 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 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), UCLA Joint Institute for Regional Earth System Science and Engineering (JIFRESSE), University of California [Los Angeles] (UCLA), University of California-University of California-NASA, Remote Sensing Solutions, University of Washington [Seattle], 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-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), School of Oceanography [Seattle], Jet Propulsion Laboratory (JPL), NASA-California Institute of Technology (CALTECH), Ifremer, Centre de Toulon, Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER), Earth and Space Research Institute [Seattle] (ESR), Nova Southeastern University (NSU), Woods Hole Oceanographic Institution (WHOI), Universities Space Research Association (USRA), GSFC Cryospheric Sciences Laboratory, NASA Goddard Space Flight Center (GSFC), Electrical and Computer Engineering Department [Orlando], University of Central Florida [Orlando] (UCF), Laboratoire de physique des océans (LPO), Institut de Recherche pour le Développement (IRD)-Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS), Remote Sensing Systems [Santa Rosa] (RSS), Atmospheric and Environmental Research, Inc. (AER), National University of Ireland [Galway] (NUI Galway), CNES, 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)), University of California (UC)-University of California (UC)-NASA, 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: Atmospheric Science, 010504 meteorology & atmospheric sciences, 0211 other engineering and technologies, Mesoscale meteorology, Stratification (water), 02 engineering and technology, [SDU.STU.ME]Sciences of the Universe [physics]/Earth Sciences/Meteorology, Atmospheric sciences, 01 natural sciences, western equatorial pacific, barrier layer, tropical oceans, north-atlantic, ocean salinity, 14. Life underwater, Water cycle, [SDU.STU.OC]Sciences of the Universe [physics]/Earth Sciences/Oceanography, 021101 geological & geomatics engineering, 0105 earth and related environmental sciences, Remote sensing, Radiometer, boundary-layer, pacific warm pool, Salinity, Ocean dynamics, band radiometer/scatterometer observations, 13. Climate action, polar-regions, air-sea interaction, Environmental science, Satellite, Microwave
Abstract: Remote sensing of salinity using satellite-mounted microwave radiometers provides new perspectives for studying ocean dynamics and the global hydrological cycle. Calibration and validation of these measurements is challenging because satellite and in situ methods measure salinity differently. Microwave radiometers measure the salinity in the top few centimeters of the ocean, whereas most in situ observations are reported below a depth of a few meters. Additionally, satellites measure salinity as a spatial average over an area of about 100 × 100 km2. In contrast, in situ sensors provide pointwise measurements at the location of the sensor. Thus, the presence of vertical gradients in, and horizontal variability of, sea surface salinity complicates comparison of satellite and in situ measurements. This paper synthesizes present knowledge of the magnitude and the processes that contribute to the formation and evolution of vertical and horizontal variability in near-surface salinity. Rainfall, freshwater plumes, and evaporation can generate vertical gradients of salinity, and in some cases these gradients can be large enough to affect validation of satellite measurements. Similarly, mesoscale to submesoscale processes can lead to horizontal variability that can also affect comparisons of satellite data to in situ data. Comparisons between satellite and in situ salinity measurements must take into account both vertical stratification and horizontal variability.
Published: 2016
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9. Compared performances of microwave passive soil moisture retrievals (SMOS) and active soil moisture retrievals (ASCAT) using land surface model estimates (MERRA-LAND)

Author: Marie Parrens, Philippe Richaume, Amen Al-Yaari, R. Fernandez, Yann Kerr, Ahmad Al Bitar, Agnès Ducharne, Wouter Dorigo, G. De Lannoy, Rolf H. Reichle, Arnaud Mialon, Jean-Pierre Wigneron, Wolfgang Wagner, Interactions Sol Plante Atmosphère (UMR ISPA), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro), Milieux Environnementaux, Transferts et Interactions dans les hydrosystèmes et les Sols (METIS), 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)-Centre National de la Recherche Scientifique (CNRS), Centre d'études spatiales de la biosphère (CESBIO), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), 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), Vienna University of Technology, Atmospheric and Environmental Research, Inc. (AER), Universitat de València (UV), IEEE Geoscience and Remote Sensing Society (GRSS). USA., Université Pierre et Marie Curie - Paris 6 (UPMC)-École Pratique des Hautes Études (EPHE), 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), 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 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 de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
