Articles | Volume 15, issue 4
https://doi.org/10.5194/gmd-15-1803-2022
© Author(s) 2022. 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-15-1803-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model evaluation paper
| 
03 Mar 2022
Model evaluation paper |
| 03 Mar 2022
| 03 Mar 2022
Variability and extremes: statistical validation of the Alfred Wegener Institute Earth System Model (AWI-ESM)
Alfred Wegener Institute, Helmholtz Centre for Polar Marine Research, Bremerhaven, Germany
Department of Environmental Physics, University of Bremen, Bremen, Germany
Thorsten Dickhaus
Institute for Statistics, University of Bremen, Bremen, Germany
Gerrit Lohmann
Alfred Wegener Institute, Helmholtz Centre for Polar Marine Research, Bremerhaven, Germany
Department of Environmental Physics, University of Bremen, Bremen, Germany
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Wee Wei Khoo, Juliane Müller, Oliver Esper, Wenshen Xiao, Christian Stepanek, Paul Gierz, Gerrit Lohmann, Walter Geibert, Jens Hefter, and Gesine Mollenhauer
Clim. Past, 21, 299–326, https://doi.org/10.5194/cp-21-299-2025, https://doi.org/10.5194/cp-21-299-2025, 2025
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Using a multiproxy approach, we analyzed biomarkers and diatom assemblages from a marine sediment core from the Powell Basin, Weddell Sea. The results reveal the first continuous coastal Antarctic sea ice record since the Last Penultimate Glacial. Our findings contribute valuable insights into past glacial–interglacial sea ice responses to a changing climate and enhance our understanding of ocean–sea ice–ice shelf interactions and dynamics.
Lutz Schirrmeister, Margret C. Fuchs, Thomas Opel, Andrei Andreev, Frank Kienast, Andrea Schneider, Larisa Nazarova, Larisa Frolova, Svetlana Kuzmina, Tatiana Kuznetsova, Vladimir Tumskoy, Heidrun Matthes, Gerit Lohmann, Guido Grosse, Viktor Kunitsky, Hanno Meyer, Heike H. Zimmermann, Ulrike Herzschuh, Thomas Boehmer, Stuart Umbo, Sevi Modestou, Sebastian F. M. Breitenbach, Anfisa Pismeniuk, Georg Schwamborn, Stephanie Kusch, and Sebastian Wetterich
Clim. Past Discuss., https://doi.org/10.5194/cp-2024-74, https://doi.org/10.5194/cp-2024-74, 2024
Revised manuscript under review for CP
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The strong ecosystem response to the Last Interglacial warming, reflected in the high diversity of proxies, shows the sensitivity of permafrost regions to rising temperatures. In particular, the development of thermokarst landscapes created a mosaic of terrestrial, wetland, and aquatic habitats, fostering an increase in biodiversity. This biodiversity is evident in the rich variety of terrestrial insects, vegetation, and aquatic invertebrates preserved in these deposits.
Hu Yang, Xiaoxu Shi, Xulong Wang, Qingsong Liu, Yi Zhong, Xiaodong Liu, Youbin Sun, Yanjun Cai, Fei Liu, Gerrit Lohmann, Martin Werner, Zhimin Jian, Tainã M. L. Pinho, Hai Cheng, Lijuan Lu, Jiping Liu, Chao-Yuan Yang, Qinghua Yang, Yongyun Hu, Xing Cheng, Jingyu Zhang, and Dake Chen
EGUsphere, https://doi.org/10.5194/egusphere-2024-2778, https://doi.org/10.5194/egusphere-2024-2778, 2024
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The precession driven low-latitude hydrological cycle is not paced by hemispheric summer insolation, but shifting perihelion.
Yugeng Chen, Pengyang Song, Xianyao Chen, and Gerrit Lohmann
Clim. Past, 20, 2001–2015, https://doi.org/10.5194/cp-20-2001-2024, https://doi.org/10.5194/cp-20-2001-2024, 2024
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Our study examines the Atlantic Meridional Overturning Circulation (AMOC) during the Last Glacial Maximum (LGM), a period with higher tidal dissipation. Despite increased tidal mixing, our model simulations show that the AMOC remained relatively shallow, consistent with paleoproxy data and resolving previous inconsistencies between proxy data and model simulations. This research highlights the importance of strong ocean stratification during the LGM and its interaction with tidal mixing.
Lars Ackermann, Thomas Rackow, Kai Himstedt, Paul Gierz, Gregor Knorr, and Gerrit Lohmann
Geosci. Model Dev., 17, 3279–3301, https://doi.org/10.5194/gmd-17-3279-2024, https://doi.org/10.5194/gmd-17-3279-2024, 2024
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We present long-term simulations with interactive icebergs in the Southern Ocean. By melting, icebergs reduce the temperature and salinity of the surrounding ocean. In our simulations, we find that this cooling effect of iceberg melting is not limited to the surface ocean but also reaches the deep ocean and propagates northward into all ocean basins. Additionally, the formation of deep-water masses in the Southern Ocean is enhanced.
Viorica Nagavciuc, Simon L. L. Michel, Daniel F. Balting, Gerhard Helle, Mandy Freund, Gerhard H. Schleser, David N. Steger, Gerrit Lohmann, and Monica Ionita
Clim. Past, 20, 573–595, https://doi.org/10.5194/cp-20-573-2024, https://doi.org/10.5194/cp-20-573-2024, 2024
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The main aim of this paper is to present the summer vapor pressure deficit (VPD) reconstruction dataset for the last 400 years over Europe based on δ18O records by using a random forest approach. We provide both a spatial and a temporal long-term perspective on the past summer VPD and new insights into the relationship between summer VPD and large-scale atmospheric circulation. This is the first gridded reconstruction of the European summer VPD over the past 400 years.
Uta Krebs-Kanzow, Christian B. Rodehacke, and Gerrit Lohmann
The Cryosphere, 17, 5131–5136, https://doi.org/10.5194/tc-17-5131-2023, https://doi.org/10.5194/tc-17-5131-2023, 2023
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We compare components of the surface energy balance from two datasets, ERA5 and ERA-Interim, which can be used to estimate the surface mass balance (SMB) on the Greenland Ice Sheet (GrIS). ERA5 differs significantly from ERA-Interim, especially in the melt regions with lower temperatures and stronger shortwave radiation. Consequently, methods that previously estimated the GrIS SMB from ERA-Interim need to be carefully recalibrated before conversion to ERA5 forcing.
Xiaoxu Shi, Martin Werner, Hu Yang, Roberta D'Agostino, Jiping Liu, Chaoyuan Yang, and Gerrit Lohmann
Clim. Past, 19, 2157–2175, https://doi.org/10.5194/cp-19-2157-2023, https://doi.org/10.5194/cp-19-2157-2023, 2023
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The Last Glacial Maximum (LGM) marks the most recent extremely cold and dry time period of our planet. Using AWI-ESM, we quantify the relative importance of Earth's orbit, greenhouse gases (GHG) and ice sheets (IS) in determining the LGM climate. Our results suggest that both GHG and IS play important roles in shaping the LGM temperature. Continental ice sheets exert a major control on precipitation, atmospheric dynamics, and the intensity of El Niño–Southern Oscillation.
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.
Ryan Love, Lev Tarasov, Heather Andres, Alan Condron, Xu Zhang, and Gerrit Lohmann
EGUsphere, https://doi.org/10.5194/egusphere-2023-2225, https://doi.org/10.5194/egusphere-2023-2225, 2023
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Freshwater injection into bands across the North Atlantic are a mainstay of climate modelling when investigating topics such as climate change or the role of glacial runoff in the glacial climate system. However, this approach is unrealistic and results in a systematic bias in the climate response to a given flux of freshwater. We evaluate the magnitude of this bias by comparison to two other approaches for introducing freshwater into a coupled climate model setup for glacial conditions.
Xiaoxu Shi, Alexandre Cauquoin, Gerrit Lohmann, Lukas Jonkers, Qiang Wang, Hu Yang, Yuchen Sun, and Martin Werner
Geosci. Model Dev., 16, 5153–5178, https://doi.org/10.5194/gmd-16-5153-2023, https://doi.org/10.5194/gmd-16-5153-2023, 2023
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We developed a new climate model with isotopic capabilities and simulated the pre-industrial and mid-Holocene periods. Despite certain regional model biases, the modeled isotope composition is in good agreement with observations and reconstructions. Based on our analyses, the observed isotope–temperature relationship in polar regions may have a summertime bias. Using daily model outputs, we developed a novel isotope-based approach to determine the onset date of the West African summer monsoon.
Di Cai, Gerrit Lohmann, Xianyao Chen, and Monica Ionita
EGUsphere, https://doi.org/10.5194/egusphere-2023-1646, https://doi.org/10.5194/egusphere-2023-1646, 2023
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Our study reveals how a decline in autumn sea ice in the Barents-Kara Seas leads to severe winters in Europe. Using observational data, we illustrate that Arctic sea ice loss isn't just a local issue – it impacts harsh winter conditions globally. Current climate models struggle to reflect these effects accurately, indicating a need for more research. Gaining a more nuanced understanding of this relationship will enhance our climate predictions and preparation for future extremes.
Pengyang Song, Dmitry Sidorenko, Patrick Scholz, Maik Thomas, and Gerrit Lohmann
Geosci. Model Dev., 16, 383–405, https://doi.org/10.5194/gmd-16-383-2023, https://doi.org/10.5194/gmd-16-383-2023, 2023
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Tides have essential effects on the ocean and climate. Most previous research applies parameterised tidal mixing to discuss their effects in models. By comparing the effect of a tidal mixing parameterisation and tidal forcing on the ocean state, we assess the advantages and disadvantages of the two methods. Our results show that tidal mixing in the North Pacific Ocean strongly affects the global thermohaline circulation. We also list some effects that are not considered in the parameterisation.
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.
Jan Streffing, Dmitry Sidorenko, Tido Semmler, Lorenzo Zampieri, Patrick Scholz, Miguel Andrés-Martínez, Nikolay Koldunov, Thomas Rackow, Joakim Kjellsson, Helge Goessling, Marylou Athanase, Qiang Wang, Jan Hegewald, Dmitry V. Sein, Longjiang Mu, Uwe Fladrich, Dirk Barbi, Paul Gierz, Sergey Danilov, Stephan Juricke, Gerrit Lohmann, and Thomas Jung
Geosci. Model Dev., 15, 6399–6427, https://doi.org/10.5194/gmd-15-6399-2022, https://doi.org/10.5194/gmd-15-6399-2022, 2022
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We developed a new atmosphere–ocean coupled climate model, AWI-CM3. Our model is significantly more computationally efficient than its predecessors AWI-CM1 and AWI-CM2. We show that the model, although cheaper to run, provides results of similar quality when modeling the historic period from 1850 to 2014. We identify the remaining weaknesses to outline future work. Finally we preview an improved simulation where the reduction in computational cost has to be invested in higher model resolution.
