273 results on '"Van Noije, Twan"'
Search Results
2. Air quality improvements are projected to weaken the Atlantic meridional overturning circulation through radiative forcing effects
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Hassan, Taufiq, Allen, Robert J., Liu, Wei, Shim, Sungbo, van Noije, Twan, Le Sager, Philippe, Oshima, Naga, Deushi, Makoto, Randles, Cynthia A., and O’Connor, Fiona M.
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- 2022
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3. Radiative effects of reduced aerosol emissions during the COVID-19 pandemic and the future recovery
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Fiedler, Stephanie, Wyser, Klaus, Rogelj, Joeri, and van Noije, Twan
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- 2021
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4. Recent improvements and maximum covariance analysis of aerosol and cloud properties in the EC-Earth3-AerChem model.
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Thomas, Manu Anna, Wyser, Klaus, Wang, Shiyu, Chatziparaschos, Marios, Georgakaki, Paraskevi, Costa-Surós, Montserrat, Gonçalves Ageitos, Maria, Kanakidou, Maria, García-Pando, Carlos Pérez, Nenes, Athanasios, van Noije, Twan, Le Sager, Philippe, and Devasthale, Abhay
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GLOBAL modeling systems ,ANALYSIS of covariance ,METEOROLOGICAL satellites ,CLOUD droplets ,AEROSOL analysis - Abstract
Given the importance of aerosols and clouds and their interactions in the climate system, it is imperative that the global Earth system models accurately represent processes associated with them. This is an important prerequisite if we are to narrow the uncertainties in future climate projections. In practice, this means that continuous model evaluations and improvements grounded in observations are necessary. Numerous studies in the past few decades have shown both the usability and the limitations of utilizing satellite-based observations in understanding and evaluating aerosol–cloud interactions, particularly under varying meteorological and satellite sensor sensitivity paradigms. Furthermore, the vast range of spatio-temporal scales at which aerosol and cloud processes occur adds another dimension to the challenges faced when evaluating climate models. In this context, the aim of this study is two-fold. (1) We evaluate the most recent, significant changes in the representation of aerosol and cloud processes implemented in the EC-Earth3-AerChem model in the framework of the EU project FORCeS compared with its previous CMIP6 version (Coupled Model Intercomparison Project Phase 6; https://pcmdi.llnl.gov/CMIP6/ , last access: 13 February 2019). We focus particularly on evaluating cloud physical properties and radiative effects, wherever possible, using a satellite simulator. We report on the overall improvements in the EC-Earth3-AerChem model. In particular, the strong warm bias chronically seen over the Southern Ocean is reduced significantly. (2) A statistical, maximum covariance analysis is carried out between aerosol optical depth (AOD) and cloud droplet (CD) effective radius based on the recent EC-Earth3-AerChem/FORCeS simulation to understand to what extent the Twomey effect can manifest itself in the larger spatio-temporal scales. We focus on the three oceanic low-level cloud regimes that are important due to their strong net cooling effect and where pollution outflow from the nearby continent is simultaneously pervasive. We report that the statistical covariability between AOD and CD effective radius is indeed dominantly visible even at the climate scale when the aerosol amount and composition are favourably preconditioned to allow for aerosol–cloud interactions. Despite this strong covariability, our analysis shows a strong cooling/warming in shortwave cloud radiative effects at the top of the atmosphere in our study regions associated with an increase/decrease in CD effective radius. This cooling/warming can be attributed to the increase/decrease in low cloud fraction, in line with previous observational studies. [ABSTRACT FROM AUTHOR]
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- 2024
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5. Recent improvements and maximum covariance analysis of aerosol and cloud properties in the EC-Earth3-AerChem model
- Author
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Thomas, Manu Anna, primary, Wyser, Klaus, additional, Wang, Shiyu, additional, Chatziparaschos, Marios, additional, Georgakaki, Paraskevi, additional, Costa-Surós, Montserrat, additional, Gonçalves Ageitos, Maria, additional, Kanakidou, Maria, additional, García-Pando, Carlos Pérez, additional, Nenes, Athanasios, additional, van Noije, Twan, additional, Le Sager, Philippe, additional, and Devasthale, Abhay, additional
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- 2024
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6. Recent improvements and maximum covariance analysis of aerosol and cloud properties in the EC-Earth3-AerChem model
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Thomas, Manu, Wyser, Klaus, Wang, Shiyu, Chatziparaschos, Marios, Georgakaki, Paraskevi, Costa-Suros, Montserrat, Goncalves Ageitos, Maria, Kanakidou, Maria, Garcia-Pando, Carlos Perez, Nenes, Athanasios, van Noije, Twan, Le Sager, Philippe, Devasthale, Abhay, Thomas, Manu, Wyser, Klaus, Wang, Shiyu, Chatziparaschos, Marios, Georgakaki, Paraskevi, Costa-Suros, Montserrat, Goncalves Ageitos, Maria, Kanakidou, Maria, Garcia-Pando, Carlos Perez, Nenes, Athanasios, van Noije, Twan, Le Sager, Philippe, and Devasthale, Abhay
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- 2024
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7. Strong increase in mortality attributable to ozone pollution under a climate change and demographic scenario
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Akritidis, Dimitris, primary, Bacer, Sara, additional, Zanis, Prodromos, additional, Georgoulias, Aristeidis K., additional, Chowdury, Sourangsu, additional, Horowitz, Larry W, additional, Naik, Vaishali, additional, O'Connor, Fiona M., additional, Keeble, James, additional, Le Sager, Philippe, additional, van Noije, Twan, additional, Zhou, Putian, additional, Turnock, Steven, additional, West, Jason, additional, Lelieveld, Jos, additional, and Pozzer, Andrea, additional
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- 2024
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8. Decomposing the effective radiative forcing of anthropogenic aerosols based on CMIP6 Earth system models.
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Kalisoras, Alkiviadis, Georgoulias, Aristeidis K., Akritidis, Dimitris, Allen, Robert J., Naik, Vaishali, Kuo, Chaincy, Szopa, Sophie, Nabat, Pierre, Olivié, Dirk, van Noije, Twan, Le Sager, Philippe, Neubauer, David, Oshima, Naga, Mulcahy, Jane, Horowitz, Larry W., and Zanis, Prodromos
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RADIATIVE forcing ,AEROSOLS ,CARBONACEOUS aerosols ,EARTH (Planet) ,CARBON-black - Abstract
Anthropogenic aerosols play a major role in the Earth–atmosphere system by influencing the Earth's radiative budget and precipitation and consequently the climate. The perturbation induced by changes in anthropogenic aerosols on the Earth's energy balance is quantified in terms of the effective radiative forcing (ERF). In this work, the present-day shortwave (SW), longwave (LW), and total (i.e., SW plus LW) ERF of anthropogenic aerosols is quantified using two different sets of experiments with prescribed sea surface temperatures (SSTs) from Earth system models (ESMs) participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6): (a) time-slice pre-industrial perturbation simulations with fixed SSTs (piClim) and (b) transient historical simulations with time-evolving SSTs (histSST) over the historical period (1850–2014). ERF is decomposed into three components for both piClim and histSST experiments: (a) ERFARI , representing aerosol–radiation interactions; (b) ERFACI , accounting for aerosol–cloud interactions (including the semi-direct effect); and (c) ERFALB , which is due to temperature, humidity, and surface albedo changes caused by anthropogenic aerosols. We present spatial patterns at the top-of-atmosphere (TOA) and global weighted field means along with inter-model variability (1 standard deviation) for all SW, LW, and total ERF components (ERFARI , ERFACI , and ERFALB) and for every experiment used in this study. Moreover, the inter-model agreement and the robustness of our results are assessed using a comprehensive method as utilized in the IPCC Sixth Assessment Report. Based on piClim experiments, the total present-day (2014) ERF from anthropogenic aerosol and precursor emissions is estimated to be - 1.11 ± 0.26 Wm-2 , mostly due to the large contribution of ERFACI to the global mean and to the inter-model variability. Based on the histSST experiments for the present-day period (1995–2014), similar results are derived, with a global mean total aerosol ERF of - 1.28 ± 0.37 Wm-2 and dominating contributions from ERFACI. The spatial patterns for total ERF and its components are similar in both the piClim and histSST experiments. Furthermore, implementing a novel approach to determine geographically the driving factor of ERF, we show that ERFACI dominates over the largest part of the Earth and that ERFALB dominates mainly over the poles, while ERFARI dominates over certain reflective surfaces. Analysis of the inter-model variability in total aerosol ERF shows that SW ERFACI is the main source of uncertainty predominantly over land regions with significant changes in aerosol optical depth (AOD), with eastern Asia contributing mostly to the inter-model spread of both ERFARI and ERFACI. The global spatial patterns of total ERF and its components from individual aerosol species, such as sulfates, organic carbon (OC), and black carbon (BC), are also calculated based on piClim experiments. The total ERF caused by sulfates (piClim- SO2) is estimated at - 1.11 ± 0.31 Wm-2 , and the OC ERF (piClim-OC) is - 0.35 ± 0.21 Wm-2 , while the ERF due to BC (piClim-BC) is 0.19 ± 0.18 Wm-2. For sulfates and OC perturbation experiments, ERFACI dominates over the globe, whereas for BC perturbation experiments ERFARI dominates over land in the Northern Hemisphere and especially in the Arctic. Generally, sulfates dominate ERF spatial patterns, exerting a strongly negative ERF especially over industrialized regions of the Northern Hemisphere (NH), such as North America, Europe, and eastern and southern Asia. Our analysis of the temporal evolution of ERF over the historical period (1850–2014) reveals that ERFACI clearly dominates over ERFARI and ERFALB for driving the total ERF temporal evolution. Moreover, since the mid-1980s, total ERF has become less negative over eastern North America and western and central Europe, while over eastern and southern Asia there is a steady increase in ERF magnitude towards more negative values until 2014. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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9. Evaluation of CMIP6 model simulations of PM2.5 and its components over China.
