Articles | Volume 13, issue 12
https://doi.org/10.5194/gmd-13-6165-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-13-6165-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Overview of the Norwegian Earth System Model (NorESM2) and key climate response of CMIP6 DECK, historical, and scenario simulations
Norwegian Meteorological Institute, Oslo, Norway
Mats Bentsen
NORCE Norwegian Research Centre AS and Bjerknes Centre for Climate Research, Bergen, Norway
Dirk Olivié
Norwegian Meteorological Institute, Oslo, Norway
Thomas Toniazzo
NORCE Norwegian Research Centre AS and Bjerknes Centre for Climate Research, Bergen, Norway
Stockholm University, Department of Meteorology, Stockholm, Sweden
Ada Gjermundsen
Norwegian Meteorological Institute, Oslo, Norway
Lise Seland Graff
Norwegian Meteorological Institute, Oslo, Norway
Jens Boldingh Debernard
Norwegian Meteorological Institute, Oslo, Norway
Alok Kumar Gupta
NORCE Norwegian Research Centre AS and Bjerknes Centre for Climate Research, Bergen, Norway
Yan-Chun He
Nansen Environmental and Remote Sensing Center, Bergen, Norway
Alf Kirkevåg
Norwegian Meteorological Institute, Oslo, Norway
Jörg Schwinger
NORCE Norwegian Research Centre AS and Bjerknes Centre for Climate Research, Bergen, Norway
Jerry Tjiputra
NORCE Norwegian Research Centre AS and Bjerknes Centre for Climate Research, Bergen, Norway
Kjetil Schanke Aas
University of Oslo, Department of Geosciences, Oslo, Norway
Ingo Bethke
Geophysical Institute, University in Bergen, and Bjerknes Centre for Climate Research, Bergen, Norway
Yuanchao Fan
NORCE Norwegian Research Centre AS and Bjerknes Centre for Climate Research, Bergen, Norway
Jan Griesfeller
Norwegian Meteorological Institute, Oslo, Norway
Alf Grini
Norwegian Meteorological Institute, Oslo, Norway
Chuncheng Guo
NORCE Norwegian Research Centre AS and Bjerknes Centre for Climate Research, Bergen, Norway
Mehmet Ilicak
Eurasia Institute of Earth Sciences, Istanbul Technical University, Istanbul, Turkey
NORCE Norwegian Research Centre AS and Bjerknes Centre for Climate Research, Bergen, Norway
Inger Helene Hafsahl Karset
University of Oslo, Department of Geosciences, Oslo, Norway
Oskar Landgren
Norwegian Meteorological Institute, Oslo, Norway
Johan Liakka
Nansen Environmental and Remote Sensing Center, Bergen, Norway
Kine Onsum Moseid
Norwegian Meteorological Institute, Oslo, Norway
Aleksi Nummelin
NORCE Norwegian Research Centre AS and Bjerknes Centre for Climate Research, Bergen, Norway
Clemens Spensberger
Geophysical Institute, University in Bergen, and Bjerknes Centre for Climate Research, Bergen, Norway
University of Oslo, Department of Geosciences, Oslo, Norway
Zhongshi Zhang
NORCE Norwegian Research Centre AS and Bjerknes Centre for Climate Research, Bergen, Norway
Christoph Heinze
Geophysical Institute, University in Bergen, and Bjerknes Centre for Climate Research, Bergen, Norway
Trond Iversen
Norwegian Meteorological Institute, Oslo, Norway
University of Oslo, Department of Geosciences, Oslo, Norway
Michael Schulz
Norwegian Meteorological Institute, Oslo, Norway
University of Oslo, Department of Geosciences, Oslo, Norway
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Winds carry vast amounts of Saharan dust across the Atlantic Ocean, influencing climate, air quality, and ocean ecosystems. Within the Aerosol Comparisons between Observations and Models (AeroCom) project, we evaluated 17 numerical models against observations. Models deposit dust too quickly, so too little reaches the Caribbean. Better simulations require emitting larger particles, treating their non-spherical shapes, and capturing processes that keep dust aloft during transport.
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This study looks at how well climate models capture the impact of rain on particles that help form cloud droplets. Using data from three measurement stations and applying both a correlation analysis and a machine learning approach, we found that models often miss how new particles form after rain and struggle in cold environments. This matters because these particles influence cloud formation and climate.
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Fangxuan Ren, Jintai Lin, Chenghao Xu, Jamiu A. Adeniran, Jingxu Wang, Randall V. Martin, Aaron van Donkelaar, Melanie S. Hammer, Larry W. Horowitz, Steven T. Turnock, Naga Oshima, Jie Zhang, Susanne Bauer, Kostas Tsigaridis, Øyvind Seland, Pierre Nabat, David Neubauer, Gary Strand, Twan van Noije, Philippe Le Sager, and Toshihiko Takemura
Geosci. Model Dev., 17, 4821–4836, https://doi.org/10.5194/gmd-17-4821-2024, https://doi.org/10.5194/gmd-17-4821-2024, 2024
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We evaluate the performance of 14 CMIP6 ESMs in simulating total PM2.5 and its 5 components over China during 2000–2014. PM2.5 and its components are underestimated in almost all models, except that black carbon (BC) and sulfate are overestimated in two models, respectively. The underestimation is the largest for organic carbon (OC) and the smallest for BC. Models reproduce the observed spatial pattern for OC, sulfate, nitrate and ammonium well, yet the agreement is poorer for BC.
Astrid Fremme, Paul J. Hezel, Øyvind Seland, and Harald Sodemann
Weather Clim. Dynam., 4, 449–470, https://doi.org/10.5194/wcd-4-449-2023, https://doi.org/10.5194/wcd-4-449-2023, 2023
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We study the atmospheric moisture transport into eastern China for past, present, and future climate. Hence, we use different climate and weather prediction model data with a moisture source identification method. We find that while the moisture to first order originates mostly from similar regions, smaller changes consistently point to differences in the recycling of precipitation over land between different climates. Some differences are larger between models than between different climates.
Peter Kuma, Frida A.-M. Bender, Alex Schuddeboom, Adrian J. McDonald, and Øyvind Seland
Atmos. Chem. Phys., 23, 523–549, https://doi.org/10.5194/acp-23-523-2023, https://doi.org/10.5194/acp-23-523-2023, 2023
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Ville Leinonen, Harri Kokkola, Taina Yli-Juuti, Tero Mielonen, Thomas Kühn, Tuomo Nieminen, Simo Heikkinen, Tuuli Miinalainen, Tommi Bergman, Ken Carslaw, Stefano Decesari, Markus Fiebig, Tareq Hussein, Niku Kivekäs, Radovan Krejci, Markku Kulmala, Ari Leskinen, Andreas Massling, Nikos Mihalopoulos, Jane P. Mulcahy, Steffen M. Noe, Twan van Noije, Fiona M. O'Connor, Colin O'Dowd, Dirk Olivie, Jakob B. Pernov, Tuukka Petäjä, Øyvind Seland, Michael Schulz, Catherine E. Scott, Henrik Skov, Erik Swietlicki, Thomas Tuch, Alfred Wiedensohler, Annele Virtanen, and Santtu Mikkonen
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Petri Räisänen, Joonas Merikanto, Risto Makkonen, Mikko Savolahti, Alf Kirkevåg, Maria Sand, Øyvind Seland, and Antti-Ilari Partanen
Atmos. Chem. Phys., 22, 11579–11602, https://doi.org/10.5194/acp-22-11579-2022, https://doi.org/10.5194/acp-22-11579-2022, 2022
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Atmos. Chem. Phys., 22, 11009–11032, https://doi.org/10.5194/acp-22-11009-2022, https://doi.org/10.5194/acp-22-11009-2022, 2022
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Ingo Bethke, Yiguo Wang, François Counillon, Noel Keenlyside, Madlen Kimmritz, Filippa Fransner, Annette Samuelsen, Helene Langehaug, Lea Svendsen, Ping-Gin Chiu, Leilane Passos, Mats Bentsen, Chuncheng Guo, Alok Gupta, Jerry Tjiputra, Alf Kirkevåg, Dirk Olivié, Øyvind Seland, Julie Solsvik Vågane, Yuanchao Fan, and Tor Eldevik
Geosci. Model Dev., 14, 7073–7116, https://doi.org/10.5194/gmd-14-7073-2021, https://doi.org/10.5194/gmd-14-7073-2021, 2021
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The Norwegian Climate Prediction Model version 1 (NorCPM1) is a new research tool for performing climate reanalyses and seasonal-to-decadal climate predictions. It adds data assimilation capability to the Norwegian Earth System Model version 1 (NorESM1) and has contributed output to the Decadal Climate Prediction Project (DCPP) as part of the sixth Coupled Model Intercomparison Project (CMIP6). We describe the system and evaluate its baseline, reanalysis and prediction performance.
Abigail L. S. Swann, Charles D. Koven, Cristian Proistosecu, Rosie A. Fisher, Benjamin M. Sanderson, Victor Brovkin, Tomohiro Hajima, Chris D. Jones, Nancy Y. Kiang, David M. Lawrence, Spencer Liddicoat, Hannah Liddy, Anastasia Romanou, Roland Séférian, Lori T. Sentman, Norman J. Steinert, Jerry Tjiputra, and Tilo Ziehn
Earth Syst. Dynam., 17, 1237–1275, https://doi.org/10.5194/esd-17-1237-2026, https://doi.org/10.5194/esd-17-1237-2026, 2026
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We analyzed simulations from Earth system models (ESM) with a constant rate of emissions, zero emissions, and negative emissions of CO2 to quantify the response of land carbon sinks. We found that under positive emissions vegetation in the tropics gained carbon. Under zero emissions and negative emissions most ESMs lost carbon from vegetation in the tropics but gained carbon in mid- and high-latitudes, mostly in soils. Our findings imply that tropical carbon is vulnerable under zero emissions.
Jianyu Zheng, Hongbin Yu, Chamara Rajapakse, Mian Chin, Michael Schulz, Yves Balkanski, Susanne E. Bauer, Huisheng Bian, Peter Colarco, Dongchul Kim, Ramiro Checa-Garcia, Yevgeny Derimian, Oleg Dubovik, Paul Ginoux, Zak Kipling, Jasper F. Kok, Harri Kokkola, Philippe Le Sager, Lei Li, Marianne Tronstad Lund, Gunnar Myhre, Hitoshi Matsui, Dirk J. L. Olivie, Samuel Remy, Oyvind Seland, Qianqian Song, Toshihiko Takemura, Qian Tan, Kostas Tsigaridis, Twan van Noije, David Winker, Bin Xie, Hua Zhang, Xindan Zhang, and Zhibo Zhang
EGUsphere, https://doi.org/10.5194/egusphere-2026-4322, https://doi.org/10.5194/egusphere-2026-4322, 2026
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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Winds carry vast amounts of Saharan dust across the Atlantic Ocean, influencing climate, air quality, and ocean ecosystems. Within the Aerosol Comparisons between Observations and Models (AeroCom) project, we evaluated 17 numerical models against observations. Models deposit dust too quickly, so too little reaches the Caribbean. Better simulations require emitting larger particles, treating their non-spherical shapes, and capturing processes that keep dust aloft during transport.
Quentin Dalaiden, François Counillon, Lea Svendsen, Ingo Bethke, and Noel Keenlyside
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2026-433, https://doi.org/10.5194/essd-2026-433, 2026
Preprint under review for ESSD
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Instrumental observations only cover a small part of Earth’s climate history, making it difficult to understand long-term climate changes. We combined information from natural climate archives, such as tree rings, corals, and ice cores, with a climate model to reconstruct climate variability over the last 500 years. Our reconstruction displays a good performance when compared with observations, provide a physically consistent picture of how the atmosphere and ocean evolved together through time.
Ragnhild Bieltvedt Skeie, Terje K. Berntsen, Ada Gjermundsen, Ragnar Bang Huseby, Gunnar Myhre, Dirk Olivié, and Trude Storelvmo
EGUsphere, https://doi.org/10.5194/egusphere-2026-4634, https://doi.org/10.5194/egusphere-2026-4634, 2026
This preprint is open for discussion and under review for Earth System Dynamics (ESD).
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Climate sensitivity is a key quantity in climate science. We tested an observation-based method for estimating climate sensitivity by replacing observations with historical climate model simulations. Estimates varied substantially among simulations of the same model where only the initial conditions differed. Since the historical climate is only one realization of the Earth’s climate, this highlights that natural variability is an important source of uncertainty in observation-based estimates.
Forrest M. Hoffman, Birgit Hassler, Ranjini Swaminathan, Jared Lewis, Bouwe Andela, Nathan Collier, Dóra Hegedűs, Jiwoo Lee, Charlotte Pascoe, Mika Pflüger, Martina Stockhause, Paul Ullrich, Min Xu, Lisa Bock, Felicity Chun, Bettina K. Gier, Douglas I. Kelley, Axel Lauer, Julien Lenhardt, Manuel Schlund, Mohanan G. Sreeush, Katja Weigel, Ed Blockley, Rebecca Beadling, Romain Beucher, Demiso D. Dugassa, Valerio Lembo, Jianhua Lu, Swen Brands, Jerry Tjiputra, Elizaveta Malinina, Brian Medeiros, Enrico Scoccimarro, Jeremy Walton, Phil Kershaw, André Lanfer Marquez, Malcolm J. Roberts, Eleanor O'Rourke, Beth Dingley, Briony Turner, Helene Hewitt, and John P. Dunne
Geosci. Model Dev., 19, 7415–7455, https://doi.org/10.5194/gmd-19-7415-2026, https://doi.org/10.5194/gmd-19-7415-2026, 2026
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The Rapid Evaluation Framework (REF) is a community-driven platform for benchmarking and performance assessment of Earth system models. Built upon four disparate community evaluation tools, the REF is designed to provide model-data comparisons for the Assessment Fast Track for the Seventh Phase of the Coupled Model Intercomparison Project. The REF will be run at the Earth System Grid Federation to enable model devleopers and scientists to quickly identify model biases and performance issues.
Sara M. Blichner, Theodore Khadir, Sini Talvinen, Paulo Artaxo, Liine Heikkinen, Harri Kokkola, Radovan Krejci, Muhammed Irfan, Twan van Noije, Tuukka Petäjä, Christopher Pöhlker, Øyvind Seland, Carl Svenhag, Antti Vartiainen, and Ilona Riipinen
Atmos. Chem. Phys., 26, 11281–11307, https://doi.org/10.5194/acp-26-11281-2026, https://doi.org/10.5194/acp-26-11281-2026, 2026
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This study looks at how well climate models capture the impact of rain on particles that help form cloud droplets. Using data from three measurement stations and applying both a correlation analysis and a machine learning approach, we found that models often miss how new particles form after rain and struggle in cold environments. This matters because these particles influence cloud formation and climate.
Natalie J. Burls, Nicky M. Wright, R. Paul Acosta, Catherine D. Bradshaw, Edward Gasson, Lennert B. Stap, Gilles Ramstein, Anna Ruth W. Halberstadt, Agatha M. De Boer, Funda Akgün, David J. Cantrill, Manuel Casas-Gallego, Nela Doláková, Boglarka Erdei, Alex Farnsworth, Sarah Feakins, Ran Feng, Tamara Fletcher, Frédéric Fluteau, J. A. Mattias Green, Anna S. von der Heydt, Matthew Huber, David K. Hutchinson, Dimiter Ivanov, Mine Sezgül Kayseri-Özer, Gregor Knorr, Marianna Kováčová, Caroline H. Lear, Allegra N. LeGrande, Shufeng Li, Xiaoqing Liu, Daniel J. Lunt, Katrin Meissner, Yunfa Miao, Trusha J. Naik, Javier B. Navarro, Joseph B. Novak, Diana Ochoa, Guy J.G. Paxman, Matthew J. Pound, James W. B. Rae, Tammo Reichgelt, Martin Renoult, Francesca Sangiorgi, Anta-Clarisse Sarr, Diane Segalla, Pierre Sepulchre, Amelia Shevenell, Sebastian Steinig, Eivind Straume, Caroline A. E. Strömberg, Clay Tabor, Torsten Utescher, Julia E. Weiffenbach, Elżbieta Worobiec, Yurui Zhang, Feng Zhu, Jiang Zhu, Alexandra Auderset, Florence Colleoni, Aisling Dolan, Rachel Havranek, Ann Holbourn, Nicholas Herold, Daeun Lee, James W. Marschalek, Bryce Mitsunaga, Sevi Modestou, Lina Perez-Angel, Mae Saslaw, Sinda Sosdian, Elena Stiles, Yong Sun, Ning Tan, Zhongshi Zhang, and Yan Zhao
EGUsphere, https://doi.org/10.5194/egusphere-2026-3595, https://doi.org/10.5194/egusphere-2026-3595, 2026
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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Simulating warm paleoclimates increases our understanding of the mechanisms that drive climatic change and tipping points. The Miocene Epoch, specifically the Miocene Climatic Optimum, has been identified as a particularly valuable past warm climate to simulate, meriting the design of a coordinated Miocene Model Intercomparison Project. Here we synthesize the latest available literature and present the experimental design for coordinated Miocene simulations and sensitivity studies.
Colin Jones, Isaline Bossert, Donovan P. Dennis, Hazel A. Jeffery, Chris D. Jones, Torben Koenigk, Sina Loriani, Benjamin Sanderson, Roland Séférian, Klaus Wyser, Shuting Yang, Manabu Abe, Sebastian Bathiany, Pascale Braconnot, Victor Brovkin, Friedrich A. Burger, Patrica Cadule, Frederic S. Castruccio, Gokhan Danabasoglu, Andrea Dittus, Jonathan F. Donges, Friederike Fröb, Thomas L. Frölicher, Goran Georgievski, Chuncheng Guo, Aixue Hu, Peter Lawrence, Paul Lerner, José Licón-Saláiz, Bette Otto-Bliesner, Anastasia Romanou, Elena Shevliakova, Yona Silvy, Didier Swingedouw, Jerry Tjiputra, Jeremy Walton, Andy Wiltshire, Ricarda Winkelmann, Richard Wood, Tokuta Yokohata, and Tilo Ziehn
Geosci. Model Dev., 19, 6941–6966, https://doi.org/10.5194/gmd-19-6941-2026, https://doi.org/10.5194/gmd-19-6941-2026, 2026
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We introduce a new Earth system model experiment protocol to help researchers understand how Earth might respond to positive, zero, and negative carbon emissions. This protocol enables different models to be compared following similar warming and cooling rates. Researchers use the models to explore how the Earth reacts to different climate futures, including the risk of tipping points being exceeded and whether changes can be reversed. The results will support improved long-term climate policy.
Marta Luffarelli, Nicolas Misk, Analy Baltodano, Thomas Popp, Stefan Kinne, Ulrike Stöffelmair, Michael Schulz, Jan Griesfeller, Ove W. Haugvalstad, Martin Stengel, Sarah Brüning, Gareth Thomas, Elisa Carboni, Daniel Robbins, and Michael Eisinger
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2026-327, https://doi.org/10.5194/essd-2026-327, 2026
Preprint under review for ESSD
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Louise C. Sime, Rachel Diamond, Christian Stepanek, Chris Brierley, David Schroeder, Masa Kageyama, Matthew Pollock, Irene Malmierca-Vallet, Ed Blockley, Alex West, Danny Feltham, Jeff Ridley, Pascale Braconnot, Charles J. R. Williams, Xiaoxu Shi, Bette L. Otto-Bliesner, Sophia I. Macarewich, Silvana Ramos Buarque, Qiong Zhang, Allegra LeGrande, Weipeng Zheng, Dabang Jiang, Polina Morozova, Chuncheng Guo, Zhongshi Zhang, Nicholas Yeung, Laurie Menviel, Sandeep Narayanasetti, Masakazu Yoshimori, Olivia Reeves, and Anni Zhao
Geosci. Model Dev., 19, 5881–5905, https://doi.org/10.5194/gmd-19-5881-2026, https://doi.org/10.5194/gmd-19-5881-2026, 2026
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The Arctic may have lost its summer sea ice 127,000 years ago during a naturally warm period in Earth’s past. Climate models can be tested by recreating those conditions, with similar sunlight and greenhouse gas levels. Analysing the large sea ice changes in these simulations helps us understand how the Arctic might respond in the near future and improves how we test and trust our climate models.
Qidi Yu, Clemens Spensberger, Linus Magnusson, and Thomas Spengler
Weather Clim. Dynam., 7, 1117–1131, https://doi.org/10.5194/wcd-7-1117-2026, https://doi.org/10.5194/wcd-7-1117-2026, 2026
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Forecast biases of winter extratropical cyclones are quantified by varying diabatic heating intensity. A southwest shift and underestimated intensity are found in the strong heating group. The weaker heating group mainly shows an intensity bias. Specific biases are identified for wind, moisture, temperature, and upper-level circulation fields. Findings highlight that representing moist processes and their interaction with atmospheric dynamics is a key area for future model developments.