Xiaoxu Shi, Martin Werner, Carolin Krug, Chris M. Brierley, Anni Zhao, Endurance Igbinosa, Pascale Braconnot, Esther Brady, Jian Cao, Roberta D'Agostino, Johann Jungclaus, Xingxing Liu, Bette Otto-Bliesner, Dmitry Sidorenko, Robert Tomas, Evgeny M. Volodin, Hu Yang, Qiong Zhang, Weipeng Zheng, and Gerrit Lohmann
Clim. Past, 18, 1047–1070, https://doi.org/10.5194/cp-18-1047-2022, https://doi.org/10.5194/cp-18-1047-2022, 2022
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Since the orbital parameters of the past are different from today, applying the modern calendar to the past climate can lead to an artificial bias in seasonal cycles. With the use of multiple model outputs, we found that such a bias is non-ignorable and should be corrected to ensure an accurate comparison between modeled results and observational records, as well as between simulated past and modern climates, especially for the Last Interglacial.
Ryan A. Green, Laurie Menviel, Katrin J. Meissner, Xavier Crosta, Deepak Chandan, Gerrit Lohmann, W. Richard Peltier, Xiaoxu Shi, and Jiang Zhu
Clim. Past, 18, 845–862, https://doi.org/10.5194/cp-18-845-2022, https://doi.org/10.5194/cp-18-845-2022, 2022
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Climate models are used to predict future climate changes and as such, it is important to assess their performance in simulating past climate changes. We analyze seasonal sea-ice cover over the Southern Ocean simulated from numerical PMIP3, PMIP4 and LOVECLIM simulations during the Last Glacial Maximum (LGM). Comparing these simulations to proxy data, we provide improved estimates of LGM seasonal sea-ice cover. Our estimate of summer sea-ice extent is 20 %–30 % larger than previous estimates.
Sebastian Hinck, Evan J. Gowan, Xu Zhang, and Gerrit Lohmann
The Cryosphere, 16, 941–965, https://doi.org/10.5194/tc-16-941-2022, https://doi.org/10.5194/tc-16-941-2022, 2022
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Proglacial lakes were pervasive along the retreating continental ice margins after the Last Glacial Maximum. Similarly to the marine ice boundary, interactions at the ice-lake interface impact ice sheet dynamics and mass balance. Previous numerical ice sheet modeling studies did not include a dynamical lake boundary. We describe the implementation of an adaptive lake boundary condition in PISM and apply the model to the glacial retreat of the Laurentide Ice Sheet.
Daniel Balting, Simon Michel, Viorica Nagavciuc, Gerhard Helle, Mandy Freund, Gerhard H. Schleser, David Steger, Gerrit Lohmann, and Monica Ionita
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-47, https://doi.org/10.5194/essd-2022-47, 2022
Preprint withdrawn
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Vapor pressure deficit is a key component of vegetation dynamics, soil science, meteorology, and soil science. In this study, we reconstruct the variability of the vapor pressure deficit in the past and examine the changes in future scenarios using climate models. In this way, past, present and future changes of the vapor pressure deficit can be detected locally, regionally, and continentally with higher statistical significance.
Stephan Krätschmer, Michèlle van der Does, Frank Lamy, Gerrit Lohmann, Christoph Völker, and Martin Werner
Clim. Past, 18, 67–87, https://doi.org/10.5194/cp-18-67-2022, https://doi.org/10.5194/cp-18-67-2022, 2022
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We use an atmospheric model coupled to an aerosol model to investigate the global mineral dust cycle with a focus on the Southern Hemisphere for warmer and colder climate states and compare our results to observational data. Our findings suggest that Australia is the predominant source of dust deposited over Antarctica during the last glacial maximum. In addition, we find that the southward transport of dust from all sources to Antarctica happens at lower altitudes in colder climates.
Martin Wegmann, Yvan Orsolini, Antje Weisheimer, Bart van den Hurk, and Gerrit Lohmann
Weather Clim. Dynam., 2, 1245–1261, https://doi.org/10.5194/wcd-2-1245-2021, https://doi.org/10.5194/wcd-2-1245-2021, 2021
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Northern Hemisphere winter weather is influenced by the strength of westerly winds 30 km above the surface, the so-called polar vortex. Eurasian autumn snow cover is thought to modulate the polar vortex. So far, however, the modeled influence of snow on the polar vortex did not fit the observed influence. By analyzing a model experiment for the time span of 110 years, we could show that the causality of this impact is indeed sound and snow cover can weaken the polar vortex.
Kim H. Stadelmaier, Patrick Ludwig, Pascal Bertran, Pierre Antoine, Xiaoxu Shi, Gerrit Lohmann, and Joaquim G. Pinto
Clim. Past, 17, 2559–2576, https://doi.org/10.5194/cp-17-2559-2021, https://doi.org/10.5194/cp-17-2559-2021, 2021
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We use regional climate simulations for the Last Glacial Maximum to reconstruct permafrost and to identify areas of thermal contraction cracking of the ground in western Europe. We find ground cracking, a precondition for the development of permafrost proxies, south of the probable permafrost border, implying that permafrost was not the limiting factor for proxy development. A good agreement with permafrost and climate proxy data is achieved when easterly winds are modelled more frequently.
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.
Nele Lamping, Juliane Müller, Jens Hefter, Gesine Mollenhauer, Christian Haas, Xiaoxu Shi, Maria-Elena Vorrath, Gerrit Lohmann, and Claus-Dieter Hillenbrand
Clim. Past, 17, 2305–2326, https://doi.org/10.5194/cp-17-2305-2021, https://doi.org/10.5194/cp-17-2305-2021, 2021
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We analysed biomarker concentrations on surface sediment samples from the Antarctic continental margin. Highly branched isoprenoids and GDGTs are used for reconstructing recent sea-ice distribution patterns and ocean temperatures respectively. We compared our biomarker-based results with data obtained from satellite observations and estimated from a numerical model and find reasonable agreements. Further, we address caveats and provide recommendations for future investigations.
Saeid Bagheri Dastgerdi, Melanie Behrens, Jean-Louis Bonne, Maria Hörhold, Gerrit Lohmann, Elisabeth Schlosser, and Martin Werner
The Cryosphere, 15, 4745–4767, https://doi.org/10.5194/tc-15-4745-2021, https://doi.org/10.5194/tc-15-4745-2021, 2021
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In this study, for the first time, water vapour isotope measurements in Antarctica for all seasons of a year are performed. Local temperature is identified as the main driver of δ18O and δD variability. A similar slope of the temperature–δ18O relationship in vapour and surface snow points to the water vapour isotope content as a potential key driver. This dataset can be used as a new dataset to evaluate the capability of isotope-enhanced climate models.
Ellen Berntell, Qiong Zhang, Qiang Li, Alan M. Haywood, Julia C. Tindall, Stephen J. Hunter, Zhongshi Zhang, Xiangyu Li, Chuncheng Guo, Kerim H. Nisancioglu, Christian Stepanek, Gerrit Lohmann, Linda E. Sohl, Mark A. Chandler, Ning Tan, Camille Contoux, Gilles Ramstein, Michiel L. J. Baatsen, Anna S. von der Heydt, Deepak Chandan, William Richard Peltier, Ayako Abe-Ouchi, Wing-Le Chan, Youichi Kamae, Charles J. R. Williams, Daniel J. Lunt, Ran Feng, Bette L. Otto-Bliesner, and Esther C. Brady
Clim. Past, 17, 1777–1794, https://doi.org/10.5194/cp-17-1777-2021, https://doi.org/10.5194/cp-17-1777-2021, 2021
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The mid-Pliocene Warm Period (~ 3.2 Ma) is often considered an analogue for near-future climate projections, and model results from the PlioMIP2 ensemble show an increase of rainfall over West Africa and the Sahara region compared to pre-industrial conditions. Though previous studies of future projections show a west–east drying–wetting contrast over the Sahel, these results indicate a uniform rainfall increase over the Sahel in warm climates characterized by increased greenhouse gas forcing.
Xiaoxu Shi, Dirk Notz, Jiping Liu, Hu Yang, and Gerrit Lohmann
Geosci. Model Dev., 14, 4891–4908, https://doi.org/10.5194/gmd-14-4891-2021, https://doi.org/10.5194/gmd-14-4891-2021, 2021
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The ice–ocean heat flux is one of the key elements controlling sea ice changes. It motivates our study, which aims to examine the responses of modeled climate to three ice–ocean heat flux parameterizations, including two old approaches that assume one-way heat transport and a new one describing a double-diffusive ice–ocean heat exchange. The results show pronounced differences in the modeled sea ice, ocean, and atmosphere states for the latter as compared to the former two parameterizations.
Masa Kageyama, Sandy P. Harrison, Marie-L. Kapsch, Marcus Lofverstrom, Juan M. Lora, Uwe Mikolajewicz, Sam Sherriff-Tadano, Tristan Vadsaria, Ayako Abe-Ouchi, Nathaelle Bouttes, Deepak Chandan, Lauren J. Gregoire, Ruza F. Ivanovic, Kenji Izumi, Allegra N. LeGrande, Fanny Lhardy, Gerrit Lohmann, Polina A. Morozova, Rumi Ohgaito, André Paul, W. Richard Peltier, Christopher J. Poulsen, Aurélien Quiquet, Didier M. Roche, Xiaoxu Shi, Jessica E. Tierney, Paul J. Valdes, Evgeny Volodin, and Jiang Zhu
Clim. Past, 17, 1065–1089, https://doi.org/10.5194/cp-17-1065-2021, https://doi.org/10.5194/cp-17-1065-2021, 2021
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The Last Glacial Maximum (LGM; ~21 000 years ago) is a major focus for evaluating how well climate models simulate climate changes as large as those expected in the future. Here, we compare the latest climate model (CMIP6-PMIP4) to the previous one (CMIP5-PMIP3) and to reconstructions. Large-scale climate features (e.g. land–sea contrast, polar amplification) are well captured by all models, while regional changes (e.g. winter extratropical cooling, precipitations) are still poorly represented.
Uta Krebs-Kanzow, Paul Gierz, Christian B. Rodehacke, Shan Xu, Hu Yang, and Gerrit Lohmann
The Cryosphere, 15, 2295–2313, https://doi.org/10.5194/tc-15-2295-2021, https://doi.org/10.5194/tc-15-2295-2021, 2021
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The surface mass balance scheme dEBM (diurnal Energy Balance Model) provides a novel, computationally inexpensive interface between the atmosphere and land ice for Earth system modeling. The dEBM is particularly suitable for Earth system modeling on multi-millennial timescales as it accounts for changes in the Earth's orbit and atmospheric greenhouse gas concentration.
Daniel F. Balting, Monica Ionita, Martin Wegmann, Gerhard Helle, Gerhard H. Schleser, Norel Rimbu, Mandy B. Freund, Ingo Heinrich, Diana Caldarescu, and Gerrit Lohmann
Clim. Past, 17, 1005–1023, https://doi.org/10.5194/cp-17-1005-2021, https://doi.org/10.5194/cp-17-1005-2021, 2021
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To extend climate information back in time, we investigate the climate sensitivity of a δ18O network from tree rings, consisting of 26 European sites and covering the last 400 years. Our results suggest that the δ18O variability is associated with large-scale anomaly patterns that resemble those observed for the El Niño–Southern Oscillation. We conclude that the investigation of large-scale climate signals far beyond instrumental records can be done with a δ18O network derived from tree rings.