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Ren, Fangxuan, Lin, Jintai, Xu, Chenghao, Adeniran, Jamiu A., Wang, Jingxu, Martin, Randall V., van Donkelaar, Aaron, Hammer, Melanie S., Horowitz, Larry W., Turnock, Steven T., Oshima, Naga, Zhang, Jie, Bauer, Susanne, Tsigaridis, Kostas, Seland, Øyvind, Nabat, Pierre, Neubauer, David, Strand, Gary, van Noije, Twan, and Le Sager, Philippe
- Subjects
PARTICULATE matter ,SOOT ,RADIATIVE forcing ,CARBON-black ,AMMONIUM nitrate ,SIMULATION methods & models - Abstract
Earth system models (ESMs) participating in the latest Coupled Model Intercomparison Project Phase 6 (CMIP6) simulate various components of fine particulate matter (PM2.5) as major climate forcers. Yet the model performance for PM2.5 components remains little evaluated due in part to a lack of observational data. Here, we evaluate near-surface concentrations of PM2.5 and its five main components over China as simulated by 14 CMIP6 models, including organic carbon (OC; available in 14 models), black carbon (BC; 14 models), sulfate (14 models), nitrate (4 models), and ammonium (5 models). For this purpose, we collect observational data between 2000 and 2014 from a satellite-based dataset for total PM2.5 and from 2469 measurement records in the literature for PM2.5 components. Seven models output total PM2.5 concentrations, and they all underestimate the observed total PM2.5 over eastern China, with GFDL-ESM4 (- 1.5 %) and MPI-ESM-1-2-HAM (- 1.1 %) exhibiting the smallest biases averaged over the whole country. The other seven models, for which we recalculate total PM2.5 from the available component output, underestimate the total PM2.5 concentrations partly because of the missing model representations of nitrate and ammonium. Concentrations of the five individual components are underestimated in almost all models, except that sulfate is overestimated in MPI-ESM-1-2-HAM by 12.6 % and in MRI-ESM2-0 by 24.5 %. The underestimation is the largest for OC (by - 71.2 % to - 37.8 % across the 14 models) and the smallest for BC (- 47.9 % to - 12.1 %). The multi-model mean (MMM) reproduces the observed spatial pattern for OC (R = 0.51), sulfate (R = 0.57), nitrate (R = 0.70) and ammonium (R = 0.74) fairly well, yet the agreement is poorer for BC (R = 0.39). The varying performances of ESMs on total PM2.5 and its components have important implications for the modeled magnitude and spatial pattern of aerosol radiative forcing. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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10. Decomposing the Effective Radiative Forcing of anthropogenic aerosols based on CMIP6 Earth System Models
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Kalisoras, Alkiviadis, primary, Georgoulias, Aristeidis K., additional, Akritidis, Dimitris, additional, Allen, Robert J., additional, Naik, Vaishali, additional, Kuo, Chaincy, additional, Szopa, Sophie, additional, Nabat, Pierre, additional, Olivié, Dirk, additional, van Noije, Twan, additional, Le Sager, Philippe, additional, Neubauer, David, additional, Oshima, Naga, additional, Mulcahy, Jane, additional, Horowitz, Larry W., additional, and Zanis, Prodromos, additional
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- 2023
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11. Supplementary material to "Decomposing the Effective Radiative Forcing of anthropogenic aerosols based on CMIP6 Earth System Models"
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Kalisoras, Alkiviadis, primary, Georgoulias, Aristeidis K., additional, Akritidis, Dimitris, additional, Allen, Robert J., additional, Naik, Vaishali, additional, Kuo, Chaincy, additional, Szopa, Sophie, additional, Nabat, Pierre, additional, Olivié, Dirk, additional, van Noije, Twan, additional, Le Sager, Philippe, additional, Neubauer, David, additional, Oshima, Naga, additional, Mulcahy, Jane, additional, Horowitz, Larry W., additional, and Zanis, Prodromos, additional
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- 2023
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12. Historical Changes and Reasons for Model Differences in Anthropogenic Aerosol Forcing in CMIP6
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Fiedler, Stephanie, primary, van Noije, Twan, additional, Smith, Christopher J., additional, Boucher, Olivier, additional, Dufresne, Jean‐Louis, additional, Kirkevåg, Alf, additional, Olivié, Dirk, additional, Pinto, Rovina, additional, Reerink, Thomas, additional, Sima, Adriana, additional, and Schulz, Michael, additional
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- 2023
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13. Supplementary material to "Simulating the dust emissions and SOA formation over Northern Africa during the mid-Holocene Green Sahara period"
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Zhou, Putian, primary, Lu, Zhengyao, additional, Keskinen, Jukka-Pekka, additional, Zhang, Qiong, additional, Lento, Juha, additional, Bian, Jianpu, additional, van Noije, Twan, additional, Le Sager, Philippe, additional, Kerminen, Veli-Matti, additional, Kulmala, Markku, additional, Boy, Michael, additional, and Makkonen, Risto, additional
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- 2023
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14. Pre‐Industrial, Present and Future Atmospheric Soluble Iron Deposition and the Role of Aerosol Acidity and Oxalate Under CMIP6 Emissions
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Bergas‐Massó, Elisa, primary, Gonçalves Ageitos, María, additional, Myriokefalitakis, Stelios, additional, Miller, Ron L., additional, van Noije, Twan, additional, Le Sager, Philippe, additional, Montané Pinto, Gilbert, additional, and Pérez García‐Pando, Carlos, additional
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- 2023
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15. Simulating dust emissions and secondary organic aerosol formation over northern Africa during the mid-Holocene Green Sahara period
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Zhou, Putian, Lu, Zhengyao, Keskinen, Jukka-Pekka, Zhang, Qiong, Lento, Juha, Bian, Jianpu, van Noije, Twan, Le Sager, Philippe, Kerminen, Veli-Matti, Kulmala, Markku, Boy, Michael, Makkonen, Risto, Zhou, Putian, Lu, Zhengyao, Keskinen, Jukka-Pekka, Zhang, Qiong, Lento, Juha, Bian, Jianpu, van Noije, Twan, Le Sager, Philippe, Kerminen, Veli-Matti, Kulmala, Markku, Boy, Michael, and Makkonen, Risto
- Abstract
Paleo-proxy data indicate that a “Green Sahara” thrived in northern Africa during the early- to mid-Holocene (MH; 11 000 to 5000 years before present), characterized by more vegetation cover and reduced dust emissions. Utilizing a state-of-the-art atmospheric chemical transport model, TM5-MP, we assessed the changes in biogenic volatile organic compound (BVOC) emissions, dust emissions and secondary organic aerosol (SOA) concentrations in northern Africa during this period relative to the pre-industrial (PI) period. Our simulations show that dust emissions reduced from 280.6 Tg a−1 in the PI to 26.8 Tg a−1 in the MH, agreeing with indications from eight marine sediment records in the Atlantic Ocean. The northward expansion in northern Africa resulted in an increase in annual emissions of isoprene and monoterpenes during the MH, around 4.3 and 3.5 times higher than that in the PI period, respectively, causing a 1.9-times increase in the SOA surface concentration. Concurrently, enhanced BVOC emissions consumed more hydroxyl radical (OH), resulting in less sulfate formation. This effect counteracted the enhanced SOA surface concentration, altogether leading to a 17 % increase in the cloud condensation nuclei at 0.2 % super saturation over northern Africa. Our simulations provide consistent emission datasets of BVOCs, dust and the SOA formation aligned with the northward shift of vegetation during the “Green Sahara” period, which could serve as a benchmark for MH aerosol input in future Earth system model simulation experiments.