Qidi Yu, Linus Magnusson, Clemens Spensberger, and Thomas Spengler
EGUsphere, https://doi.org/10.5194/egusphere-2026-3727, https://doi.org/10.5194/egusphere-2026-3727, 2026
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Forecast models still struggle to capture moisture and how it interacts with winter ocean storms. We compared 12-hour forecasts from a leading physics-based model at 9 km resolution and its artificial intelligence model. Both improve on the previous version, yet the former underestimates storm strength, linked to how it represents the vertical distribution of heating, while the latter shows a physical inconsistency: near-surface winds that do not match its pressure pattern.
Chris Smith, Lennart Ramme, Christopher D. Wells, Ada Gjermundsen, Hongmei Li, Tatiana Ilyina, Adakudlu Muralidhar, Timothée Bourgeois, Jörg Schwinger, Alejandro Romero-Prieto, Chao Li, and Cecilie Mauritzen
Earth Syst. Dynam., 17, 893–911, https://doi.org/10.5194/esd-17-893-2026, https://doi.org/10.5194/esd-17-893-2026, 2026
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We run two Earth System Models models in CO2 emissions-driven mode to 2300 for three climate scenarios. For climate overshoot scenarios, there is a large residual warming in the 22nd century in one model, despite negative CO2 emissions, related to Southern Ocean heat release. In both models, while global mean surface temperature is largely reversible, other global and regional climate models exhibit hysteresis and irreversibility.
Suki C. K. Wong, Galen A. McKinley, Richard Seager, Tess Wei-Ping Jacobson, Amanda Fay, Özgür Gürses, Nicolas Gruber, Tatiana Ilyina, Tereza Jarnikova, Laure Resplandy, Jörg Schwinger, and Roland Séférian
EGUsphere, https://doi.org/10.5194/egusphere-2026-3104, https://doi.org/10.5194/egusphere-2026-3104, 2026
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The ocean absorbs nearly a third of human-made carbon dioxide, slowing climate change. This uptake varies from decade to decade for reasons we do not fully understand. Using a 66-year ocean carbon dataset, we found that the tropical Pacific and Southern Ocean drive this variability, in step with broader climate patterns across the Pacific. But these patterns cannot fully explain the recent weakening of the Southern Ocean sink, suggesting biological processes may also play an important role.
Damien Couespel, Xabier Davila, Nadine Goris, Emil Jeansson, Siv K. Lauvset, and Jerry Tjiputra
Biogeosciences, 23, 3433–3466, https://doi.org/10.5194/bg-23-3433-2026, https://doi.org/10.5194/bg-23-3433-2026, 2026
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Remineralised carbon storage is projected to increase along the 21st century, but the magnitude of increase varies depending on the Earth system models. To constrain projections, we explore the relationship between remineralised carbon and deep ocean circulation. We show that the sensitivity of remineralised carbon to circulation slowdown varies considerably between models. More observational data and a larger model ensemble is needed to constrain projections of remineralised carbon storage.
Benjamin M. Sanderson, Marit Sandstad, Alejandro Romero-Prieto, Stuart Jenkins, Charles Koven, Glen Peters, Roland Séfèrian, Andrew H. MacDougall, Ashwin Seshadri, Victor Brovkin, John Dunne, Abigail L. S. Swann, Torben Koenigk, Rosie A. Fisher, David Hohn, Tatiana Ilyina, Chris D. Jones, Hongmei Li, Peter Lawrence, Spencer Liddicoat, Nadine Mengis, Anastasia Romanou, Lori T. Sentman, Chris Smith, Norman J. Steinert, Jerry Tjiputra, and Tilo Ziehn
EGUsphere, https://doi.org/10.5194/egusphere-2026-1875, https://doi.org/10.5194/egusphere-2026-1875, 2026
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When humanity stops emitting carbon dioxide, will temperatures keep rising, stabilize, or fall? Our study reveals in most models, temperatures remain nearly stable, but this hides a balance between the warming in response to radiation imbalance, and the cooling due to uptake of carbon in the land and ocean. Understanding this balance helps refine how much more CO2 we can safely emit.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Peter Landschützer, Corinne Le Quéré, Hongmei Li, Ingrid T. Luijkx, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Kjetil Aas, Simone R. Alin, Peter Anthoni, Leticia Barbero, Nicholas R. Bates, Nicolas Bellouin, Alice Benoit-Cattin, Carla F. Berghoff, Raffaele Bernardello, Laurent Bopp, Ida Bagus Mandhara Brasika, Matthew A. Chamberlain, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Nathan O. Collier, Thomas H. Colligan, Margot Cronin, Laique M. Djeutchouang, Xinyu Dou, Matt P. Enright, Kazutaka Enyo, Michael Erb, Wiley Evans, Richard A. Feely, Liang Feng, Daniel J. Ford, Adrianna Foster, Filippa Fransner, Thomas Gasser, Marion Gehlen, Thanos Gkritzalis, Jefferson Goncalves De Souza, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Bertrand Guenet, Özgür Gürses, Kirsty Harrington, Ian Harris, Jens Heinke, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Akihiko Ito, Andrew R. Jacobson, Atul K. Jain, Tereza Jarníková, Annika Jersild, Fei Jiang, Steve D. Jones, Etsushi Kato, Ralph F. Keeling, Kees Klein Goldewijk, Jürgen Knauer, Yawen Kong, Jan Ivar Korsbakken, Charles Koven, Taro Kunimitsu, Xin Lan, Junjie Liu, Zhiqiang Liu, Zhu Liu, Claire Lo Monaco, Lei Ma, Gregg Marland, Patrick C. McGuire, Galen A. McKinley, Joe R. Melton, Natalie Monacci, Erwan Monier, Eric J. Morgan, David R. Munro, Jens D. Müller, Shin-Ichiro Nakaoka, Lorna R. Nayagam, Yosuke Niwa, Tobias Nutzel, Are Olsen, Abdirahman M. Omar, Naiqing Pan, Sudhanshu Pandey, Denis Pierrot, Zhangcai Qin, Pierre Regnier, Gregor Rehder, Laure Resplandy, Alizée Roobaert, Thais M. Rosan, Christian Rödenbeck, Jörg Schwinger, Ingunn Skjelvan, T. Luke Smallman, Victoria Spada, Mohanan G. Sreeush, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Didier Swingedouw, Roland Séférian, Shintaro Takao, Hiroaki Tatebe, Hanqin Tian, Xiangjun Tian, Bronte Tilbrook, Hiroyuki Tsujino, Francesco Tubiello, Erik van Ooijen, Guido R. van der Werf, Sebastiaan J. van de Velde, Anthony P. Walker, Rik Wanninkhof, Xiaojuan Yang, Wenping Yuan, Xu Yue, and Jiye Zeng
Earth Syst. Sci. Data, 18, 3211–3288, https://doi.org/10.5194/essd-18-3211-2026, https://doi.org/10.5194/essd-18-3211-2026, 2026
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The Global Carbon Budget 2025 describes the methodology, main results, and datasets used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land ecosystems, and the ocean over the historical period (1750–2025). These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Jozef Skákala, Shubha Sathyendranath, Yuri Artioli, Deep S. Banerjee, Heather Bouman, Robert J. W. Brewin, Momme Butenschön, Stefano Ciavatta, Stephanie Dutkiewicz, Yanna Fidai, David Ford, Grinson George, Karen Guihou, Bror Jönsson, Marija Bačeković Koloper, Žarko Kovač, Lekshmi Krishnakumary, Gemma Kulk, Charlotte Laufkötter, Gennadi Lessin, Jann Paul Mattern, Angélique Melet, Alexandre Mignot, David Moffat, Fanny Monteiro, Mayra Rodriguez Bennadji, Cécile S. Rousseaux, Ranjini Swaminathan, Osvaldo Ulloa, and Jerry Tjiputra
Ocean Sci., 22, 1457–1481, https://doi.org/10.5194/os-22-1457-2026, https://doi.org/10.5194/os-22-1457-2026, 2026
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Marine primary production (PP) is a key component of the Earth's climate system, but its current estimates and future projections are highly uncertain. We review the PP uncertainties and discuss their sources both across the ecosystem and satellite models. We propose to reduce the PP uncertainties by better addressing the PP model structures and parametrizations. We also argue that for many models it is desirable to consider spatial and temporal variability in the model parameter values.
Caixin Wang, Jens Debernard, and Keguang Wang
EGUsphere, https://doi.org/10.5194/egusphere-2026-1525, https://doi.org/10.5194/egusphere-2026-1525, 2026
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NorESM2 generally reproduces the spatial distribution and seasonal evolution of MPs, although MPs forms later and develops faster compared to observations. Additionally, NorESM2 demonstrated a systematic underestimation of MPs in May and June, which was attributed to the low DSR in NorESM2 and the potential overestimation of MPF in MODIS and MERIS due to the coarse-resolution of the optical sensors. The absence of MPs in the early melt season has profound implications for the Arctic system.
Jianing Guo, Xiaoning Xie, Gunnar Myhre, Drew Shindell, Alf Kirkevåg, Trond Iversen, Apostolos Voulgarakis, Toshihiko Takemura, Ke Shang, Xinzhou Li, Zhengguo Shi, Yangang Liu, Xiaodong Liu, and Hong Yan
Atmos. Chem. Phys., 26, 5169–5184, https://doi.org/10.5194/acp-26-5169-2026, https://doi.org/10.5194/acp-26-5169-2026, 2026
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Central Asia has grown wetter in recent decades, but the drivers differ by season. We analyzed observations and climate model experiments to understand these changes and their future. Our analysis reveals that greenhouse gases from human activities drive winter wetting, whereas aerosol from Asia urbanization and industrialization enhances summer precipitation. As future reductions in air pollution, the region may experience drier summers and create new risks for regional water resources.
Quentin Dalaiden and Ingo Bethke
The Cryosphere, 20, 2089–2098, https://doi.org/10.5194/tc-20-2089-2026, https://doi.org/10.5194/tc-20-2089-2026, 2026
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Historical Antarctic climate before satellites contain uncertainties, a modern state-of-the-art atmospheric reanalysis indicates an unrealistically cold Antarctica in 1958–1978. We test how much of this bias comes from uncertain ocean and sea-ice conditions by performing two climate model ensembles with different ocean datasets. These differences affect Antarctic climate, but they explain only a fraction of the cold bias, meaning other factors also contribute.
Gunnar Myhre, Øivind Hodnebrog, Srinath Krishnan, Maria Sand, Marit Sandstad, Ragnhild B. Skeie, Lieven Clarisse, Bruno Franco, Dylan B. Millet, Kelley C. Wells, Alexander Archibald, Hannah N. Bryant, Alex T. Chaudhri, David S. Stevenson, Didier Hauglustaine, Michael Prather, J. Christopher Kaiser, Dirk J. L. Olivie, Michael Schulz, Oliver Wild, Ye Wang, Thérèse Salameh, Jason E. Williams, Philippe Le Sager, Fabien Paulot, Kostas Tsigaridis, and Haley E. Plaas
Geosci. Model Dev., 19, 2577–2591, https://doi.org/10.5194/gmd-19-2577-2026, https://doi.org/10.5194/gmd-19-2577-2026, 2026
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Volatile organic compounds (VOCs) affect air quality and climate, but their behavior in the atmosphere is still uncertain. We launched a global research effort to compare how different models represent these compounds and to improve their accuracy. By analyzing model results alongside observations and satellite data, we aim to better understand the atmospheric composition of these compounds.
Jörg Schwinger, Leon Merfort, Nico Bauer, Raffaele Bernadello, Momme Butenschön, Timothée Bourgeois, Matthew J. Gidden, Shraddha Gupta, Hanna Lee, Nadine Mengis, Yiannis Moustakis, Helene Muri, Lars Nieradzik, Daniele Peano, Julia Pongratz, Pascal Sauer, Etienne Tourigny, and David Wårlind
EGUsphere, https://doi.org/10.5194/egusphere-2026-833, https://doi.org/10.5194/egusphere-2026-833, 2026
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Earth system models can simulate CO2 removal by representing the activity that removes CO2 from the atmosphere, e.g. growing bioenergy crops for energy production with CCS or enhancing the surface oceans’ alkalinity. We describe a simulation framework, spanning the modeling chain from integrated assessment to Earth system models, that allows separating the intrinsic efficiency of CDR options from the overall atmospheric CO2 reduction, the latter including the effect of carbon-cycle feedbacks.
Jakob Dörr, Carlo Mans, Marius Årthun, Kristofer Döös, Dafydd Gwyn Evans, and Yanchun He
Ocean Sci., 22, 565–585, https://doi.org/10.5194/os-22-565-2026, https://doi.org/10.5194/os-22-565-2026, 2026
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The Arctic Ocean plays a key role in the global ocean circulation by producing dense waters that feed the lower limb of the Atlantic meridional overturning circulation (AMOC). We use a high-resolution ocean simulation to investigate the pathways and mechanisms through which these dense waters are formed in the Arctic. Our results show that surface cooling in the Barents Sea dominates the dense water production, but that internal mixing plays a role at high densities.
Morven Muilwijk, Tore Hattermann, Rebecca L. Beadling, Neil C. Swart, Aleksi Nummelin, Chuncheng Guo, David M. Chandler, Petra M. Langebroek, Shenjie Zhou, Pierre Dutrieux, Jia-Jia Chen, Christopher Danek, Matthew H. England, Stephen M. Griffies, F. Alexander Haumann, André Jüling, Ombeline Jouet, Qian Li, Torge Martin, John Marshall, Andrew G. Pauling, Ariaan Purich, Zihan Song, Inga J. Smith, Max Thomas, Irene Trombini, Eveline C. van der Linden, and Xiaoqi Xu
The Cryosphere, 20, 1087–1117, https://doi.org/10.5194/tc-20-1087-2026, https://doi.org/10.5194/tc-20-1087-2026, 2026
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Antarctic meltwater affects ocean stratification and temperature, which in turn influences the rate of ice shelf melting – a coupling missing in most climate models. We analyze a suite of climate models with added meltwater to explore this feedback in different regions. While meltwater generally enhances ocean warming and melt, in West Antarctica most models simulate coastal cooling, suggesting a negative feedback that could slow future ice loss there.
Peter W. Thorne, John M. Nicklas, John J. Kennedy, Bruce Calvert, Baylor Fox-Kemper, Mark T. Richardson, Adrian Simmons, Ed Hawkins, Robert Rhode, Kathryn Cowtan, Nerilie J. Abram, Axel Andersson, Simon Noone, Phillipe Marbaix, Nathan Lenssen, Dirk Olonscheck, Tristram Walsh, Stephen Outten, Ingo Bethke, Bjorn H. Samset, Chris Smith, Anna Pirani, Jan Fuglestvedt, Lavanya Rajamani, Richard A. Betts, Elizabeth C. Kent, Blair Trewin, Colin Morice, Tim Osborn, Samantha N. Burgess, Oliver Geden, Andrew Parnell, Piers M. Forster, Chris Hewitt, Zeke Hausfather, Valerie Masson-Delmotte, Jochem Marotzke, Nathan Gillett, Sonia I. Seneviratne, Gavin A. Schmidt, Duo Chan, Stefan Brönnimann, Andy Reisinger, Matthew Menne, Maisa Rojas Corradi, Christopher Kadow, Peter Huybers, David B. Stephenson, Emily Wallis, Joeri Rogelj, Andrew Schurer, Karen McKinnon, Panmao Zhai, Fatima Driouech, Wilfran Moufouma Okia, Saeed Vazifehkhah, Sophie Szopa, Christopher J. Merchant, Shoji Hirahara, Masayoshi Ishii, Francois A. Engelbrecht, Qingxiang Li, June-Yi Lee, Alex J. Cannon, Christophe Cassou, Karina von Schuckmann, Amir H. Delju, and Ellie Murtagh
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-825, https://doi.org/10.5194/essd-2025-825, 2026
Preprint under review for ESSD
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We reassess the basis for determining the present level of long-term global warming. Unbiased estimates of both realised warming and anthropogenic warming are possible that approximate a 20-year retrospective mean. Our resulting estimates of 1.40 [1.23–1.58] °C (realised) and 1.34 [1.18–1.50] °C (anthropogenic) as at end of 2024 highlight the urgency of immediate, far-reaching and sustained climate mitigation actions if we are to meet the long term temperature goal of the Paris Agreement.
Johannes Max Müller, Oskar Andreas Landgren, and Dörthe Handorf
Weather Clim. Dynam., 6, 1895–1921, https://doi.org/10.5194/wcd-6-1895-2025, https://doi.org/10.5194/wcd-6-1895-2025, 2025
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Weather and climate is determined by large-scale air pressure patterns, which can be grouped into a small number of representative patterns. We use two different statistical methods and data from 20 climate models to detect significant changes in a future scenario of strong warming. We focus on the summer season as this is important for both human activities and natural ecosystems. We find an increase in high pressure above Europe and low pressure above the Arctic ocean.
Hannah Vickers, Priscilla Mooney, and Oskar Landgren
The Cryosphere, 19, 6907–6926, https://doi.org/10.5194/tc-19-6907-2025, https://doi.org/10.5194/tc-19-6907-2025, 2025
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Rain-on-snow (ROS) events are becoming a common feature in winter in Svalbard due to climate warming. Understanding how ROS events are changing and how they will change in the coming decades is crucial to minimise their impacts. Using atmospheric reanalyses and climate projections we found contrasting trends between coastal and inland areas, and that the most dramatic future changes in ROS will occur in glaciated areas which will have considerable consequences for Svalbard's hydrology.
Hui Tang, Samuli Launianen, Julius Vira, Liisa Kulmala, Taru Palosuo, Hermanni Aaltonen, Olli Nevalainen, Istem Fer, Henriikka Vekuri, Jari-Pekka Nousu, Mika Korkiakoski, and Jari Liski
EGUsphere, https://doi.org/10.5194/egusphere-2025-5972, https://doi.org/10.5194/egusphere-2025-5972, 2025
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We present a modelling approach to study how crops in northern climates deal with water stress. By combining several years of field measurements with the modelling approach, we show that both oat and forage grasses use water cautiously, helping them preserve enough soil water to stay productive during dry periods. Our results highlight the need to better understand how northern crops use water for improving their food production in the future, when more frequent and severe drought will occur.
Philip J. Wallhead, Jörg Schwinger, Jerry Tjiputra, Trond Kristiansen, and Richard G. J. Bellerby
Earth Syst. Sci. Data, 17, 6763–6805, https://doi.org/10.5194/essd-17-6763-2025, https://doi.org/10.5194/essd-17-6763-2025, 2025
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We developed a novel method to combine ocean data from observations and models, and applied it to produce gridded estimates of nutrients, oxygen, dissolved inorganic carbon and total alkalinity concentrations at latitudes >40° N and years 1980–2020. The new estimates showed improved accuracy and coverage relative to previous estimates, but highlighted remaining uncertainty in some poorly sampled regions. The work was largely motivated by a need for accurate input data for regional ocean models.
Jean Rabault, Trygve Halsne, Ana Carrasco, Anton Korosov, Joey Voermans, Patrik Bohlinger, Jens Boldingh Debernard, Malte Müller, Øyvind Breivik, Takehiko Nose, Gaute Hope, Fabrice Collard, Sylvain Herlédan, Tsubasa Kodaira, Nick Hughes, Qin Zhang, Kai Håkon Christensen, Alexander Babanin, Lars Willas Dreyer, Cyril Palerme, Lotfi Aouf, Konstantinos Christakos, Atle Jensen, Johannes Röhrs, Aleksey Marchenko, Graig Sutherland, Trygve Kvåle Løken, and Takuji Waseda
The Cryosphere, 19, 6229–6260, https://doi.org/10.5194/tc-19-6229-2025, https://doi.org/10.5194/tc-19-6229-2025, 2025
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We observe strongly modulated waves-in-ice significant wave height using buoys deployed East of Svalbard. We show that these observations likely cannot be explained by wave-current interaction or tide-induced modulation alone. We also demonstrate a strong correlation between the waves height modulation, and the rate of sea ice convergence. Therefore, our data suggest that the rate of sea ice convergence and divergence may modulate wave in ice energy dissipation.
Victor Brovkin, Benjamin M. Sanderson, Noel G. Brizuela, Tomohiro Hajima, Tatiana Ilyina, Chris D. Jones, Charles Koven, David Lawrence, Peter Lawrence, Hongmei Li, Spencer Liddcoat, Anastasia Romanou, Roland Séférian, Lori T. Sentman, Abigail L. S. Swann, Jerry Tjiputra, Tilo Ziehn, and Alexander J. Winkler
Earth Syst. Dynam., 16, 2021–2034, https://doi.org/10.5194/esd-16-2021-2025, https://doi.org/10.5194/esd-16-2021-2025, 2025
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Idealized experiments with Earth system models provide a basis for understanding the response of the carbon cycle to emissions. We show that most models exhibit a quasi-linear relationship between cumulative carbon uptake on land and in the ocean and hypothesize that this relationship does not depend on emission pathways. We reduce the coupled system to only one differential equation, which represents a powerful simplification of the Earth system dynamics as a function of fossil fuel emissions.