James Keeble, Birgit Hassler, Antara Banerjee, Ramiro Checa-Garcia, Gabriel Chiodo, Sean Davis, Veronika Eyring, Paul T. Griffiths, Olaf Morgenstern, Peer Nowack, Guang Zeng, Jiankai Zhang, Greg Bodeker, Susannah Burrows, Philip Cameron-Smith, David Cugnet, Christopher Danek, Makoto Deushi, Larry W. Horowitz, Anne Kubin, Lijuan Li, Gerrit Lohmann, Martine Michou, Michael J. Mills, Pierre Nabat, Dirk Olivié, Sungsu Park, Øyvind Seland, Jens Stoll, Karl-Hermann Wieners, and Tongwen Wu
Atmos. Chem. Phys., 21, 5015–5061, https://doi.org/10.5194/acp-21-5015-2021, https://doi.org/10.5194/acp-21-5015-2021, 2021
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Stratospheric ozone and water vapour are key components of the Earth system; changes to both have important impacts on global and regional climate. We evaluate changes to these species from 1850 to 2100 in the new generation of CMIP6 models. There is good agreement between the multi-model mean and observations, although there is substantial variation between the individual models. The future evolution of both ozone and water vapour is strongly dependent on the assumed future emissions scenario.
Zhongshi Zhang, Xiangyu Li, Chuncheng Guo, Odd Helge Otterå, Kerim H. Nisancioglu, Ning Tan, Camille Contoux, Gilles Ramstein, Ran Feng, Bette L. Otto-Bliesner, Esther Brady, Deepak Chandan, W. Richard Peltier, Michiel L. J. Baatsen, Anna S. von der Heydt, Julia E. Weiffenbach, Christian Stepanek, Gerrit Lohmann, Qiong Zhang, Qiang Li, Mark A. Chandler, Linda E. Sohl, Alan M. Haywood, Stephen J. Hunter, Julia C. Tindall, Charles Williams, Daniel J. Lunt, Wing-Le Chan, and Ayako Abe-Ouchi
Clim. Past, 17, 529–543, https://doi.org/10.5194/cp-17-529-2021, https://doi.org/10.5194/cp-17-529-2021, 2021
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The Atlantic Meridional Overturning Circulation (AMOC) is an important topic in the Pliocene Model Intercomparison Project. Previous studies have suggested a much stronger AMOC during the Pliocene than today. However, our current multi-model intercomparison shows large model spreads and model–data discrepancies, which can not support the previous hypothesis. Our study shows good consistency with future projections of the AMOC.
Daniel J. Lunt, Fran Bragg, Wing-Le Chan, David K. Hutchinson, Jean-Baptiste Ladant, Polina Morozova, Igor Niezgodzki, Sebastian Steinig, Zhongshi Zhang, Jiang Zhu, Ayako Abe-Ouchi, Eleni Anagnostou, Agatha M. de Boer, Helen K. Coxall, Yannick Donnadieu, Gavin Foster, Gordon N. Inglis, Gregor Knorr, Petra M. Langebroek, Caroline H. Lear, Gerrit Lohmann, Christopher J. Poulsen, Pierre Sepulchre, Jessica E. Tierney, Paul J. Valdes, Evgeny M. Volodin, Tom Dunkley Jones, Christopher J. Hollis, Matthew Huber, and Bette L. Otto-Bliesner
Clim. Past, 17, 203–227, https://doi.org/10.5194/cp-17-203-2021, https://doi.org/10.5194/cp-17-203-2021, 2021
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This paper presents the first modelling results from the Deep-Time Model Intercomparison Project (DeepMIP), in which we focus on the early Eocene climatic optimum (EECO, 50 million years ago). We show that, in contrast to previous work, at least three models (CESM, GFDL, and NorESM) produce climate states that are consistent with proxy indicators of global mean temperature and polar amplification, and they achieve this at a CO2 concentration that is consistent with the CO2 proxy record.
Masa Kageyama, Louise C. Sime, Marie Sicard, Maria-Vittoria Guarino, Anne de Vernal, Ruediger Stein, David Schroeder, Irene Malmierca-Vallet, Ayako Abe-Ouchi, Cecilia Bitz, Pascale Braconnot, Esther C. Brady, Jian Cao, Matthew A. Chamberlain, Danny Feltham, Chuncheng Guo, Allegra N. LeGrande, Gerrit Lohmann, Katrin J. Meissner, Laurie Menviel, Polina Morozova, Kerim H. Nisancioglu, Bette L. Otto-Bliesner, Ryouta O'ishi, Silvana Ramos Buarque, David Salas y Melia, Sam Sherriff-Tadano, Julienne Stroeve, Xiaoxu Shi, Bo Sun, Robert A. Tomas, Evgeny Volodin, Nicholas K. H. Yeung, Qiong Zhang, Zhongshi Zhang, Weipeng Zheng, and Tilo Ziehn
Clim. Past, 17, 37–62, https://doi.org/10.5194/cp-17-37-2021, https://doi.org/10.5194/cp-17-37-2021, 2021
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The Last interglacial (ca. 127 000 years ago) is a period with increased summer insolation at high northern latitudes, resulting in a strong reduction in Arctic sea ice. The latest PMIP4-CMIP6 models all simulate this decrease, consistent with reconstructions. However, neither the models nor the reconstructions agree on the possibility of a seasonally ice-free Arctic. Work to clarify the reasons for this model divergence and the conflicting interpretations of the records will thus be needed.
Bette L. Otto-Bliesner, Esther C. Brady, Anni Zhao, Chris M. Brierley, Yarrow Axford, Emilie Capron, Aline Govin, Jeremy S. Hoffman, Elizabeth Isaacs, Masa Kageyama, Paolo Scussolini, Polychronis C. Tzedakis, Charles J. R. Williams, Eric Wolff, Ayako Abe-Ouchi, Pascale Braconnot, Silvana Ramos Buarque, Jian Cao, Anne de Vernal, Maria Vittoria Guarino, Chuncheng Guo, Allegra N. LeGrande, Gerrit Lohmann, Katrin J. Meissner, Laurie Menviel, Polina A. Morozova, Kerim H. Nisancioglu, Ryouta O'ishi, David Salas y Mélia, Xiaoxu Shi, Marie Sicard, Louise Sime, Christian Stepanek, Robert Tomas, Evgeny Volodin, Nicholas K. H. Yeung, Qiong Zhang, Zhongshi Zhang, and Weipeng Zheng
Clim. Past, 17, 63–94, https://doi.org/10.5194/cp-17-63-2021, https://doi.org/10.5194/cp-17-63-2021, 2021
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The CMIP6–PMIP4 Tier 1 lig127k experiment was designed to address the climate responses to strong orbital forcing. We present a multi-model ensemble of 17 climate models, most of which have also completed the CMIP6 DECK experiments and are thus important for assessing future projections. The lig127ksimulations show strong summer warming over the NH continents. More than half of the models simulate a retreat of the Arctic minimum summer ice edge similar to the average for 2000–2018.
Gerrit Lohmann
Earth Syst. Dynam., 11, 1195–1208, https://doi.org/10.5194/esd-11-1195-2020, https://doi.org/10.5194/esd-11-1195-2020, 2020
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With the development of computer capacities, simpler models like energy balance models have not disappeared, and a stronger emphasis has been given to the concept of a hierarchy of models. The global temperature is calculated by the radiation budget through the incoming energy from the Sun and the outgoing energy from the Earth. The argument that the temperature can be calculated by a simple radiation budget is revisited, and it is found that the effective heat capacity matters.
Maria-Elena Vorrath, Juliane Müller, Lorena Rebolledo, Paola Cárdenas, Xiaoxu Shi, Oliver Esper, Thomas Opel, Walter Geibert, Práxedes Muñoz, Christian Haas, Gerhard Kuhn, Carina B. Lange, Gerrit Lohmann, and Gesine Mollenhauer
Clim. Past, 16, 2459–2483, https://doi.org/10.5194/cp-16-2459-2020, https://doi.org/10.5194/cp-16-2459-2020, 2020
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We tested the applicability of the organic biomarker IPSO25 for sea ice reconstructions in the industrial era at the western Antarctic Peninsula. We successfully evaluated our data with satellite sea ice observations. The comparison with marine and ice core records revealed that sea ice interpretations must consider climatic and sea ice dynamics. Sea ice biomarker production is mainly influenced by the Southern Annular Mode, while the El Niño–Southern Oscillation seems to have a minor impact.
Wesley de Nooijer, Qiong Zhang, Qiang Li, Qiang Zhang, Xiangyu Li, Zhongshi Zhang, Chuncheng Guo, Kerim H. Nisancioglu, Alan M. Haywood, Julia C. Tindall, Stephen J. Hunter, Harry J. Dowsett, Christian Stepanek, Gerrit Lohmann, Bette L. Otto-Bliesner, Ran Feng, Linda E. Sohl, Mark A. Chandler, Ning Tan, Camille Contoux, Gilles Ramstein, Michiel L. J. Baatsen, Anna S. von der Heydt, Deepak Chandan, W. Richard Peltier, Ayako Abe-Ouchi, Wing-Le Chan, Youichi Kamae, and Chris M. Brierley
Clim. Past, 16, 2325–2341, https://doi.org/10.5194/cp-16-2325-2020, https://doi.org/10.5194/cp-16-2325-2020, 2020
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The simulations for the past climate can inform us about the performance of climate models in different climate scenarios. Here, we analyse Arctic warming in an ensemble of 16 simulations of the mid-Pliocene Warm Period (mPWP), when the CO2 level was comparable to today. The results highlight the importance of slow feedbacks in the model simulations and imply that we must be careful when using simulations of the mPWP as an analogue for future climate change.
Christian Stepanek, Eric Samakinwa, Gregor Knorr, and Gerrit Lohmann
Clim. Past, 16, 2275–2323, https://doi.org/10.5194/cp-16-2275-2020, https://doi.org/10.5194/cp-16-2275-2020, 2020
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Future climate is expected to be warmer than today. We study climate based on simulations of the mid-Pliocene (about 3 million years ago), which was a time of elevated temperatures, and discuss implications for the future. Our results are provided towards a comparison to both proxy evidence and output of other climate models. We simulate a mid-Pliocene climate that is both warmer and wetter than today. Some climate characteristics can be more directly transferred to the near future than others.
Florian Fuhrmann, Benedikt Diensberg, Xun Gong, Gerrit Lohmann, and Frank Sirocko
Clim. Past, 16, 2221–2238, https://doi.org/10.5194/cp-16-2221-2020, https://doi.org/10.5194/cp-16-2221-2020, 2020
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Proxy data of sediment cores, speleothem, pollen and isotope data were used to reconstruct past aridity of eight regions of the world over the last 60 000 years. These regions show humid conditions during the early MIS3 (60 to 45 ka). Also the early Holocene (14 to 6 ka) was humid throughout the regions. In contrast, MIS2 and the LGM were arid in Northern Nemisphere records. On- and offsets of aridity/humidity differ between the regions. All this is in good agreement with recent model results.