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- 2023
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16. Historical Changes and Reasons for Model Differences in Anthropogenic Aerosol Forcing in CMIP6
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Fiedler, Stephanie, van Noije, Twan, Smith, Christopher J., Boucher, Olivier, Dufresne, Jean‐Louis, Kirkevåg, Alf, Olivié, Dirk, Pinto, Rovina, Reerink, Thomas, Sima, Adriana, Schulz, Michael, Fiedler, Stephanie, van Noije, Twan, Smith, Christopher J., Boucher, Olivier, Dufresne, Jean‐Louis, Kirkevåg, Alf, Olivié, Dirk, Pinto, Rovina, Reerink, Thomas, Sima, Adriana, and Schulz, Michael
- Abstract
The Radiative Forcing Model Intercomparison Project (RFMIP) allows estimates of effective radiative forcing (ERF) in the Coupled Model Intercomparison Project phase six (CMIP6). We analyze the RFMIP output, including the new experiments from models that use the same parameterization for anthropogenic aerosols (RFMIP-SpAer), to characterize and better understand model differences in aerosol ERF. We find little changes in the aerosol ERF for 1970–2014 in the CMIP6 multi-model mean, which implies greenhouse gases primarily explain the positive trend in the total anthropogenic ERF. Cloud-mediated effects dominate the present-day aerosol ERF in most models. The results highlight a regional increase in marine cloudiness due to aerosols, despite suppressed cloud lifetime effects in that RFMIP-SpAer experiment. Negative cloud-mediated effects mask positive direct effects in many models, which arise from strong anthropogenic aerosol absorption. The findings suggest opportunities to better constrain simulated ERF by revisiting the optical properties and long-range transport of aerosols. Key Points: - Coupled Model Intercomparison Project phase six (CMIP6) averaged trend in aerosol effective radiative forcing (ERF) is small for 1970–2014 and weakly positive for 2000–2014 - Positive direct aerosol radiative effects in CMIP6 models are associated with strong aerosol absorption - Diverse and often strong cloud-mediated effects primarily determine the magnitude of aerosol ERF in CMIP6
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- 2023
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17. Pre-industrial, present and future atmospheric soluble iron deposition and the role of aerosol acidity and oxalate under CMIP6 emissions
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Universitat Politècnica de Catalunya. Doctorat en Enginyeria Ambiental, Universitat Politècnica de Catalunya. Departament d'Enginyeria de Projectes i de la Construcció, Bergas Massó, Elisa, Gonçalves Ageitos, María, Myriokefalitakis, Stelios, Miller, Ron L., van Noije, Twan, Le Sager, Philippe, Montané Pinto, Gilbert, García Pando, Carlos Pérez, Universitat Politècnica de Catalunya. Doctorat en Enginyeria Ambiental, Universitat Politècnica de Catalunya. Departament d'Enginyeria de Projectes i de la Construcció, Bergas Massó, Elisa, Gonçalves Ageitos, María, Myriokefalitakis, Stelios, Miller, Ron L., van Noije, Twan, Le Sager, Philippe, Montané Pinto, Gilbert, and García Pando, Carlos Pérez
- Abstract
Atmospheric iron (Fe) deposition to the open ocean affects net primary productivity, nitrogen fixation, and carbon uptake. We investigate changes in soluble Fe (SFe) deposition from the pre-industrial period to the late 21st century using the EC-Earth3-Iron Earth System model. EC-Earth3-Iron considers various sources of Fe, including dust, fossil fuel combustion, and biomass burning, and features comprehensive atmospheric chemistry, representing atmospheric oxalate, sulfate, and Fe cycles. We show that anthropogenic activity has changed the magnitude and spatial distribution of SFe deposition by increasing combustion Fe emissions and atmospheric acidity and oxalate levels. We report that SFe deposition has doubled since the early industrial era, using the Coupled Model Intercomparison Project Phase 6 emission inventory. We highlight acidity as the main solubilization pathway for dust-Fe and oxalate-promoted processing for the solubilization of combustion-Fe. We project a global SFe deposition increase of 40% by the late 21st century relative to present day under Shared Socioeconomic Pathway (SSP) 3–7.0, which assumes weak climate change mitigation policies. Conversely, SSPs with stronger mitigation pathways (1–2.6 and 2–4.5) result in 35% and 10% global decreases, respectively. Despite these differences, SFe deposition increases over the equatorial Pacific and decreases in the Southern Ocean (SO) for all SSPs. We further observe that deposition over the equatorial Pacific and SO are highly sensitive to future changes in dust emissions from Australia and South America, as well as from North Africa. Future studies should focus on the potential impact of climate- and human-induced changes in dust and wildfires combined., This work was funded by the European Research Council under the Horizon 2020 research and innovation programme through the ERC Consolidator Grant FRAGMENT (grant agreement no. 773051), the AXA Research Fund through the AXA Chair on Sand and Dust Storms at BSC, the Spanish Ministerio de Economía y Competitividad through the NUTRIENT project (CGL2017-88911-R), the European Union's Horizon 2020 research and innovation programme under grant agreement no 821205 (FORCeS), and ESA through the DOMOS project (ESA AO/1-10546/20/I-NB). We acknowledge the EMIT project, which is supported by the National Aeronautics and Space Administration Earth Venture Instrument program, under the Earth Science Division of the Science Mission Directorate. RLM received additional support from the NASA Modeling, Analysis and Prediction Program (NNG14HH42I). We also acknowledge the resources obtained on the Marenostrum4 supercomputer at BSC, granted through the PRACE project eFRAGMENT2 and RES project AECT-2020-3-0020, along with the technical support provided by BSC and the Computational Earth Sciences team of the BSC Earth Sciences Department., Peer Reviewed, Postprint (published version)
- Published
- 2023
18. Decomposing the Effective Radiative Forcing of anthropogenic aerosols based on CMIP6 Earth System Models.
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Kalisoras, Alkiviadis, Georgoulias, Aristeidis K., Akritidis, Dimitris, Allen, Robert J., Naik, Vaishali, Kuo, Chaincy, Szopa, Sophie, Nabat, Pierre, Olivié, Dirk, van Noije, Twan, Le Sager, Philippe, Neubauer, David, Naga Oshima, Mulcahy, Jane, Horowitz, Larry W., and Zanis, Prodromos
- Abstract
Anthropogenic aerosols play a major role for the Earth-Atmosphere system by influencing the Earth’s radiative budget and climate. The effect of the perturbation induced by changes in anthropogenic aerosols on the Earth's energy balance is quantified in terms of the effective radiative forcing (ERF) which is the recommended metric for perturbations affecting the Earth’s top-of-atmosphere energy budget since it is a better way to link this perturbation to subsequent global mean surface temperature change. In this work, the present-day ERF of anthropogenic aerosols is quantified using simulations from Earth system models (ESMs) participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6). The ERFs of individual aerosol species, such as sulphates, organic carbon (OC), and black carbon (BC) are calculated along with the ERF due to all anthropogenic aerosols and the transient ERF over the historical period (1850–2014). Additionally, ERF is analyzed into three components: (a) ERF
ARI , representing aerosol-radiation interactions, (b) ERFACI , accounting for aerosol-cloud interactions, and (c) ERFALB , which is mainly due to the contribution of surface albedo changes caused by anthropogenic aerosols. Here, the total anthropogenic aerosol ERF (calculated using the piClim-aer experiment) is estimated to be -1.11 ± 0.26 W m-2 , mostly due to the large contribution of ERFACI (-1.14 ± 0.33 W m-2 ), compared to ERFARI (-0.02 ± 0.20 W m-2 ) and ERFALB (0.05 ± 0.07 W m-2 ). The total ERF caused by sulphates (piClim-SO2 ) is estimated at -1.11 ± 0.31 W m-2 , the OC ERF (piClim-OC) is -0.35 ± 0.21 W m-2 , whereas the ERF exerted by BC (piClim-BC) is 0.19 ± 0.18 W m-2 . On top of that, our analysis reveals that ERFACI clearly prevails over the largest part of the Earth except for the BC experiment where ERFARI prevails over land. By the end of the historical period (1995–2014), the global mean total aerosol ERF is estimated at -1.28 ± 0.37 W m-2 (calculated using the histSST experiment). We find that sulphates dominate both present-day and transient ERF spatial patterns at the top of the atmosphere, exerting a strongly negative ERF especially over industrialized regions of the Northern Hemisphere, such as North America, Europe, East and South Asia. Since the mid-1980s ERF has become less negative over Eastern North America and Western and Central Europe, while over East and South Asia there is a steady increase in ERF magnitude towards more negative values until 2014. [ABSTRACT FROM AUTHOR]- Published
- 2023
- Full Text
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19. Evaluation of CMIP6 model simulations of PM2.5 and its components over China.