Subjects: [SDE.MCG]Environmental Sciences/Global Changes, Biome, Climate change, [SDU.STU]Sciences of the Universe [physics]/Earth Sciences, Land cover, Vegetation, 15. Life on land, Scatterometer, Arid, Tundra, biomes, ASCAT, 13. Climate action, Climatology, Environmental science, soil moisture, Water content, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, Remote sensing, SMOS
Abstract: International audience; Performances of two global satellite-based surface soil moisture (SSM) retrievals with respect to model-based SSM derived from the MERRA (Modern-Era Retrospective analysis for Research and Applications) rea-nalysis were explored in this paper: (i) Soil Moisture and Ocean Salinity (SMOS; passive) Level-3 SSM (SMOSL3) and (ii) the Advanced Scatterometer (ASCAT; active) SSM. Temporal correlation was used to investigate the performance of SMOSL3 and ASCAT SSM products during the period 05/2010–2012 on a global basis. Both SMOSL3 and ASCAT (slightly better) captured well (R>0.70) the long-term variability of the modelled SSM, particularly, over the Indian subcontinent, the Great Plains of North America, and the Sahel. However, ASCAT had negative correlations in arid regions, in particular across the Sahara and the Arabian Peninsula. This may be due to complex scattering mechanisms over very dry surfaces. To explore the land cover dependence of the analyzed statistical indicators, the global correlation results were averaged per biome extracted from a global map of biomes. In general, SMOSL3 and ASCAT performances behaved differently from one biome to another. For SMOSL3, the highest average correlation was observed over “tropical semi-arid” (R = ∼ 0.5) and “temperate semi-arid” biomes, whereas for ASCAT, the highest correlations were observed over “tropical semi-arid” (R = ∼ 0.7) and “tropical humid” biomes. The poorest agreement for both SMOSL3 and ASCAT was generally found over “tundra” and “desert temperate” biomes, particularly for ASCAT. This study showed that the performance of both SMOSL3 and ASCAT is highly dependent on vegetation. We also showed that both of them provide complementary information on SSM, which implies a potential for data fusion which would be pertinent for the ESA climate change initiative (CCI).
Published: 2014
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10. Tropospheric methanol observations from space: retrieval evaluation and constraints on the seasonality of biogenic emissions

Author: Allen H. Goldstein, Lu Hu, Lieven Clarisse, Hanwant B. Singh, Carsten Warneke, Mark W. Shephard, Y. Xiao, Eric C. Apel, Barkley C. Sive, J. A. de Gouw, Cathy Clerbaux, Dylan B. Millet, Kelley C. Wells, Karen Cady-Pereira, Pierre-François Coheur, Spectroscopie de l'atmosphère, Service de Chimie Quantique et Photophysique, Université libre de Bruxelles (ULB), Atmospheric and Environmental Research, Inc. (AER), Environment and Climate Change Canada, Atmospheric and Climate Applications, Inc. (ACApps), TROPO - LATMOS, Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), Atmospheric Chemistry Division [Boulder], National Center for Atmospheric Research [Boulder] (NCAR), NOAA Earth System Research Laboratory (ESRL), National Oceanic and Atmospheric Administration (NOAA), Cooperative Institute for Research in Environmental Sciences (CIRES), University of Colorado [Boulder]-National Oceanic and Atmospheric Administration (NOAA), NASA Ames Research Center (ARC), Department of Environmental Science, Policy, and Management [Berkeley] (ESPM), University of California [Berkeley] (UC Berkeley), University of California (UC)-University of California (UC), Appalachian State University, University of North Carolina System (UNC), University of California [Berkeley], and University of California-University of California
Subjects: Atmospheric Science, Chemical transport model, 010504 meteorology & atmospheric sciences, Télédétection, [SDE.MCG]Environmental Sciences/Global Changes, 010501 environmental sciences, Infrared atmospheric sounding interferometer, Atmospheric sciences, 010502 geochemistry & geophysics, 01 natural sciences, Article, Troposphere, lcsh:Chemistry, Phénomènes atmosphériques, medicine, Leaf area index, 0105 earth and related environmental sciences, [PHYS.PHYS.PHYS-AO-PH]Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph], Seasonality, 15. Life on land, medicine.disease, lcsh:QC1-999, Trace gas, Sciences de la terre et du cosmos, Tropospheric Emission Spectrometer, lcsh:QD1-999, 13. Climate action, Environmental science, Satellite, lcsh:Physics