Ove W. Haugvaldstad, Dirk Olivié, Trude Storelvmo, and Michael Schulz
Atmos. Chem. Phys., 25, 13199–13219, https://doi.org/10.5194/acp-25-13199-2025, https://doi.org/10.5194/acp-25-13199-2025, 2025
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Our study examines what would happen if desert dust in the atmosphere doubled, motivated by dust sedimentation records showing a large increase in dust levels since industrialization began. Using climate model simulations, we assess how more dust affects Earth's energy balance and rainfall. We found that models disagree on whether more dust overall cools or warms the planet. Additionally, more dust tends to reduce rainfall because it absorbs radiation and encourages the formation of ice clouds.
Lise Seland Graff, Jerry Tjiputra, Ada Gjermundsen, Andreas Born, Jens Boldingh Debernard, Heiko Goelzer, Yan-Chun He, Petra Margaretha Langebroek, Aleksi Nummelin, Dirk Olivié, Øyvind Seland, Trude Storelvmo, Mats Bentsen, Chuncheng Guo, Andrea Rosendahl, Dandan Tao, Thomas Toniazzo, Camille Li, Stephen Outten, and Michael Schulz
Earth Syst. Dynam., 16, 1671–1698, https://doi.org/10.5194/esd-16-1671-2025, https://doi.org/10.5194/esd-16-1671-2025, 2025
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The magnitude of future Arctic amplification is highly uncertain. Using the Norwegian Earth System Model, we explore the effect of improving the representation of clouds, ocean eddies, the Greenland ice sheet, sea ice, and ozone on the projected Arctic winter warming in a coordinated experiment set. These improvements all lead to enhanced projected Arctic warming, with the largest changes found in the sea ice retreat regions and the largest uncertainty found on the Atlantic side.
Paul Dees, Friederike Fröb, Beatriz Arellano-Nava, David G. Johns, and Christoph Heinze
Ocean Sci., 21, 2397–2417, https://doi.org/10.5194/os-21-2397-2025, https://doi.org/10.5194/os-21-2397-2025, 2025
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In this paper we describe a novel methodology to automate the estimation of ecological regime shift probability in a single time series. We have applied this new methodology to the continuous plankton recorder dataset in the North Sea and have shown how the model is able to estimate the likelihood of a regime shift using abundance data of multiple phytoplankton and zooplankton species.
Timothée Bourgeois, Giang T. Tran, Aurich Jeltsch-Thömmes, Jörg Schwinger, Friederike Fröb, Thomas L. Frölicher, Thorsten Blenckner, Olivier Torres, Jean Negrel, David P. Keller, Andreas Oschlies, Laurent Bopp, and Fortunat Joos
Biogeosciences, 22, 5435–5462, https://doi.org/10.5194/bg-22-5435-2025, https://doi.org/10.5194/bg-22-5435-2025, 2025
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Anthropogenic greenhouse gas emissions significantly impact ocean ecosystems through climate change and acidification, leading to either progressive or abrupt changes. This study maps the crossing of physical and ecological limits for various ocean impact metrics under three emission scenarios. Using Earth system models, we identify when these limits are exceeded, highlighting the urgent need for ambitious climate action to safeguard the world's oceans and ecosystems.
Mingxuan Wu, Hailong Wang, Zheng Lu, Xiaohong Liu, Huisheng Bian, David D. Cohen, Yan Feng, Mian Chin, Didier A. Hauglustaine, Vlassis A. Karydis, Marianne T. Lund, Gunnar Myhre, Andrea Pozzer, Michael Schulz, Ragnhild B. Skeie, Alexandra P. Tsimpidi, Svetlana G. Tsyro, and Shaocheng Xie
Atmos. Chem. Phys., 25, 10049–10074, https://doi.org/10.5194/acp-25-10049-2025, https://doi.org/10.5194/acp-25-10049-2025, 2025
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A key challenge in simulating the life cycle of nitrate aerosol in global models is accurately representing the mass size distribution of nitrate aerosol, which lacks sufficient observational constraints. We found that most global models underestimate the mass fraction of fine-mode nitrate at the surface in all regions. Our study highlights the importance of gas–aerosol partitioning parameterization and the simulation of dust and sea salt in correctly simulating the mass size distribution of nitrate.
Emmanouil Proestakis, Vassilis Amiridis, Carlos Pérez García-Pando, Svetlana Tsyro, Jan Griesfeller, Antonis Gkikas, Thanasis Georgiou, María Gonçalves Ageitos, Jeronimo Escribano, Stelios Myriokefalitakis, Elisa Bergas Masso, Enza Di Tomaso, Sara Basart, Jan-Berend W. Stuut, and Angela Benedetti
Earth Syst. Sci. Data, 17, 4351–4395, https://doi.org/10.5194/essd-17-4351-2025, https://doi.org/10.5194/essd-17-4351-2025, 2025
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Quantification of dust deposition into the broader Atlantic Ocean is provided, with the estimates established based on Earth observations. The dataset is considered unique with respect to a range of applications, including compensating for spatiotemporal gaps of sediment-trap measurements, assessments of model simulations, shedding light on physical processes related to the dust cycle, and improving the understanding of dust biogeochemical impacts on oceanic ecosystems, weather, and climate.
Benjamin M. Sanderson, Victor Brovkin, Rosie A. Fisher, David Hohn, Tatiana Ilyina, Chris D. Jones, Torben Koenigk, Charles Koven, Hongmei Li, David M. Lawrence, Peter Lawrence, Spencer Liddicoat, Andrew H. MacDougall, Nadine Mengis, Zebedee Nicholls, Eleanor O'Rourke, Anastasia Romanou, Marit Sandstad, Jörg Schwinger, Roland Séférian, Lori T. Sentman, Isla R. Simpson, Chris Smith, Norman J. Steinert, Abigail L. S. Swann, Jerry Tjiputra, and Tilo Ziehn
Geosci. Model Dev., 18, 5699–5724, https://doi.org/10.5194/gmd-18-5699-2025, https://doi.org/10.5194/gmd-18-5699-2025, 2025
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This study investigates how climate models warm in response to simplified carbon emissions trajectories, refining the understanding of climate reversibility and commitment. Metrics are defined for warming response to cumulative emissions and for the cessation of emissions or ramp-down to net-zero and net-negative levels. Results indicate that previous concentration-driven experiments may have overstated the Zero Emissions Commitment due to emissions rates exceeding historical levels.
Ling Zhang, Lu Li, Zhongshi Zhang, Joël Arnault, Stefan Sobolowski, Xiaoling Chen, Jianzhong Lu, Anthony Musili Mwanthi, Pratik Kad, Mohammed Abdullahi Hassan, Tanja Portele, Harald Kunstmann, and Zhengkang Zuo
Hydrol. Earth Syst. Sci., 29, 4109–4132, https://doi.org/10.5194/hess-29-4109-2025, https://doi.org/10.5194/hess-29-4109-2025, 2025
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To address challenges related to unreliable hydrological simulations, we present an enhanced hydrological simulation with a refined climate model and a more comprehensive hydrological model. The model with the two parts outperforms that without, especially in migrating bias in peak flow and dry-season flow. Our findings highlight the enhanced hydrological simulation capability, with the refined climate and lake module contributing 24 % and 76 % improvement, respectively.
William E. Chapman, Francine Schevenhoven, Judith Berner, Noel Keenlyside, Ingo Bethke, Ping-Gin Chiu, Alok Gupta, and Jesse Nusbaumer
Geosci. Model Dev., 18, 5451–5465, https://doi.org/10.5194/gmd-18-5451-2025, https://doi.org/10.5194/gmd-18-5451-2025, 2025
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We introduce the first state-of-the-art atmosphere-connected supermodel, where two advanced atmospheric models share information in real time to form a new dynamical system. By synchronizing the models, particularly in storm track regions, we achieve better predictions without losing variability. This approach maintains key climate patterns and reduces bias in some variables compared to traditional models, demonstrating a useful technique for improving atmospheric simulations.
William J. Collins, Fiona M. O'Connor, Rachael E. Byrom, Øivind Hodnebrog, Patrick Jöckel, Mariano Mertens, Gunnar Myhre, Matthias Nützel, Dirk Olivié, Ragnhild Bieltvedt Skeie, Laura Stecher, Larry W. Horowitz, Vaishali Naik, Gregory Faluvegi, Ulas Im, Lee T. Murray, Drew Shindell, Kostas Tsigaridis, Nathan Luke Abraham, and James Keeble
Atmos. Chem. Phys., 25, 9031–9060, https://doi.org/10.5194/acp-25-9031-2025, https://doi.org/10.5194/acp-25-9031-2025, 2025
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We used 7 climate models that include atmospheric chemistry and find that in a scenario with weak controls on air quality, the warming effects (over 2015 to 2050) of decreases in ozone-depleting substances and increases in air quality pollutants are approximately equal and would make ozone the second highest contributor to warming over this period. We find that for stratospheric ozone recovery, the standard measure of climate effects underestimates a more comprehensive measure.
Brendan R. Carter, Jörg Schwinger, Rolf Sonnerup, Andrea J. Fassbender, Jonathan D. Sharp, Larissa M. Dias, and Daniel E. Sandborn
Earth Syst. Sci. Data, 17, 3073–3088, https://doi.org/10.5194/essd-17-3073-2025, https://doi.org/10.5194/essd-17-3073-2025, 2025
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We infer ocean gas exchange and circulation from ocean tracer measurements and use this to create code to estimate the amount of carbon dioxide dissolved in the ocean that is there due to human emissions of CO2 into the atmosphere. The code works across the ocean depths for the past, present, or future from information about the location, temperature, and salinity of the seawater. We produce a data product with estimates throughout the ocean throughout the last ~300 and the next ~500 years.
Haichao Guo, Wolfgang Koeve, Andreas Oschlies, Yan-Chun He, Tronje Peer Kemena, Lennart Gerke, and Iris Kriest
Ocean Sci., 21, 1167–1182, https://doi.org/10.5194/os-21-1167-2025, https://doi.org/10.5194/os-21-1167-2025, 2025
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We evaluated the effectiveness of the inverse Gaussian transit time distribution (IG-TTD) with respect to estimating the mean state and temporal changes of seawater age, defined as the duration since water last had contact with the atmosphere, within the tropical thermocline. Results suggest that the IG-TTD underestimates seawater age. Moreover, the IG-TTD constrained by a single tracer gives spurious trends in water age. Incorporating an additional tracer improves IG-TTD's accuracy for estimating temporal change of seawater age.
Rachael E. Byrom, Gunnar Myhre, Øivind Hodnebrog, Dirk Olivié, and Michael Schulz
Atmos. Chem. Phys., 25, 5683–5693, https://doi.org/10.5194/acp-25-5683-2025, https://doi.org/10.5194/acp-25-5683-2025, 2025
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Addressing the cause of model spread in CO2 effective radiative forcing (ERF) is important for reducing uncertainty in climate change. We investigate stratospheric O3 as a driver of this spread by altering its concentration by 50 % and analysing the impact on CO2 forcing. Our experiments show a significant effect on stratospheric temperature that impacts instantaneous radiative forcing, primarily due to the influence on longwave emission. However, the impact on ERF is minimal.
Clemens Spensberger, Kjersti Konstali, and Thomas Spengler
Weather Clim. Dynam., 6, 431–446, https://doi.org/10.5194/wcd-6-431-2025, https://doi.org/10.5194/wcd-6-431-2025, 2025
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The transport of moisture from warmer and moister to colder and drier regions mainly occurs in brief and narrow bursts. In the mid-latitudes, such bursts are generally referred to as atmospheric rivers; in the Arctic they are often referred to as warm moist intrusions. We introduce a new definition to identify such bursts which is based primarily on their elongated structure. With this more general definition, we show that bursts in moisture transport occur frequently across all climate zones.
Ngoc Thi Nhu Do, Kengo Sudo, Akihiko Ito, Louisa K. Emmons, Vaishali Naik, Kostas Tsigaridis, Øyvind Seland, Gerd A. Folberth, and Douglas I. Kelley
Geosci. Model Dev., 18, 2079–2109, https://doi.org/10.5194/gmd-18-2079-2025, https://doi.org/10.5194/gmd-18-2079-2025, 2025
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Understanding historical isoprene emission changes is important for predicting future climate, but trends and their controlling factors remain uncertain. This study shows that long-term isoprene trends vary among Earth system models mainly due to partially incorporating CO2 effects and land cover changes rather than to climate. Future models that refine these factors’ effects on isoprene emissions, along with long-term observations, are essential for better understanding plant–climate interactions.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Judith Hauck, Peter Landschützer, Corinne Le Quéré, Hongmei Li, Ingrid T. Luijkx, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Almut Arneth, Vivek Arora, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Carla F. Berghoff, Henry C. Bittig, Laurent Bopp, Patricia Cadule, Katie Campbell, Matthew A. Chamberlain, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Thomas Colligan, Jeanne Decayeux, Laique M. Djeutchouang, Xinyu Dou, Carolina Duran Rojas, Kazutaka Enyo, Wiley Evans, Amanda R. Fay, Richard A. Feely, Daniel J. Ford, Adrianna Foster, Thomas Gasser, Marion Gehlen, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Jens Heinke, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Andrew R. Jacobson, Atul K. Jain, Tereza Jarníková, Annika Jersild, Fei Jiang, Zhe Jin, Etsushi Kato, Ralph F. Keeling, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Xin Lan, Siv K. Lauvset, Nathalie Lefèvre, Zhu Liu, Junjie Liu, Lei Ma, Shamil Maksyutov, Gregg Marland, Nicolas Mayot, Patrick C. McGuire, Nicolas Metzl, Natalie M. Monacci, Eric J. Morgan, Shin-Ichiro Nakaoka, Craig Neill, Yosuke Niwa, Tobias Nützel, Lea Olivier, Tsuneo Ono, Paul I. Palmer, Denis Pierrot, Zhangcai Qin, Laure Resplandy, Alizée Roobaert, Thais M. Rosan, Christian Rödenbeck, Jörg Schwinger, T. Luke Smallman, Stephen M. Smith, Reinel Sospedra-Alfonso, Tobias Steinhoff, Qing Sun, Adrienne J. Sutton, Roland Séférian, Shintaro Takao, Hiroaki Tatebe, Hanqin Tian, Bronte Tilbrook, Olivier Torres, Etienne Tourigny, Hiroyuki Tsujino, Francesco Tubiello, Guido van der Werf, Rik Wanninkhof, Xuhui Wang, Dongxu Yang, Xiaojuan Yang, Zhen Yu, Wenping Yuan, Xu Yue, Sönke Zaehle, Ning Zeng, and Jiye Zeng
Earth Syst. Sci. Data, 17, 965–1039, https://doi.org/10.5194/essd-17-965-2025, https://doi.org/10.5194/essd-17-965-2025, 2025
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The Global Carbon Budget 2024 describes the methodology, main results, and datasets used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land ecosystems, and the ocean over the historical period (1750–2024). These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Yona Silvy, Thomas L. Frölicher, Jens Terhaar, Fortunat Joos, Friedrich A. Burger, Fabrice Lacroix, Myles Allen, Raffaele Bernardello, Laurent Bopp, Victor Brovkin, Jonathan R. Buzan, Patricia Cadule, Martin Dix, John Dunne, Pierre Friedlingstein, Goran Georgievski, Tomohiro Hajima, Stuart Jenkins, Michio Kawamiya, Nancy Y. Kiang, Vladimir Lapin, Donghyun Lee, Paul Lerner, Nadine Mengis, Estela A. Monteiro, David Paynter, Glen P. Peters, Anastasia Romanou, Jörg Schwinger, Sarah Sparrow, Eric Stofferahn, Jerry Tjiputra, Etienne Tourigny, and Tilo Ziehn
Earth Syst. Dynam., 15, 1591–1628, https://doi.org/10.5194/esd-15-1591-2024, https://doi.org/10.5194/esd-15-1591-2024, 2024
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The adaptive emission reduction approach is applied with Earth system models to generate temperature stabilization simulations. These simulations provide compatible emission pathways and budgets for a given warming level, uncovering uncertainty ranges previously missing in the Coupled Model Intercomparison Project scenarios. These target-based emission-driven simulations offer a more coherent assessment across models for studying both the carbon cycle and its impacts under climate stabilization.
Fang Li, Xiang Song, Sandy P. Harrison, Jennifer R. Marlon, Zhongda Lin, L. Ruby Leung, Jörg Schwinger, Virginie Marécal, Shiyu Wang, Daniel S. Ward, Xiao Dong, Hanna Lee, Lars Nieradzik, Sam S. Rabin, and Roland Séférian
Geosci. Model Dev., 17, 8751–8771, https://doi.org/10.5194/gmd-17-8751-2024, https://doi.org/10.5194/gmd-17-8751-2024, 2024
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This study provides the first comprehensive assessment of historical fire simulations from 19 Earth system models in phase 6 of the Coupled Model Intercomparison Project (CMIP6). Most models reproduce global totals, spatial patterns, seasonality, and regional historical changes well but fail to simulate the recent decline in global burned area and underestimate the fire response to climate variability. CMIP6 simulations address three critical issues of phase-5 models.
Colin G. Jones, Fanny Adloff, Ben B. B. Booth, Peter M. Cox, Veronika Eyring, Pierre Friedlingstein, Katja Frieler, Helene T. Hewitt, Hazel A. Jeffery, Sylvie Joussaume, Torben Koenigk, Bryan N. Lawrence, Eleanor O'Rourke, Malcolm J. Roberts, Benjamin M. Sanderson, Roland Séférian, Samuel Somot, Pier Luigi Vidale, Detlef van Vuuren, Mario Acosta, Mats Bentsen, Raffaele Bernardello, Richard Betts, Ed Blockley, Julien Boé, Tom Bracegirdle, Pascale Braconnot, Victor Brovkin, Carlo Buontempo, Francisco Doblas-Reyes, Markus Donat, Italo Epicoco, Pete Falloon, Sandro Fiore, Thomas Frölicher, Neven S. Fučkar, Matthew J. Gidden, Helge F. Goessling, Rune Grand Graversen, Silvio Gualdi, José M. Gutiérrez, Tatiana Ilyina, Daniela Jacob, Chris D. Jones, Martin Juckes, Elizabeth Kendon, Erik Kjellström, Reto Knutti, Jason Lowe, Matthew Mizielinski, Paola Nassisi, Michael Obersteiner, Pierre Regnier, Romain Roehrig, David Salas y Mélia, Carl-Friedrich Schleussner, Michael Schulz, Enrico Scoccimarro, Laurent Terray, Hannes Thiemann, Richard A. Wood, Shuting Yang, and Sönke Zaehle
Earth Syst. Dynam., 15, 1319–1351, https://doi.org/10.5194/esd-15-1319-2024, https://doi.org/10.5194/esd-15-1319-2024, 2024
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We propose a number of priority areas for the international climate research community to address over the coming decade. Advances in these areas will both increase our understanding of past and future Earth system change, including the societal and environmental impacts of this change, and deliver significantly improved scientific support to international climate policy, such as future IPCC assessments and the UNFCCC Global Stocktake.
Henrik Auestad, Clemens Spensberger, Andrea Marcheggiani, Paulo Ceppi, Thomas Spengler, and Tim Woollings
Weather Clim. Dynam., 5, 1269–1286, https://doi.org/10.5194/wcd-5-1269-2024, https://doi.org/10.5194/wcd-5-1269-2024, 2024
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Latent heating due to condensation can influence atmospheric circulation by strengthening or weakening horizontal temperature contrasts. Strong temperature contrasts intensify storms and imply the existence of strong upper tropospheric winds called jets. It remains unclear whether latent heating preferentially reinforces or abates the existing jet. We show that this disagreement is attributable to how the jet is defined, confirming that latent heating reinforces the jet.
Shunya Koseki, Lander R. Crespo, Jerry Tjiputra, Filippa Fransner, Noel S. Keenlyside, and David Rivas
Biogeosciences, 21, 4149–4168, https://doi.org/10.5194/bg-21-4149-2024, https://doi.org/10.5194/bg-21-4149-2024, 2024
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We investigated how the physical biases of an Earth system model influence the marine biogeochemical processes in the tropical Atlantic. With four different configurations of the model, we have shown that the versions with better SST reproduction tend to better represent the primary production and air–sea CO2 flux in terms of climatology, seasonal cycle, and response to climate variability.