Xavier Fettweis, Stefan Hofer, Uta Krebs-Kanzow, Charles Amory, Teruo Aoki, Constantijn J. Berends, Andreas Born, Jason E. Box, Alison Delhasse, Koji Fujita, Paul Gierz, Heiko Goelzer, Edward Hanna, Akihiro Hashimoto, Philippe Huybrechts, Marie-Luise Kapsch, Michalea D. King, Christoph Kittel, Charlotte Lang, Peter L. Langen, Jan T. M. Lenaerts, Glen E. Liston, Gerrit Lohmann, Sebastian H. Mernild, Uwe Mikolajewicz, Kameswarrao Modali, Ruth H. Mottram, Masashi Niwano, Brice Noël, Jonathan C. Ryan, Amy Smith, Jan Streffing, Marco Tedesco, Willem Jan van de Berg, Michiel van den Broeke, Roderik S. W. van de Wal, Leo van Kampenhout, David Wilton, Bert Wouters, Florian Ziemen, and Tobias Zolles
The Cryosphere, 14, 3935–3958, https://doi.org/10.5194/tc-14-3935-2020, https://doi.org/10.5194/tc-14-3935-2020, 2020
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We evaluated simulated Greenland Ice Sheet surface mass balance from 5 kinds of models. While the most complex (but expensive to compute) models remain the best, the faster/simpler models also compare reliably with observations and have biases of the same order as the regional models. Discrepancies in the trend over 2000–2012, however, suggest that large uncertainties remain in the modelled future SMB changes as they are highly impacted by the meltwater runoff biases over the current climate.
Alan M. Haywood, Julia C. Tindall, Harry J. Dowsett, Aisling M. Dolan, Kevin M. Foley, Stephen J. Hunter, Daniel J. Hill, Wing-Le Chan, Ayako Abe-Ouchi, Christian Stepanek, Gerrit Lohmann, Deepak Chandan, W. Richard Peltier, Ning Tan, Camille Contoux, Gilles Ramstein, Xiangyu Li, Zhongshi Zhang, Chuncheng Guo, Kerim H. Nisancioglu, Qiong Zhang, Qiang Li, Youichi Kamae, Mark A. Chandler, Linda E. Sohl, Bette L. Otto-Bliesner, Ran Feng, Esther C. Brady, Anna S. von der Heydt, Michiel L. J. Baatsen, and Daniel J. Lunt
Clim. Past, 16, 2095–2123, https://doi.org/10.5194/cp-16-2095-2020, https://doi.org/10.5194/cp-16-2095-2020, 2020
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The large-scale features of middle Pliocene climate from the 16 models of PlioMIP Phase 2 are presented. The PlioMIP2 ensemble average was ~ 3.2 °C warmer and experienced ~ 7 % more precipitation than the pre-industrial era, although there are large regional variations. PlioMIP2 broadly agrees with a new proxy dataset of Pliocene sea surface temperatures. Combining PlioMIP2 and proxy data suggests that a doubling of atmospheric CO2 would increase globally averaged temperature by 2.6–4.8 °C.
Chris M. Brierley, Anni Zhao, Sandy P. Harrison, Pascale Braconnot, Charles J. R. Williams, David J. R. Thornalley, Xiaoxu Shi, Jean-Yves Peterschmitt, Rumi Ohgaito, Darrell S. Kaufman, Masa Kageyama, Julia C. Hargreaves, Michael P. Erb, Julien Emile-Geay, Roberta D'Agostino, Deepak Chandan, Matthieu Carré, Partrick J. Bartlein, Weipeng Zheng, Zhongshi Zhang, Qiong Zhang, Hu Yang, Evgeny M. Volodin, Robert A. Tomas, Cody Routson, W. Richard Peltier, Bette Otto-Bliesner, Polina A. Morozova, Nicholas P. McKay, Gerrit Lohmann, Allegra N. Legrande, Chuncheng Guo, Jian Cao, Esther Brady, James D. Annan, and Ayako Abe-Ouchi
Clim. Past, 16, 1847–1872, https://doi.org/10.5194/cp-16-1847-2020, https://doi.org/10.5194/cp-16-1847-2020, 2020
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This paper provides an initial exploration and comparison to climate reconstructions of the new climate model simulations of the mid-Holocene (6000 years ago). These use state-of-the-art models developed for CMIP6 and apply the same experimental set-up. The models capture several key aspects of the climate, but some persistent issues remain.
Josephine R. Brown, Chris M. Brierley, Soon-Il An, Maria-Vittoria Guarino, Samantha Stevenson, Charles J. R. Williams, Qiong Zhang, Anni Zhao, Ayako Abe-Ouchi, Pascale Braconnot, Esther C. Brady, Deepak Chandan, Roberta D'Agostino, Chuncheng Guo, Allegra N. LeGrande, Gerrit Lohmann, Polina A. Morozova, Rumi Ohgaito, Ryouta O'ishi, Bette L. Otto-Bliesner, W. Richard Peltier, Xiaoxu Shi, Louise Sime, Evgeny M. Volodin, Zhongshi Zhang, and Weipeng Zheng
Clim. Past, 16, 1777–1805, https://doi.org/10.5194/cp-16-1777-2020, https://doi.org/10.5194/cp-16-1777-2020, 2020
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El Niño–Southern Oscillation (ENSO) is the largest source of year-to-year variability in the current climate, but the response of ENSO to past or future changes in climate is uncertain. This study compares the strength and spatial pattern of ENSO in a set of climate model simulations in order to explore how ENSO changes in different climates, including past cold glacial climates and past climates with different seasonal cycles, as well as gradual and abrupt future warming cases.
Jesper Sjolte, Florian Adolphi, Bo M. Vinther, Raimund Muscheler, Christophe Sturm, Martin Werner, and Gerrit Lohmann
Clim. Past, 16, 1737–1758, https://doi.org/10.5194/cp-16-1737-2020, https://doi.org/10.5194/cp-16-1737-2020, 2020
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In this study we investigate seasonal climate reconstructions produced by matching climate model output to ice core and tree-ring data, and we evaluate the model–data reconstructions against meteorological observations. The reconstructions capture the main patterns of variability in sea level pressure and temperature in summer and winter. The performance of the reconstructions depends on seasonal climate variability itself, and definitions of seasons can be optimized to capture this variability.
Martin Renoult, James Douglas Annan, Julia Catherine Hargreaves, Navjit Sagoo, Clare Flynn, Marie-Luise Kapsch, Qiang Li, Gerrit Lohmann, Uwe Mikolajewicz, Rumi Ohgaito, Xiaoxu Shi, Qiong Zhang, and Thorsten Mauritsen
Clim. Past, 16, 1715–1735, https://doi.org/10.5194/cp-16-1715-2020, https://doi.org/10.5194/cp-16-1715-2020, 2020
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Interest in past climates as sources of information for the climate system has grown in recent years. In particular, studies of the warm mid-Pliocene and cold Last Glacial Maximum showed relationships between the tropical surface temperature of the Earth and its sensitivity to an abrupt doubling of atmospheric CO2. In this study, we develop a new and promising statistical method and obtain similar results as previously observed, wherein the sensitivity does not seem to exceed extreme values.
Erin L. McClymont, Heather L. Ford, Sze Ling Ho, Julia C. Tindall, Alan M. Haywood, Montserrat Alonso-Garcia, Ian Bailey, Melissa A. Berke, Kate Littler, Molly O. Patterson, Benjamin Petrick, Francien Peterse, A. Christina Ravelo, Bjørg Risebrobakken, Stijn De Schepper, George E. A. Swann, Kaustubh Thirumalai, Jessica E. Tierney, Carolien van der Weijst, Sarah White, Ayako Abe-Ouchi, Michiel L. J. Baatsen, Esther C. Brady, Wing-Le Chan, Deepak Chandan, Ran Feng, Chuncheng Guo, Anna S. von der Heydt, Stephen Hunter, Xiangyi Li, Gerrit Lohmann, Kerim H. Nisancioglu, Bette L. Otto-Bliesner, W. Richard Peltier, Christian Stepanek, and Zhongshi Zhang
Clim. Past, 16, 1599–1615, https://doi.org/10.5194/cp-16-1599-2020, https://doi.org/10.5194/cp-16-1599-2020, 2020
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We examine the sea-surface temperature response to an interval of climate ~ 3.2 million years ago, when CO2 concentrations were similar to today and the near future. Our geological data and climate models show that global mean sea-surface temperatures were 2.3 to 3.2 ºC warmer than pre-industrial climate, that the mid-latitudes and high latitudes warmed more than the tropics, and that the warming was particularly enhanced in the North Atlantic Ocean.
Eric Samakinwa, Christian Stepanek, and Gerrit Lohmann
Clim. Past, 16, 1643–1665, https://doi.org/10.5194/cp-16-1643-2020, https://doi.org/10.5194/cp-16-1643-2020, 2020
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Boundary conditions, forcing, and methodology for the two phases of PlioMIP differ considerably. We compare results from PlioMIP1 and PlioMIP2 simulations. We also carry out sensitivity experiments to infer the relative contribution of different boundary conditions to mid-Pliocene warmth. Our results show dominant effects of mid-Pliocene geography on the climate state and also that prescribing orbital forcing for different time slices within the mid-Pliocene could lead to pronounced variations.
Paul Gierz, Lars Ackermann, Christian B. Rodehacke, Uta Krebs-Kanzow, Christian Stepanek, Dirk Barbi, and Gerrit Lohmann
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-159, https://doi.org/10.5194/gmd-2020-159, 2020
Publication in GMD not foreseen
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In this study, we describe the SCOPE coupler, which is used connect the ECHAM6/JSBACH/FESOM1.4 climate model to the PISM 1.1.4 ice sheet model. This system is used to simulate IPCC scenarios projected for the future, and several warm periods in the past; the mid Holocene and the Last Interglacial. Our new model allows us to simulate the ice sheet’s response to changes in the climatic conditions, providing a new avenue of investigation over the previous models, which keep the cryosphere fixed.
Martin Wegmann, Marco Rohrer, María Santolaria-Otín, and Gerrit Lohmann
Earth Syst. Dynam., 11, 509–524, https://doi.org/10.5194/esd-11-509-2020, https://doi.org/10.5194/esd-11-509-2020, 2020
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Predicting the climate of the upcoming season is of big societal benefit, but finding out which component of the climate system can act as a predictor is difficult. In this study, we focus on Eurasian snow cover as such a component and show that knowing the snow cover in November is very helpful in predicting the state of winter over Europe. However, this mechanism was questioned in the past. Using snow data that go back 150 years into the past, we are now very confident in this relationship.
Jianjun Zou, Xuefa Shi, Aimei Zhu, Selvaraj Kandasamy, Xun Gong, Lester Lembke-Jene, Min-Te Chen, Yonghua Wu, Shulan Ge, Yanguang Liu, Xinru Xue, Gerrit Lohmann, and Ralf Tiedemann
Clim. Past, 16, 387–407, https://doi.org/10.5194/cp-16-387-2020, https://doi.org/10.5194/cp-16-387-2020, 2020
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Large-scale reorganization of global ocean circulation has been documented in a variety of marine archives, including the enhanced North Pacific Intermediate Water NPIW. Our data support both the model- and data-based ideas that the enhanced NPIW mainly developed during cold spells, while an expansion of oxygen-poor zones occurred at warming intervals (Bölling-Alleröd).
Xingxing Liu, Youbin Sun, Jef Vandenberghe, Peng Cheng, Xu Zhang, Evan J. Gowan, Gerrit Lohmann, and Zhisheng An
Clim. Past, 16, 315–324, https://doi.org/10.5194/cp-16-315-2020, https://doi.org/10.5194/cp-16-315-2020, 2020
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The East Asian summer monsoon and winter monsoon are anticorrelated on a centennial timescale during 16–1 ka. The centennial monsoon variability is connected to changes of both solar activity and North Atlantic cooling events during the Early Holocene. Then, North Atlantic cooling became the major forcing of events during the Late Holocene. This work presents the great challenge and potential to understand the response of the monsoon system to global climate changes in the past and the future.