Abstract: Methanol retrievals from nadir-viewing space-based sensors offer powerful new information for quantifying methanol emissions on a global scale. Here we apply an ensemble of aircraft observations over North America to evaluate new methanol measurements from the Tropospheric Emission Spectrometer (TES) on the Aura satellite, and combine the TES data with observations from the Infrared Atmospheric Sounding Interferometer (IASI) on the MetOp-A satellite to investigate the seasonality of methanol emissions from northern midlatitude ecosystems. Using the GEOS-Chem chemical transport model as an intercomparison platform, we find that the TES retrieval performs well when the degrees of freedom for signal (DOFS) are above 0.5, in which case the model:TES regressions are generally consistent with the model:aircraft comparisons. Including retrievals with DOFS below 0.5 degrades the comparisons, as these are excessively influenced by the a priori. The comparisons suggest DOFS >0.5 as a minimum threshold for interpreting retrievals of trace gases with a weak tropospheric signal. We analyze one full year of satellite observations and find that GEOS-Chem, driven with MEGANv2.1 biogenic emissions, underestimates observed methanol concentrations throughout the midlatitudes in springtime, with the timing of the seasonal peak in model emissions 1-2 months too late. We attribute this discrepancy to an underestimate of emissions from new leaves in MEGAN, and apply the satellite data to better quantify the seasonal change in methanol emissions for midlatitude ecosystems. The derived parameters (relative emission factors of 11.0, 0.26, 0.12 and 3.0 for new, growing, mature, and old leaves, respectively, plus a leaf area index activity factor of 0.5 for expanding canopies with leaf area index, SCOPUS: ar.j, info:eu-repo/semantics/published
Published: 2012
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11. Subsurface emission effects in AMSR-E measurements: Implications for land surface microwave emissivity retrieval

Author: Jean-Luc Moncet, Alan E. Lipton, Christopher Grassotti, Gennady Uymin, Catherine Prigent, John F. Galantowicz, Pan Liang, Atmospheric and Environmental Research, Inc. (AER), Laboratoire d'Etude du Rayonnement et de la Matière en Astrophysique (LERMA), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université de Cergy Pontoise (UCP), and Université Paris-Seine-Université Paris-Seine-Centre National de la Recherche Scientifique (CNRS)
Subjects: Atmospheric Science, Ecology, Diurnal temperature variation, Equator, Paleontology, Soil Science, Forestry, Vegetation, Aquatic Science, Oceanography, Geophysics, Space and Planetary Science, Geochemistry and Petrology, Brightness temperature, Earth and Planetary Sciences (miscellaneous), Emissivity, International Satellite Cloud Climatology Project, Environmental science, Precipitation, Moderate-resolution imaging spectroradiometer, [PHYS.ASTR]Physics [physics]/Astrophysics [astro-ph], Earth-Surface Processes, Water Science and Technology, Remote sensing
Abstract: International audience; An analysis of land surface microwave emission time series shows that the characteristic diurnal signatures associated with subsurface emission in sandy deserts carry over to arid and semiarid regions worldwide. Prior work found that diurnal variation of Special Sensor Microwave/Imager (SSM/I) brightness temperatures in deserts was small relative to International Satellite Cloud Climatology Project land surface temperature (LST) variation and that the difference varied with surface type and was largest in sand sea regions. Here we find more widespread subsurface emission effects in Advanced Microwave Scanning Radiometer-EOS (AMSR-E) measurements. The AMSR-E orbit has equator crossing times near 01:30 and 13:30 local time, resulting in sampling when near-surface temperature gradients are likely to be large and amplifying the influence of emission depth on effective emitting temperature relative to other factors. AMSR-E measurements are also temporally coincident with Moderate Resolution Imaging Spectroradiometer (MODIS) LST measurements, eliminating time lag as a source of LST uncertainty and reducing LST errors due to undetected clouds. This paper presents monthly global emissivity and emission depth index retrievals for 2003 at 11, 19, 37, and 89 GHz from AMSR-E, MODIS, and SSM/I time series data. Retrieval model fit error, stability, self-consistency, and land surface modeling results provide evidence for the validity of the subsurface emission hypothesis and the retrieval approach. An analysis of emission depth index, emissivity, precipitation, and vegetation index seasonal trends in northern and southern Africa suggests that changes in the emission depth index may be tied to changes in land surface moisture and vegetation conditions.