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Fangxuan Ren, Jintai Lin, Chenghao Xu, Adeniran, Jamiu A., Jingxu Wang, Martin, Randall V., van Donkelaar, Aaron, Hammer, Melanie S., Horowitz, Larry W., Turnock, Steven T., Naga Oshima, Jie Zhang, Bauer, Susanne, Tsigaridis, Kostas, Seland, Øyvind, Nabat, Pierre, Neubauer, David, Strand, Gary, van Noije, Twan, and Le Sager, Philippe
- Subjects
RADIATIVE forcing ,PARTICULATE matter ,AMMONIUM nitrate ,CARBON-black ,SIMULATION methods & models - Abstract
Earth system models (ESMs) participating in the latest Coupled Model Intercomparison Project Phase 6 (CMIP6) simulate various components of fine particulate matter (PM
2.5 ) as major climate forcers. Yet the model performance for PM2.5 components remains little evaluated due in part to lack of observational data. Here, we evaluate near-surface concentrations of PM2.5 and its five main components over China as simulated by fourteen CMIP6 models, including organic carbon (OC, available in 14 models), black carbon (BC, 14 models), sulfate (14 models), nitrate (4 models), and ammonium (5 models). For this purpose, we collect observational data between 2000 and 2014 from a satellite-based dataset for total PM2.5 and from 2469 measurement records in the literature for PM2.5 components. Seven models output total PM2.5 concentrations, and they all underestimate the observed total PM2.5 over eastern China, with GFDL-ESM4 (–1.5 %) and MPI-ESM-1-2-HAM (–1.1 %) exhibiting the smallest biases averaged over the whole country. The other seven models, for which we recalculate total PM2.5 from the available components output, underestimate the total PM2.5 concentrations, partly because of the missing model representations of nitrate and ammonium. Concentrations of the five individual components are underestimated in almost all models, except that sulfate is overestimated in MPI-ESM-1-2-HAM by 12.6 % and in MRI-ESM2-0 by 24.5 %. The underestimation is the largest for OC (by –71.2 % to –37.8 % across the 14 models) and the smallest for BC (–47.9 % to –12.1 %). The multi-model mean (MMM) reproduces fairly well the observed spatial pattern for OC (R = 0.51), sulfate (R = 0.57), nitrate (R = 0.70) and ammonium (R = 0.75), yet the agreement is poorer for BC (R = 0.39). The varying performances of ESMs on total PM2.5 and its components have important implications for the modeled magnitude and spatial pattern of aerosol radiative forcing. [ABSTRACT FROM AUTHOR]- Published
- 2023
- Full Text
- View/download PDF
20. A case study to investigate the role of aerosols reduction on the East Asian summer monsoon seasonal prediction
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Cherchi, Annalisa, primary, Tourigny, Etienne, additional, Acosta Navarro, Juan C, additional, Ortega, Pablo, additional, Davini, Paolo, additional, Alessandri, Andrea, additional, Catalano, Franco, additional, and van Noije, Twan, additional
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- 2023
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21. New Aerosol-sensitive Heterogeneous Ice Nucleation Parameterization in the EC-Earth3 Earth System Model: evaluation and climate response
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Costa-Surós, Montserrat, primary, Gonçalves, Maria, additional, Chatziparaschos, Marios, additional, Georgakaki, Paraskevi, additional, Ilić, Luka, additional, Montane, Gilbert, additional, Myriokefalitakis, Stelios, additional, van Noije, Twan, additional, Le Sager, Pilippe, additional, Kanakidou, Maria, additional, Nenes, Athanasios, additional, and Pérez García-Pando, Carlos, additional
- Published
- 2023
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22. Future projection of ozone-related mortality under SSP3-7.0 scenario based on CMIP6 simulations
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Akritidis, Dimitris, primary, Bacer, Sara, additional, Zanis, Prodromos, additional, Georgoulias, Aristeidis K., additional, Horowitz, Larry W., additional, Naik, Vaishali, additional, O'Connor, Fiona M., additional, Keeble, James, additional, Le Sager, Philippe, additional, van Noije, Twan, additional, Zhou, Putian, additional, and Pozzer, Andrea, additional
- Published
- 2023
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23. Global impacts of surface ozone changes on crop yields and land use
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Chuwah, Clifford, van Noije, Twan, van Vuuren, Detlef P., Stehfest, Elke, and Hazeleger, Wilco
- Published
- 2015
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24. Evaluation of Global Simulations of Aerosol Particle and Cloud Condensation Nuclei Number, with Implications for Cloud Droplet Formation
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Fanourgakis, George S, Kanakidou, Maria, Nenes, Athanasios, Bauer, Susanne E, Bergman, Tommi, Carslaw, Ken S, Grini, Alf, Hamilton, Douglas S, Johnson, Jill S, Karydis, Vlassis A, Kirkevag, Alf, Kodros, John K, Lohmann, Ulrike, Luo, Gan, Makkonen, Risto, Matsui, Hitoshi, Neubauer, David, Pierce, Jeffrey R, Schmale, Julia, Stier, Philip, Tsigaridis, Kostas, van Noije, Twan, Wang, Hailong, Watson-Parris, Duncan, Westervelt, Daniel M, Yang, Yang, Yoshioka, Masaru, Daskalakis, Nikos, Decesari, Stefano, Gysel-Beer, Martin, Kalivitis, Nikos, Liu, Xiaohong, Mahowald, Natalie M, Myriokefalitakis, Stelios, Schrodner, Roland, Sfakianaki, Maria, Tsimpidi, Alexandra P, Wu, Mingxuan, and Yu, Fangqun
- Subjects
Meteorology And Climatology - Abstract
A total of 16 global chemistry transport models and general circulation models have participated in this study; 14 models have been evaluated with regard to their ability to reproduce the near-surface observed number concentration of aerosol particles and cloud condensation nuclei (CCN), as well as derived cloud droplet number concentration (CDNC). Model results for the period 2011-2015 are compared with aerosol measurements (aerosol particle number, CCN and aerosol particle composition in the submicron fraction) from nine surface stations located in Europe and Japan. The evaluation focuses on the ability of models to simulate the average across time state in diverse environments and on the seasonal and short-term variability in the aerosol properties. There is no single model that systematically performs best across all environments represented by the observations. Models tend to underestimate the observed aerosol particle and CCN number concentrations, with average normalized mean bias (NMB) of all models and for all stations, where data are available, of -24% and -35% for particles with dry diameters > 50 and > 120nm, as well as -36% and -34% for CCN at supersaturations of 0.2% and 1.0%, respectively. However, they seem to behave differently for particles activating at very low supersaturations (< 0.1%) than at higher ones. A total of 15 models have been used to produce ensemble annual median distributions of relevant parameters. The model diversity (defined as the ratio of standard deviation to mean) is up to about 3 for simulated N3 (number concentration of particles with dry diameters larger than 3 nm) and up to about 1 for simulated CCN in the extra-polar regions. A global mean reduction of a factor of about 2 is found in the model diversity for CCN at a supersaturation of 0.2% (CCN(0.2)) compared to that for N3, maximizing over regions where new particle formation is important. An additional model has been used to investigate potential causes of model diversity in CCN and bias compared to the observations by performing a perturbed parameter ensemble (PPE) accounting for uncertainties in 26 aerosol-related model input parameters. This PPE suggests that biogenic secondary organic aerosol formation and the hygroscopic properties of the organic material are likely to be the major sources of CCN uncertainty in summer, with dry deposition and cloud processing being dominant in winter. Models capture the relative amplitude of the seasonal variability of the aerosol particle number concentration for all studied particle sizes with available observations (dry diameters larger than 50, 80 and 120nm). The short-term persistence time (on the order of a few days) of CCN concentrations, which is a measure of aerosol dynamic behavior in the models, is underestimated on average by the models by 40% during winter and 20% in summer.
- Published
- 2019
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25. How to Utilise the Knowledge of Causal Responses?
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Hari, Pertti, Havimo, Mikko, Helmisaari, Heljä-Sisko, Kulmala, Liisa, Nikinmaa, Eero, Vesala, Timo, Räisänen, Jouni, Petäjä, Tuukka, Siivola, Erkki, Tuomenvirta, Heikki, Bäck, Jaana, Grace, John, Magnani, Federico, van Noije, Twan, Pumpanen, Jukka, Stevenson, David, Kulmala, Markku, Smolander, Sampo, Riipinen, Ilona, dal Maso, Miikka, Hari, Pertti, editor, Heliövaara, Kari, editor, and Kulmala, Liisa, editor
- Published
- 2013
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26. Contribution of Dynamic Vegetation Phenology to Decadal Climate Predictability
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Weiss, Martina, Miller, Paul A., van den Hurk, Bart J. J. M., van Noije, Twan, Ştefănescu, Simona, Haarsma, Reindert, van Ulft, Lambertus H., Hazeleger, Wilco, Le Sager, Philippe, Smith, Benjamin, and Schurgers, Guy
- Published
- 2014
27. Comparison of particle number size distribution trends in ground measurements and climate models
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Leinonen, Ville, Kokkola, Harri, Yli-Juuti, Taina, Mielonen, Tero, Kühn, Thomas, Nieminen, Tuomo, Heikkinen, Simo, Miinalainen, Tuuli, Bergman, Tommi, Carslaw, Ken, Decesari, Stefano, Fiebig, Markus, Hussein, Tareq, Kivekäs, Niku, Krejci, Radovan, Kulmala, Markku, Leskinen, Ari, Massling, Andreas, Mihalopoulos, Nikos, Mulcahy, Jane P., Noe, Steffen M., van Noije, Twan, O'Connor, Fiona M., O'Dowd, Colin, Olivie, Dirk, Pernov, Jakob B., Petäjä, Tuukka, Seland, Øyvind, Schulz, Michael, Scott, Catherine E., Skov, Henrik, Swietlicki, Erik, Tuch, Thomas, Wiedensohler, Alfred, Virtanen, Annele, Mikkonen, Santtu, Global Atmosphere-Earth surface feedbacks, Institute for Atmospheric and Earth System Research (INAR), and Air quality research group
- Subjects
SECTIONAL AEROSOL MODULE ,1171 Geosciences ,GLOBAL ANALYSIS ,WIND-SPEED ,LONG-TERM ,ATMOSPHERIC AEROSOL ,SULFUR EMISSIONS ,DECADAL TRENDS ,ORGANIC AEROSOL ,114 Physical sciences ,LIFE-CYCLE ,1172 Environmental sciences ,GAS-EXCHANGE - Abstract
Despite a large number of studies, out of all drivers of radiative forcing, the effect of aerosols has the largest uncertainty in global climate model radiative forcing estimates. There have been studies of aerosol optical properties in climate models, but the effects of particle number size distribution need a more thorough inspection. We investigated the trends and seasonality of particle number concentrations in nucleation, Aitken, and accumulation modes at 21 measurement sites in Europe and the Arctic. For 13 of those sites, with longer measurement time series, we compared the field observations with the results from five climate models, namely EC-Earth3, ECHAM-M7, ECHAM-SALSA, NorESM1.2, and UKESM1. This is the first extensive comparison of detailed aerosol size distribution trends between in situ observations from Europe and five earth system models (ESMs). We found that the trends of particle number concentrations were mostly consistent and decreasing in both measurements and models. However, for many sites, climate models showed weaker decreasing trends than the measurements. Seasonal variability in measured number concentrations, quantified by the ratio between maximum and minimum monthly number concentration, was typically stronger at northern measurement sites compared to other locations. Models had large differences in their seasonal representation, and they can be roughly divided into two categories: for EC-Earth and NorESM, the seasonal cycle was relatively similar for all sites, and for other models the pattern of seasonality varied between northern and southern sites. In addition, the variability in concentrations across sites varied between models, some having relatively similar concentrations for all sites, whereas others showed clear differences in concentrations between remote and urban sites. To conclude, although all of the model simulations had identical input data to describe anthropogenic mass emissions, trends in differently sized particles vary among the models due to assumptions in emission sizes and differences in how models treat size-dependent aerosol processes. The inter-model variability was largest in the accumulation mode, i.e. sizes which have implications for aerosol-cloud interactions. Our analysis also indicates that between models there is a large variation in efficiency of long-range transportation of aerosols to remote locations. The differences in model results are most likely due to the more complex effect of different processes instead of one specific feature (e.g. the representation of aerosol or emission size distributions). Hence, a more detailed characterization of microphysical processes and deposition processes affecting the long-range transport is needed to understand the model variability.