Alexandre Cauquoin, Martin Werner, and Gerrit Lohmann
Clim. Past, 15, 1913–1937, https://doi.org/10.5194/cp-15-1913-2019, https://doi.org/10.5194/cp-15-1913-2019, 2019
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We present here the first model results of a newly developed isotope-enhanced version of the Earth system model MPI-ESM. Our model setup has a finer spatial resolution compared to other isotope-enabled fully coupled models. We evaluate the model for preindustrial and mid-Holocene climate conditions. Our analyses show a good to very good agreement with various isotopic data. The spatial and temporal links between isotopes and climate variables under warm climatic conditions are also analyzed.
Lennert B. Stap, Peter Köhler, and Gerrit Lohmann
Earth Syst. Dynam., 10, 333–345, https://doi.org/10.5194/esd-10-333-2019, https://doi.org/10.5194/esd-10-333-2019, 2019
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Processes causing the same global-average radiative forcing might lead to different global temperature changes. We expand the theoretical framework by which we calculate paleoclimate sensitivity with an efficacy factor. Applying the revised approach to radiative forcing caused by CO2 and land ice albedo perturbations, inferred from data of the past 800 000 years, gives a new paleo-based estimate of climate sensitivity.
Monica Ionita, Klaus Grosfeld, Patrick Scholz, Renate Treffeisen, and Gerrit Lohmann
Earth Syst. Dynam., 10, 189–203, https://doi.org/10.5194/esd-10-189-2019, https://doi.org/10.5194/esd-10-189-2019, 2019
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Based on a simple statistical model we show that the September sea ice extent has a high predictive skill, up to 4 months ahead, based on previous months' oceanic and atmospheric conditions. Our statistical model skillfully captures the interannual variability of the September sea ice extent and could provide a valuable tool for identifying relevant regions and oceanic and atmospheric parameters that are important for the sea ice development in the Arctic.
Evan J. Gowan, Lu Niu, Gregor Knorr, and Gerrit Lohmann
Earth Syst. Sci. Data, 11, 375–391, https://doi.org/10.5194/essd-11-375-2019, https://doi.org/10.5194/essd-11-375-2019, 2019
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The speed of ice sheet flow is largely controlled by the strength of the ice–bed interface. We present three datasets on the geological properties of regions in North America, Greenland and Iceland that were covered by Quaternary ice sheets. These include the grain size of glacial sediments, the continuity of sediment cover and bedrock geology. Simple ice modelling experiments show that altering the basal strength of the ice sheet on the basis of these datasets impacts ice thickness.
Uta Krebs-Kanzow, Paul Gierz, and Gerrit Lohmann
The Cryosphere, 12, 3923–3930, https://doi.org/10.5194/tc-12-3923-2018, https://doi.org/10.5194/tc-12-3923-2018, 2018
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We present a new surface melt scheme for land ice. Derived from the energy balance of melting surfaces, the scheme may be particularly suitable for long ice-sheet simulations of past and future climates. It is computationally inexpensive and can be adapted to changes in the Earth's orbit and atmospheric composition. The scheme yields a better spatial representation of surface melt than common empirical schemes when applied to the Greenland Ice Sheet under present-day climate conditions.
Gerrit Lohmann
Earth Syst. Dynam., 9, 1279–1281, https://doi.org/10.5194/esd-9-1279-2018, https://doi.org/10.5194/esd-9-1279-2018, 2018
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Long-term sea surface temperature trends and variability are underestimated in models compared to paleoclimate data. The idea is presented that the trends and variability are related, which is elaborated in a conceptual model framework. The temperature spectrum can be used to estimate the timescale-dependent climate sensitivity.
Axel Wagner, Gerrit Lohmann, and Matthias Prange
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2018-172, https://doi.org/10.5194/gmd-2018-172, 2018
Publication in GMD not foreseen
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This study demonstrates the dependence of simulated surface air temperatures on variations in grid resolution and resolution-dependent orography in simulations of the Mid-Holocene. A set of Mid-Holocene sensitivity experiments is carried out. The simulated Mid-Holocene temperature differences (low versus high resolution) reveal a response that regionally exceeds the Mid-Holocene to preindustrial modelled temperature anomalies, and show partly reversed signs across the same geographical regions.
Jesper Sjolte, Christophe Sturm, Florian Adolphi, Bo M. Vinther, Martin Werner, Gerrit Lohmann, and Raimund Muscheler
Clim. Past, 14, 1179–1194, https://doi.org/10.5194/cp-14-1179-2018, https://doi.org/10.5194/cp-14-1179-2018, 2018
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Tropical volcanic eruptions and variations in solar activity have been suggested to influence the strength of westerly winds across the North Atlantic. We use Greenland ice core records together with a climate model simulation, and find stronger westerly winds for five winters following tropical volcanic eruptions. We see a delayed response to solar activity of 5 years, and the response to solar minima corresponds well to the cooling pattern during the period known as the Little Ice Age.
Sebastian G. Mutz, Todd A. Ehlers, Martin Werner, Gerrit Lohmann, Christian Stepanek, and Jingmin Li
Earth Surf. Dynam., 6, 271–301, https://doi.org/10.5194/esurf-6-271-2018, https://doi.org/10.5194/esurf-6-271-2018, 2018
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We use a climate model and statistics to provide an overview of regional climates from different times in the late Cenozoic. We focus on tectonically active mountain ranges in particular. Our results highlight significant changes in climates throughout the late Cenozoic, which should be taken into consideration when interpreting erosion rates. We also document the differences between model- and proxy-based estimates for late Cenozoic climate change in South America and Tibet.
Akil Hossain, Xu Zhang, and Gerrit Lohmann
Clim. Past Discuss., https://doi.org/10.5194/cp-2018-9, https://doi.org/10.5194/cp-2018-9, 2018
Revised manuscript not accepted
Norel Rimbu, Monica Ionita, Markus Czymzik, Achim Brauer, and Gerrit Lohmann
Clim. Past Discuss., https://doi.org/10.5194/cp-2017-137, https://doi.org/10.5194/cp-2017-137, 2017
Manuscript not accepted for further review
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Multi-decadal to millennial flood frequency variations in the Mid- to Late Holocene in a flood layer record from Lake Ammersee is strongly related to the occurrence of extreme precipitation and temperatures in the northeastern Europe.
Bette L. Otto-Bliesner, Pascale Braconnot, Sandy P. Harrison, Daniel J. Lunt, Ayako Abe-Ouchi, Samuel Albani, Patrick J. Bartlein, Emilie Capron, Anders E. Carlson, Andrea Dutton, Hubertus Fischer, Heiko Goelzer, Aline Govin, Alan Haywood, Fortunat Joos, Allegra N. LeGrande, William H. Lipscomb, Gerrit Lohmann, Natalie Mahowald, Christoph Nehrbass-Ahles, Francesco S. R. Pausata, Jean-Yves Peterschmitt, Steven J. Phipps, Hans Renssen, and Qiong Zhang
Geosci. Model Dev., 10, 3979–4003, https://doi.org/10.5194/gmd-10-3979-2017, https://doi.org/10.5194/gmd-10-3979-2017, 2017
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The PMIP4 and CMIP6 mid-Holocene and Last Interglacial simulations provide an opportunity to examine the impact of two different changes in insolation forcing on climate at times when other forcings were relatively similar to present. This will allow exploration of the role of feedbacks relevant to future projections. Evaluating these simulations using paleoenvironmental data will provide direct out-of-sample tests of the reliability of state-of-the-art models to simulate climate changes.
Masa Kageyama, Samuel Albani, Pascale Braconnot, Sandy P. Harrison, Peter O. Hopcroft, Ruza F. Ivanovic, Fabrice Lambert, Olivier Marti, W. Richard Peltier, Jean-Yves Peterschmitt, Didier M. Roche, Lev Tarasov, Xu Zhang, Esther C. Brady, Alan M. Haywood, Allegra N. LeGrande, Daniel J. Lunt, Natalie M. Mahowald, Uwe Mikolajewicz, Kerim H. Nisancioglu, Bette L. Otto-Bliesner, Hans Renssen, Robert A. Tomas, Qiong Zhang, Ayako Abe-Ouchi, Patrick J. Bartlein, Jian Cao, Qiang Li, Gerrit Lohmann, Rumi Ohgaito, Xiaoxu Shi, Evgeny Volodin, Kohei Yoshida, Xiao Zhang, and Weipeng Zheng
Geosci. Model Dev., 10, 4035–4055, https://doi.org/10.5194/gmd-10-4035-2017, https://doi.org/10.5194/gmd-10-4035-2017, 2017
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The Last Glacial Maximum (LGM, 21000 years ago) is an interval when global ice volume was at a maximum, eustatic sea level close to a minimum, greenhouse gas concentrations were lower, atmospheric aerosol loadings were higher than today, and vegetation and land-surface characteristics were different from today. This paper describes the implementation of the LGM numerical experiment for the PMIP4-CMIP6 modelling intercomparison projects and the associated sensitivity experiments.
Lu Niu, Gerrit Lohmann, Sebastian Hinck, and Evan J. Gowan
Clim. Past Discuss., https://doi.org/10.5194/cp-2017-105, https://doi.org/10.5194/cp-2017-105, 2017
Revised manuscript not accepted
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The sensitivity of Northern Hemisphere ice sheets to atmospheric forcing during the last glacial-interglacial cycle is investigated by using output from PMIP3 models. The results show large diversity in simulated ice sheets between different models. We found that summer surface air temperature pattern resembles the ice sheet extent pattern at the LGM. This study implies careful constrains on climate output is essential for simulating reliable glacial-interglacial Northern Hemisphere ice sheets.
Vera D. Meyer, Jens Hefter, Gerrit Lohmann, Lars Max, Ralf Tiedemann, and Gesine Mollenhauer
Clim. Past, 13, 359–377, https://doi.org/10.5194/cp-13-359-2017, https://doi.org/10.5194/cp-13-359-2017, 2017
Bette L. Otto-Bliesner, Pascale Braconnot, Sandy P. Harrison, Daniel J. Lunt, Ayako Abe-Ouchi, Samuel Albani, Patrick J. Bartlein, Emilie Capron, Anders E. Carlson, Andrea Dutton, Hubertus Fischer, Heiko Goelzer, Aline Govin, Alan Haywood, Fortunat Joos, Allegra N. Legrande, William H. Lipscomb, Gerrit Lohmann, Natalie Mahowald, Christoph Nehrbass-Ahles, Jean-Yves Peterschmidt, Francesco S.-R. Pausata, Steven Phipps, and Hans Renssen
Clim. Past Discuss., https://doi.org/10.5194/cp-2016-106, https://doi.org/10.5194/cp-2016-106, 2016
Preprint retracted
Madlene Pfeiffer and Gerrit Lohmann
Clim. Past, 12, 1313–1338, https://doi.org/10.5194/cp-12-1313-2016, https://doi.org/10.5194/cp-12-1313-2016, 2016
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The Last Interglacial was warmer, with a reduced Greenland Ice Sheet (GIS), compared to the late Holocene. We analyse – through climate model simulations – the impact of a reduced GIS on the global surface air temperature and find a relatively strong warming especially in the Northern Hemisphere. These results are then compared to temperature reconstructions, indicating good agreement with respect to the pattern. However, the simulated temperatures underestimate the proxy-based temperatures.