Published: 2011
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12. Land surface microwave emissivities derived from AMSR-E and MODIS measurements with advanced quality control

Author: Catherine Prigent, Alan E. Lipton, Jean-Luc Moncet, Gennady Uymin, John F. Galantowicz, Christopher Grassotti, Pan Liang, Atmospheric and Environmental Research, Inc. (AER), Laboratoire d'Etude du Rayonnement et de la Matière en Astrophysique (LERMA), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université de Cergy Pontoise (UCP), Université Paris-Seine-Université Paris-Seine-Centre National de la Recherche Scientifique (CNRS), Instrumentation et télédétection, Laboratoire d'Etude du Rayonnement et de la Matière en Astrophysique et Atmosphères = Laboratory for Studies of Radiation and Matter in Astrophysics and Atmospheres (LERMA), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-CY Cergy Paris Université (CY)-École normale supérieure - Paris (ENS-PSL), and Université Paris sciences et lettres (PSL)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-CY Cergy Paris Université (CY)
Subjects: Atmospheric Science, Meteorology, Cloud cover, Soil Science, Climate change, Aquatic Science, Oceanography, Microwave emissivity, Geochemistry and Petrology, Earth and Planetary Sciences (miscellaneous), Emissivity, Earth-Surface Processes, Water Science and Technology, Remote sensing, Ecology, Spacecraft, business.industry, Paleontology, Forestry, Geophysics, Space and Planetary Science, Homogeneous, Environmental science, Moderate-resolution imaging spectroradiometer, business, [PHYS.ASTR]Physics [physics]/Astrophysics [astro-ph], Microwave
Abstract: International audience; A microwave emissivity database has been developed with data from the Advanced Microwave Scanning Radiometer-EOS (AMSR-E) and with ancillary land surface temperature (LST) data from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the same Aqua spacecraft. The primary intended application of the database is to provide surface emissivity constraints in atmospheric and surface property retrieval or assimilation. An additional application is to serve as a dynamic indicator of land surface properties relevant to climate change monitoring. The precision of the emissivity data is estimated to be significantly better than in prior databases from other sensors due to the precise collocation with high-quality MODIS LST data and due to the quality control features of our data analysis system. The accuracy of the emissivities in deserts and semiarid regions is enhanced by applying, in those regions, a version of the emissivity retrieval algorithm that accounts for the penetration of microwave radiation through dry soil with diurnally varying vertical temperature gradients. These results suggest that this penetration effect is more widespread and more significant to interpretation of passive microwave measurements than had been previously established. Emissivity coverage in areas where persistent cloudiness interferes with the availability of MODIS LST data is achieved using a classification-based method to spread emissivity data from less-cloudy areas that have similar microwave surface properties. Evaluations and analyses of the emissivity products over homogeneous snow-free areas are presented, including application to retrieval of soil temperature profiles. Spatial inhomogeneities are the largest in the vicinity of large water bodies due to the large water/land emissivity contrast and give rise to large apparent temporal variability in the retrieved emissivities when satellite footprint locations vary over time. This issue will be dealt with in the future by including a water fraction correction. Also note that current reliance on the MODIS day-night algorithm as a source of LST limits the coverage of the database in the Polar Regions. We will consider relaxing the current restrictions as part of future development.
Published: 2011
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13. Satellite monitoring of ammonia: A case study of the San Joaquin Valley

Author: Cathy Clerbaux, Mark W. Shephard, Karen Cady-Pereira, Franck Dentener, Lieven Clarisse, Martin Van Damme, Federico Karagulian, Daniel Hurtmans, Pierre-François Coheur, Spectroscopie de l'atmosphère, Service de Chimie Quantique et Photophysique, Université libre de Bruxelles (ULB), Atmospheric and Environmental Research, Inc. (AER), JRC Institute for Environment and Sustainability (IES), European Commission - Joint Research Centre [Ispra] (JRC), TROPO - LATMOS, Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS), and Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)
Subjects: Atmospheric Science, 010504 meteorology & atmospheric sciences, Meteorology, Soil Science, 010501 environmental sciences, Aquatic Science, Infrared atmospheric sounding interferometer, Oceanography, Atmospheric sciences, 01 natural sciences, Atmosphere, Troposphere, Altitude, Geochemistry and Petrology, Ammonia, Earth and Planetary Sciences (miscellaneous), Inversion temperature, 0105 earth and related environmental sciences, Earth-Surface Processes, Water Science and Technology, [PHYS.PHYS.PHYS-AO-PH]Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph], Ecology, Paleontology, Forestry, Remote sensing, Depth sounding, Geophysics, Tropospheric Emission Spectrometer, 13. Climate action, Space and Planetary Science, Environmental science, San Joaquin, Infrared
Abstract: International audience; Atmospheric ammonia (NH3) has recently been observed with infrared sounders from space. Here we present 1 year of detailed bidaily satellite retrievals with the Infrared Atmospheric Sounding Interferometer and some retrievals of the Tropospheric Emission Spectrometer over the San Joaquin Valley, California, a highly polluted agricultural production region. Several sensitivity issues are discussed related to the sounding of ammonia, in terms of degrees of freedom, averaging kernels, and altitude of maximum sensitivity and in relation to thermal contrast and concentration. We also discuss their seasonal dependence and sources of errors. We demonstrate boundary layer sensitivity of infrared sounders when there is a large thermal contrast between the surface and the bottom of the atmosphere. For the San Joaquin Valley, large thermal contrast is the case for daytime measurements in spring, summer, and autumn and for nighttime measurements in autumn and winter when a large negative thermal contrast is amplified by temperature inversion.