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- 2022
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28. Comparison of particle number size distribution trends in ground measurements and climate models
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Leinonen, Ville, primary, Kokkola, Harri, additional, Yli-Juuti, Taina, additional, Mielonen, Tero, additional, Kühn, Thomas, additional, Nieminen, Tuomo, additional, Heikkinen, Simo, additional, Miinalainen, Tuuli, additional, Bergman, Tommi, additional, Carslaw, Ken, additional, Decesari, Stefano, additional, Fiebig, Markus, additional, Hussein, Tareq, additional, Kivekäs, Niku, additional, Krejci, Radovan, additional, Kulmala, Markku, additional, Leskinen, Ari, additional, Massling, Andreas, additional, Mihalopoulos, Nikos, additional, Mulcahy, Jane P., additional, Noe, Steffen M., additional, van Noije, Twan, additional, O'Connor, Fiona M., additional, O'Dowd, Colin, additional, Olivie, Dirk, additional, Pernov, Jakob B., additional, Petäjä, Tuukka, additional, Seland, Øyvind, additional, Schulz, Michael, additional, Scott, Catherine E., additional, Skov, Henrik, additional, Swietlicki, Erik, additional, Tuch, Thomas, additional, Wiedensohler, Alfred, additional, Virtanen, Annele, additional, and Mikkonen, Santtu, additional
- Published
- 2022
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29. Satellite-based evaluation of AeroCom model bias in biomass burning regions
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Zhong, Qirui, primary, Schutgens, Nick, additional, van der Werf, Guido, additional, van Noije, Twan, additional, Tsigaridis, Kostas, additional, Bauer, Susanne E., additional, Mielonen, Tero, additional, Kirkevåg, Alf, additional, Seland, Øyvind, additional, Kokkola, Harri, additional, Checa-Garcia, Ramiro, additional, Neubauer, David, additional, Kipling, Zak, additional, Matsui, Hitoshi, additional, Ginoux, Paul, additional, Takemura, Toshihiko, additional, Le Sager, Philippe, additional, Rémy, Samuel, additional, Bian, Huisheng, additional, Chin, Mian, additional, Zhang, Kai, additional, Zhu, Jialei, additional, Tsyro, Svetlana G., additional, Curci, Gabriele, additional, Protonotariou, Anna, additional, Johnson, Ben, additional, Penner, Joyce E., additional, Bellouin, Nicolas, additional, Skeie, Ragnhild B., additional, and Myhre, Gunnar, additional
- Published
- 2022
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30. OpenIFS/AC: atmospheric chemistry and aerosol in OpenIFS 43r3
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Huijnen, Vincent, primary, Le Sager, Philippe, additional, Köhler, Marcus O., additional, Carver, Glenn, additional, Rémy, Samuel, additional, Flemming, Johannes, additional, Chabrillat, Simon, additional, Errera, Quentin, additional, and van Noije, Twan, additional
- Published
- 2022
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31. Implications of alternative assumptions regarding future air pollution control in scenarios similar to the Representative Concentration Pathways
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Chuwah, Clifford, van Noije, Twan, van Vuuren, Detlef P., Hazeleger, Wilco, Strunk, Achim, Deetman, Sebastiaan, Beltran, Angelica Mendoza, and van Vliet, Jasper
- Published
- 2013
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32. Kinetic Theory of Granular Gases
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van Noije, Twan P.C., Ernst, Matthieu H., Beig, R., editor, Ehlers, J., editor, Frisch, U., editor, Hepp, K., editor, Hillebrandt, W., editor, Imboden, D., editor, Jaffe, R. L., editor, Kippenhahn, R., editor, Lipowsky, R., editor, v. Löhneysen, H., editor, Ojima, I., editor, Weidenmüller, H. A., editor, Wess, J., editor, Zittartz, J., editor, Pöschel, Thorsten, editor, and Luding, Stefan, editor
- Published
- 2001
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33. Global and regional climate impacts of future aerosol mitigation in an RCP6.0-like scenario in EC-Earth
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Chuwah, Clifford, van Noije, Twan, van Vuuren, Detlef P., Le Sager, Philippe, and Hazeleger, Wilco
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- 2016
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34. Simulating the dust emissions and SOA formation over Northern Africa during the mid-Holocene Green Sahara period.
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Putian Zhou, Zhengyao Lu, Keskinen, Jukka-Pekka, Qiong Zhang, Lento, Juha, Jianpu Bian, van Noije, Twan, Le Sager, Philippe, Kerminen, Veli-Matti, Kulmala, Markku, Boy, Michael, and Makkonen, Risto
- Abstract
Paleo-proxy data indicates that a "Green Sahara" thrived in Northern Africa during the early- to mid-Holocene (MH; 11,000 to 5,000 years before present), characterized by more vegetation cover and reduced dust emission. Utilizing a state-of-the-art atmospheric chemical transport model TM5-MP, we assessed the changes in biogenic volatile organic compounds (BVOCs) emissions, dust emission and secondary organic aerosol (SOA) concentration in Northern Africa during this period relative to the pre-industrial (PI) period. Our simulations show that dust emissions reduced from 280.6 Tg a
-1 in the PI to 26.8 Tg a-1 in the MH, agreeing with indications from eight marine sediment records in the Atlantic Ocean. The northward expansion in Northern Africa resulted in an increase in annual emissions of isoprene and monoterpenes during the MH, around 4.3 and 3.5 times higher than that in the PI period, respectively, causing 1.9 times increase in the SOA surface concentration. The enhanced SOA surface concentration and decreased sulfate surface concentration counteracted each other, leading to a 17% increase in the cloud condensation nuclei at 0.2% super saturation over Northern Africa. Our simulations provide consistent emission datasets of BVOCs, dust, and the SOA formation aligned with the northward shift of vegetation during the "Green Sahara" period, which could serve as a benchmark for MH aerosol input in future Earth system model simulation experiments. [ABSTRACT FROM AUTHOR]- Published
- 2023
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35. Aerosols at the Poles: An Aerocom Phase II Multi-Model Evaluation
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Sand, Maria, Bauer, Susanne E, Samset, Bjorn H, Balkanski, Yves, Bellouin, Nicolas, Berntsen, Terje K, Bian, Huisheng, Chin, Mian, Diehl, Thomas, Easter, Richard, Ghan, Steven J, Iversen, Trond, Kirkevag, Alf, Lamarque, Jean-Francois, Lin, Guangxing, Liu, Xiaohong, Luo, Gan, Myhre, Gunnar, van Noije, Twan, Penner, Joyce E, Schulz, Michael, Seland, Oyvind, Skeie, Ragnhild B, Stier, Philip, Takemura, Toshihiko, Tsigaridis, Kostas, Yu, Fangqun, Zhang, Kai, and Zhang, Hua
- Subjects
Meteorology And Climatology ,Earth Resources And Remote Sensing - Abstract
Atmospheric aerosols from anthropogenic and natural sources reach the polar regions through long-range transport and affect the local radiation balance. Such transport is, however, poorly constrained in present-day global climate models, and few multi-model evaluations of polar anthropogenic aerosol radiative forcing exist. Here we compare the aerosol optical depth (AOD) at 550 nm from simulations with 16 global aerosol models from the AeroCom Phase II model intercomparison project with available observations at both poles. We show that the annual mean multi-model median is representative of the observations in Arctic, but that the intermodel spread is large. We also document the geographical distribution and seasonal cycle of the AOD for the individual aerosol species: black carbon (BC) from fossil fuel and biomass burning, sulfate, organic aerosols (OAs), dust, and sea-salt. For a subset of models that represent nitrate and secondary organic aerosols (SOAs), we document the role of these aerosols at high latitudes. The seasonal dependence of natural and anthropogenic aerosols differs with natural aerosols peaking in winter (seasalt) and spring (dust), whereas AOD from anthropogenic aerosols peaks in late spring and summer. The models produce a median annual mean AOD of 0.07 in the Arctic (defined here as north of 60 degrees N). The models also predict a noteworthy aerosol transport to the Antarctic (south of 70 degrees S) with a resulting AOD varying between 0.01 and 0.02. The models have estimated the shortwave anthropogenic radiative forcing contributions to the direct aerosol effect (DAE) associated with BC and OA from fossil fuel and biofuel (FF), sulfate, SOAs, nitrate, and biomass burning from BC and OA emissions combined. The Arctic modelled annual mean DAE is slightly negative (-0.12 W m(exp. -2), dominated by a positive BC FF DAE in spring and a negative sulfate DAE in summer. The Antarctic DAE is governed by BC FF. We perform sensitivity experiments with one of the AeroCom models (GISS modelE) to investigate how regional emissions of BC and sulfate and the lifetime of BC influence the Arctic and Antarctic AOD. A doubling of emissions in eastern Asia results in a 33 percent increase in Arctic AOD of BC. A doubling of the BC lifetime results in a 39 percent increase in Arctic AOD of BC. However, these radical changes still fall within the AeroCom model range.