Norel Rimbu, Markus Czymzik, Monica Ionita, Gerrit Lohmann, and Achim Brauer
Clim. Past, 12, 377–385, https://doi.org/10.5194/cp-12-377-2016, https://doi.org/10.5194/cp-12-377-2016, 2016
M. Werner, B. Haese, X. Xu, X. Zhang, M. Butzin, and G. Lohmann
Geosci. Model Dev., 9, 647–670, https://doi.org/10.5194/gmd-9-647-2016, https://doi.org/10.5194/gmd-9-647-2016, 2016
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This paper presents the first results of a new isotope-enabled GCM set-up, based on the ECHAM5/MPI-OM fully coupled atmosphere-ocean model. Results of two equilibrium simulations under pre-industrial and Last Glacial Maximum conditions reveal a good to very good agreement with many delta O-18 and delta D observational records, and a remarkable improvement for the modelling of the deuterium excess signal in Antarctic ice cores.
M. Stärz, G. Lohmann, and G. Knorr
Clim. Past, 12, 151–170, https://doi.org/10.5194/cp-12-151-2016, https://doi.org/10.5194/cp-12-151-2016, 2016
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In order to account for coupled climate-soil processes, we developed a soil scheme which is asynchronously coupled to an earth system model. We tested the scheme and found additional warming for a relatively warm climate (mid-Holocene), and extra cooling for a colder (Last Glacial Maximum) than preindustrial climate. These findings indicate a relatively strong positive soil feedback to climate, which may help to reduce model-data discrepancies for the climate of the geological past.
M. Forrest, J. T. Eronen, T. Utescher, G. Knorr, C. Stepanek, G. Lohmann, and T. Hickler
Clim. Past, 11, 1701–1732, https://doi.org/10.5194/cp-11-1701-2015, https://doi.org/10.5194/cp-11-1701-2015, 2015
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We simulated Late Miocene (11-7 Million years ago) vegetation using two plausible CO2 concentrations: 280ppm CO2 and 450ppm CO2. We compared the simulated vegetation to existing plant fossil data for the whole Northern Hemisphere. Our results suggest that during the Late Miocene the CO2 levels have been relatively low, or that other factors that are not included in the models maintained the seasonal temperate forests and open vegetation.
X. Shi and G. Lohmann
Earth Syst. Dynam. Discuss., https://doi.org/10.5194/esdd-6-2137-2015, https://doi.org/10.5194/esdd-6-2137-2015, 2015
Revised manuscript not accepted
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Our work is to investigate to what degree the open water ice formation affects the ice and ocean properties.
Our results show a positive feedback among the Arctic sea ice, the AMOC, and the surface air temperature in the Arctic.
The sea ice transport affects the freshwater budget in regions of deep water formation.
A link between the climate of Northern Hemisphere continents and the lead closing rate during ice formation period is also shown by the model.
B. de Boer, A. M. Dolan, J. Bernales, E. Gasson, H. Goelzer, N. R. Golledge, J. Sutter, P. Huybrechts, G. Lohmann, I. Rogozhina, A. Abe-Ouchi, F. Saito, and R. S. W. van de Wal
The Cryosphere, 9, 881–903, https://doi.org/10.5194/tc-9-881-2015, https://doi.org/10.5194/tc-9-881-2015, 2015
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We present results from simulations of the Antarctic ice sheet by means of an intercomparison project with six ice-sheet models. Our results demonstrate the difficulty of all models used here to simulate a significant retreat or re-advance of the East Antarctic ice grounding line. Improved grounding-line physics could be essential for a correct representation of the migration of the grounding line of the Antarctic ice sheet during the Pliocene.
A. M. Dolan, S. J. Hunter, D. J. Hill, A. M. Haywood, S. J. Koenig, B. L. Otto-Bliesner, A. Abe-Ouchi, F. Bragg, W.-L. Chan, M. A. Chandler, C. Contoux, A. Jost, Y. Kamae, G. Lohmann, D. J. Lunt, G. Ramstein, N. A. Rosenbloom, L. Sohl, C. Stepanek, H. Ueda, Q. Yan, and Z. Zhang
Clim. Past, 11, 403–424, https://doi.org/10.5194/cp-11-403-2015, https://doi.org/10.5194/cp-11-403-2015, 2015
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Climate and ice sheet models are often used to predict the nature of ice sheets in Earth history. It is important to understand whether such predictions are consistent among different models, especially in warm periods of relevance to the future. We use input from 15 different climate models to run one ice sheet model and compare the predictions over Greenland. We find that there are large differences between the predicted ice sheets for the warm Pliocene (c. 3 million years ago).
D. Barbi, G. Lohmann, K. Grosfeld, and M. Thoma
Geosci. Model Dev., 7, 2003–2013, https://doi.org/10.5194/gmd-7-2003-2014, https://doi.org/10.5194/gmd-7-2003-2014, 2014
T. Goelles, K. Grosfeld, and G. Lohmann
Geosci. Model Dev., 7, 1395–1408, https://doi.org/10.5194/gmd-7-1395-2014, https://doi.org/10.5194/gmd-7-1395-2014, 2014
A. Basu, M. G. Schultz, S. Schröder, L. Francois, X. Zhang, G. Lohmann, and T. Laepple
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-14-3193-2014, https://doi.org/10.5194/acpd-14-3193-2014, 2014
Revised manuscript not accepted
D. J. Hill, A. M. Haywood, D. J. Lunt, S. J. Hunter, F. J. Bragg, C. Contoux, C. Stepanek, L. Sohl, N. A. Rosenbloom, W.-L. Chan, Y. Kamae, Z. Zhang, A. Abe-Ouchi, M. A. Chandler, A. Jost, G. Lohmann, B. L. Otto-Bliesner, G. Ramstein, and H. Ueda
Clim. Past, 10, 79–90, https://doi.org/10.5194/cp-10-79-2014, https://doi.org/10.5194/cp-10-79-2014, 2014
X. Zhang, G. Lohmann, G. Knorr, and X. Xu
Clim. Past, 9, 2319–2333, https://doi.org/10.5194/cp-9-2319-2013, https://doi.org/10.5194/cp-9-2319-2013, 2013
B. Haese, M. Werner, and G. Lohmann
Geosci. Model Dev., 6, 1463–1480, https://doi.org/10.5194/gmd-6-1463-2013, https://doi.org/10.5194/gmd-6-1463-2013, 2013
R. Zhang, Q. Yan, Z. S. Zhang, D. Jiang, B. L. Otto-Bliesner, A. M. Haywood, D. J. Hill, A. M. Dolan, C. Stepanek, G. Lohmann, C. Contoux, F. Bragg, W.-L. Chan, M. A. Chandler, A. Jost, Y. Kamae, A. Abe-Ouchi, G. Ramstein, N. A. Rosenbloom, L. Sohl, and H. Ueda
Clim. Past, 9, 2085–2099, https://doi.org/10.5194/cp-9-2085-2013, https://doi.org/10.5194/cp-9-2085-2013, 2013
Z.-S. Zhang, K. H. Nisancioglu, M. A. Chandler, A. M. Haywood, B. L. Otto-Bliesner, G. Ramstein, C. Stepanek, A. Abe-Ouchi, W.-L. Chan, F. J. Bragg, C. Contoux, A. M. Dolan, D. J. Hill, A. Jost, Y. Kamae, G. Lohmann, D. J. Lunt, N. A. Rosenbloom, L. E. Sohl, and H. Ueda
Clim. Past, 9, 1495–1504, https://doi.org/10.5194/cp-9-1495-2013, https://doi.org/10.5194/cp-9-1495-2013, 2013
M. Kageyama, U. Merkel, B. Otto-Bliesner, M. Prange, A. Abe-Ouchi, G. Lohmann, R. Ohgaito, D. M. Roche, J. Singarayer, D. Swingedouw, and X Zhang
Clim. Past, 9, 935–953, https://doi.org/10.5194/cp-9-935-2013, https://doi.org/10.5194/cp-9-935-2013, 2013
C. Giry, T. Felis, M. Kölling, W. Wei, G. Lohmann, and S. Scheffers
Clim. Past, 9, 841–858, https://doi.org/10.5194/cp-9-841-2013, https://doi.org/10.5194/cp-9-841-2013, 2013
A. M. Haywood, D. J. Hill, A. M. Dolan, B. L. Otto-Bliesner, F. Bragg, W.-L. Chan, M. A. Chandler, C. Contoux, H. J. Dowsett, A. Jost, Y. Kamae, G. Lohmann, D. J. Lunt, A. Abe-Ouchi, S. J. Pickering, G. Ramstein, N. A. Rosenbloom, U. Salzmann, L. Sohl, C. Stepanek, H. Ueda, Q. Yan, and Z. Zhang
Clim. Past, 9, 191–209, https://doi.org/10.5194/cp-9-191-2013, https://doi.org/10.5194/cp-9-191-2013, 2013
G. Lohmann, A. Wackerbarth, P. M. Langebroek, M. Werner, J. Fohlmeister, D. Scholz, and A. Mangini
Clim. Past, 9, 89–98, https://doi.org/10.5194/cp-9-89-2013, https://doi.org/10.5194/cp-9-89-2013, 2013
S. Dietrich, M. Werner, T. Spangehl, and G. Lohmann
Clim. Past, 9, 13–26, https://doi.org/10.5194/cp-9-13-2013, https://doi.org/10.5194/cp-9-13-2013, 2013
Related subject area
Climate and Earth system modeling
WRF-ELM v1.0: a regional climate model to study land–atmosphere interactions over heterogeneous land use regions
Modeling commercial-scale CO2 storage in the gas hydrate stability zone with PFLOTRAN v6.0
DiuSST: a conceptual model of diurnal warm layers for idealized atmospheric simulations with interactive sea surface temperature
High-Resolution Model Intercomparison Project phase 2 (HighResMIP2) towards CMIP7
T&C-CROP: representing mechanistic crop growth with a terrestrial biosphere model (T&C, v1.5) – model formulation and validation
An updated non-intrusive, multi-scale, and flexible coupling interface in WRF 4.6.0
Monitoring and benchmarking Earth system model simulations with ESMValTool v2.12.0
The Earth Science Box Modeling Toolkit (ESBMTK 0.14.0.11): a Python library for research and teaching
CropSuite v1.0 – a comprehensive open-source crop suitability model considering climate variability for climate impact assessment
ICON ComIn – the ICON Community Interface (ComIn version 0.1.0, with ICON version 2024.01-01)
Using feature importance as an exploratory data analysis tool on Earth system models
A new metrics framework for quantifying and intercomparing atmospheric rivers in observations, reanalyses, and climate models
The real challenges for climate and weather modelling on its way to sustained exascale performance: a case study using ICON (v2.6.6)
Improving the representation of major Indian crops in the Community Land Model version 5.0 (CLM5) using site-scale crop data
Evaluation of CORDEX ERA5-forced NARCliM2.0 regional climate models over Australia using the Weather Research and Forecasting (WRF) model version 4.1.2
Design, evaluation, and future projections of the NARCliM2.0 CORDEX-CMIP6 Australasia regional climate ensemble
Amending the algorithm of aerosol–radiation interactions in WRF-Chem (v4.4)
The very-high-resolution configuration of the EC-Earth global model for HighResMIP
GOSI9: UK Global Ocean and Sea Ice configurations
Decomposition of skill scores for conditional verification: impact of Atlantic Multidecadal Oscillation phases on the predictability of decadal temperature forecasts
Virtual Integration of Satellite and In-situ Observation Networks (VISION) v1.0: In-Situ Observations Simulator (ISO_simulator)
Climate model downscaling in central Asia: a dynamical and a neural network approach
Multi-year simulations at kilometre scale with the Integrated Forecasting System coupled to FESOM2.5 and NEMOv3.4
Subsurface hydrological controls on the short-term effects of hurricanes on nitrate–nitrogen runoff loading: a case study of Hurricane Ida using the Energy Exascale Earth System Model (E3SM) Land Model (v2.1)
CARIB12: a regional Community Earth System Model/Modular Ocean Model 6 configuration of the Caribbean Sea
Architectural insights into and training methodology optimization of Pangu-Weather
Evaluation of global fire simulations in CMIP6 Earth system models
Evaluating downscaled products with expected hydroclimatic co-variances
Software sustainability of global impact models
fair-calibrate v1.4.1: calibration, constraining, and validation of the FaIR simple climate model for reliable future climate projections