Published: 2010
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14. Multivariate quantification of landscape spatial heterogeneity using variogram models

Author: Jeffrey T. Morisette, Denis Allard, Sébastien Garrigues, Frédéric Baret, Atmospheric and Environmental Research, Inc. (AER), Biostatistique et Processus Spatiaux (BioSP), Institut National de la Recherche Agronomique (INRA), Environnement Méditerranéen et Modélisation des Agro-Hydrosystèmes (EMMAH), and Avignon Université (AU)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
Subjects: [SPI.OTHER]Engineering Sciences [physics]/Other, Spatial correlation, VARIOGRAM, MULTIVARIATE VARIOGRAM MODEL, STATIONARITY, DIGITAL IMAGE, LANDSCAPE STRUCTURE, RED AND NEAR INFRARED, SPATIAL HETEROGENEITY, LINEAR MODEL, LENGTH SCALE, SPATIAL STRUCTURE, MODERATE SPATIAL RESOLUTION, NDVI, 010504 meteorology & atmospheric sciences, télédétection, variogramme, 0211 other engineering and technologies, Soil Science, modélisation spatiale, 02 engineering and technology, Astrophysics::Cosmology and Extragalactic Astrophysics, hétérogénéité spatiale, 01 natural sciences, Normalized Difference Vegetation Index, lumière rouge et infra rouge, modèle linéaire, paysage, Computers in Earth Sciences, végétation, Variogram, Astrophysics::Galaxy Astrophysics, 021101 geological & geomatics engineering, 0105 earth and related environmental sciences, Remote sensing, Geology, Vegetation, Spectral bands, 15. Life on land, Spatial heterogeneity, échelle, Autre (Sciences de l'ingénieur), image numérique, Environmental science, Spatial variability, Scale (map)
Abstract: International audience; The monitoring of earth surface processes at a global scale requires high temporal frequency remote sensing observations provided up to now by moderate spatial resolution sensors (from 250 m to 7 kin). Non-linear estimation processes of land surface variables derived from remote sensing data can be biased by the surface spatial heterogeneity within the moderate spatial resolution pixel. Quantifying this surface spatial heterogeneity is thus required to correct non-linear estimation processes of land surface variables. The first step in this process is to properly characterize the scale of spatial variation of the processes structuring the landscape. Since the description of land surface processes generally involves various spectral bands, a multivariate approach to characterize the surface spatial heterogeneity from multi-spectral remote sensing observations has to be established. This work aims at quantifying the landscape spatial heterogeneity captured by red and near infrared high spatial resolution images using direct and cross-variograms modeled together with the geostatistical linear model of coregionalization. This model quantifies the overall spatial variability and correlation of red and near infrared reflectances over the scene. In addition, it provides an explicit understanding of the landscape spatial structures captured by red and near infrared reflectances and is thus appropriate to describe landscapes composed of areas with contrasted red and near infrared spectral properties. The application of the linear model of coregionalization to 18 contrasted landscapes provides a spatial signature of red and near infrared spectral properties characterizing each type of landscape. Low vegetation cover sites are characterized by positive spatial correlation between red and near infrared. The mosaic pattern of vegetation fields and bare soil fields over crop sites generates high and negative spatial correlation between red and near infrared and increases the spatial variability of red and near infrared. On forest sites, the important amount of vegetation limits the spatial variability of red and the shadow effects mainly captured by near infrared induce a low and positive spatial correlation between red and near infrared. Finally, the linear model of coregionalization applied to red and near infrared is shown to be more powerful than the univariate variogram modeling applied to NDVI because the second order stationarity hypothesis on which variogram modeling relies is more frequently verified for red and near infrared than for NDVI.