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- 2017
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36. EC-Earth : A Seamless Earth-System Prediction Approach in Action
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Hazeleger, Wilco, Severijns, Camiel, Semmler, Tido, Ştefănescu, Simona, Yang, Shuting, Wang, Xueli, Wyser, Klaus, Dutra, Emanuel, Baldasano, José M., Bintanja, Richard, Bougeault, Philippe, Caballero, Rodrigo, Ekman, Annica M. L., Christensen, Jens H., van den Hurk, Bart, Jimenez, Pedro, Jones, Colin, Kållberg, Per, Koenigk, Torben, McGrath, Ray, Miranda, Pedro, van Noije, Twan, Palmer, Tim, Parodi, José A., Schmith, Torben, Selten, Frank, Storelvmo, Trude, Sterl, Andreas, Tapamo, Honoré, Vancoppenolle, Martin, Viterbo, Pedro, and Willén, Ulrika
- Published
- 2010
37. The EC-Earth3 Earth system model for the Coupled Model Intercomparison Project 6
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Döscher, Ralf, Acosta, Mario, Alessandri, Andrea, Anthoni, Peter, Arsouze, Thomas, Bergman, Tommi, Bernardello, Raffaele, Boussetta, Souhail, Caron, Louis-Philippe, Carver, Glenn, Castrillo, Miguel, Catalano, Franco, Cvijanovic, Ivana, Davini, Paolo, Dekker, Evelien, Doblas-Reyes, Francisco J., Docquier, David, Echevarria, Pablo, Fladrich, Uwe, Fuentes-Franco, Ramon, Gröger, Matthias, Hardenberg, Jost, Hieronymus, Jenny, Karami, M. Pasha, Keskinen, Jukka-Pekka, Koenigk, Torben, Makkonen, Risto, Massonnet, François, Ménégoz, Martin, Miller, Paul A., Moreno-Chamarro, Eduardo, Nieradzik, Lars, van Noije, Twan, Nolan, Paul, O'Donnell, Declan, Ollinaho, Pirkka, van den Oord, Gijs, Ortega, Pablo, Tintó Prims, Oriol, Ramos, Arthur, Reerink, Thomas, Rousset, Clement, Ruprich-Robert, Yohan, Le Sager, Philippe, Schmith, Torben, Schrödner, Roland, Serva, Federico, Sicardi, Valentina, Madsen, Marianne Sloth, Smith, Benjamin, Tian, Tian, Tourigny, Etienne, Uotila, Petteri, Vancoppenolle, Martin, Wang, Shiyu, Wårlind, David, Willén, Ulrika, Wyser, Klaus, Yang, Shuting, Yepes-Arbós, Xavier, Zhang, Qiong, Döscher, Ralf, Acosta, Mario, Alessandri, Andrea, Anthoni, Peter, Arsouze, Thomas, Bergman, Tommi, Bernardello, Raffaele, Boussetta, Souhail, Caron, Louis-Philippe, Carver, Glenn, Castrillo, Miguel, Catalano, Franco, Cvijanovic, Ivana, Davini, Paolo, Dekker, Evelien, Doblas-Reyes, Francisco J., Docquier, David, Echevarria, Pablo, Fladrich, Uwe, Fuentes-Franco, Ramon, Gröger, Matthias, Hardenberg, Jost, Hieronymus, Jenny, Karami, M. Pasha, Keskinen, Jukka-Pekka, Koenigk, Torben, Makkonen, Risto, Massonnet, François, Ménégoz, Martin, Miller, Paul A., Moreno-Chamarro, Eduardo, Nieradzik, Lars, van Noije, Twan, Nolan, Paul, O'Donnell, Declan, Ollinaho, Pirkka, van den Oord, Gijs, Ortega, Pablo, Tintó Prims, Oriol, Ramos, Arthur, Reerink, Thomas, Rousset, Clement, Ruprich-Robert, Yohan, Le Sager, Philippe, Schmith, Torben, Schrödner, Roland, Serva, Federico, Sicardi, Valentina, Madsen, Marianne Sloth, Smith, Benjamin, Tian, Tian, Tourigny, Etienne, Uotila, Petteri, Vancoppenolle, Martin, Wang, Shiyu, Wårlind, David, Willén, Ulrika, Wyser, Klaus, Yang, Shuting, Yepes-Arbós, Xavier, and Zhang, Qiong
- Abstract
The Earth system model EC-Earth3 for contributions to CMIP6 is documented here, with its flexible coupling framework, major model configurations, a methodology for ensuring the simulations are comparable across different high-performance computing (HPC) systems, and with the physical performance of base configurations over the historical period. The variety of possible configurations and sub-models reflects the broad interests in the EC-Earth community. EC-Earth3 key performance metrics demonstrate physical behavior and biases well within the frame known from recent CMIP models. With improved physical and dynamic features, new Earth system model (ESM) components, community tools, and largely improved physical performance compared to the CMIP5 version, EC-Earth3 represents a clear step forward for the only European community ESM. We demonstrate here that EC-Earth3 is suited for a range of tasks in CMIP6 and beyond.
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- 2022
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38. The EC-Earth3 Earth system model for the Coupled Model Intercomparison Project 6
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Doescher, Ralf, Acosta, Mario, Alessandri, Andrea, Anthoni, Peter, Arsouze, Thomas, Bergman, Tommi, Bernardello, Raffaele, Boussetta, Souhail, Caron, Louis-Philippe, Carver, Glenn, Castrillo, Miguel, Catalano, Franco, Cvijanovic, Ivana, Davini, Paolo, Dekker, Evelien, Doblas-Reyes, Francisco J., Docquier, David, Echevarria, Pablo, Fladrich, Uwe, Fuentes Franco, Ramon, Groger, Matthias, Hardenberg, Jost, V, Hieronymus, Jenny, Karami, Pasha, Keskinen, Jukka-Pekka, Koenigk, Torben, Makkonen, Risto, Massonnet, Francois, Menegoz, Martin, Miller, Paul A., Moreno-Chamarro, Eduardo, Nieradzik, Lars, van Noije, Twan, Nolan, Paul, O'Donnell, Declan, Ollinaho, Pirkka, van den Oord, Gijs, Ortega, Pablo, Tinto Prims, Oriol, Ramos, Arthur, Reerink, Thomas, Rousset, Clement, Ruprich-Robert, Yohan, Le Sager, Philippe, Schmith, Torben, Schrodner, Roland, Serva, Federico, Sicardi, Valentina, Madsen, Marianne Sloth, Smith, Benjamin, Tian, Tian, Tourigny, Etienne, Uotila, Petteri, Vancoppenolle, Martin, Wang, Shiyu, Warlind, David, Willen, Ulrika, Wyser, Klaus, Yang, Shuting, Yepes-Arbos, Xavier, Zhang, Qiong, Doescher, Ralf, Acosta, Mario, Alessandri, Andrea, Anthoni, Peter, Arsouze, Thomas, Bergman, Tommi, Bernardello, Raffaele, Boussetta, Souhail, Caron, Louis-Philippe, Carver, Glenn, Castrillo, Miguel, Catalano, Franco, Cvijanovic, Ivana, Davini, Paolo, Dekker, Evelien, Doblas-Reyes, Francisco J., Docquier, David, Echevarria, Pablo, Fladrich, Uwe, Fuentes Franco, Ramon, Groger, Matthias, Hardenberg, Jost, V, Hieronymus, Jenny, Karami, Pasha, Keskinen, Jukka-Pekka, Koenigk, Torben, Makkonen, Risto, Massonnet, Francois, Menegoz, Martin, Miller, Paul A., Moreno-Chamarro, Eduardo, Nieradzik, Lars, van Noije, Twan, Nolan, Paul, O'Donnell, Declan, Ollinaho, Pirkka, van den Oord, Gijs, Ortega, Pablo, Tinto Prims, Oriol, Ramos, Arthur, Reerink, Thomas, Rousset, Clement, Ruprich-Robert, Yohan, Le Sager, Philippe, Schmith, Torben, Schrodner, Roland, Serva, Federico, Sicardi, Valentina, Madsen, Marianne Sloth, Smith, Benjamin, Tian, Tian, Tourigny, Etienne, Uotila, Petteri, Vancoppenolle, Martin, Wang, Shiyu, Warlind, David, Willen, Ulrika, Wyser, Klaus, Yang, Shuting, Yepes-Arbos, Xavier, and Zhang, Qiong
- Published
- 2022
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39. The EC-Earth3 Earth system model for the Coupled Model Intercomparison Project 6
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UCL - SST/ELI/ELIC - Earth & Climate, Döscher, Ralf, Acosta, Mario, Alessandri, Andrea, Anthoni, Peter, Arsouze, Thomas, Bergman, Tommi, Bernardello, Raffaele, Boussetta, Souhail, Caron, Louis-Philippe, Carver, Glenn, Castrillo, Miguel, Catalano, Franco, Cvijanovic, Ivana, Davini, Paolo, Dekker, Evelien, Doblas-Reyes, Francisco J., Docquier, David, Echevarria, Pablo, Fladrich, Uwe, Fuentes-Franco, Ramon, Gröger, Matthias, v. Hardenberg, Jost, Hieronymus, Jenny, Karami, M. Pasha, Keskinen, Jukka-Pekka, Koenigk, Torben, Makkonen, Risto, Massonnet, François, Ménégoz, Martin, Miller, Paul A., Moreno-Chamarro, Eduardo, Nieradzik, Lars, van Noije, Twan, Nolan, Paul, O'Donnell, Declan, Ollinaho, Pirkka, van den Oord, Gijs, Ortega, Pablo, Prims, Oriol Tintó, Ramos, Arthur, Reerink, Thomas, Rousset, Clement, Ruprich-Robert, Yohan, Le Sager, Philippe, Schmith, Torben, Schrödner, Roland, Serva, Federico, Sicardi, Valentina, Sloth Madsen, Marianne, Smith, Benjamin, Tian, Tian, Tourigny, Etienne, Uotila, Petteri, Vancoppenolle, Martin, Wang, Shiyu, Wårlind, David, Willén, Ulrika, Wyser, Klaus, Yang, Shuting, Yepes-Arbós, Xavier, Zhang, Qiong, UCL - SST/ELI/ELIC - Earth & Climate, Döscher, Ralf, Acosta, Mario, Alessandri, Andrea, Anthoni, Peter, Arsouze, Thomas, Bergman, Tommi, Bernardello, Raffaele, Boussetta, Souhail, Caron, Louis-Philippe, Carver, Glenn, Castrillo, Miguel, Catalano, Franco, Cvijanovic, Ivana, Davini, Paolo, Dekker, Evelien, Doblas-Reyes, Francisco J., Docquier, David, Echevarria, Pablo, Fladrich, Uwe, Fuentes-Franco, Ramon, Gröger, Matthias, v. Hardenberg, Jost, Hieronymus, Jenny, Karami, M. Pasha, Keskinen, Jukka-Pekka, Koenigk, Torben, Makkonen, Risto, Massonnet, François, Ménégoz, Martin, Miller, Paul A., Moreno-Chamarro, Eduardo, Nieradzik, Lars, van Noije, Twan, Nolan, Paul, O'Donnell, Declan, Ollinaho, Pirkka, van den Oord, Gijs, Ortega, Pablo, Prims, Oriol Tintó, Ramos, Arthur, Reerink, Thomas, Rousset, Clement, Ruprich-Robert, Yohan, Le Sager, Philippe, Schmith, Torben, Schrödner, Roland, Serva, Federico, Sicardi, Valentina, Sloth Madsen, Marianne, Smith, Benjamin, Tian, Tian, Tourigny, Etienne, Uotila, Petteri, Vancoppenolle, Martin, Wang, Shiyu, Wårlind, David, Willén, Ulrika, Wyser, Klaus, Yang, Shuting, Yepes-Arbós, Xavier, and Zhang, Qiong
- Published
- 2022
40. Climate change penalty and benefit on surface ozone : A global perspective based on CMIP6 earth system models