ISOM 1.0: a fully mesoscale-resolving idealized Southern Ocean model and the diversity of multiscale eddy interactions
A computationally lightweight model for ensemble forecasting of environmental hazards: General TAMSAT-ALERT v1.2.1
Introducing the MESMER-M-TPv0.1.0 module: spatially explicit Earth system model emulation for monthly precipitation and temperature
Investigating Carbon and Nitrogen Conservation in Reported CMIP6 Earth System Model Data
The need for carbon-emissions-driven climate projections in CMIP7
Robust handling of extremes in quantile mapping – “Murder your darlings”
A protocol for model intercomparison of impacts of marine cloud brightening climate intervention
An extensible perturbed parameter ensemble for the Community Atmosphere Model version 6
Coupling the regional climate model ICON-CLM v2.6.6 to the Earth system model GCOAST-AHOI v2.0 using OASIS3-MCT v4.0
A fully coupled solid-particle microphysics scheme for stratospheric aerosol injections within the aerosol–chemistry–climate model SOCOL-AERv2
The Tropical Basin Interaction Model Intercomparison Project (TBIMIP)
An improved representation of aerosol in the ECMWF IFS-COMPO 49R1 through the integration of EQSAM4Climv12 – a first attempt at simulating aerosol acidity
At-scale Model Output Statistics in mountain environments (AtsMOS v1.0)
Impact of ocean vertical-mixing parameterization on Arctic sea ice and upper-ocean properties using the NEMO-SI3 model
Development and evaluation of a new 4DEnVar-based weakly coupled ocean data assimilation system in E3SMv2
Bridging the gap: a new module for human water use in the Community Earth System Model version 2.2.1
PaleoSTeHM v1.0-rc: a modern, scalable spatio-temporal hierarchical modeling framework for paleo-environmental data
From Weather Data to River Runoff: Leveraging Spatiotemporal Convolutional Networks for Comprehensive Discharge Forecasting
Historical Trends and Controlling Factors of Isoprene Emissions in CMIP6 Earth System Models
A new lightning scheme in the Canadian Atmospheric Model (CanAM5.1): implementation, evaluation, and projections of lightning and fire in future climates
Huilin Huang, Yun Qian, Gautam Bisht, Jiali Wang, Tirthankar Chakraborty, Dalei Hao, Jianfeng Li, Travis Thurber, Balwinder Singh, Zhao Yang, Ye Liu, Pengfei Xue, William J. Sacks, Ethan Coon, and Robert Hetland
Geosci. Model Dev., 18, 1427–1443, https://doi.org/10.5194/gmd-18-1427-2025, https://doi.org/10.5194/gmd-18-1427-2025, 2025
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We integrate the E3SM Land Model (ELM) with the WRF model through the Lightweight Infrastructure for Land Atmosphere Coupling (LILAC) Earth System Modeling Framework (ESMF). This framework includes a top-level driver, LILAC, for variable communication between WRF and ELM and ESMF caps for ELM initialization, execution, and finalization. The LILAC–ESMF framework maintains the integrity of the ELM's source code structure and facilitates the transfer of future ELM model developments to WRF-ELM.
Michael Nole, Jonah Bartrand, Fawz Naim, and Glenn Hammond
Geosci. Model Dev., 18, 1413–1425, https://doi.org/10.5194/gmd-18-1413-2025, https://doi.org/10.5194/gmd-18-1413-2025, 2025
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Safe carbon dioxide (CO2) storage is likely to be critical for mitigating some of the most severe effects of climate change. We present a simulation framework for modeling CO2 storage beneath the seafloor, where CO2 can form a solid. This can aid in permanent CO2 storage for long periods of time. Our models show what a commercial-scale CO2 injection would look like in a marine environment. We discuss what would need to be considered when designing a subsea CO2 injection.
Reyk Börner, Jan O. Haerter, and Romain Fiévet
Geosci. Model Dev., 18, 1333–1356, https://doi.org/10.5194/gmd-18-1333-2025, https://doi.org/10.5194/gmd-18-1333-2025, 2025
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The daily cycle of sea surface temperature (SST) impacts clouds above the ocean and could influence the clustering of thunderstorms linked to extreme rainfall and hurricanes. However, daily SST variability is often poorly represented in modeling studies of how clouds cluster. We present a simple, wind-responsive model of upper-ocean temperature for use in atmospheric simulations. Evaluating the model against observations, we show that it performs significantly better than common slab models.
Malcolm J. Roberts, Kevin A. Reed, Qing Bao, Joseph J. Barsugli, Suzana J. Camargo, Louis-Philippe Caron, Ping Chang, Cheng-Ta Chen, Hannah M. Christensen, Gokhan Danabasoglu, Ivy Frenger, Neven S. Fučkar, Shabeh ul Hasson, Helene T. Hewitt, Huanping Huang, Daehyun Kim, Chihiro Kodama, Michael Lai, Lai-Yung Ruby Leung, Ryo Mizuta, Paulo Nobre, Pablo Ortega, Dominique Paquin, Christopher D. Roberts, Enrico Scoccimarro, Jon Seddon, Anne Marie Treguier, Chia-Ying Tu, Paul A. Ullrich, Pier Luigi Vidale, Michael F. Wehner, Colin M. Zarzycki, Bosong Zhang, Wei Zhang, and Ming Zhao
Geosci. Model Dev., 18, 1307–1332, https://doi.org/10.5194/gmd-18-1307-2025, https://doi.org/10.5194/gmd-18-1307-2025, 2025
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HighResMIP2 is a model intercomparison project focusing on high-resolution global climate models, that is, those with grid spacings of 25 km or less in the atmosphere and ocean, using simulations of decades to a century in length. We are proposing an update of our simulation protocol to make the models more applicable to key questions for climate variability and hazard in present-day and future projections and to build links with other communities to provide more robust climate information.
Jordi Buckley Paules, Simone Fatichi, Bonnie Warring, and Athanasios Paschalis
Geosci. Model Dev., 18, 1287–1305, https://doi.org/10.5194/gmd-18-1287-2025, https://doi.org/10.5194/gmd-18-1287-2025, 2025
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We present and validate enhancements to the process-based T&C model aimed at improving its representation of crop growth and management practices. The updated model, T&C-CROP, enables applications such as analysing the hydrological and carbon storage impacts of land use transitions (e.g. conversions between crops, forests, and pastures) and optimizing irrigation and fertilization strategies in response to climate change.
Sébastien Masson, Swen Jullien, Eric Maisonnave, David Gill, Guillaume Samson, Mathieu Le Corre, and Lionel Renault
Geosci. Model Dev., 18, 1241–1263, https://doi.org/10.5194/gmd-18-1241-2025, https://doi.org/10.5194/gmd-18-1241-2025, 2025
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This article details a new feature we implemented in the popular regional atmospheric model WRF. This feature allows for data exchange between WRF and any other model (e.g. an ocean model) using the coupling library Ocean–Atmosphere–Sea–Ice–Soil Model Coupling Toolkit (OASIS3-MCT). This coupling interface is designed to be non-intrusive, flexible and modular. It also offers the possibility of taking into account the nested zooms used in WRF or in the models with which it is coupled.
Axel Lauer, Lisa Bock, Birgit Hassler, Patrick Jöckel, Lukas Ruhe, and Manuel Schlund
Geosci. Model Dev., 18, 1169–1188, https://doi.org/10.5194/gmd-18-1169-2025, https://doi.org/10.5194/gmd-18-1169-2025, 2025
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Earth system models are important tools to improve our understanding of current climate and to project climate change. Thus, it is crucial to understand possible shortcomings in the models. New features of the ESMValTool software package allow one to compare and visualize a model's performance with respect to reproducing observations in the context of other climate models in an easy and user-friendly way. We aim to help model developers assess and monitor climate simulations more efficiently.
Ulrich G. Wortmann, Tina Tsan, Mahrukh Niazi, Irene A. Ma, Ruben Navasardyan, Magnus-Roland Marun, Bernardo S. Chede, Jingwen Zhong, and Morgan Wolfe
Geosci. Model Dev., 18, 1155–1167, https://doi.org/10.5194/gmd-18-1155-2025, https://doi.org/10.5194/gmd-18-1155-2025, 2025
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The Earth Science Box Modeling Toolkit (ESBMTK) is a user-friendly Python library that simplifies the creation of models to study earth system processes, such as the carbon cycle and ocean chemistry. It enhances learning by emphasizing concepts over programming and is accessible to students and researchers alike. By automating complex calculations and promoting code clarity, ESBMTK accelerates model development while improving reproducibility and the usability of scientific research.
Florian Zabel, Matthias Knüttel, and Benjamin Poschlod
Geosci. Model Dev., 18, 1067–1087, https://doi.org/10.5194/gmd-18-1067-2025, https://doi.org/10.5194/gmd-18-1067-2025, 2025
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CropSuite is a new open-source crop suitability model. It provides a GUI and a wide range of options, including a spatial downscaling of climate data. We apply CropSuite to 48 staple and opportunity crops at a 1 km spatial resolution in Africa. We find that climate variability significantly impacts suitable areas but also affects optimal sowing dates and multiple cropping potential. The results provide valuable information for climate impact assessments, adaptation, and land-use planning.
Kerstin Hartung, Bastian Kern, Nils-Arne Dreier, Jörn Geisbüsch, Mahnoosh Haghighatnasab, Patrick Jöckel, Astrid Kerkweg, Wilton Jaciel Loch, Florian Prill, and Daniel Rieger
Geosci. Model Dev., 18, 1001–1015, https://doi.org/10.5194/gmd-18-1001-2025, https://doi.org/10.5194/gmd-18-1001-2025, 2025
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The ICOsahedral Non-hydrostatic (ICON) model system Community Interface (ComIn) library supports connecting third-party modules to the ICON model. Third-party modules can range from simple diagnostic Python scripts to full chemistry models. ComIn offers a low barrier for code extensions to ICON, provides multi-language support (Fortran, C/C++, and Python), and reduces the migration effort in response to new ICON releases. This paper presents the ComIn design principles and a range of use cases.
Daniel Ries, Katherine Goode, Kellie McClernon, and Benjamin Hillman
Geosci. Model Dev., 18, 1041–1065, https://doi.org/10.5194/gmd-18-1041-2025, https://doi.org/10.5194/gmd-18-1041-2025, 2025
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Machine learning has advanced research in the climate science domain, but its models are difficult to understand. In order to understand the impacts and consequences of climate interventions such as stratospheric aerosol injection, complex models are often necessary. We use a case study to illustrate how we can understand the inner workings of a complex model. We present this technique as an exploratory tool that can be used to quickly discover and assess relationships in complex climate data.