Published: 2008
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15. Validation of NO2 and HNO3 measurements from the Improved Limb Atmospheric Spectrometer (ILAS) with the version 5.20 retrieval algorithm

Author: David G. Johnson, Kenneth W. Jucks, Hermann Oelhaf, Takakiyo Nakazawa, Farahnaz Khosrawi, Yasuhiro Sasano, Gerald Wetzel, Shuji Aoki, Hitoshi Irie, Hiroshi Kanzawa, Bhaswar Sen, G. C. Toon, Hideaki Nakajima, Rolf Müller, Andreas Engel, Wesley A. Traub, Tatsuya Yokota, Takafumi Sugita, Solar-Terrestrial Environment Laboratory [Nagoya] (STEL), Nagoya University, Research Center for Advanced Science and Technology [Tokyo] (RCAST), The University of Tokyo (UTokyo), Department of Earth and Planetary Sciences [TITECH Tokyo], Tokyo Institute of Technology [Tokyo] (TITECH), Atmospheric and Environmental Research, Inc. (AER), Laboratoire de Physique moléculaire et applications (LPMA), Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS), Service d'aéronomie (SA), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), Institute for Meteorology and Climate Research (IMK), Karlsruhe Institute of Technology (KIT), Jet Propulsion Laboratory (JPL), NASA-California Institute of Technology (CALTECH), Naval Research Laboratory (NRL), NASA Langley Research Center [Hampton] (LaRC), Laboratoire de physique et chimie de l'environnement (LPCE), Institut national des sciences de l'Univers (INSU - CNRS)-Université d'Orléans (UO)-Centre National de la Recherche Scientifique (CNRS), National Institute for Environmental Studies (NIES), and Université d'Orléans (UO)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)
Subjects: Atmospheric Science, 010504 meteorology & atmospheric sciences, Meteorology, Instrumentation, Soil Science, Aquatic Science, Oceanography, 01 natural sciences, 010305 fluids & plasmas, Altitude, Geochemistry and Petrology, 0103 physical sciences, Earth and Planetary Sciences (miscellaneous), Stratosphere, Retrieval algorithm, 0105 earth and related environmental sciences, Earth-Surface Processes, Water Science and Technology, Remote sensing, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, Ecology, Spectrometer, Northern Hemisphere, Paleontology, Forestry, On board, Geophysics, 13. Climate action, Space and Planetary Science, Environmental science, Satellite
Abstract: [1] Measurements of CFC-12 were made by the Improved Limb Atmospheric Spectrometer (ILAS) between 57°N and 72°N in the Northern Hemisphere and between 64°S and 89°S in the Southern Hemisphere. ILAS was launched on 17 August 1996 on board the Advanced Earth Observing Satellite (ADEOS). The ILAS validation balloon campaigns were carried out from Kiruna, Sweden (68°N, 21°E), in February and March 1997 and from Fairbanks, Alaska (65°N, 148°W), in April and May 1997. During these validation balloon campaigns, CFC-12 was measured with the in situ instruments ASTRID, BONBON, and SAKURA and the remote sensing spectrometers MIPAS-B, FIRS-2, and MkIV. ILAS version 6.0 CFC-12 profiles obtained at the nearest location to the validation balloon measurement are compared with these validation balloon measurements. The quality of ILAS CFC-12 data processed with the version 6.0 algorithm improved significantly compared to previous versions. Low relative differences between ILAS CFC-12 and the correlative measurements of about 10% were found between 13 and 20 km. The comparison of vertical profiles shows that ILAS CFC-12 data are useful below about 20–22 km inside the vortex and below about 25 km outside the vortex. However, at greater altitudes the relative percentage difference increases very strongly with increasing altitude. Further, correlations of CFC-12 with N2O show a good agreement with the correlative measurements for N2O values of N2O > 150 ppbv. In summary, ILAS CFC-12 data are now suitable for scientific studies in the lower stratosphere.