- Author
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Zanis, Prodromos, Akritidis, Dimitris, Turnock, Steven, Naik, Vaishali, Szopa, Sophie, Georgoulias, Aristeidis K., Bauer, Susanne E., Deushi, Makoto, Horowitz, Larry W., Keeble, James, Le Sager, Philippe, O'Connor, Fiona M., Oshima, Naga, Tsigaridis, Konstantinos, Van Noije, Twan, Zanis, Prodromos, Akritidis, Dimitris, Turnock, Steven, Naik, Vaishali, Szopa, Sophie, Georgoulias, Aristeidis K., Bauer, Susanne E., Deushi, Makoto, Horowitz, Larry W., Keeble, James, Le Sager, Philippe, O'Connor, Fiona M., Oshima, Naga, Tsigaridis, Konstantinos, and Van Noije, Twan
- Abstract
This work presents an analysis of the effect of climate change on surface ozone discussing the related penalties and benefits around the globe from the global modelling perspective based on simulations with five CMIP6 (Coupled Model Intercomparison Project Phase 6) Earth System Models. As part of AerChemMIP (Aerosol Chemistry Model Intercomparison Project) all models conducted simulation experiments considering future climate (ssp370SST) and present-day climate (ssp370pdSST) under the same future emissions trajectory (SSP3-7.0). A multi-model global average climate change benefit on surface ozone of -0.96 ± 0.07 ppbv °C-1 is calculated which is mainly linked to the dominating role of enhanced ozone destruction with higher water vapour abundances under a warmer climate. Over regions remote from pollution sources, there is a robust decline in mean surface ozone concentration on an annual basis as well as for boreal winter and summer varying spatially from -0.2 to -2 ppbv °C-1, with strongest decline over tropical oceanic regions. The implication is that over regions remote from pollution sources (except over the Arctic) there is a consistent climate change benefit for baseline ozone due to global warming. However, ozone increases over regions close to anthropogenic pollution sources or close to enhanced natural biogenic volatile organic compounds emission sources with a rate ranging regionally from 0.2 to 2 ppbv C-1, implying a regional surface ozone penalty due to global warming. Overall, the future climate change enhances the efficiency of precursor emissions to generate surface ozone in polluted regions and thus the magnitude of this effect depends on the regional emission changes considered in this study within the SSP3_7.0 scenario. The comparison of the climate change impact effect on surface ozone versus the combined effect of climate and emission changes indicates the dominant role of precursor emission changes in projecting surface ozone concentrations under
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- 2022
41. Multiphase processes in the EC-Earth model and their relevance to the atmospheric oxalate, sulfate, and iron cycles
- Author
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Universitat Politècnica de Catalunya. Doctorat en Enginyeria Ambiental, Universitat Politècnica de Catalunya. Departament d'Enginyeria de Projectes i de la Construcció, Barcelona Supercomputing Center, Myriokefalitakis, Stelios, Bergas Massó, Elisa, Gonçalves Ageitos, María, Pérez García-Pando, Carlos, van Noije, Twan, Le Sager, Philippe, Ito, Akinori, Athanasopoulou, Eleni, Nenes, Athanasios, Kanakidou, Maria, Krol, Maarten, Gerasopoulos, Evangelos, Universitat Politècnica de Catalunya. Doctorat en Enginyeria Ambiental, Universitat Politècnica de Catalunya. Departament d'Enginyeria de Projectes i de la Construcció, Barcelona Supercomputing Center, Myriokefalitakis, Stelios, Bergas Massó, Elisa, Gonçalves Ageitos, María, Pérez García-Pando, Carlos, van Noije, Twan, Le Sager, Philippe, Ito, Akinori, Athanasopoulou, Eleni, Nenes, Athanasios, Kanakidou, Maria, Krol, Maarten, and Gerasopoulos, Evangelos
- Abstract
Understanding how multiphase processes affect the iron-containing aerosol cycle is key to predicting ocean biogeochemistry changes and hence the feedback effects on climate. For this work, the EC-Earth Earth system model in its climate–chemistry configuration is used to simulate the global atmospheric oxalate (OXL), sulfate (SO), and iron (Fe) cycles after incorporating a comprehensive representation of the multiphase chemistry in cloud droplets and aerosol water. The model considers a detailed gas-phase chemistry scheme, all major aerosol components, and the partitioning of gases in aerosol and atmospheric water phases. The dissolution of Fe-containing aerosols accounts kinetically for the solution's acidity, oxalic acid, and irradiation. Aerosol acidity is explicitly calculated in the model, both for accumulation and coarse modes, accounting for thermodynamic processes involving inorganic and crustal species from sea salt and dust. Simulations for present-day conditions (2000–2014) have been carried out with both EC-Earth and the atmospheric composition component of the model in standalone mode driven by meteorological fields from ECMWF's ERA-Interim reanalysis. The calculated global budgets are presented and the links between the (1) aqueous-phase processes, (2) aerosol dissolution, and (3) atmospheric composition are demonstrated and quantified. The model results are supported by comparison to available observations. We obtain an average global OXL net chemical production of 12.615 ± 0.064 Tg yr−1 in EC-Earth, with glyoxal being by far the most important precursor of oxalic acid. In comparison to the ERA-Interim simulation, differences in atmospheric dynamics and the simulated weaker oxidizing capacity in EC-Earth overall result in a ∼ 30 % lower OXL source. On the other hand, the more explicit representation of the aqueous-phase chemistry in EC-Earth compared to the previous versions of the model leads to an overall ∼ 20 % higher sulfate production, but this is, Stelios Myriokefalitakis, Evangelos Gerasopoulos, and Maria Kanakidou acknowledge support by the project “PANhellenic infrastructure for Atmospheric Composition and climatE change” (MIS 5021516) implemented under the Action “Reinforcement of the Research and Innovation Infrastructure”, which is funded by the Operational Programme “Competitiveness, Entrepreneurship and Innovation” (NSRF 2014–2020) and cofinanced by Greece and the European Union (European Regional Development Fund). This work was supported by computational time granted from the National Infrastructures for Research and Technology S.A. (GRNET S.A.) in the National HPC facility – ARIS – under project ID 010003 (ANION). Elisa Bergas-Massó, María Gonçalves-Ageitos, and Carlos Pérez García-Pando gratefully acknowledge the computer resources at Marenostrum4 granted through the PRACE project eFRAGMENT3 and the RES project AECT-2020-3-0020, as well as the technical support provided by the Barcelona Supercomputing Center (BSC) and the CES team of the Earth Sciences Department. Their work was supported by the ERC Consolidator Grant FRAGMENT (grant agreement no. 773051) and the AXA Chair on Sand and Dust Storms at BSC funded by the AXA Research Fund, both of which are led by Carlos Pérez García-Pando, who also acknowledges the Ramon y Cajal program (grant no. RYC-2015-18690) of the Spanish Ministry of Science, Innovation and Universities and the ICREA program. The research leading to these results has also received funding from the Spanish Ministerio de Economía y Competitividad as part of the NUTRIENT project (CGL2017-88911-R) and the H2020 GA 821205 project FORCeS. Support for this research was provided to Akinori Ito by the JSPS KAKENHI (grant no. 20H04329) and the Integrated Research Program for Advancing Climate Models (TOUGOU) (grant no. JPMXD0717935715) from the Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan. Twan van Noije, Philippe Le Sager, Maria Kanakidou, and Stelios Myr, Peer Reviewed, Postprint (published version)
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- 2022
42. Multiphase processes in the EC-Earth model and their relevance to the atmospheric oxalate, sulfate, and iron cycles
- Author
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Myriokefalitakis, Stelios, Bergas-Massó, Elisa, Gonçalves-Ageitos, María, García-Pando, Carlos Pérez, Van Noije, Twan, Le Sager, Philippe, Ito, Akinori, Athanasopoulou, Eleni, Nenes, Athanasios, Kanakidou, Maria, Krol, Maarten C., Gerasopoulos, Evangelos, Myriokefalitakis, Stelios, Bergas-Massó, Elisa, Gonçalves-Ageitos, María, García-Pando, Carlos Pérez, Van Noije, Twan, Le Sager, Philippe, Ito, Akinori, Athanasopoulou, Eleni, Nenes, Athanasios, Kanakidou, Maria, Krol, Maarten C., and Gerasopoulos, Evangelos
- Abstract