Jean-François Lemieux, William H. Lipscomb, Anthony Craig, David A. Bailey, Elizabeth C. Hunke, Philippe Blain, Till A. S. Rasmussen, Mats Bentsen, Frédéric Dupont, David Hebert, and Richard Allard
Geosci. Model Dev., 17, 6703–6724, https://doi.org/10.5194/gmd-17-6703-2024, https://doi.org/10.5194/gmd-17-6703-2024, 2024
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We present the latest version of the CICE model. It solves equations that describe the dynamics and the growth and melt of sea ice. To do so, the domain is divided into grid cells and variables are positioned at specific locations in the cells. A new implementation (C-grid) is presented, with the velocity located on cell edges. Compared to the previous B-grid, the C-grid allows for a natural coupling with some oceanic and atmospheric models. It also allows for ice transport in narrow channels.
Henk Eskes, Athanasios Tsikerdekis, Melanie Ades, Mihai Alexe, Anna Carlin Benedictow, Yasmine Bennouna, Lewis Blake, Idir Bouarar, Simon Chabrillat, Richard Engelen, Quentin Errera, Johannes Flemming, Sebastien Garrigues, Jan Griesfeller, Vincent Huijnen, Luka Ilić, Antje Inness, John Kapsomenakis, Zak Kipling, Bavo Langerock, Augustin Mortier, Mark Parrington, Isabelle Pison, Mikko Pitkänen, Samuel Remy, Andreas Richter, Anja Schoenhardt, Michael Schulz, Valerie Thouret, Thorsten Warneke, Christos Zerefos, and Vincent-Henri Peuch
Atmos. Chem. Phys., 24, 9475–9514, https://doi.org/10.5194/acp-24-9475-2024, https://doi.org/10.5194/acp-24-9475-2024, 2024
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The Copernicus Atmosphere Monitoring Service (CAMS) provides global analyses and forecasts of aerosols and trace gases in the atmosphere. On 27 June 2023 a major upgrade, Cy48R1, became operational. Comparisons with in situ, surface remote sensing, aircraft, and balloon and satellite observations show that the new CAMS system is a significant improvement. The results quantify the skill of CAMS to forecast impactful events, such as wildfires, dust storms and air pollution peaks.
Xavier J. Levine, Ryan S. Williams, Gareth Marshall, Andrew Orr, Lise Seland Graff, Dörthe Handorf, Alexey Karpechko, Raphael Köhler, René R. Wijngaard, Nadine Johnston, Hanna Lee, Lars Nieradzik, and Priscilla A. Mooney
Earth Syst. Dynam., 15, 1161–1177, https://doi.org/10.5194/esd-15-1161-2024, https://doi.org/10.5194/esd-15-1161-2024, 2024
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While the most recent climate projections agree that the Arctic is warming, differences remain in how much and in other climate variables such as precipitation. This presents a challenge for stakeholders who need to develop mitigation and adaptation strategies. We tackle this problem by using the storyline approach to generate four plausible and actionable realisations of end-of-century climate change for the Arctic, spanning its most likely range of variability.
Alkiviadis Kalisoras, Aristeidis K. Georgoulias, Dimitris Akritidis, Robert J. Allen, Vaishali Naik, Chaincy Kuo, Sophie Szopa, Pierre Nabat, Dirk Olivié, Twan van Noije, Philippe Le Sager, David Neubauer, Naga Oshima, Jane Mulcahy, Larry W. Horowitz, and Prodromos Zanis
Atmos. Chem. Phys., 24, 7837–7872, https://doi.org/10.5194/acp-24-7837-2024, https://doi.org/10.5194/acp-24-7837-2024, 2024
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Effective radiative forcing (ERF) is a metric for estimating how human activities and natural agents change the energy flow into and out of the Earth’s climate system. We investigate the anthropogenic aerosol ERF, and we estimate the contribution of individual processes to the total ERF using simulations from Earth system models within the Coupled Model Intercomparison Project Phase 6 (CMIP6). Our findings highlight that aerosol–cloud interactions drive ERF variability during the last 150 years.
Dennis Booge, Jerry F. Tjiputra, Dirk J. L. Olivié, Birgit Quack, and Kirstin Krüger
Earth Syst. Dynam., 15, 801–816, https://doi.org/10.5194/esd-15-801-2024, https://doi.org/10.5194/esd-15-801-2024, 2024
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Oceanic bromoform, produced by algae, is an important precursor of atmospheric bromine, highlighting the importance of implementing these emissions in climate models. The simulated mean oceanic concentrations align well with observations, while the mean atmospheric values are lower than the observed ones. Modelled annual mean emissions mostly occur from the sea to the air and are driven by oceanic concentrations, sea surface temperature, and wind speed, which depend on season and location.
Fangxuan Ren, Jintai Lin, Chenghao Xu, Jamiu A. Adeniran, Jingxu Wang, Randall V. Martin, Aaron van Donkelaar, Melanie S. Hammer, Larry W. Horowitz, Steven T. Turnock, Naga Oshima, Jie Zhang, Susanne Bauer, Kostas Tsigaridis, Øyvind Seland, Pierre Nabat, David Neubauer, Gary Strand, Twan van Noije, Philippe Le Sager, and Toshihiko Takemura
Geosci. Model Dev., 17, 4821–4836, https://doi.org/10.5194/gmd-17-4821-2024, https://doi.org/10.5194/gmd-17-4821-2024, 2024
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We evaluate the performance of 14 CMIP6 ESMs in simulating total PM2.5 and its 5 components over China during 2000–2014. PM2.5 and its components are underestimated in almost all models, except that black carbon (BC) and sulfate are overestimated in two models, respectively. The underestimation is the largest for organic carbon (OC) and the smallest for BC. Models reproduce the observed spatial pattern for OC, sulfate, nitrate and ammonium well, yet the agreement is poorer for BC.
Jenny Hieronymus, Magnus Hieronymus, Matthias Gröger, Jörg Schwinger, Raffaele Bernadello, Etienne Tourigny, Valentina Sicardi, Itzel Ruvalcaba Baroni, and Klaus Wyser
Biogeosciences, 21, 2189–2206, https://doi.org/10.5194/bg-21-2189-2024, https://doi.org/10.5194/bg-21-2189-2024, 2024
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The timing of the net primary production annual maxima in the North Atlantic in the period 1750–2100 is investigated using two Earth system models and the high-emissions scenario SSP5-8.5. It is found that, for most of the region, the annual maxima occur progressively earlier, with the most change occurring after the year 2000. Shifts in the seasonality of the primary production may impact the entire ecosystem, which highlights the need for long-term monitoring campaigns in this area.
Julia E. Weiffenbach, Henk A. Dijkstra, Anna S. von der Heydt, Ayako Abe-Ouchi, Wing-Le Chan, Deepak Chandan, Ran Feng, Alan M. Haywood, Stephen J. Hunter, Xiangyu Li, Bette L. Otto-Bliesner, W. Richard Peltier, Christian Stepanek, Ning Tan, Julia C. Tindall, and Zhongshi Zhang
Clim. Past, 20, 1067–1086, https://doi.org/10.5194/cp-20-1067-2024, https://doi.org/10.5194/cp-20-1067-2024, 2024
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Elevated atmospheric CO2 concentrations and a smaller Antarctic Ice Sheet during the mid-Pliocene (~ 3 million years ago) cause the Southern Ocean surface to become fresher and warmer, which affects the global ocean circulation. The CO2 concentration and the smaller Antarctic Ice Sheet both have a similar and approximately equal impact on the Southern Ocean. The conditions of the Southern Ocean in the mid-Pliocene could therefore be analogous to those in a future climate with smaller ice sheets.
Clemens Spensberger
Weather Clim. Dynam., 5, 659–669, https://doi.org/10.5194/wcd-5-659-2024, https://doi.org/10.5194/wcd-5-659-2024, 2024
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It is well-established that variations in convection in the tropical Indo-Pacific can influence weather in far-away regions. In this idea, I argue that the main theory used to explain this influence over large distances is incomplete. I propose hypotheses that could lead the way towards a more fundamental explanation and outline a novel approach that could be used to test the hypotheses I raise. The suggested approach might be useful to address also other long-standing questions.
Stephanie Fiedler, Vaishali Naik, Fiona M. O'Connor, Christopher J. Smith, Paul Griffiths, Ryan J. Kramer, Toshihiko Takemura, Robert J. Allen, Ulas Im, Matthew Kasoar, Angshuman Modak, Steven Turnock, Apostolos Voulgarakis, Duncan Watson-Parris, Daniel M. Westervelt, Laura J. Wilcox, Alcide Zhao, William J. Collins, Michael Schulz, Gunnar Myhre, and Piers M. Forster
Geosci. Model Dev., 17, 2387–2417, https://doi.org/10.5194/gmd-17-2387-2024, https://doi.org/10.5194/gmd-17-2387-2024, 2024
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Climate scientists want to better understand modern climate change. Thus, climate model experiments are performed and compared. The results of climate model experiments differ, as assessed in the latest Intergovernmental Panel on Climate Change (IPCC) assessment report. This article gives insights into the challenges and outlines opportunities for further improving the understanding of climate change. It is based on views of a group of experts in atmospheric composition–climate interactions.
Ali Asaadi, Jörg Schwinger, Hanna Lee, Jerry Tjiputra, Vivek Arora, Roland Séférian, Spencer Liddicoat, Tomohiro Hajima, Yeray Santana-Falcón, and Chris D. Jones
Biogeosciences, 21, 411–435, https://doi.org/10.5194/bg-21-411-2024, https://doi.org/10.5194/bg-21-411-2024, 2024
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Carbon cycle feedback metrics are employed to assess phases of positive and negative CO2 emissions. When emissions become negative, we find that the model disagreement in feedback metrics increases more strongly than expected from the assumption that the uncertainties accumulate linearly with time. The geographical patterns of such metrics over land highlight that differences in response between tropical/subtropical and temperate/boreal ecosystems are a major source of model disagreement.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Peter Landschützer, Corinne Le Quéré, Ingrid T. Luijkx, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Peter Anthoni, Leticia Barbero, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Bertrand Decharme, Laurent Bopp, Ida Bagus Mandhara Brasika, Patricia Cadule, Matthew A. Chamberlain, Naveen Chandra, Thi-Tuyet-Trang Chau, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Xinyu Dou, Kazutaka Enyo, Wiley Evans, Stefanie Falk, Richard A. Feely, Liang Feng, Daniel J. Ford, Thomas Gasser, Josefine Ghattas, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Jens Heinke, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Andrew R. Jacobson, Atul Jain, Tereza Jarníková, Annika Jersild, Fei Jiang, Zhe Jin, Fortunat Joos, Etsushi Kato, Ralph F. Keeling, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Arne Körtzinger, Xin Lan, Nathalie Lefèvre, Hongmei Li, Junjie Liu, Zhiqiang Liu, Lei Ma, Greg Marland, Nicolas Mayot, Patrick C. McGuire, Galen A. McKinley, Gesa Meyer, Eric J. Morgan, David R. Munro, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin M. O'Brien, Are Olsen, Abdirahman M. Omar, Tsuneo Ono, Melf Paulsen, Denis Pierrot, Katie Pocock, Benjamin Poulter, Carter M. Powis, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Thais M. Rosan, Jörg Schwinger, Roland Séférian, T. Luke Smallman, Stephen M. Smith, Reinel Sospedra-Alfonso, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Shintaro Takao, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Hiroyuki Tsujino, Francesco Tubiello, Guido R. van der Werf, Erik van Ooijen, Rik Wanninkhof, Michio Watanabe, Cathy Wimart-Rousseau, Dongxu Yang, Xiaojuan Yang, Wenping Yuan, Xu Yue, Sönke Zaehle, Jiye Zeng, and Bo Zheng
Earth Syst. Sci. Data, 15, 5301–5369, https://doi.org/10.5194/essd-15-5301-2023, https://doi.org/10.5194/essd-15-5301-2023, 2023
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The Global Carbon Budget 2023 describes the methodology, main results, and data sets used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land ecosystems, and the ocean over the historical period (1750–2023). These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Hamza Ahsan, Hailong Wang, Jingbo Wu, Mingxuan Wu, Steven J. Smith, Susanne Bauer, Harrison Suchyta, Dirk Olivié, Gunnar Myhre, Hitoshi Matsui, Huisheng Bian, Jean-François Lamarque, Ken Carslaw, Larry Horowitz, Leighton Regayre, Mian Chin, Michael Schulz, Ragnhild Bieltvedt Skeie, Toshihiko Takemura, and Vaishali Naik
Atmos. Chem. Phys., 23, 14779–14799, https://doi.org/10.5194/acp-23-14779-2023, https://doi.org/10.5194/acp-23-14779-2023, 2023
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We examine the impact of the assumed effective height of SO2 injection, SO2 and BC emission seasonality, and the assumed fraction of SO2 emissions injected as SO4 on climate and chemistry model results. We find that the SO2 injection height has a large impact on surface SO2 concentrations and, in some models, radiative flux. These assumptions are a
hiddensource of inter-model variability and may be leading to bias in some climate model results.
Veli Çağlar Yumruktepe, Erik Askov Mousing, Jerry Tjiputra, and Annette Samuelsen
Geosci. Model Dev., 16, 6875–6897, https://doi.org/10.5194/gmd-16-6875-2023, https://doi.org/10.5194/gmd-16-6875-2023, 2023
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We present an along BGC-Argo track 1D modelling framework. The model physics is constrained by the BGC-Argo temperature and salinity profiles to reduce the uncertainties related to mixed layer dynamics, allowing the evaluation of the biogeochemical formulation and parameterization. We objectively analyse the model with BGC-Argo and satellite data and improve the model biogeochemical dynamics. We present the framework, example cases and routines for model improvement and implementations.
Xin Ren, Daniel J. Lunt, Erica Hendy, Anna von der Heydt, Ayako Abe-Ouchi, Bette Otto-Bliesner, Charles J. R. Williams, Christian Stepanek, Chuncheng Guo, Deepak Chandan, Gerrit Lohmann, Julia C. Tindall, Linda E. Sohl, Mark A. Chandler, Masa Kageyama, Michiel L. J. Baatsen, Ning Tan, Qiong Zhang, Ran Feng, Stephen Hunter, Wing-Le Chan, W. Richard Peltier, Xiangyu Li, Youichi Kamae, Zhongshi Zhang, and Alan M. Haywood
Clim. Past, 19, 2053–2077, https://doi.org/10.5194/cp-19-2053-2023, https://doi.org/10.5194/cp-19-2053-2023, 2023
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We investigate the Maritime Continent climate in the mid-Piacenzian warm period and find it is warmer and wetter and the sea surface salinity is lower compared with preindustrial period. Besides, the fresh and warm water transfer through the Maritime Continent was stronger. In order to avoid undue influence from closely related models in the multimodel results, we introduce a new metric, the multi-cluster mean, which could reveal spatial signals that are not captured by the multimodel mean.
Christoph Heinze, Thorsten Blenckner, Peter Brown, Friederike Fröb, Anne Morée, Adrian L. New, Cara Nissen, Stefanie Rynders, Isabel Seguro, Yevgeny Aksenov, Yuri Artioli, Timothée Bourgeois, Friedrich Burger, Jonathan Buzan, B. B. Cael, Veli Çağlar Yumruktepe, Melissa Chierici, Christopher Danek, Ulf Dieckmann, Agneta Fransson, Thomas Frölicher, Giovanni Galli, Marion Gehlen, Aridane G. González, Melchor Gonzalez-Davila, Nicolas Gruber, Örjan Gustafsson, Judith Hauck, Mikko Heino, Stephanie Henson, Jenny Hieronymus, I. Emma Huertas, Fatma Jebri, Aurich Jeltsch-Thömmes, Fortunat Joos, Jaideep Joshi, Stephen Kelly, Nandini Menon, Precious Mongwe, Laurent Oziel, Sólveig Ólafsdottir, Julien Palmieri, Fiz F. Pérez, Rajamohanan Pillai Ranith, Juliano Ramanantsoa, Tilla Roy, Dagmara Rusiecka, J. Magdalena Santana Casiano, Yeray Santana-Falcón, Jörg Schwinger, Roland Séférian, Miriam Seifert, Anna Shchiptsova, Bablu Sinha, Christopher Somes, Reiner Steinfeldt, Dandan Tao, Jerry Tjiputra, Adam Ulfsbo, Christoph Völker, Tsuyoshi Wakamatsu, and Ying Ye
Biogeosciences Discuss., https://doi.org/10.5194/bg-2023-182, https://doi.org/10.5194/bg-2023-182, 2023
Revised manuscript not accepted
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For assessing the consequences of human-induced climate change for the marine realm, it is necessary to not only look at gradual changes but also at abrupt changes of environmental conditions. We summarise abrupt changes in ocean warming, acidification, and oxygen concentration as the key environmental factors for ecosystems. Taking these abrupt changes into account requires greenhouse gas emissions to be reduced to a larger extent than previously thought to limit respective damage.
Johannes Röhrs, Yvonne Gusdal, Edel S. U. Rikardsen, Marina Durán Moro, Jostein Brændshøi, Nils Melsom Kristensen, Sindre Fritzner, Keguang Wang, Ann Kristin Sperrevik, Martina Idžanović, Thomas Lavergne, Jens Boldingh Debernard, and Kai H. Christensen
Geosci. Model Dev., 16, 5401–5426, https://doi.org/10.5194/gmd-16-5401-2023, https://doi.org/10.5194/gmd-16-5401-2023, 2023
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A model to predict ocean currents, temperature, and sea ice is presented, covering the Barents Sea and northern Norway. To quantify forecast uncertainties, the model calculates ensemble forecasts with 24 realizations of ocean and ice conditions. Observations from satellites, buoys, and ships are ingested by the model. The model forecasts are compared with observations, and we show that the ocean model has skill in predicting sea surface temperatures.
Matteo Willeit, Tatiana Ilyina, Bo Liu, Christoph Heinze, Mahé Perrette, Malte Heinemann, Daniela Dalmonech, Victor Brovkin, Guy Munhoven, Janine Börker, Jens Hartmann, Gibran Romero-Mujalli, and Andrey Ganopolski
Geosci. Model Dev., 16, 3501–3534, https://doi.org/10.5194/gmd-16-3501-2023, https://doi.org/10.5194/gmd-16-3501-2023, 2023
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In this paper we present the carbon cycle component of the newly developed fast Earth system model CLIMBER-X. The model can be run with interactive atmospheric CO2 to investigate the feedbacks between climate and the carbon cycle on temporal scales ranging from decades to > 100 000 years. CLIMBER-X is expected to be a useful tool for studying past climate–carbon cycle changes and for the investigation of the long-term future evolution of the Earth system.
Rasmus E. Benestad, Abdelkader Mezghani, Julia Lutz, Andreas Dobler, Kajsa M. Parding, and Oskar A. Landgren
Geosci. Model Dev., 16, 2899–2913, https://doi.org/10.5194/gmd-16-2899-2023, https://doi.org/10.5194/gmd-16-2899-2023, 2023
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A mathematical method known as common EOFs is not widely used within the climate research community, but it offers innovative ways of evaluating climate models. We show how common EOFs can be used to evaluate large ensembles of global climate model simulations and distill information about their ability to reproduce salient features of the regional climate. We can say that they represent a kind of machine learning (ML) for dealing with big data.
Astrid Fremme, Paul J. Hezel, Øyvind Seland, and Harald Sodemann
Weather Clim. Dynam., 4, 449–470, https://doi.org/10.5194/wcd-4-449-2023, https://doi.org/10.5194/wcd-4-449-2023, 2023
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We study the atmospheric moisture transport into eastern China for past, present, and future climate. Hence, we use different climate and weather prediction model data with a moisture source identification method. We find that while the moisture to first order originates mostly from similar regions, smaller changes consistently point to differences in the recycling of precipitation over land between different climates. Some differences are larger between models than between different climates.
Qi Shu, Qiang Wang, Chuncheng Guo, Zhenya Song, Shizhu Wang, Yan He, and Fangli Qiao
Geosci. Model Dev., 16, 2539–2563, https://doi.org/10.5194/gmd-16-2539-2023, https://doi.org/10.5194/gmd-16-2539-2023, 2023
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Ocean models are often used for scientific studies on the Arctic Ocean. Here the Arctic Ocean simulations by state-of-the-art global ocean–sea-ice models participating in the Ocean Model Intercomparison Project (OMIP) were evaluated. The simulations on Arctic Ocean hydrography, freshwater content, stratification, sea surface height, and gateway transports were assessed and the common biases were detected. The simulations forced by different atmospheric forcing were also evaluated.
Claire Waelbroeck, Jerry Tjiputra, Chuncheng Guo, Kerim H. Nisancioglu, Eystein Jansen, Natalia Vázquez Riveiros, Samuel Toucanne, Frédérique Eynaud, Linda Rossignol, Fabien Dewilde, Elodie Marchès, Susana Lebreiro, and Silvia Nave
Clim. Past, 19, 901–913, https://doi.org/10.5194/cp-19-901-2023, https://doi.org/10.5194/cp-19-901-2023, 2023
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The precise geometry and extent of Atlantic circulation changes that accompanied rapid climate changes of the last glacial period are still unknown. Here, we combine carbon isotopic records from 18 Atlantic sediment cores with numerical simulations and decompose the carbon isotopic change across a cold-to-warm transition into remineralization and circulation components. Our results show that the replacement of southern-sourced by northern-sourced water plays a dominant role below ~ 3000 m depth.