Published: 2002
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16. Evaluation and intercomparison of global atmospheric transport models using 222Rn and other short‐lived tracers

Author: Run-Lie Shia, Gé Verver, Johann Feichter, K. S. Law, S. R. Beagley, Peter H. Zimmermann, Margaret Brown, Yves Balkanski, Philip J. Rasch, D. A. Rotman, Oliver Wild, I. Köhler, William L. Grose, Christophe Genthon, Hu Yang, Jane Dignon, Michel Ramonet, Michael J. Prather, Masaru Chiba, Prasad S. Kasibhatla, J. de Grandpré, Daniel Bergmann, Daniel J. Jacob, Peter van Velthoven, Mark A. Kritz, Martyn P. Chipperfield, Deianeira Z. Stockwell, Joyce E. Penner, Claire E. Reeves, W. T. Blackshear, Department of Earth and Planetary Sciences [Cambridge, USA] (EPS), Harvard University [Cambridge], University of California [Irvine] (UCI), University of California, National Center for Atmospheric Research [Boulder] (NCAR), Atmospheric and Environmental Research, Inc. (AER), Laboratoire de Modélisation du Climat et de l'Environnement (LMCE), York University [Toronto], Lawrence Livermore National Laboratory (LLNL), NASA Langley Research Center [Hampton] (LaRC), Department of Applied Mathematics [Seattle], University of Washington [Seattle], Meteorological Research Institute [Tsukuba] (MRI), Japan Meteorological Agency (JMA), Department of Chemistry [Cambridge, UK], University of Cambridge [UK] (CAM), Max-Planck-Institut für Meteorologie (MPI-M), Max-Planck-Gesellschaft, 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), School of Earth and Atmospheric Sciences [Atlanta], Georgia Institute of Technology [Atlanta], DLR Institut für Physik der Atmosphäre (IPA), Deutsches Zentrum für Luft- und Raumfahrt [Oberpfaffenhofen-Wessling] (DLR), Atmospheric Sciences Research Center (ASRC), University at Albany [SUNY], State University of New York (SUNY)-State University of New York (SUNY), Centre des Faibles Radioactivités, Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), School of Environmental and Life Sciences, University of East Anglia [Norwich] (UEA), Royal Netherlands Meteorological Institute (KNMI), Harvard University, University of California [Irvine] (UC Irvine), University of California (UC), 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), and Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Centre National de la Recherche Scientifique (CNRS)
Subjects: Convection, Atmospheric Science, 010504 meteorology & atmospheric sciences, Meteorology, Soil Science, Magnitude (mathematics), Zonal and meridional, 010501 environmental sciences, Aquatic Science, Oceanography, Atmospheric sciences, 01 natural sciences, Latitude, Troposphere, Geochemistry and Petrology, Atmospheric convection, Synoptic scale meteorology, Earth and Planetary Sciences (miscellaneous), 14. Life underwater, 0105 earth and related environmental sciences, Earth-Surface Processes, Water Science and Technology, [PHYS.PHYS.PHYS-AO-PH]Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph], [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, Ecology, Paleontology, Forestry, Numerical diffusion, Geophysics, 13. Climate action, Space and Planetary Science, Environmental science
Abstract: International audience; Simulations of 222Rn and other short‐lived tracers are used to evaluate and intercompare the representations of convective and synoptic processes in 20 global atmospheric transport models. Results show that most established three‐dimensional models simulate vertical mixing in the troposphere to within the constraints offered by the observed mean 222Rn concentrations and that subgrid parameterization of convection is essential for this purpose. However, none of the models captures the observed variability of 222Rn concentrations in the upper troposphere, and none reproduces the high 222Rn concentrations measured at 200 hPa over Hawaii. The established three‐dimensional models reproduce the frequency and magnitude of high‐222Rn episodes observed at Crozet Island in the Indian Ocean, demonstrating that they can resolve the synoptic‐scale transport of continental plumes with no significant numerical diffusion. Large differences between models are found in the rates of meridional transport in the upper troposphere (interhemispheric exchange, exchange between tropics and high latitudes). The four two‐dimensional models which participated in the intercomparison tend to underestimate the rate of vertical transport from the lower to the upper troposphere but show concentrations of 222Rn in the lower troposphere that are comparable to the zonal mean values in the three‐dimensional models.
Published: 1997
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17. Sensitivity analysis of a model of CO2exchange in tundra ecosystems by the adjoint method

Author: C. Waelbroeck, J.-F. Louis, Laboratoire de Modélisation du Climat et de l'Environnement (LMCE), and Atmospheric and Environmental Research, Inc. (AER)
Subjects: 0106 biological sciences, Atmospheric Science, 010504 meteorology & atmospheric sciences, Soil Science, Flux, Perturbation (astronomy), Aquatic Science, Oceanography, Atmospheric sciences, 010603 evolutionary biology, 01 natural sciences, Carbon cycle, Geochemistry and Petrology, Earth and Planetary Sciences (miscellaneous), Sensitivity (control systems), [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, Nitrogen cycle, Physics::Atmospheric and Oceanic Physics, 0105 earth and related environmental sciences, Earth-Surface Processes, Water Science and Technology, Positive feedback, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, Ecology, Paleontology, Primary production, Forestry, 15. Life on land, Tundra, Geophysics, 13. Climate action, Space and Planetary Science, Climatology, Environmental science
Abstract: International audience; A model of net primary production (NPP), decomposition, and nitrogen cycling in tundra ecosystems has been developed. The adjoint technique is used to study the sensitivity of the computed annual net CO2 flux to perturbations in initial conditions, climatic inputs, and model's main parameters describing current seasonal CO2 exchange in wet sedge tundra at Barrow, Alaska. The results show that net CO2 flux is most sensitive to parameters characterizing litter chemical composition and more sensitive to decomposition parameters than to NPP parameters. This underlines the fact that in nutrient-limited ecosystems, decomposition drives net CO2 exchange by controlling mineralization of main nutrients. The results also indicate that the shortterm (1 year) response of wet sedge tundra to CO2-induced warming is a significant increase in CO2 emission, creating a positive feedback to atmospheric CO2 accumulation. However, a cloudiness increase during the same year can severely alter this response and lead to either a slight decrease or a strong increase in emitted CO2, depending on its exact timing. These results demonstrate that the adjoint method is well suited to study systems encountering regime changes, as a single run of the adjoint model provides sensitivities of the net CO2 flux to perturbations in all parameters and variables at any time of the year. Moreover, it is shown that large errors due to the presence of thresholds can be avoided by first delimiting the range of applicability of the adjoint results.