Understanding how multiphase processes affect the iron-containing aerosol cycle is key to predicting ocean biogeochemistry changes and hence the feedback effects on climate. For this work, the EC-Earth Earth system model in its climate-chemistry configuration is used to simulate the global atmospheric oxalate (OXL), sulfate (SO42-), and iron (Fe) cycles after incorporating a comprehensive representation of the multiphase chemistry in cloud droplets and aerosol water. The model considers a detailed gas-phase chemistry scheme, all major aerosol components, and the partitioning of gases in aerosol and atmospheric water phases. The dissolution of Fe-containing aerosols accounts kinetically for the solution's acidity, oxalic acid, and irradiation. Aerosol acidity is explicitly calculated in the model, both for accumulation and coarse modes, accounting for thermodynamic processes involving inorganic and crustal species from sea salt and dust. Simulations for present-day conditions (2000-2014) have been carried out with both EC-Earth and the atmospheric composition component of the model in standalone mode driven by meteorological fields from ECMWF's ERA-Interim reanalysis. The calculated global budgets are presented and the links between the (1) aqueous-phase processes, (2) aerosol dissolution, and (3) atmospheric composition are demonstrated and quantified. The model results are supported by comparison to available observations. We obtain an average global OXL net chemical production of 12.615 ± 0.064 Tg yr-1 in EC-Earth, with glyoxal being by far the most important precursor of oxalic acid. In comparison to the ERA-Interim simulation, differences in atmospheric dynamics and the simulated weaker oxidizing capacity in EC-Earth overall result in a ∼ 30 % lower OXL source. On the other hand, the more explicit representation of the aqueous-phase chemistry in EC-Earth compared to the previous versions of the model leads to an overall ∼ 20 % higher sulfate production, but this
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- 2022
43. Multiphase processes in the EC-Earth model and their relevance to the atmospheric oxalate, sulfate, and iron cycles
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Myriokefalitakis, Stelios, primary, Bergas-Massó, Elisa, additional, Gonçalves-Ageitos, María, additional, Pérez García-Pando, Carlos, additional, van Noije, Twan, additional, Le Sager, Philippe, additional, Ito, Akinori, additional, Athanasopoulou, Eleni, additional, Nenes, Athanasios, additional, Kanakidou, Maria, additional, Krol, Maarten C., additional, and Gerasopoulos, Evangelos, additional
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- 2022
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44. The EC-Earth3 Earth system model for the Coupled Model Intercomparison Project 6
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Döscher, Ralf, primary, Acosta, Mario, additional, Alessandri, Andrea, additional, Anthoni, Peter, additional, Arsouze, Thomas, additional, Bergman, Tommi, additional, Bernardello, Raffaele, additional, Boussetta, Souhail, additional, Caron, Louis-Philippe, additional, Carver, Glenn, additional, Castrillo, Miguel, additional, Catalano, Franco, additional, Cvijanovic, Ivana, additional, Davini, Paolo, additional, Dekker, Evelien, additional, Doblas-Reyes, Francisco J., additional, Docquier, David, additional, Echevarria, Pablo, additional, Fladrich, Uwe, additional, Fuentes-Franco, Ramon, additional, Gröger, Matthias, additional, v. Hardenberg, Jost, additional, Hieronymus, Jenny, additional, Karami, M. Pasha, additional, Keskinen, Jukka-Pekka, additional, Koenigk, Torben, additional, Makkonen, Risto, additional, Massonnet, François, additional, Ménégoz, Martin, additional, Miller, Paul A., additional, Moreno-Chamarro, Eduardo, additional, Nieradzik, Lars, additional, van Noije, Twan, additional, Nolan, Paul, additional, O'Donnell, Declan, additional, Ollinaho, Pirkka, additional, van den Oord, Gijs, additional, Ortega, Pablo, additional, Prims, Oriol Tintó, additional, Ramos, Arthur, additional, Reerink, Thomas, additional, Rousset, Clement, additional, Ruprich-Robert, Yohan, additional, Le Sager, Philippe, additional, Schmith, Torben, additional, Schrödner, Roland, additional, Serva, Federico, additional, Sicardi, Valentina, additional, Sloth Madsen, Marianne, additional, Smith, Benjamin, additional, Tian, Tian, additional, Tourigny, Etienne, additional, Uotila, Petteri, additional, Vancoppenolle, Martin, additional, Wang, Shiyu, additional, Wårlind, David, additional, Willén, Ulrika, additional, Wyser, Klaus, additional, Yang, Shuting, additional, Yepes-Arbós, Xavier, additional, and Zhang, Qiong, additional
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- 2022
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45. Effects of aerosols reduction on the Asian summer monsoon prediction: the case of summer 2020
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Cherchi, Annalisa, primary, Alessandri, Andrea, additional, Tourigny, Etienne, additional, Acosta Navarro, Juan C, additional, Ortega, Pablo, additional, Davini, Paolo, additional, Volpi, Danila, additional, Catalano, Franco, additional, and van Noije, Twan, additional
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- 2022
- Full Text
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46. Climate change impact on surface ozone based on CMIP6 Earth System Models
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Zanis, Prodromos, primary, Akritidis, Dimitris, additional, Turnock, Steven, additional, Naik, Vaishali, additional, Szopa, Sophie, additional, Georgoulias, Aristeidis Κ., additional, Bauer, Susanne E., additional, Deushi, Makoto, additional, Horowitz, Larry W., additional, Keeble, James, additional, Le Sager, Philippe, additional, O'Connor, Fiona M., additional, Oshima, Naga, additional, Tsigaridis, Konstantinos, additional, and van Noije, Twan, additional
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- 2022
- Full Text
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47. Supplementary material to "Comparison of particle number size distribution trends in ground measurements and climate models"
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Leinonen, Ville, primary, Kokkola, Harri, additional, Yli-Juuti, Taina, additional, Mielonen, Tero, additional, Kühn, Thomas, additional, Nieminen, Tuomo, additional, Heikkinen, Simo, additional, Miinalainen, Tuuli, additional, Bergman, Tommi, additional, Carslaw, Ken, additional, Decesari, Stefano, additional, Fiebig, Markus, additional, Hussein, Tareq, additional, Kivekäs, Niku, additional, Kulmala, Markku, additional, Leskinen, Ari, additional, Massling, Andreas, additional, Mihalopoulos, Nikos, additional, Mulcahy, Jane P., additional, Noe, Steffen M., additional, van Noije, Twan, additional, O'Connor, Fiona M., additional, O'Dowd, Colin, additional, Olivie, Dirk, additional, Pernov, Jakob B., additional, Petäjä, Tuukka, additional, Seland, Øyvind, additional, Schulz, Michael, additional, Scott, Catherine E., additional, Skov, Henrik, additional, Swietlicki, Erik, additional, Tuch, Thomas, additional, Wiedensohler, Alfred, additional, Virtanen, Annele, additional, and Mikkonen, Santtu, additional
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- 2022
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48. Supplementary material to "Satellite-based evaluation of AeroCom model bias in biomass burning regions"
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Zhong, Qirui, primary, Schutgens, Nick, additional, van der Werf, Guido, additional, van Noije, Twan, additional, Tsigaridis, Kostas, additional, Bauer, Susanne E., additional, Mielonen, Tero, additional, Kirkevåg, Alf, additional, Seland, Øyvind, additional, Kokkola, Harri, additional, Checa-Garcia, Ramiro, additional, Neubauer, David, additional, Kipling, Zak, additional, Matsui, Hitoshi, additional, Ginoux, Paul, additional, Takemura, Toshihiko, additional, Le Sager, Philippe, additional, Rémy, Samuel, additional, Bian, Huisheng, additional, Chin, Mian, additional, Zhang, Kai, additional, Zhu, Jialei, additional, Tsyro, Svetlana G., additional, Curci, Gabriele, additional, Protonotariou, Anna, additional, Johnson, Ben, additional, Penner, Joyce E., additional, Bellouin, Nicolas, additional, Skeie, Ragnhild B., additional, and Myhre, Gunnar, additional
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- 2022
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49. Long-term temporal relationships between environmental conditions and xylem functional traits: a meta-analysis across a range of woody species along climatic and nitrogen deposition gradients
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Borghetti, Marco, Gentilesca, Tiziana, Leonardi, Stefano, van Noije, Twan, and Rita, Angelo
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- 2017
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50. EC-Earth3.3.2.1-Fe
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Myriokefalitakis, Stelios, Bergas-Massó, Elisa, Gonçalves-Ageitos, María, Pérez García Pando, Carlos, van Noije, Twan, and Le Sager, Philippe
- Subjects
EC-Earth, iron, oxalate, sulfate - Abstract
Model outputs used forthe publication entitled"Multiphase processes in the EC-Earth Earth System model and their relevance to the atmospheric oxalate, sulfate, and iron cycles" by S. Myriokefalitakis et al.,currently under review for the journal GMD. (seehttps://doi.org/10.5194/gmd-2021-357).
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- 2021
- Full Text
- View/download PDF
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