Nadine Goris, Klaus Johannsen, and Jerry Tjiputra
Geosci. Model Dev., 16, 2095–2117, https://doi.org/10.5194/gmd-16-2095-2023, https://doi.org/10.5194/gmd-16-2095-2023, 2023
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Climate projections of a high-CO2 future are highly uncertain. A new study provides a novel approach to identifying key regions that dynamically explain the model uncertainty. To yield an accurate estimate of the future North Atlantic carbon uptake, we find that a correct simulation of the upper- and interior-ocean volume transport at 25–30° N is key. However, results indicate that models rarely perform well for both indicators and point towards inconsistencies within the model ensemble.
Alban Planchat, Lester Kwiatkowski, Laurent Bopp, Olivier Torres, James R. Christian, Momme Butenschön, Tomas Lovato, Roland Séférian, Matthew A. Chamberlain, Olivier Aumont, Michio Watanabe, Akitomo Yamamoto, Andrew Yool, Tatiana Ilyina, Hiroyuki Tsujino, Kristen M. Krumhardt, Jörg Schwinger, Jerry Tjiputra, John P. Dunne, and Charles Stock
Biogeosciences, 20, 1195–1257, https://doi.org/10.5194/bg-20-1195-2023, https://doi.org/10.5194/bg-20-1195-2023, 2023
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Ocean alkalinity is critical to the uptake of atmospheric carbon and acidification in surface waters. We review the representation of alkalinity and the associated calcium carbonate cycle in Earth system models. While many parameterizations remain present in the latest generation of models, there is a general improvement in the simulated alkalinity distribution. This improvement is related to an increase in the export of biotic calcium carbonate, which closer resembles observations.
Lauren E. Burton, Alan M. Haywood, Julia C. Tindall, Aisling M. Dolan, Daniel J. Hill, Ayako Abe-Ouchi, Wing-Le Chan, Deepak Chandan, Ran Feng, Stephen J. Hunter, Xiangyu Li, W. Richard Peltier, Ning Tan, Christian Stepanek, and Zhongshi Zhang
Clim. Past, 19, 747–764, https://doi.org/10.5194/cp-19-747-2023, https://doi.org/10.5194/cp-19-747-2023, 2023
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Warm climates of the Pliocene (~ 3 million years ago) are similar to projections of the near future. We find elevated concentrations of atmospheric carbon dioxide to be the most important forcing for driving changes in Pliocene surface air temperature, sea surface temperature, and precipitation. However, changes caused by the nature of Pliocene ice sheets and orography are also important, affecting the extent to which we can use the Pliocene as an analogue for our warmer future.
Peter Kuma, Frida A.-M. Bender, Alex Schuddeboom, Adrian J. McDonald, and Øyvind Seland
Atmos. Chem. Phys., 23, 523–549, https://doi.org/10.5194/acp-23-523-2023, https://doi.org/10.5194/acp-23-523-2023, 2023
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We present a machine learning method for determining cloud types in climate model output and satellite observations based on ground observations of cloud genera. We analyse cloud type biases and changes with temperature in climate models and show that the bias is anticorrelated with climate sensitivity. Models simulating decreasing stratiform and increasing cumuliform clouds with increased CO2 concentration tend to have higher climate sensitivity than models simulating the opposite tendencies.
Shuang Gao, Jörg Schwinger, Jerry Tjiputra, Ingo Bethke, Jens Hartmann, Emilio Mayorga, and Christoph Heinze
Biogeosciences, 20, 93–119, https://doi.org/10.5194/bg-20-93-2023, https://doi.org/10.5194/bg-20-93-2023, 2023
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We assess the impact of riverine nutrients and carbon (C) on projected marine primary production (PP) and C uptake using a fully coupled Earth system model. Riverine inputs alleviate nutrient limitation and thus lessen the projected PP decline by up to 0.7 Pg C yr−1 globally. The effect of increased riverine C may be larger than the effect of nutrient inputs in the future on the projected ocean C uptake, while in the historical period increased nutrient inputs are considered the largest driver.
Julia E. Weiffenbach, Michiel L. J. Baatsen, Henk A. Dijkstra, Anna S. von der Heydt, Ayako Abe-Ouchi, Esther C. Brady, Wing-Le Chan, Deepak Chandan, Mark A. Chandler, Camille Contoux, Ran Feng, Chuncheng Guo, Zixuan Han, Alan M. Haywood, Qiang Li, Xiangyu Li, Gerrit Lohmann, Daniel J. Lunt, Kerim H. Nisancioglu, Bette L. Otto-Bliesner, W. Richard Peltier, Gilles Ramstein, Linda E. Sohl, Christian Stepanek, Ning Tan, Julia C. Tindall, Charles J. R. Williams, Qiong Zhang, and Zhongshi Zhang
Clim. Past, 19, 61–85, https://doi.org/10.5194/cp-19-61-2023, https://doi.org/10.5194/cp-19-61-2023, 2023
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We study the behavior of the Atlantic Meridional Overturning Circulation (AMOC) in the mid-Pliocene. The mid-Pliocene was about 3 million years ago and had a similar CO2 concentration to today. We show that the stronger AMOC during this period relates to changes in geography and that this has a significant influence on ocean temperatures and heat transported northwards by the Atlantic Ocean. Understanding the behavior of the mid-Pliocene AMOC can help us to learn more about our future climate.
Marius S. A. Lambert, Hui Tang, Kjetil S. Aas, Frode Stordal, Rosie A. Fisher, Yilin Fang, Junyan Ding, and Frans-Jan W. Parmentier
Geosci. Model Dev., 15, 8809–8829, https://doi.org/10.5194/gmd-15-8809-2022, https://doi.org/10.5194/gmd-15-8809-2022, 2022
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In this study, we implement a hardening mortality scheme into CTSM5.0-FATES-Hydro and evaluate how it impacts plant hydraulics and vegetation growth. Our work shows that the hydraulic modifications prescribed by the hardening scheme are necessary to model realistic vegetation growth in cold climates, in contrast to the default model that simulates almost nonexistent and declining vegetation due to abnormally large water loss through the roots.
Jörg Schwinger, Ali Asaadi, Norman Julius Steinert, and Hanna Lee
Earth Syst. Dynam., 13, 1641–1665, https://doi.org/10.5194/esd-13-1641-2022, https://doi.org/10.5194/esd-13-1641-2022, 2022
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We test whether climate change can be partially reversed if CO2 is removed from the atmosphere to compensate for too large past and near-term emissions by using idealized model simulations of overshoot pathways. On a timescale of 100 years, we find a high degree of reversibility if the overshoot size remains small, and we do not find tipping points even for intense overshoots. We caution that current Earth system models are most likely not able to skilfully model tipping points in ecosystems.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Luke Gregor, Judith Hauck, Corinne Le Quéré, Ingrid T. Luijkx, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Ramdane Alkama, Almut Arneth, Vivek K. Arora, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Henry C. Bittig, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Wiley Evans, Stefanie Falk, Richard A. Feely, Thomas Gasser, Marion Gehlen, Thanos Gkritzalis, Lucas Gloege, Giacomo Grassi, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Atul K. Jain, Annika Jersild, Koji Kadono, Etsushi Kato, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Peter Landschützer, Nathalie Lefèvre, Keith Lindsay, Junjie Liu, Zhu Liu, Gregg Marland, Nicolas Mayot, Matthew J. McGrath, Nicolas Metzl, Natalie M. Monacci, David R. Munro, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin O'Brien, Tsuneo Ono, Paul I. Palmer, Naiqing Pan, Denis Pierrot, Katie Pocock, Benjamin Poulter, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Carmen Rodriguez, Thais M. Rosan, Jörg Schwinger, Roland Séférian, Jamie D. Shutler, Ingunn Skjelvan, Tobias Steinhoff, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Shintaro Takao, Toste Tanhua, Pieter P. Tans, Xiangjun Tian, Hanqin Tian, Bronte Tilbrook, Hiroyuki Tsujino, Francesco Tubiello, Guido R. van der Werf, Anthony P. Walker, Rik Wanninkhof, Chris Whitehead, Anna Willstrand Wranne, Rebecca Wright, Wenping Yuan, Chao Yue, Xu Yue, Sönke Zaehle, Jiye Zeng, and Bo Zheng
Earth Syst. Sci. Data, 14, 4811–4900, https://doi.org/10.5194/essd-14-4811-2022, https://doi.org/10.5194/essd-14-4811-2022, 2022
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The Global Carbon Budget 2022 describes the datasets and methodology used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, the land ecosystems, and the ocean. These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Ville Leinonen, Harri Kokkola, Taina Yli-Juuti, Tero Mielonen, Thomas Kühn, Tuomo Nieminen, Simo Heikkinen, Tuuli Miinalainen, Tommi Bergman, Ken Carslaw, Stefano Decesari, Markus Fiebig, Tareq Hussein, Niku Kivekäs, Radovan Krejci, Markku Kulmala, Ari Leskinen, Andreas Massling, Nikos Mihalopoulos, Jane P. Mulcahy, Steffen M. Noe, Twan van Noije, Fiona M. O'Connor, Colin O'Dowd, Dirk Olivie, Jakob B. Pernov, Tuukka Petäjä, Øyvind Seland, Michael Schulz, Catherine E. Scott, Henrik Skov, Erik Swietlicki, Thomas Tuch, Alfred Wiedensohler, Annele Virtanen, and Santtu Mikkonen
Atmos. Chem. Phys., 22, 12873–12905, https://doi.org/10.5194/acp-22-12873-2022, https://doi.org/10.5194/acp-22-12873-2022, 2022
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We provide the first extensive comparison of detailed aerosol size distribution trends between in situ observations from Europe and five different earth system models. We investigated aerosol modes (nucleation, Aitken, and accumulation) separately and were able to show the differences between measured and modeled trends and especially their seasonal patterns. The differences in model results are likely due to complex effects of several processes instead of certain specific model features.
Johannes Quaas, Hailing Jia, Chris Smith, Anna Lea Albright, Wenche Aas, Nicolas Bellouin, Olivier Boucher, Marie Doutriaux-Boucher, Piers M. Forster, Daniel Grosvenor, Stuart Jenkins, Zbigniew Klimont, Norman G. Loeb, Xiaoyan Ma, Vaishali Naik, Fabien Paulot, Philip Stier, Martin Wild, Gunnar Myhre, and Michael Schulz
Atmos. Chem. Phys., 22, 12221–12239, https://doi.org/10.5194/acp-22-12221-2022, https://doi.org/10.5194/acp-22-12221-2022, 2022
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Pollution particles cool climate and offset part of the global warming. However, they are washed out by rain and thus their effect responds quickly to changes in emissions. We show multiple datasets to demonstrate that aerosol emissions and their concentrations declined in many regions influenced by human emissions, as did the effects on clouds. Consequently, the cooling impact on the Earth energy budget became smaller. This change in trend implies a relative warming.
Petri Räisänen, Joonas Merikanto, Risto Makkonen, Mikko Savolahti, Alf Kirkevåg, Maria Sand, Øyvind Seland, and Antti-Ilari Partanen
Atmos. Chem. Phys., 22, 11579–11602, https://doi.org/10.5194/acp-22-11579-2022, https://doi.org/10.5194/acp-22-11579-2022, 2022
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A climate model is used to evaluate how the radiative forcing (RF) associated with black carbon (BC) emissions depends on the latitude, longitude, and seasonality of emissions. It is found that both the direct RF (BC absorption of solar radiation in air) and snow RF (BC absorption in snow/ice) depend strongly on the emission region and season. The results suggest that, for a given mass of BC emitted, climatic impacts are likely to be largest for high-latitude emissions due to the large snow RF.
Qirui Zhong, Nick Schutgens, Guido van der Werf, Twan van Noije, Kostas Tsigaridis, Susanne E. Bauer, Tero Mielonen, Alf Kirkevåg, Øyvind Seland, Harri Kokkola, Ramiro Checa-Garcia, David Neubauer, Zak Kipling, Hitoshi Matsui, Paul Ginoux, Toshihiko Takemura, Philippe Le Sager, Samuel Rémy, Huisheng Bian, Mian Chin, Kai Zhang, Jialei Zhu, Svetlana G. Tsyro, Gabriele Curci, Anna Protonotariou, Ben Johnson, Joyce E. Penner, Nicolas Bellouin, Ragnhild B. Skeie, and Gunnar Myhre
Atmos. Chem. Phys., 22, 11009–11032, https://doi.org/10.5194/acp-22-11009-2022, https://doi.org/10.5194/acp-22-11009-2022, 2022
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Aerosol optical depth (AOD) errors for biomass burning aerosol (BBA) are evaluated in 18 global models against satellite datasets. Notwithstanding biases in satellite products, they allow model evaluations. We observe large and diverse model biases due to errors in BBA. Further interpretations of AOD diversities suggest large biases exist in key processes for BBA which require better constraining. These results can contribute to further model improvement and development.
Pradeebane Vaittinada Ayar, Laurent Bopp, Jim R. Christian, Tatiana Ilyina, John P. Krasting, Roland Séférian, Hiroyuki Tsujino, Michio Watanabe, Andrew Yool, and Jerry Tjiputra
Earth Syst. Dynam., 13, 1097–1118, https://doi.org/10.5194/esd-13-1097-2022, https://doi.org/10.5194/esd-13-1097-2022, 2022
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The El Niño–Southern Oscillation is the main driver for the natural variability of global atmospheric CO2. It modulates the CO2 fluxes in the tropical Pacific with anomalous CO2 influx during El Niño and outflux during La Niña. This relationship is projected to reverse by half of Earth system models studied here under the business-as-usual scenario. This study shows models that simulate a positive bias in surface carbonate concentrations simulate a shift in the ENSO–CO2 flux relationship.
Pedro Duarte, Jostein Brændshøi, Dmitry Shcherbin, Pauline Barras, Jon Albretsen, Yvonne Gusdal, Nicholas Szapiro, Andreas Martinsen, Annette Samuelsen, Keguang Wang, and Jens Boldingh Debernard
Geosci. Model Dev., 15, 4373–4392, https://doi.org/10.5194/gmd-15-4373-2022, https://doi.org/10.5194/gmd-15-4373-2022, 2022
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Sea ice models are often implemented for very large domains beyond the regions of sea ice formation, such as the whole Arctic or all of Antarctica. In this study, we implement changes in the Los Alamos Sea Ice Model, allowing it to be implemented for relatively small regions within the Arctic or Antarctica and yet considering the presence and influence of sea ice outside the represented areas. Such regional implementations are important when spatially detailed results are required.
Noah D. Smith, Eleanor J. Burke, Kjetil Schanke Aas, Inge H. J. Althuizen, Julia Boike, Casper Tai Christiansen, Bernd Etzelmüller, Thomas Friborg, Hanna Lee, Heather Rumbold, Rachael H. Turton, Sebastian Westermann, and Sarah E. Chadburn
Geosci. Model Dev., 15, 3603–3639, https://doi.org/10.5194/gmd-15-3603-2022, https://doi.org/10.5194/gmd-15-3603-2022, 2022
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The Arctic has large areas of small mounds that are caused by ice lifting up the soil. Snow blown by wind gathers in hollows next to these mounds, insulating them in winter. The hollows tend to be wetter, and thus the soil absorbs more heat in summer. The warm wet soil in the hollows decomposes, releasing methane. We have made a model of this, and we have tested how it behaves and whether it looks like sites in Scandinavia and Siberia. Sometimes we get more methane than a model without mounds.
Cynthia H. Whaley, Rashed Mahmood, Knut von Salzen, Barbara Winter, Sabine Eckhardt, Stephen Arnold, Stephen Beagley, Silvia Becagli, Rong-You Chien, Jesper Christensen, Sujay Manish Damani, Xinyi Dong, Konstantinos Eleftheriadis, Nikolaos Evangeliou, Gregory Faluvegi, Mark Flanner, Joshua S. Fu, Michael Gauss, Fabio Giardi, Wanmin Gong, Jens Liengaard Hjorth, Lin Huang, Ulas Im, Yugo Kanaya, Srinath Krishnan, Zbigniew Klimont, Thomas Kühn, Joakim Langner, Kathy S. Law, Louis Marelle, Andreas Massling, Dirk Olivié, Tatsuo Onishi, Naga Oshima, Yiran Peng, David A. Plummer, Olga Popovicheva, Luca Pozzoli, Jean-Christophe Raut, Maria Sand, Laura N. Saunders, Julia Schmale, Sangeeta Sharma, Ragnhild Bieltvedt Skeie, Henrik Skov, Fumikazu Taketani, Manu A. Thomas, Rita Traversi, Kostas Tsigaridis, Svetlana Tsyro, Steven Turnock, Vito Vitale, Kaley A. Walker, Minqi Wang, Duncan Watson-Parris, and Tahya Weiss-Gibbons
Atmos. Chem. Phys., 22, 5775–5828, https://doi.org/10.5194/acp-22-5775-2022, https://doi.org/10.5194/acp-22-5775-2022, 2022
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Air pollutants, like ozone and soot, play a role in both global warming and air quality. Atmospheric models are often used to provide information to policy makers about current and future conditions under different emissions scenarios. In order to have confidence in those simulations, in this study we compare simulated air pollution from 18 state-of-the-art atmospheric models to measured air pollution in order to assess how well the models perform.
Pierre Friedlingstein, Matthew W. Jones, Michael O'Sullivan, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Corinne Le Quéré, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Rob B. Jackson, Simone R. Alin, Peter Anthoni, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Laurent Bopp, Thi Tuyet Trang Chau, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Kim I. Currie, Bertrand Decharme, Laique M. Djeutchouang, Xinyu Dou, Wiley Evans, Richard A. Feely, Liang Feng, Thomas Gasser, Dennis Gilfillan, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Ingrid T. Luijkx, Atul Jain, Steve D. Jones, Etsushi Kato, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Arne Körtzinger, Peter Landschützer, Siv K. Lauvset, Nathalie Lefèvre, Sebastian Lienert, Junjie Liu, Gregg Marland, Patrick C. McGuire, Joe R. Melton, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Yosuke Niwa, Tsuneo Ono, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Thais M. Rosan, Jörg Schwinger, Clemens Schwingshackl, Roland Séférian, Adrienne J. Sutton, Colm Sweeney, Toste Tanhua, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Francesco Tubiello, Guido R. van der Werf, Nicolas Vuichard, Chisato Wada, Rik Wanninkhof, Andrew J. Watson, David Willis, Andrew J. Wiltshire, Wenping Yuan, Chao Yue, Xu Yue, Sönke Zaehle, and Jiye Zeng
Earth Syst. Sci. Data, 14, 1917–2005, https://doi.org/10.5194/essd-14-1917-2022, https://doi.org/10.5194/essd-14-1917-2022, 2022
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The Global Carbon Budget 2021 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Clemens Spensberger, Trond Thorsteinsson, and Thomas Spengler
Geosci. Model Dev., 15, 2711–2729, https://doi.org/10.5194/gmd-15-2711-2022, https://doi.org/10.5194/gmd-15-2711-2022, 2022
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In order to understand the atmosphere, we rely on a hierarchy of models ranging from very simple to very complex. Comparing different steps in this hierarchy usually entails comparing different models. Here we combine two such steps that are commonly used in one modelling framework. This makes comparisons both much easier and much more direct.
Filippa Fransner, Friederike Fröb, Jerry Tjiputra, Nadine Goris, Siv K. Lauvset, Ingunn Skjelvan, Emil Jeansson, Abdirahman Omar, Melissa Chierici, Elizabeth Jones, Agneta Fransson, Sólveig R. Ólafsdóttir, Truls Johannessen, and Are Olsen
Biogeosciences, 19, 979–1012, https://doi.org/10.5194/bg-19-979-2022, https://doi.org/10.5194/bg-19-979-2022, 2022
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Ocean acidification, a direct consequence of the CO2 release by human activities, is a serious threat to marine ecosystems. In this study, we conduct a detailed investigation of the acidification of the Nordic Seas, from 1850 to 2100, by using a large set of samples taken during research cruises together with numerical model simulations. We estimate the effects of changes in different environmental factors on the rate of acidification and its potential effects on cold-water corals.
Thorben Dunse, Kaixing Dong, Kjetil Schanke Aas, and Leif Christian Stige
Biogeosciences, 19, 271–294, https://doi.org/10.5194/bg-19-271-2022, https://doi.org/10.5194/bg-19-271-2022, 2022
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We investigate the effect of glacier meltwater on phytoplankton dynamics in Svalbard. Phytoplankton forms the basis of the marine food web, and its seasonal dynamics depend on the availability of light and nutrients, both of which are affected by glacier runoff. We use satellite ocean color, an indicator of phytoplankton biomass, and glacier mass balance modeling to find that the overall effect of glacier runoff on marine productivity is positive within the major fjord systems of Svalbard.