Published: 1995
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18. The Polar Amplification Model Intercomparison Project (PAMIP) contribution to CMIP6: investigating the causes and consequences of polar amplification

Author: Doug Smith, Xiangdong Zhang, Michael Sigmond, John C. Fyfe, Jin-Ho Yoon, Yannick Peings, Jinro Ukita, Vladimir M. Kattsov, Judah Cohen, Clara Deser, Javier García-Serrano, Rym Msadek, Thomas Jung, Daniela Matei, James A. Screen, Department of Chemistry [Bath], University of Bath [Bath], National Center for Atmospheric Research [Boulder] (NCAR), Atmospheric and Environmental Research, Inc. (AER), Institut Català de Ciènces del Clima (IC3), Max Planck Institute for Meteorology (MPI-M), Max-Planck-Gesellschaft, NOAA Geophysical Fluid Dynamics Laboratory (GFDL), National Oceanic and Atmospheric Administration (NOAA), Department of Earth System Science [Irvine] (ESS), University of California [Irvine] (UCI), University of California-University of California, Niigata University, Atmospheric Sciences and Global Change Division, and Pacific Northwest National Laboratory (PNNL)
Subjects: Coupled model intercomparison project, geography, geography.geographical_feature_category, 010504 meteorology & atmospheric sciences, lcsh:QE1-996.5, Global warming, Polar Amplification, Climate change, Antarctic sea ice, 010502 geochemistry & geophysics, 01 natural sciences, Arctic ice pack, PAMIP, lcsh:Geology, 13. Climate action, Climatology, [SDE]Environmental Sciences, Sea ice, Polar amplification, Environmental science, Climate model, CMIP6, ComputingMilieux_MISCELLANEOUS, 0105 earth and related environmental sciences
Abstract: Polar amplification – the phenomenon where ex- ternal radiative forcing produces a larger change in surface temperature at high latitudes than the global average – is a key aspect of anthropogenic climate change, but its causes and consequences are not fully understood. The Polar Am- plification Model Intercomparison Project (PAMIP) contri- bution to the sixth Coupled Model Intercomparison Project (CMIP6; Eyring et al., 2016) seeks to improve our under- standing of this phenomenon through a coordinated set of numerical model experiments documented here. In partic- ular, PAMIP will address the following primary questions: (1) what are the relative roles of local sea ice and remote sea surface temperature changes in driving polar amplification? (2) How does the global climate system respond to changes in Arctic and Antarctic sea ice? These issues will be addressed with multi-model simulations that are forced with different combinations of sea ice and/or sea surface tempera- tures representing present-day, pre-industrial and future con- ditions. The use of three time periods allows the signals of interest to be diagnosed in multiple ways. Lower-priority tier experiments are proposed to investigate additional aspects and provide further understanding of the physical processes. These experiments will address the following specific ques- tions: what role does ocean–atmosphere coupling play in the response to sea ice? How and why does the atmospheric re- sponse to Arctic sea ice depend on the pattern of sea ice forcing? How and why does the atmospheric response to Arctic sea ice depend on the model background state? What have been the roles of local sea ice and remote sea surface temper- ature in polar amplification, and the response to sea ice, over the recent period since 1979? How does the response to sea ice evolve on decadal and longer timescales? A key goal of PAMIP is to determine the real-world sit- uation using imperfect climate models. Although the exper- iments proposed here form a coordinated set, we anticipate a large spread across models. However, this spread will be exploited by seeking “emergent constraints” in which model uncertainty may be reduced by using an observable quantity that physically explains the intermodel spread. In summary, PAMIP will improve our understanding of the physical pro- cesses that drive polar amplification and its global climate impacts, thereby reducing the uncertainties in future projec- tions and predictions of climate change and variability.
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18. The Polar Amplification Model Intercomparison Project (PAMIP) contribution to CMIP6: investigating the causes and consequences of polar amplification

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