Zixuan Han, Qiong Zhang, Qiang Li, Ran Feng, Alan M. Haywood, Julia C. Tindall, Stephen J. Hunter, Bette L. Otto-Bliesner, Esther C. Brady, Nan Rosenbloom, Zhongshi Zhang, Xiangyu Li, Chuncheng Guo, Kerim H. Nisancioglu, Christian Stepanek, Gerrit Lohmann, Linda E. Sohl, Mark A. Chandler, Ning Tan, Gilles Ramstein, Michiel L. J. Baatsen, Anna S. von der Heydt, Deepak Chandan, W. Richard Peltier, Charles J. R. Williams, Daniel J. Lunt, Jianbo Cheng, Qin Wen, and Natalie J. Burls
Clim. Past, 17, 2537–2558, https://doi.org/10.5194/cp-17-2537-2021, https://doi.org/10.5194/cp-17-2537-2021, 2021
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Understanding the potential processes responsible for large-scale hydrological cycle changes in a warmer climate is of great importance. Our study implies that an imbalance in interhemispheric atmospheric energy during the mid-Pliocene could have led to changes in the dynamic effect, offsetting the thermodynamic effect and, hence, altering mid-Pliocene hydroclimate cycling. Moreover, a robust westward shift in the Pacific Walker circulation can moisten the northern Indian Ocean.
Arthur M. Oldeman, Michiel L. J. Baatsen, Anna S. von der Heydt, Henk A. Dijkstra, Julia C. Tindall, Ayako Abe-Ouchi, Alice R. Booth, Esther C. Brady, Wing-Le Chan, Deepak Chandan, Mark A. Chandler, Camille Contoux, Ran Feng, Chuncheng Guo, Alan M. Haywood, Stephen J. Hunter, Youichi Kamae, Qiang Li, Xiangyu Li, Gerrit Lohmann, Daniel J. Lunt, Kerim H. Nisancioglu, Bette L. Otto-Bliesner, W. Richard Peltier, Gabriel M. Pontes, Gilles Ramstein, Linda E. Sohl, Christian Stepanek, Ning Tan, Qiong Zhang, Zhongshi Zhang, Ilana Wainer, and Charles J. R. Williams
Clim. Past, 17, 2427–2450, https://doi.org/10.5194/cp-17-2427-2021, https://doi.org/10.5194/cp-17-2427-2021, 2021
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In this work, we have studied the behaviour of El Niño events in the mid-Pliocene, a period of around 3 million years ago, using a collection of 17 climate models. It is an interesting period to study, as it saw similar atmospheric carbon dioxide levels to the present day. We find that the El Niño events were less strong in the mid-Pliocene simulations, when compared to pre-industrial climate. Our results could help to interpret El Niño behaviour in future climate projections.
Clio Michel, Erica Madonna, Clemens Spensberger, Camille Li, and Stephen Outten
Weather Clim. Dynam., 2, 1131–1148, https://doi.org/10.5194/wcd-2-1131-2021, https://doi.org/10.5194/wcd-2-1131-2021, 2021
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Climate models still struggle to correctly represent blocking frequency over the North Atlantic–European domain. This study makes use of five large ensembles of climate simulations and the ERA-Interim reanalyses to investigate the Greenland blocking frequency and one of its drivers, namely cyclonic Rossby wave breaking. We particularly try to understand the discrepancies between two specific models, out of the five, that behave differently.
Ingo Bethke, Yiguo Wang, François Counillon, Noel Keenlyside, Madlen Kimmritz, Filippa Fransner, Annette Samuelsen, Helene Langehaug, Lea Svendsen, Ping-Gin Chiu, Leilane Passos, Mats Bentsen, Chuncheng Guo, Alok Gupta, Jerry Tjiputra, Alf Kirkevåg, Dirk Olivié, Øyvind Seland, Julie Solsvik Vågane, Yuanchao Fan, and Tor Eldevik
Geosci. Model Dev., 14, 7073–7116, https://doi.org/10.5194/gmd-14-7073-2021, https://doi.org/10.5194/gmd-14-7073-2021, 2021
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The Norwegian Climate Prediction Model version 1 (NorCPM1) is a new research tool for performing climate reanalyses and seasonal-to-decadal climate predictions. It adds data assimilation capability to the Norwegian Earth System Model version 1 (NorESM1) and has contributed output to the Decadal Climate Prediction Project (DCPP) as part of the sixth Coupled Model Intercomparison Project (CMIP6). We describe the system and evaluate its baseline, reanalysis and prediction performance.
Maria Sand, Bjørn H. Samset, Gunnar Myhre, Jonas Gliß, Susanne E. Bauer, Huisheng Bian, Mian Chin, Ramiro Checa-Garcia, Paul Ginoux, Zak Kipling, Alf Kirkevåg, Harri Kokkola, Philippe Le Sager, Marianne T. Lund, Hitoshi Matsui, Twan van Noije, Dirk J. L. Olivié, Samuel Remy, Michael Schulz, Philip Stier, Camilla W. Stjern, Toshihiko Takemura, Kostas Tsigaridis, Svetlana G. Tsyro, and Duncan Watson-Parris
Atmos. Chem. Phys., 21, 15929–15947, https://doi.org/10.5194/acp-21-15929-2021, https://doi.org/10.5194/acp-21-15929-2021, 2021
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Absorption of shortwave radiation by aerosols can modify precipitation and clouds but is poorly constrained in models. A total of 15 different aerosol models from AeroCom phase III have reported total aerosol absorption, and for the first time, 11 of these models have reported in a consistent experiment the contributions to absorption from black carbon, dust, and organic aerosol. Here, we document the model diversity in aerosol absorption.
Leonidas Tsopouridis, Thomas Spengler, and Clemens Spensberger
Weather Clim. Dynam., 2, 953–970, https://doi.org/10.5194/wcd-2-953-2021, https://doi.org/10.5194/wcd-2-953-2021, 2021
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Comparing simulations with realistic and smoothed SSTs, we find that the intensification of individual cyclones in the Gulf Stream and Kuroshio regions is only marginally affected by reducing the SST gradient. In contrast, we observe a reduced cyclone activity and a shift in storm tracks. Considering differences of the variables occurring within/outside of a radius of any cyclone, we find cyclones to play only a secondary role in explaining the mean states differences among the SST experiments.
Tao Tang, Drew Shindell, Yuqiang Zhang, Apostolos Voulgarakis, Jean-Francois Lamarque, Gunnar Myhre, Gregory Faluvegi, Bjørn H. Samset, Timothy Andrews, Dirk Olivié, Toshihiko Takemura, and Xuhui Lee
Atmos. Chem. Phys., 21, 13797–13809, https://doi.org/10.5194/acp-21-13797-2021, https://doi.org/10.5194/acp-21-13797-2021, 2021
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Previous studies showed that black carbon (BC) could warm the surface with decreased incoming radiation. With climate models, we found that the surface energy redistribution plays a more crucial role in surface temperature compared with other forcing agents. Though BC could reduce the surface heating, the energy dissipates less efficiently, which is manifested by reduced convective and evaporative cooling, thereby warming the surface.
Cited articles
Adler, R. F., Huffman, G. J., Chang, A., Ferraro, R., Xie, P.-P., Janowiak, J.,
Rudolf, B., Schneider, U., Curtis, S., Bolvin, D., Gruber, A., Susskind, J.,
Arkin, P., and Nelkin, E.: The Version-2 Global Precipitation Climatology
Project (GPCP) Monthly Precipitation Analysis (1979–Present), J.
Hydrometeorol., 4, 1147–1167,
https://doi.org/10.1175/1525-7541(2003)004<1147:TVGPCP>2.0.CO;2, 2003. a
Annamalai, H. and Slingo, J. M.: Active/break cycles: diagnosis of the
intraseasonal variability of the Asian Summer Monsoon, Clim. Dynam., 18,
85–102, https://doi.org/10.1007/s003820100161, 2001. a
Arora, V. K., Katavouta, A., Williams, R. G., Jones, C. D., Brovkin, V., Friedlingstein, P., Schwinger, J., Bopp, L., Boucher, O., Cadule, P., Chamberlain, M. A., Christian, J. R., Delire, C., Fisher, R. A., Hajima, T., Ilyina, T., Joetzjer, E., Kawamiya, M., Koven, C. D., Krasting, J. P., Law, R. M., Lawrence, D. M., Lenton, A., Lindsay, K., Pongratz, J., Raddatz, T., Séférian, R., Tachiiri, K., Tjiputra, J. F., Wiltshire, A., Wu, T., and Ziehn, T.: Carbon–concentration and carbon–climate feedbacks in CMIP6 models and their comparison to CMIP5 models, Biogeosciences, 17, 4173–4222, https://doi.org/10.5194/bg-17-4173-2020, 2020. a, b
Assur, A.: Composition of sea ice and its tensile strength, Publs. Natl. Res. Coun. Wash., 598, 10–138, 1958. a
Avitabile, V., Herold, M., Heuvelink, G. B. M., Lewis, S. L., Phillips, O. L.,
Asner, G. P., Armston, J., Ashton, P. S., Banin, L., Bayol, N., Berry, N. J.,
Boeckx, P., de Jong, B. H. J., DeVries, B., Girardin, C. A. J., Kearsley, E.,
Lindsell, J. A., Lopez-Gonzalez, G., Lucas, R., Malhi, Y., Morel, A.,
Mitchard, E. T. A., Nagy, L., Qie, L., Quinones, M. J., Ryan, C. M., Ferry,
S. J. F., Sunderland, T., Laurin, G. V., Gatti, R. C., Valentini, R.,
Verbeeck, H., Wijaya, A., and Willcock, S.: An integrated pan‐tropical
biomass map using multiple reference datasets, Glob. Change Biol., 22,
1406–1420, https://doi.org/10.1111/gcb.13139, 2016. a
Behrens, E., Rickard, G., Morgenstern, O., Martin, T., Osprey, A., and Joshi,
M.: Southern Ocean deep convection in global climate models: A driver for
variability of subpolar gyres and Drake Passage transport on decadal
timescales, J. Geophys. Res.-Oceans, 121, 3905–3925,
https://doi.org/10.1002/2015JC011286,
2016. a
Bentsen, M.: “Bergen Layered Ocean Model (BLOM): Description and evaluation of global ocean–sea-ice experiments”, Geosci. Model. Dev. Discuss., in preparation, 2020.
Bentsen, M., Bethke, I., Debernard, J. B., Iversen, T., Kirkevåg, A., Seland, Ø., Drange, H., Roelandt, C., Seierstad, I. A., Hoose, C., and Kristjánsson, J. E.: The Norwegian Earth System Model, NorESM1-M – Part 1: Description and basic evaluation of the physical climate, Geosci. Model Dev., 6, 687–720, https://doi.org/10.5194/gmd-6-687-2013, 2013. a, b, c, d
Bentsen, M., Oliviè, D. J. L., Seland, Ø., Toniazzo, T., Gjermundsen,
A., Graff, L. S., Debernard, J. B., Gupta, A. K., He, Y., Kirkevåg, A.,
Schwinger, J., Tjiputra, J., Aas, K. S., Bethke, I., Fan, Y., Griesfeller,
J., Grini, A., Guo, C., Ilicak, M., Karset, I. H. H., Landgren, O. A.,
Liakka, J., Moseid, K. O., Nummelin, A., Spensberger, C., Tang, H., Zhang,
Z., Heinze, C., Iversen, T., and Schulz, M.: NCC NorESM2-MM model output
prepared for CMIP6 CMIP, CMIP6.CMIP.NCC.NorESM2-MM, https://doi.org/10.22033/ESGF/CMIP6.506, 2019. a
Blackmon, M. L.: A Climatological Spectral Study of the 500 mb Geopotential
Height of the Northern Hemisphere, J. Atmos. Sci., 33,
1607–1623, https://doi.org/10.1175/1520-0469(1976)033<1607:ACSSOT>2.0.CO;2, 1976. a, b
Blackmon, M. L., Wallace, J. M., Lau, N.-C., and Mullen, S. L.: An
Observational Study of the Northern Hemisphere Wintertime Circulation,
J. Atmos. Sci., 34, 1040–1053,
https://doi.org/10.1175/1520-0469(1977)034<1040:AOSOTN>2.0.CO;2, 1977. a, b, c
Boer, G. J. and Yu, B.: Dynamical aspects of climate sensitivity, Geophys.
Res. Lett., 30, 1135, https://doi.org/10.1029/2002GL016549, 2003. a
Bogenschutz, P. A., Gettelman, A., Hannay, C., Larson, V. E., Neale, R. B., Craig, C., and Chen, C.-C.: The path to CAM6: coupled simulations with CAM5.4 and CAM5.5, Geosci. Model Dev., 11, 235–255, https://doi.org/10.5194/gmd-11-235-2018, 2018. a, b, c
Briegleb, B. P. and Light, B.: A Delta-Eddington Mutiple Scattering
Parameterization for Solar Radiation in the Sea Ice Component of the
Community Climate System Model, Tech. Rep. No. NCAR/TN-472+STR, University
Corporation for Atmospheric Research, Boulder, Colerado, USA,
https://doi.org/10.5065/D6B27S71, 2007. a
Bryan, F. O., Hecht, M. W., and Smith, R. D.: Resolution convergence and
sensitivity studies with North Atlantic circulation models. Part I: The
western boundary current system, Ocean Model., 16, 141–159,
https://doi.org/10.1016/j.ocemod.2006.08.005,
2007. a, b
Cassou, C.: Intraseasonal interaction between the Madden-Julian Oscillation
and the North Atlantic Oscillation, Nature, 455, 523–527,
https://doi.org/10.1038/nature07286, 2009. a
Chang, E. K. M., Lee, S., and Swanson, K. L.: Storm Track Dynamics, J. Climate, 15, 2163–2183, https://doi.org/10.1175/1520-0442(2002)015<02163:STD>2.0.CO;2,
2002. a
Collins, W. D., Rasch, P. J., Boville, B. A., Hack, J. J., McCaa, J. R.,
Williamson, D. L., and Briegleb, B. P.: The Formulation and Atmospheric
Simulation of the Community Atmosphere Model Version 3 (CAM3), J. Climate,
19, 2144–2161, 2006. a
Danabasoglu, G., Lamarque, J.-F., Bacmeister, J., Bailey, D. A., DuVivier,
A. K., Edwards, J., Emmons, L. K., Fasullo, J., Garcia, R., Gettelman, A.,
Hannay, C., Holland, M. M., Large, W. G., Lauritzen, P. H., Lawrence, D. M.,
Lenaerts, J. T. M., Lindsay, K., Lipscomb, W. H., Mills, M. J., Neale, R.,
Oleson, K. W., Otto-Bliesner, B., Phillips, A. S., Sacks, W., Tilmes, S., van
Kampenhout, L., Vertenstein, M., Bertini, A., Dennis, J., Deser, C.,
Fischer, C., Fox-Kemper, B., Kay, J. E., Kinnison, D., Kushner, P. J.,
Larson, V. E., Long, M. C., Mickelson, S., Moore, J. K., Nienhouse, E.,
Polvani, L., Rasch, P. J., and Strand, W. G.: The Community Earth System
Model Version 2 (CESM2), J. Adv. Model. Earth Sy., 12,
e2019MS001916, https://doi.org/10.1029/2019MS001916, 2020. a, b, c, d, e, f, g, h, i
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi,
S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P.,
Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C.,
Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B.,
Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler, M.,
Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette, J.-J., Park,
B.-K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J.-N., and Vitart,
F.: The ERA-Interim reanalysis: configuration and performance of the data
assimilation system, Q. J. Roy. Meteor. Soc.,
137, 553–597, https://doi.org/10.1002/qj.828, 2011. a
Dentener, F., Kinne, S., Bond, T., Boucher, O., Cofala, J., Generoso, S., Ginoux, P., Gong, S., Hoelzemann, J. J., Ito, A., Marelli, L., Penner, J. E., Putaud, J.-P., Textor, C., Schulz, M., van der Werf, G. R., and Wilson, J.: Emissions of primary aerosol and precursor gases in the years 2000 and 1750 prescribed data-sets for AeroCom, Atmos. Chem. Phys., 6, 4321–4344, https://doi.org/10.5194/acp-6-4321-2006, 2006. a, b
Dickson, A., Sabine, C., and Christian, J.: Guide to best practices for ocean
CO2 measurements, PICES special publication 3, North Pacific Marine
Science Organization (PICES), Sidney, British Columbia, Canada, 2007. a
Eden, C. and Greatbatch, R. J.: Towards a mesoscale eddy closure, Ocean
Model., 20, 223–239, https://doi.org/10.1016/j.ocemod.2007.09.002, 2008. a
Eden, C., Jochum, M., and Danabasoglu, G.: Effects of different closures for
thickness diffusivity, Ocean Mo
del., 26, 47–59,
https://doi.org/10.1016/j.ocemod.2008.08.004, 2009. a
Eyring, V., Bony, S., Meehl, G. A., Senior, C. A., Stevens, B., Stouffer, R. J., and Taylor, K. E.: Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization, Geosci. Model Dev., 9, 1937–1958, https://doi.org/10.5194/gmd-9-1937-2016, 2016. a, b, c, d
Fairall, C. W., Bradley, E. F., Hare, J. E., Grachev, A. A., and Edson, J. B.:
Bulk parametrization of Air-Sea Fluxes: Updates and Verification for the
COARE Algorithm, J. Climate, 16, 571–591, 2003. a
FAO/IIASA/ISRIC/ISSCAS/JRC: Harmonized World Soil Database (version 1.10), FAO, Rome, Italy and IIASA, Laxenburg, Austria, 2012.
Forster, P. M., Andrews, T., Good, P., Gregory, J. M., Jackson, L. S., and
Zelinka, M.: Evaluating adjusted forcing and model spread for historical and
future scenarios in the CMIP5 generation of climate models, J. Geophys. Res.-Atmos., 118, 1139–1150, https://doi.org/10.1002/jgrd.50174, 2013. a
Garcia, H. E., Locarnini, R. A., Boyer, T. P., Antonov, J. I., Baranova, O.,
Zweng, M., Reagan, J., and Johnson, D.: World Ocean Atlas 2013, Volume 3:
Dissolved Oxygen, Apparent Oxygen Utilization, and Oxygen Saturation, in:
NOAA Atlas NESDIS 75, edited by: Levitus, S. and Mishonov, A., 27 pp.,
2014a. a
Garcia, H. E., Locarnini, R. A., Boyer, T. P., Antonov, J. I., Baranova, O.,
Zweng, M., Reagan, J., and Johnson, D.: World Ocean Atlas 2013, Volume 4:
Dissolved Inorganic Nutrients (phosphate, nitrate, silicate), in: NOAA
Atlas NESDIS 76, edited by: Levitus, S. and Mishonov, A., 25 pp.,
2014b. a
Gent, P. R. and McWilliams, J. C.: Isopycnal Mixing in Ocean Circulation
Models, J. Phys Oceanogr., 20, 150–155, 1990. a
Gettelman, A., Hannay, C., Bacmeister, J. T., Neale, R. B., Pendergrass, A. G.,
Danabasoglu, G., Lamarque, J.-F., Fasullo, J. T., Bailey, D. A., Lawrence,
D. M., and Mills, M. J.: High Climate Sensitivity in the Community Earth
System Model Version 2 (CESM2), Geophys. Res. Lett., 46, 8329–8337,
https://doi.org/10.1029/2019GL083978, 2019a. a, b, c
Gettelman, A., Mills, M. J., Kinnison, D. E., Garcia, R. R., Smith, A. K.,
Marsh, D. R., Tilmes, S., Vitt, F., Bardeen, C. G., McInerny, J., Liu, H.-L.,
Solomon, S. C., Polvani, L. M., Emmons, L. K., Lamarque, J.-F., Richter,
J. H., Glanville, A. S., Bacmeister, J. T., Phillips, A. S., Neale, R. B.,
Simpson, I. R., DuVivier, A. K., Hodzic, A., and Randel, W. J.: The Whole
Atmosphere Community Climate Model Version 6 (WACCM6), J. Geophys.
Res.-Atmos., 124, 12380–12403, https://doi.org/10.1029/2019JD030943, 2019b. a
Gidden, M. J., Riahi, K., Smith, S. J., Fujimori, S., Luderer, G., Kriegler, E., van Vuuren, D. P., van den Berg, M., Feng, L., Klein, D., Calvin, K., Doelman, J. C., Frank, S., Fricko, O., Harmsen, M., Hasegawa, T., Havlik, P., Hilaire, J., Hoesly, R., Horing, J., Popp, A., Stehfest, E., and Takahashi, K.: Global emissions pathways under different socioeconomic scenarios for use in CMIP6: a dataset of harmonized emissions trajectories through the end of the century, Geosci. Model Dev., 12, 1443–1475, https://doi.org/10.5194/gmd-12-1443-2019, 2019. a
Gillett, N. P., Arora, V. K., Matthews, D., and Allen, M. R.: Constraining the
Ratio of Global Warming to Cumulative CO2 Emissions Using CMIP5 Simulations,
J. Climate, 26, 6844–6858, https://doi.org/10.1175/JCLI-D-12-00476.1, 2013. a
Gliß, J., Mortier, A., Schulz, M., Andrews, E., Balkanski, Y., Bauer, S. E., Benedictow, A. M. K., Bian, H., Checa-Garcia, R., Chin, M., Ginoux, P., Griesfeller, J. J., Heckel, A., Kipling, Z., Kirkevåg, A., Kokkola, H., Laj, P., Le Sager, P., Lund, M. T., Lund Myhre, C., Matsui, H., Myhre, G., Neubauer, D., van Noije, T., North, P., Olivié, D. J. L., Sogacheva, L., Takemura, T., Tsigaridis, K., and Tsyro, S. G.: Multi-model evaluation of aerosol optical properties in the AeroCom phase III Control experiment, using ground and space based columnar observations from AERONET, MODIS, AATSR and a merged satellite product as well as surface in-situ observations from GAW sites, Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2019-1214, in review, 2020. a, b
Graff, L. S. and LaCasce, J. H.: Changes in the Extratropical Storm Tracks in
Response to Changes in SST in an AGCM, J. Climate, 25, 1854–1870,
https://doi.org/10.1175/JCLI-D-11-00174.1, 2012. a
Graff, L. S., Iversen, T., Bethke, I., Debernard, J. B., Seland, Ø., Bentsen, M., Kirkevåg, A., Li, C., and Olivié, D. J. L.: Arctic amplification under global warming of 1.5 and 2 °C in NorESM1-Happi, Earth Syst. Dynam., 10, 569–598, https://doi.org/10.5194/esd-10-569-2019, 2019. a, b, c, d, e, f, g, h
Gregory, J. M., Ingram, W. J., Palmer, M. A., Jones, G. S., Stott, P. A.,
Thorpe, R. B., Lowe, J. A., Johns, T. C., and Williams, K. D.: A new method
for diagnosing radiative forcing and climate sensitivity, Geophys.
Res. Lett., 31, L03205, https://doi.org/10.1029/2003GL018747, 2004. a, b, c, d
Griffies, S. M., Danabasoglu, G., Durack, P. J., Adcroft, A. J., Balaji, V., Böning, C. W., Chassignet, E. P., Curchitser, E., Deshayes, J., Drange, H., Fox-Kemper, B., Gleckler, P. J., Gregory, J. M., Haak, H., Hallberg, R. W., Heimbach, P., Hewitt, H. T., Holland, D. M., Ilyina, T., Jungclaus, J. H., Komuro, Y., Krasting, J. P., Large, W. G., Marsland, S. J., Masina, S., McDougall, T. J., Nurser, A. J. G., Orr, J. C., Pirani, A., Qiao, F., Stouffer, R. J., Taylor, K. E., Treguier, A. M., Tsujino, H., Uotila, P., Valdivieso, M., Wang, Q., Winton, M., and Yeager, S. G.: OMIP contribution to CMIP6: experimental and diagnostic protocol for the physical component of the Ocean Model Intercomparison Project, Geosci. Model Dev., 9, 3231–3296, https://doi.org/10.5194/gmd-9-3231-2016, 2016. a
Guinehut, S. C., Coatanoan, A.-L., Dhomps, P.-Y., and Larnicol, G.: On the use
of satellite altimeter data in Argo quality control, J. Atmos.
Ocean. Tech., 26, 395–402, https://doi.org/10.1175/2008JTECHO648.1, 2009. a
Harrison, E. F., Minnis, P., Barkstrom, B. R., Ramanathan, V., Cess, R. D., and
Gibson, G. G.: Seasonal variation of cloud radiative forcing derived from the
Earth Radiation Budget Experiment, J. Geophys. Res.-Atmos., 95, 18687–18703, https://doi.org/10.1029/JD095iD11p18687, 1990. a
Hendon, H. H., Wheeler, M. C., and Zhang, C.: Seasonal Dependence of the
MJO-ENSO Relationship, J. Climate, 20, 531–543,
https://doi.org/10.1175/JCLI4003.1, 2007. a
Hoesly, R. M., Smith, S. J., Feng, L., Klimont, Z., Janssens-Maenhout, G., Pitkanen, T., Seibert, J. J., Vu, L., Andres, R. J., Bolt, R. M., Bond, T. C., Dawidowski, L., Kholod, N., Kurokawa, J.-I., Li, M., Liu, L., Lu, Z., Moura, M. C. P., O'Rourke, P. R., and Zhang, Q.: Historical (1750–2014) anthropogenic emissions of reactive gases and aerosols from the Community Emissions Data System (CEDS), Geosci. Model Dev., 11, 369–408, https://doi.org/10.5194/gmd-11-369-2018, 2018. a
Hunke, E. C., Hebert, D. A., and Lecomte, O.: Level-ice melt ponds in the Los
Alamos sea ice model, CICE, Ocean Model., 71, 26–42,
https://doi.org/10.1016/j.ocemod.2012.11.008, 2013. a
Ilicak, M., Özgökmen, T. M., Peters, H., Baumert, H. Z., and
Iskandarani, M.: Performance of two-equation turbulence closures in
three-dimensional simulations of the Red Sea overflow, Ocean Model., 24,
122–139, https://doi.org/10.1016/j.ocemod.2008.06.001, 2008. a
Iversen, T., Bentsen, M., Bethke, I., Debernard, J. B., Kirkevåg, A., Seland, Ø., Drange, H., Kristjansson, J. E., Medhaug, I., Sand, M., and Seierstad, I. A.: The Norwegian Earth System Model, NorESM1-M – Part 2: Climate response and scenario projections, Geosci. Model Dev., 6, 389–415, https://doi.org/10.5194/gmd-6-389-2013, 2013. a, b, c, d, e, f
Jung, M., Reichstein, M., Margolis, H. A., Cescatti, A., Richardson, A. D.,
Arain, M. A., Arneth, A., Bernhofer, C., Bonal, D., Chen, J., Gianelle, D.,
Gobron, N., Kiely, G., Kutsch, W., Lasslop, G., Law, B. E., Lindroth, A.,
Merbold, L., Montagnani, L., Moors, E. J., Papale, D., Sottocornola, M.,
Vaccari, F., and Williams, C.: Global patterns of land-atmosphere fluxes of
carbon dioxide, latent heat, and sensible heat derived from eddy covariance,
satellite, and meteorological observations., J. Geophys. Res.-Biogeo.,
116, G00J07, https://doi.org/10.1029/2010jg001566, 2011. a
Kanamitsu, M., Ebisuzaki, W., Woollen, J., Yang, S.-K., Hnilo, J. J., Fiorino,
M., and Potter, G. L.: NCEP-DOE AMIP-II Reanalysis (R-2), B. Am. Meteorol. Soc., 83, 1631–1644,
https://doi.org/10.1175/BAMS-83-11-1631, 2002. a
Kiehl, J. T. and Trenberth, K. E.: Earth's Annual Global Mean Energy Budget,
B. Am. Meteorol. Soc., 78, 197–208,
https://doi.org/10.1175/1520-0477(1997)078<0197:EAGMEB>2.0.CO;2, 1997. a
Kirkevåg, A., Iversen, T., Seland, Ø., Hoose, C., Kristjánsson, J. E., Struthers, H., Ekman, A. M. L., Ghan, S., Griesfeller, J., Nilsson, E. D., and Schulz, M.: Aerosol–climate interactions in the Norwegian Earth System Model – NorESM1-M, Geosci. Model Dev., 6, 207–244, https://doi.org/10.5194/gmd-6-207-2013, 2013. a, b, c, d
Kirkevåg, A., Grini, A., Olivié, D., Seland, Ø., Alterskjær, K., Hummel, M., Karset, I. H. H., Lewinschal, A., Liu, X., Makkonen, R., Bethke, I., Griesfeller, J., Schulz, M., and Iversen, T.: A production-tagged aerosol module for Earth system models, OsloAero5.3 – extensions and updates for CAM5.3-Oslo, Geosci. Model Dev., 11, 3945–3982, https://doi.org/10.5194/gmd-11-3945-2018, 2018. a, b, c, d, e, f, g, h
Kuang, C., McMurry, P. H., and McCormick, A. V.: Determination of cloud
condensation nuclei production from measured new particle formation events,
Geophys. Res. Lett., 36, L09822, https://doi.org/10.1029/2009GL037584, 2009. a
Lana, A., Bell, T. G., Simó, R., Vallina, S. M., Ballabrera-Poy, J., Kettle,
A. J., Dachs, J., Bopp, L., Saltzman, E. S., Stefels, J., Johnson, J. E., and
Liss, P. S.: An updated climatology of surface dimethlysulfide concentrations
and emission fluxes in the global ocean, Global Biogeochem. Cy., 25, GB1004,
https://doi.org/10.1029/2010GB003850, 2011. a
Large, W. G. and Yeager, S. G.: The global climatology of an interannually
varying air-sea flux data set, Clim. Dynam., 33, 341–364,
https://doi.org/10.1007/s00382-008-0441-3, 2009. a
Large, W. G., McWilliams, J. C., and Doney, S. C.: Ocean vertical mixing: a
review and a model with a nonlocal boundary layer parameterization, Rev.
Geophys., 32, 363–403, 1994. a
Lauvset, S. K., Key, R. M., Olsen, A., van Heuven, S., Velo, A., Lin, X., Schirnick, C., Kozyr, A., Tanhua, T., Hoppema, M., Jutterström, S., Steinfeldt, R., Jeansson, E., Ishii, M., Perez, F. F., Suzuki, T., and Watelet, S.: A new global interior ocean mapped climatology: the 1° × 1° GLODAP version 2, Earth Syst. Sci. Data, 8, 325–340, https://doi.org/10.5194/essd-8-325-2016, 2016. a
Lavergne, T., Sørensen, A. M., Kern, S., Tonboe, R., Notz, D., Aaboe, S., Bell, L., Dybkjær, G., Eastwood, S., Gabarro, C., Heygster, G., Killie, M. A., Brandt Kreiner, M., Lavelle, J., Saldo, R., Sandven, S., and Pedersen, L. T.: Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records, The Cryosphere, 13, 49–78, https://doi.org/10.5194/tc-13-49-2019, 2019. a, b, c
Lawrence, D. M., Fisher, R. A., Koven, C. D., Oleson, K. W., Swenson, S. C.,
Bonan, G., Collier, N., Ghimire, B., van Kampenhout, L., Kennedy, D., Kluzek,
E., Lawrence, P. J., Li, F., Li, H., Lombardozzi, D., Riley, W. J., Sacks,
W. J., Shi, M., Vertenstein, M., Wieder, W. R., Xu, C., Ali, A. A., Badger,
A. M., Bisht, G., van den Broeke, M., Brunke, M. A., Burns, S. P., Buzan, J.,
Clark, M., Craig, A., Dahlin, K., Drewniak, B., Fisher, J. B., Flanner, M.,
Fox, A. M., Gentine, P., Hoffman, F., Keppel-Aleks, G., Knox, R., Kumar, S.,
Lenaerts, J., Leung, L. R., Lipscomb, W. H., Lu, Y., Pandey, A., Pelletier,
J. D., Perket, J., Randerson, J. T., Ricciuto, D. M., Sanderson, B. M.,
Slater, A., Subin, Z. M., Tang, J., Thomas, R. Q., Val Martin, M., and Zeng,
X.: The Community Land Model Version 5: Description of New Features,
Benchmarking, and Impact of Forcing Uncertainty, J. Adv. Model. Earth Sy., 11, 4245–4287, https://doi.org/10.1029/2018MS001583, 2019. a, b, c, d
Lecomte, O., Fichefet, T., Vancoppenolle, M., Domine, F., Massonnet, F.,
Mathiot, P., Morin, S., and Barriat, P. Y.: On the formulation of snow
thermal conductivity in large-scale sea ice models, J. Adv. Model. Earth Sy., 5, 542–557, https://doi.org/10.1002/jame.20039, 2013. a
L'Ecuyer, T. S., Wood, N. B., Haladay, T., Stephens, G. L., and Stackhouse Jr.,
P. W.: Impact of clouds on atmospheric heating based on the R04 CloudSat
fluxes and heating rates data set, J. Geophys. Res.-Atmos., 113, D00A15, https://doi.org/10.1029/2008JD009951, 2008. a
Lenaerts, J. T. M., Gettelman, A., Van Tricht, K., van Kampenhout, L., and
Miller, N. B.: Impact of cloud physics on the Greenland Ice Sheet
near‐surface climate: a study with the Community Atmosphere Model, J. Geophys. Res.-Atmos., 125, e2019JD031470, https://doi.org/10.1029/2019JD031470, 2020. a
Li, H., Wigmosta, M. S., Wu, H., Huang, M., Ke, Y., Coleman, A. M., and Leung,
L. R.: A Physically Based Runoff Routing Model for Land Surface and Earth
System Models, J. Hydrometeorol., 14, 808–828,
https://doi.org/10.1175/JHM-D-12-015.1, 2013. a
Liebmann, B., Hendon, H. H., and Glick, J. D.: The Relationship Between
Tropical Cyclones of the Western Pacific and Indian Oceans and the
Madden-Julian Oscillation, J. Meteorol. Soc. Jpn.,
72, 401–412, https://doi.org/10.2151/jmsj1965.72.3_401, 1994. a
Lin, S.-J. and Rood, R. B.: An explicit flux-form semi-Lagrangian shallow-water
model on the sphere, Q. J. R. Meteorol. Soc., 123, 2477–2498, 1997. a
Lipscomb, W. H., Price, S. F., Hoffman, M. J., Leguy, G. R., Bennett, A. R., Bradley, S. L., Evans, K. J., Fyke, J. G., Kennedy, J. H., Perego, M., Ranken, D. M., Sacks, W. J., Salinger, A. G., Vargo, L. J., and Worley, P. H.: Description and evaluation of the Community Ice Sheet Model (CISM) v2.1, Geosci. Model Dev., 12, 387–424, https://doi.org/10.5194/gmd-12-387-2019, 2019. a
Locarnini, R. A., Mishonov, A. V., Baranova, O. K., Boyer, T. P., Zweng, M. M.,
Garcia, H. E., Reagan, J. R., Seidov, D., Weathers, K., Paver, C. R., and
Smolyar, I.: World Ocean Atlas 2018, Volume 1: Temperature. NOAA Atlas NESDIS 81, edited by: Mishonov, A., National Oceanic and Atmospheric Administration, U.S. Department of Commerce, 52 pp., 2018. a, b
Loeb, N. G., Kato, S., Loukachine, K., and Manalo-Smith, N.: Angular
Distribution Models for Top-of-Atmosphere Radiative Flux Estimation from the
Clouds and the Earth’s Radiant Energy System Instrument on the Terra
Satellite. Part I: Methodology, J. Atmos. Ocean. Tech., 22, 338–351, https://doi.org/10.1175/JTECH1712.1, 2005. a, b
Loeb, N. G., Wielicki, B. A., Doelling, D. R., Smith, G. L., Keyes, D. F.,
Kato, S., Manalo-Smith, N., and Wong, T.: Toward Optimal Closure of the
Earth's Top-of-Atmosphere Radiation Budget, J. Climate, 22, 748–766,
https://doi.org/10.1175/2008JCLI2637.1, 2009. a, b
Loeb, N. G., Lyman, J. M., Johnson, G. C., Allan, R. P., Doelling, D. R., Wong,
T., Soden, B. J., and Stephens, G. L.: Observed changes in
top-of-the-atmosphere radiation and upper-ocean heating consistent within
uncertainty, Nat. Geosci., 5, 110–113, https://doi.org/10.1038/ngeo1375, 2012. a, b
Madden, R. A. and Julian, P. R.: Detection of a 40–50 Day Oscillation in the
Zonal Wind in the Tropical Pacific, J. Atmos. Sci., 28,
702–708, https://doi.org/10.1175/1520-0469(1971)028<0702:DOADOI>2.0.CO;2, 1971. a
Mahowald, N., Baker, A., Bergametti, G., Brooks, N., Duce, R., Jickells, T.,
Kubilay, N., Prospero, J., and Tegen, I.: Atmospheric global dust cycle and
iron inputs to the ocean, Global Biogeochem. Cy., 19, GB4025,
https://doi.org/10.1029/2004GB002402, 2005. a
Marks, K. and Smith, W.: An Evaluation of Publicly Available Global Bathymetry
Grids, Mar. Geophys. Res., 27, 19–34, https://doi.org/10.1007/s11001-005-2095-4,
2006. a
Matthes, K., Funke, B., Andersson, M. E., Barnard, L., Beer, J., Charbonneau, P., Clilverd, M. A., Dudok de Wit, T., Haberreiter, M., Hendry, A., Jackman, C. H., Kretzschmar, M., Kruschke, T., Kunze, M., Langematz, U., Marsh, D. R., Maycock, A. C., Misios, S., Rodger, C. J., Scaife, A. A., Seppälä, A., Shangguan, M., Sinnhuber, M., Tourpali, K., Usoskin, I., van de Kamp, M., Verronen, P. T., and Versick, S.: Solar forcing for CMIP6 (v3.2), Geosci. Model Dev., 10, 2247–2302, https://doi.org/10.5194/gmd-10-2247-2017, 2017. a
Meinshausen, M., Vogel, E., Nauels, A., Lorbacher, K., Meinshausen, N., Etheridge, D. M., Fraser, P. J., Montzka, S. A., Rayner, P. J., Trudinger, C. M., Krummel, P. B., Beyerle, U., Canadell, J. G., Daniel, J. S., Enting, I. G., Law, R. M., Lunder, C. R., O'Doherty, S., Prinn, R. G., Reimann, S., Rubino, M., Velders, G. J. M., Vollmer, M. K., Wang, R. H. J., and Weiss, R.: Historical greenhouse gas concentrations for climate modelling (CMIP6), Geosci. Model Dev., 10, 2057–2116, https://doi.org/10.5194/gmd-10-2057-2017, 2017. a
Mitchell, D., AchutaRao, K., Allen, M., Bethke, I., Beyerle, U., Ciavarella, A., Forster, P. M., Fuglestvedt, J., Gillett, N., Haustein, K., Ingram, W., Iversen, T., Kharin, V., Klingaman, N., Massey, N., Fischer, E., Schleussner, C.-F., Scinocca, J., Seland, Ø., Shiogama, H., Shuckburgh, E., Sparrow, S., Stone, D., Uhe, P., Wallom, D., Wehner, M., and Zaaboul, R.: Half a degree additional warming, prognosis and projected impacts (HAPPI): background and experimental design, Geosci. Model Dev., 10, 571–583, https://doi.org/10.5194/gmd-10-571-2017, 2017. a
Morice, C. P., Kennedy, J. J., Rayner, N. A., and Jones, P. D.: Quantifying
uncertainties in global and regional temperature change using an ensemble of
observational estimates: The HadCRUT4 dataset, J. Geophys.
Res.-Atmos., 117, D08101, https://doi.org/10.1029/2011JD017187, 2012. a
O’Dell, C. W., Wentz, F. J., and Bennartz, R.: Cloud Liquid Water Path from
Satellite-Based Passive Microwave Observations: A New Climatology over the
Global Oceans, J. Climate, 21, 1721–1739,
https://doi.org/10.1175/2007JCLI1958.1, 2008. a
Olivié, D. : Evaluation of radiative forcing in the Norwegian Earth System Model NorESM2, Atmos. Chem. Phys. Discuss., in preparation, 2020.
O'Neill, B. C., Tebaldi, C., van Vuuren, D. P., Eyring, V., Friedlingstein, P., Hurtt, G., Knutti, R., Kriegler, E., Lamarque, J.-F., Lowe, J., Meehl, G. A., Moss, R., Riahi, K., and Sanderson, B. M.: The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6, Geosci. Model Dev., 9, 3461–3482, https://doi.org/10.5194/gmd-9-3461-2016, 2016. a, b
Onogi, K., Tustsui, J., Koide, H., Sakamoto, M., Kokayaski, S., Hatsushika, H.,
Matsumoto, T., Yamazaki, N., Kamahori, H., Takahashi, K., Kadokura, S., Wada,
K., Kato, K., Oyama, R., Ose, T., Mannoji, N., and Taira, R.: The JRA-25
Reanalysis, J. Meteorol. Soc. Jpn., 85,
369–432, https://doi.org/10.2151/jmsj.85.369, 2007. a
Orr, J. C., Najjar, R. G., Aumont, O., Bopp, L., Bullister, J. L., Danabasoglu, G., Doney, S. C., Dunne, J. P., Dutay, J.-C., Graven, H., Griffies, S. M., John, J. G., Joos, F., Levin, I., Lindsay, K., Matear, R. J., McKinley, G. A., Mouchet, A., Oschlies, A., Romanou, A., Schlitzer, R., Tagliabue, A., Tanhua, T., and Yool, A.: Biogeochemical protocols and diagnostics for the CMIP6 Ocean Model Intercomparison Project (OMIP), Geosci. Model Dev., 10, 2169–2199, https://doi.org/10.5194/gmd-10-2169-2017, 2017. a
Paynter, D., Frölicher, T. L., Horowitz, L. W., and Silvers, L. G.:
Equilibrium Climate Sensitivity Obtained From Multimillennial Runs of Two
GFDL Climate Models, J. Geophys. Res.-Atmos., 123,
1921–1941, https://doi.org/10.1002/2017JD027885, 2018. a
Pelly, J. L. and Hoskins, B. J.: A New Perspective on Blocking, J. Atmos. Sci., 60, 743–755,
https://doi.org/10.1175/1520-0469(2003)060<0743:ANPOB>2.0.CO;2, 2003. a, b
Praveen Kumar, B., Vialard, J., Lengaigne, M., Murty, V. S. N., and McPhaden,
M. J.: TropFlux: air-sea fluxes for the global tropical oceans – description
and evaluation, Clim. Dynam., 38, 1521–1543, https://doi.org/10.1001/s00382-011-1115-0,
2012. a
Rackow, T., Sein, D. V., Semmler, T., Danilov, S., Koldunov, N. V., Sidorenko, D., Wang, Q., and Jung, T.: Sensitivity of deep ocean biases to horizontal resolution in prototype CMIP6 simulations with AWI-CM1.0, Geosci. Model Dev., 12, 2635–2656, https://doi.org/10.5194/gmd-12-2635-2019, 2019. a, b
Rayner, N. A., Parker, D. E., Horton, E. B., Folland, C. K., Alexander, L. V.,
Rowell, D. P., Kent, E. C., and Kaplan, A.: Global analyses of sea surface
temperature, sea ice, and night marine air temperature since the late
nineteenth century, J. Geophys. Res.-Atmos., 108, 4407,
https://doi.org/10.1029/2002JD002670, 2003. a, b
Rossow, W. B. and Dueñas, E. N.: The International Satellite Cloud
Climatology Project (ISCCP) web site: an online resource for research, B.
Am. Meteorol. Soc., 85, 167–172, https://doi.org/10.1175/BAMS-85-2-167, 2004. a
Rossow, W. B. and Schiffer, R. A.: Advances in Understanding Clouds from ISCCP,
B. Am. Meteorol. Soc., 80, 2261–2288,
https://doi.org/10.1175/1520-0477(1999)080<2261:AIUCFI>2.0.CO;2, 1999. a
Saba, V. S., Griffies, S. M., Anderson, W. G., Winton, M., Alexander, M. A.,
Delworth, T. L., Hare, J. A., Harrison, M. J., Rosati, A., Vecchi, G. A., and
Zhang, R.: Enhanced warming of the Northwest Atlantic Ocean under climate
change, J. Geophys. Res.-Oceans, 121, 118–132,
https://doi.org/10.1002/2015JC011346, 2016. a, b, c
Salter, M. E., Zieger, P., Acosta Navarro, J. C., Grythe, H., Kirkevåg, A., Rosati, B., Riipinen, I., and Nilsson, E. D.: An empirically derived inorganic sea spray source function incorporating sea surface temperature, Atmos. Chem. Phys., 15, 11047–11066, https://doi.org/10.5194/acp-15-11047-2015, 2015. a
Santoro, M., Beaudoin, A., Beer, C., Cartus, O., Fransson, J. B. S., Hall,
R. J., Pathe, C., Schmullius, C., Schepaschenko, D., Shvidenko, A., Thurner,
M., and Wegmüller, U.: Forest growing stock volume of the northern
hemisphere: Spatially explicit estimates for 2010 derived from Envisat ASAR,
Remote Sens. Environ., 168, 316–334,
https://doi.org/10.1016/j.rse.2015.07.005, 2015. a
Schurer, A., Hegerl, G., Ribes, A., Polson, D., Morice, C., and Tett, S.:
Estimating the Transient Climate Response from Observed Warming, J. Climate, 31, 8645–8663, https://doi.org/10.1175/JCLI-D-17-0717.1, 2018. a
Schwinger, J., Goris, N., Tjiputra, J. F., Kriest, I., Bentsen, M., Bethke, I., Ilicak, M., Assmann, K. M., and Heinze, C.: Evaluation of NorESM-OC (versions 1 and 1.2), the ocean carbon-cycle stand-alone configuration of the Norwegian Earth System Model (NorESM1), Geosci. Model Dev., 9, 2589–2622, https://doi.org/10.5194/gmd-9-2589-2016, 2016. a
Schwinger, J., Tjiputra, J., Goris, N., Six, K. D., Kirkevåg, A., Seland, Ø., Heinze, C., and Ilyina, T.: Amplification of global warming through pH dependence of DMS production simulated with a fully coupled Earth system model, Biogeosciences, 14, 3633–3648, https://doi.org/10.5194/bg-14-3633-2017, 2017. a, b
Seland, Ø.: NorESM1 1 degree resolution coupled simulations for HappiEVA
project, available at: https://archive.sigma2.no/pages/public/datasetDetail.jsf?id=10.11582/2020.00021, last access: 1 December
2020. a
Seland, Ø., Bentsen, M., Oliviè, D. J. L., Toniazzo, T., Gjermundsen,
A., Graff, L. S., Debernard, J. B., Gupta, A. K., He, Y., Kirkevåg, A.,
Schwinger, J., Tjiputra, J., Aas, K. S., Bethke, I., Fan, Y., Griesfeller,
J., Grini, A., Guo, C., Ilicak, M., Karset, I. H. H., Landgren, O. A.,
Liakka, J., Moseid, K. O., Nummelin, A., Spensberger, C., Tang, H., Zhang,
Z., Heinze, C., Iversen, T., and Schulz, M.: NCC NorESM2-LM model output
prepared for CMIP6 CMIP, CMIP6.CMIP.NCC.NorESM2-LM, https://doi.org/10.22033/ESGF/CMIP6.502, 2019. a
Seland, Ø., Bentsen, M., Olivié, D., Toniazzo, T., Gjermundsen, A., Graff,
L. S., Debernard, J. B., Gupta, A. K., He, Y., Kirkevåg, A., Schwinger, J.,
Tjiputra, J., Aas, K. S., Bethke, I., Fan, Y., Gao, S., Griesfeller, J.,
Grini, A., Guo, C., Ilicak, M., Karset, I. H. H., Landgren, O., Liakka, J.,
Moree, A., Moseid, K. O., Nummelin, A., Spensberger, C., Tang, H., Zhang, Z.,
Heinze, C., Iversen, T., and Schulz, M.: NorESM2 source code as used for
CMIP6 simulations (includes additional experimental setups, extended model
documentation, automated inputdata download, restructuring of BLOM/iHAMOCC
input data), Zenodo, https://doi.org/10.5281/zenodo.3905091, 2020. a
Shonk, J. K. P., Guyliardi, E., Toniazzo, T., Woolnough, S. J., and Stockdale,
T.: Identifying causes of western Pacific ITCZ drift in ECMWF System 4
hindcasts, Clim. Dynam., 50, 939–954, https://doi.org/10.1007/s00382-017-3650-9, 2018. a
SIMIP Community: Arctic Sea Ice in CMIP6, Geophys. Res. Lett., 47,
e2019GL086749, https://doi.org/10.1029/2019GL086749, 2020. a
Sporre, M. K., Blichner, S. M., Karset, I. H. H., Makkonen, R., and Berntsen, T. K.: BVOC–aerosol–climate feedbacks investigated using NorESM, Atmos. Chem. Phys., 19, 4763–4782, https://doi.org/10.5194/acp-19-4763-2019, 2019. a
Stammer, D., Bracco, A., Achuta Rao, K., Beal, L., Bindoff, N. L., Braconnot,
P., Cai, W., Chen, D., Collins, M., Danabasoglu, G., Dewitte, B., Farneti,
R., Fox-Kemper, B., Fyfe, J., Griffies, S. M., Jayne, S. R., Lazar, A.,
Lengaigne, M., Lin, X., Marsland, S., Minobe, S., Monteiro, P. M. S.,
Robinson, W., Roxy, M. K., Rykaczewski, R. R., Speich, S., Smith, I. J.,
Solomon, A., Storto, A., Takahashi, K., Toniazzo, T., and Vialard, J.: Ocean
climate observing requirements in support of climate research and climate
information, Front. Mar. Sci., 6, 1–18, https://doi.org/10.3389/mars.2019.00444, 2019. a
Steele, M., Morley, R., and Ermold, W.: PHC: A Global Ocean Hydrography with a
High-Quality Arctic Ocean, J. Climate, 14, 2079–2087, 2001. a
Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S. K., Boschung,
J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. (Eds.): Climate change 2013:
the physical science basis, Contribution of working group I to the fifth
assessment report of the intergovernmental panel on climate change, Cambridge
University Press, Cambridge, United Kingdom and New York, USA, 2013. a
Taylor, K. E., Stouffer, R. J., and Meehl, G. A.: An Overview of CMIP5 and the
Experiment Design, B. Am. Meteorol. Soc., 93,
485–498, https://doi.org/10.1175/BAMS-D-11-00094.1, 2012. a
Textor, C., Schulz, M., Guibert, S., Kinne, S., Balkanski, Y., Bauer, S., Berntsen, T., Berglen, T., Boucher, O., Chin, M., Dentener, F., Diehl, T., Easter, R., Feichter, H., Fillmore, D., Ghan, S., Ginoux, P., Gong, S., Grini, A., Hendricks, J., Horowitz, L., Huang, P., Isaksen, I., Iversen, I., Kloster, S., Koch, D., Kirkevåg, A., Kristjansson, J. E., Krol, M., Lauer, A., Lamarque, J. F., Liu, X., Montanaro, V., Myhre, G., Penner, J., Pitari, G., Reddy, S., Seland, Ø., Stier, P., Takemura, T., and Tie, X.: Analysis and quantification of the diversities of aerosol life cycles within AeroCom, Atmos. Chem. Phys., 6, 1777–1813, https://doi.org/10.5194/acp-6-1777-2006, 2006. a
Thomason, L. W., Ernest, N., Millán, L., Rieger, L., Bourassa, A., Vernier, J.-P., Manney, G., Luo, B., Arfeuille, F., and Peter, T.: A global space-based stratospheric aerosol climatology: 1979–2016, Earth Syst. Sci. Data, 10, 469–492, https://doi.org/10.5194/essd-10-469-2018, 2018. a
Tibaldi, S. and Molteni, F.: On the operational predictability of blocking,
Tellus A, 42, 343–365, https://doi.org/10.1034/j.1600-0870.1990.t01-2-00003.x, 1990. a, b
Tjiputra, J. F., Roelandt, C., Bentsen, M., Lawrence, D. M., Lorentzen, T., Schwinger, J., Seland, Ø., and Heinze, C.: Evaluation of the carbon cycle components in the Norwegian Earth System Model (NorESM), Geosci. Model Dev., 6, 301–325, https://doi.org/10.5194/gmd-6-301-2013, 2013. a, b, c, d
Tjiputra, J. F., Schwinger, J., Bentsen, M., Morée, A. L., Gao, S., Bethke, I., Heinze, C., Goris, N., Gupta, A., He, Y.-C., Olivié, D., Seland, Ø., and Schulz, M.: Ocean biogeochemistry in the Norwegian Earth System Model version 2 (NorESM2), Geosci. Model Dev., 13, 2393–2431, https://doi.org/10.5194/gmd-13-2393-2020, 2020. a, b, c, d, e, f
Toniazzo T.: Sensitivity to prescribed SSTs of TOA imbalance and variability in AMIP simulations with CAM6-Nor., Geosci. Model Dev. Discuss., in preparation, 2020.
Toniazzo, T. and Woolnough, S.: Development of warm SST errors in the southern
tropical Altantic in decadal hindcasts, Clim. Dynam., 43, 2889–2913,
https://doi.org/10.1007/s00382-013-1691-2, 2014. a
Toniazzo, T., Bentsen, M., Craig, C., Eaton, B. E., Edwards, J., Goldhaber, S., Jablonowski, C., and Lauritzen, P. H.: Enforcing conservation of axial angular momentum in the atmospheric general circulation model CAM6, Geosci. Model Dev., 13, 685–705, https://doi.org/10.5194/gmd-13-685-2020, 2020. a, b, c, d, e, f
Trenberth, K. E., Fasullo, J. T., and Mackaro, J.: Atmospheric Moisture
Transports from Ocean to Land and Global Energy Flows in Reanalyses, J. Climate, 24, 4907–4924, https://doi.org/10.1175/2011JCLI4171.1, 2011. a, b, c, d
Tsujino, H., Urakawa, S., Nakano, H., Small, R. J., Kim, W. M., Yeager, S. G.,
Danabasoglu, G., Suzuki, T., Bamber, J. L., Bentsen, M., Böning, C. W.,
Bozec, A., Chassignet, E. P., Curchitser, E., Dias, F. B., Durack, P. J.,
Griffies, S. M., Harada, Y., Ilicak, M., Josey, S. A., Kobayashi, C.,
Kobayashi, S., Komuro, Y., Large, W. G., Sommer, J. L., Marsland, S. J.,
Masina, S., Scheinert, M., Tomita, H., Valdivieso, M., and Yamazaki, D.:
JRA-55 based surface dataset for driving ocean-sea-ice models (JRA55-do),
Ocean Model., 130, 79–139, https://doi.org/10.1016/j.ocemod.2018.07.002, 2018. a
Osores, S., Ruiz, J., Folch, A., and Collini, E.: Volcanic ash forecast using ensemble-based data assimilation: an ensemble transform Kalman filter coupled with the FALL3D-7.2 model (ETKF–FALL3D version 1.0), Geosci. Model Dev., 13, 1–22, https://doi.org/10.5194/gmd-13-1-2020, 2020. a, b, c
Turner, A. K. and Hunke, E. C.: Impacts of a mushy-layer thermodynamic approach
in global sea-ice simulations using the CICE sea-ice model, J.
Geophys. Res.-Oceans, 120, 1253–1275, https://doi.org/10.1002/2014JC010358,
2015. a
Umlauf, L. and Burchard, H.: Second-order turbulence closure models for
geophysical boundary layers. A review of recent work, Cont. Shelf Res., 25,
795–827, https://doi.org/10.1016/j.csr.2004.08.004, 2005. a
Uppala, S. M., Kållberg, P. W., Simmons, A. J., Andrae, U., Bechtold, V.
D. C., Fiorino, M., Gibson, J. K., Haseler, J., Hernandez, A., Kelly, G. A.,
Li, X., Onogi, K., Saarinen, S., Sokka, N., Allan, R. P., Andersson, E.,
Arpe, K., Balmaseda, M. A., Beljaars, A. C. M., Berg, L. V. D., Bidlot, J.,
Bormann, N., Caires, S., Chevallier, F., Dethof, A., Dragosavac, M., Fisher,
M., Fuentes, M., Hagemann, S., Hólm, E., Hoskins, B. J., Isaksen, L.,
Janssen, P. A. E. M., Jenne, R., Mcnally, A. P., Mahfouf, J.-F., Morcrette,
J.-J., Rayner, N. A., Saunders, R. W., Simon, P., Sterl, A., Trenberth,
K. E., Untch, A., Vasiljevic, D., Viterbo, P., and Woollen, J.: The ERA-40
re-analysis, Q. J. Roy. Meteor. Soc., 131,
2961–3012, https://doi.org/10.1256/qj.04.176, 2005. a
van Marle, M. J. E., Kloster, S., Magi, B. I., Marlon, J. R., Daniau, A.-L., Field, R. D., Arneth, A., Forrest, M., Hantson, S., Kehrwald, N. M., Knorr, W., Lasslop, G., Li, F., Mangeon, S., Yue, C., Kaiser, J. W., and van der Werf, G. R.: Historic global biomass burning emissions for CMIP6 (BB4CMIP) based on merging satellite observations with proxies and fire models (1750–2015), Geosci. Model Dev., 10, 3329–3357, https://doi.org/10.5194/gmd-10-3329-2017, 2017. a
Waliser, D., Sperber, K., Hendon, H., Kim, D., Wheeler, M., Weickmann, K.,
Zhang, C., Donner, L., Gottschalck, J., Higgins, W., Kang, I. S., Legler, D.,
Moncrieff, M., Vitart, F., Wang, B., Wang, W., Woolnough, S., Maloney, E.,
Schubert, S., and Stern, W.: MJO Simulation Diagnostics, J. Climate,
22, 3006–3030, https://doi.org/10.1175/2008JCLI2731.1, 2009.
a
Wang, C., Zhang, L., Lee, S.-K., Wu, L., and Mechoso, C. R.: A global
perspective on CMIP5 climate model biases, Nat. Clim. Change, 4,
201–205, https://doi.org/10.1038/nclimate2118, 2016. a
Wernli, H. and Schwierz, C.: Surface Cyclones in the ERA-40 Dataset
(1958–2001). Part I: Novel Identification Method and Global Climatology,
J. Atmos. Sci., 63, 2486–2507, https://doi.org/10.1175/JAS3766.1,
2006. a
Xie, P. and Arkin, P. A.: Global precipitation: A 17-year monthly analysis
based on gauge observations, satellite estimates, and numerical model
outputs, B. Am. Meteorol. Soc., 78, 2539–2558,
https://doi.org/10.1145/1520-0477(1997)078<2539:GPAYAMA>2.0.CO;2, 1997. a
Yu, L. and Weller, R. A.: Objectively Analyzed Air-Sea Heat Fluxes for the
Global Ice-Free Oceans (1981–2005), B. Am. Meteorol. Soc., 88, 527–540, https://doi.org/10.1175/BAMS-88-4-527, 2007. a
Yu, L., Jin, X., and Weller, R. A.: Multidecade Global Flux Datasets from the
Objectively Analyzed Air-sea Fluxes (OAFlux) Project: Latent and sensible
heat fluxes, ocean evaporation, and related surface meteorological
variables, Tech. Rep. OA-2008-01, Woods Hole Oceanographic Institution,
Woods Hole, Massachusetts, USA, 2008. a
Zhang, C.: Madden-Julian Oscillation, Rev. Geophys., 43, RG2003,
https://doi.org/10.1029/2004RG000158, 2005. a
Zhang, G. J. and McFarlane, N. A.: Sensitivity of climate simulations to the
parameterization of cumulus convection in the Canadian Climate Centre general
circulation model, Atmosphere-Ocean, 33, 407–446, 1995. a
Zhang, H., Wang, M., Guo, Z., Zhou, C., Zhou, T., Qian, Y., Larson, V. E.,
Ghan, S., Ovchinnikov, M., Bogenschutz, P. A., and Gettelman, A.: Low-Cloud
Feedback in CAM5-CLUBB: Physical Mechanisms and Parameter Sensitivity
Analysis, J. Adv. Model. Earth Sy., 10, 2844–2864,
https://doi.org/10.1029/2018MS001423, 2018. a
Zuidema, P., Chang, P., Medeiros, B., Kirtman, B. P., Mechoso, R., Schneider,
E. K., Toniazzo, T., Richter, I., Small, R. J., Bellomo, K., Brandt, P.,
de Szoeke, S., Farrar, J. T., Jung, E., Kato, S., Li, M., Patricola, C.,
Wang, Z., Wood, R., and Xu, Z.: Challenges and prospects for reducing coupled
climate model SST biases in the eastern tropical Atlantic and Pacific oceans, B. Am. Meteorol. Soc., 97, 2305–2328, https://doi.org/10.1175/BAMS-D-15-00274.1, 2016. a
Zweng, M. M., Reagan, J. R., Seidov, D., Boyer, T. P., Locarnini, R. A.,
Garcia, H. E., Mishonov, A. V., Baranova, O. K., Weathers, K., Paver, C. R.,
and Smolyar, I.: World Ocean Atlas 2018, Vol- ume 2: Salinity. NOAA Atlas NESDIS 81, edited by: Mishonov, A., National Oceanic and Atmospheric Administration, U.S. Department of Commerce, 50 pp., 2018. a, b
Short summary
The second version of the coupled Norwegian Earth System Model (NorESM2) is presented and evaluated. The temperature and precipitation patterns has improved compared to NorESM1. The model reaches present-day warming levels to within 0.2 °C of observed temperature but with a delayed warming during the late 20th century. Under the four scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5), the warming in the period of 2090–2099 compared to 1850–1879 reaches 1.3, 2.2, 3.1, and 3.9 K.
The second version of the coupled Norwegian Earth System Model (NorESM2) is presented and...