Bo Dong, Paul Ullrich, Jiwoo Lee, Peter Gleckler, Kristin Chang, and Travis A. O'Brien
Geosci. Model Dev., 18, 961–976, https://doi.org/10.5194/gmd-18-961-2025, https://doi.org/10.5194/gmd-18-961-2025, 2025
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A metrics package designed for easy analysis of atmospheric river (AR) characteristics and statistics is presented. The tool is efficient for diagnosing systematic AR bias in climate models and useful for evaluating new AR characteristics in model simulations. In climate models, landfalling AR precipitation shows dry biases globally, and AR tracks are farther poleward (equatorward) in the North and South Atlantic (South Pacific and Indian Ocean).
Panagiotis Adamidis, Erik Pfister, Hendryk Bockelmann, Dominik Zobel, Jens-Olaf Beismann, and Marek Jacob
Geosci. Model Dev., 18, 905–919, https://doi.org/10.5194/gmd-18-905-2025, https://doi.org/10.5194/gmd-18-905-2025, 2025
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In this paper, we investigated performance indicators of the climate model ICON (ICOsahedral Nonhydrostatic) on different compute architectures to answer the question of how to generate high-resolution climate simulations. Evidently, it is not enough to use more computing units of the conventionally used architectures; higher memory throughput is the most promising approach. More potential can be gained from single-node optimization rather than simply increasing the number of compute nodes.
Kangari Narender Reddy, Somnath Baidya Roy, Sam S. Rabin, Danica L. Lombardozzi, Gudimetla Venkateswara Varma, Ruchira Biswas, and Devavat Chiru Naik
Geosci. Model Dev., 18, 763–785, https://doi.org/10.5194/gmd-18-763-2025, https://doi.org/10.5194/gmd-18-763-2025, 2025
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The study aimed to improve the representation of wheat and rice in a land model for the Indian region. The modified model performed significantly better than the default model in simulating crop phenology, yield, and carbon, water, and energy fluxes compared to observations. The study highlights the need for global land models to use region-specific crop parameters for accurately simulating vegetation processes and land surface processes.
Giovanni Di Virgilio, Fei Ji, Eugene Tam, Jason P. Evans, Jatin Kala, Julia Andrys, Christopher Thomas, Dipayan Choudhury, Carlos Rocha, Yue Li, and Matthew L. Riley
Geosci. Model Dev., 18, 703–724, https://doi.org/10.5194/gmd-18-703-2025, https://doi.org/10.5194/gmd-18-703-2025, 2025
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We evaluate the skill in simulating the Australian climate of some of the latest generation of regional climate models. We show when and where the models simulate this climate with high skill versus model limitations. We show how new models perform relative to the previous-generation models, assessing how model design features may underlie key performance improvements. This work is of national and international relevance as it can help guide the use and interpretation of climate projections.
Giovanni Di Virgilio, Jason P. Evans, Fei Ji, Eugene Tam, Jatin Kala, Julia Andrys, Christopher Thomas, Dipayan Choudhury, Carlos Rocha, Stephen White, Yue Li, Moutassem El Rafei, Rishav Goyal, Matthew L. Riley, and Jyothi Lingala
Geosci. Model Dev., 18, 671–702, https://doi.org/10.5194/gmd-18-671-2025, https://doi.org/10.5194/gmd-18-671-2025, 2025
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We introduce new climate models that simulate Australia’s future climate at regional scales, including at an unprecedented resolution of 4 km for 1950–2100. We describe the model design process used to create these new climate models. We show how the new models perform relative to previous-generation models and compare their climate projections. This work is of national and international relevance as it can help guide climate model design and the use and interpretation of climate projections.
Jiawang Feng, Chun Zhao, Qiuyan Du, Zining Yang, and Chen Jin
Geosci. Model Dev., 18, 585–603, https://doi.org/10.5194/gmd-18-585-2025, https://doi.org/10.5194/gmd-18-585-2025, 2025
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In this study, we improved the calculation of how aerosols in the air interact with radiation in WRF-Chem. The original model used a simplified method, but we developed a more accurate approach. We found that this method significantly changes the properties of the estimated aerosols and their effects on radiation, especially for dust aerosols. It also impacts the simulated weather conditions. Our work highlights the importance of correctly representing aerosol–radiation interactions in models.
Eduardo Moreno-Chamarro, Thomas Arsouze, Mario Acosta, Pierre-Antoine Bretonnière, Miguel Castrillo, Eric Ferrer, Amanda Frigola, Daria Kuznetsova, Eneko Martin-Martinez, Pablo Ortega, and Sergi Palomas
Geosci. Model Dev., 18, 461–482, https://doi.org/10.5194/gmd-18-461-2025, https://doi.org/10.5194/gmd-18-461-2025, 2025
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We present the high-resolution model version of the EC-Earth global climate model to contribute to HighResMIP. The combined model resolution is about 10–15 km in both the ocean and atmosphere, which makes it one of the finest ever used to complete historical and scenario simulations. This model is compared with two lower-resolution versions, with a 100 km and a 25 km grid. The three models are compared with observations to study the improvements thanks to the increased resolution.
Catherine Guiavarc'h, David Storkey, Adam T. Blaker, Ed Blockley, Alex Megann, Helene Hewitt, Michael J. Bell, Daley Calvert, Dan Copsey, Bablu Sinha, Sophia Moreton, Pierre Mathiot, and Bo An
Geosci. Model Dev., 18, 377–403, https://doi.org/10.5194/gmd-18-377-2025, https://doi.org/10.5194/gmd-18-377-2025, 2025
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The Global Ocean and Sea Ice configuration version 9 (GOSI9) is the new UK hierarchy of model configurations based on the Nucleus for European Modelling of the Ocean (NEMO) and available at three resolutions. It will be used for various applications, e.g. weather forecasting and climate prediction. It improves upon the previous version by reducing global temperature and salinity biases and enhancing the representation of Arctic sea ice and the Antarctic Circumpolar Current.
Andy Richling, Jens Grieger, and Henning W. Rust
Geosci. Model Dev., 18, 361–375, https://doi.org/10.5194/gmd-18-361-2025, https://doi.org/10.5194/gmd-18-361-2025, 2025
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The performance of weather and climate prediction systems is variable in time and space. It is of interest how this performance varies in different situations. We provide a decomposition of a skill score (a measure of forecast performance) as a tool for detailed assessment of performance variability to support model development or forecast improvement. The framework is exemplified with decadal forecasts to assess the impact of different ocean states in the North Atlantic on temperature forecast.
Maria R. Russo, Sadie L. Bartholomew, David Hassell, Alex M. Mason, Erica Neininger, A. James Perman, David A. J. Sproson, Duncan Watson-Parris, and Nathan Luke Abraham
Geosci. Model Dev., 18, 181–191, https://doi.org/10.5194/gmd-18-181-2025, https://doi.org/10.5194/gmd-18-181-2025, 2025
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Observational data and modelling capabilities have expanded in recent years, but there are still barriers preventing these two data sources from being used in synergy. Proper comparison requires generating, storing, and handling a large amount of data. This work describes the first step in the development of a new set of software tools, the VISION toolkit, which can enable the easy and efficient integration of observational and model data required for model evaluation.
Bijan Fallah, Masoud Rostami, Emmanuele Russo, Paula Harder, Christoph Menz, Peter Hoffmann, Iulii Didovets, and Fred F. Hattermann
Geosci. Model Dev., 18, 161–180, https://doi.org/10.5194/gmd-18-161-2025, https://doi.org/10.5194/gmd-18-161-2025, 2025
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We tried to contribute to a local climate change impact study in central Asia, a region that is water-scarce and vulnerable to global climate change. We use regional models and machine learning to produce reliable local data from global climate models. We find that regional models show more realistic and detailed changes in heavy precipitation than global climate models. Our work can help assess the future risks of extreme events and plan adaptation strategies in central Asia.
Thomas Rackow, Xabier Pedruzo-Bagazgoitia, Tobias Becker, Sebastian Milinski, Irina Sandu, Razvan Aguridan, Peter Bechtold, Sebastian Beyer, Jean Bidlot, Souhail Boussetta, Willem Deconinck, Michail Diamantakis, Peter Dueben, Emanuel Dutra, Richard Forbes, Rohit Ghosh, Helge F. Goessling, Ioan Hadade, Jan Hegewald, Thomas Jung, Sarah Keeley, Lukas Kluft, Nikolay Koldunov, Aleksei Koldunov, Tobias Kölling, Josh Kousal, Christian Kühnlein, Pedro Maciel, Kristian Mogensen, Tiago Quintino, Inna Polichtchouk, Balthasar Reuter, Domokos Sármány, Patrick Scholz, Dmitry Sidorenko, Jan Streffing, Birgit Sützl, Daisuke Takasuka, Steffen Tietsche, Mirco Valentini, Benoît Vannière, Nils Wedi, Lorenzo Zampieri, and Florian Ziemen
Geosci. Model Dev., 18, 33–69, https://doi.org/10.5194/gmd-18-33-2025, https://doi.org/10.5194/gmd-18-33-2025, 2025
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Detailed global climate model simulations have been created based on a numerical weather prediction model, offering more accurate spatial detail down to the scale of individual cities ("kilometre-scale") and a better understanding of climate phenomena such as atmospheric storms, whirls in the ocean, and cracks in sea ice. The new model aims to provide globally consistent information on local climate change with greater precision, benefiting environmental planning and local impact modelling.
Yilin Fang, Hoang Viet Tran, and L. Ruby Leung
Geosci. Model Dev., 18, 19–32, https://doi.org/10.5194/gmd-18-19-2025, https://doi.org/10.5194/gmd-18-19-2025, 2025
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Hurricanes may worsen water quality in the lower Mississippi River basin (LMRB) by increasing nutrient runoff. We found that runoff parameterizations greatly affect nitrate–nitrogen runoff simulated using an Earth system land model. Our simulations predicted increased nitrogen runoff in the LMRB during Hurricane Ida in 2021, albeit less pronounced than the observations, indicating areas for model improvement to better understand and manage nutrient runoff loss during hurricanes in the region.
Giovanni Seijo-Ellis, Donata Giglio, Gustavo Marques, and Frank Bryan
Geosci. Model Dev., 17, 8989–9021, https://doi.org/10.5194/gmd-17-8989-2024, https://doi.org/10.5194/gmd-17-8989-2024, 2024
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A CESM–MOM6 regional configuration of the Caribbean Sea was developed in response to the rising need for high-resolution models for climate impact studies. The configuration is validated for the period 2000–2020 and improves significant errors in a low-resolution model. Oceanic properties are well represented. Patterns of freshwater associated with the Amazon River are well captured, and the mean flows of ocean waters across multiple passages in the Caribbean Sea agree with observations.
Deifilia To, Julian Quinting, Gholam Ali Hoshyaripour, Markus Götz, Achim Streit, and Charlotte Debus
Geosci. Model Dev., 17, 8873–8884, https://doi.org/10.5194/gmd-17-8873-2024, https://doi.org/10.5194/gmd-17-8873-2024, 2024
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Pangu-Weather is a breakthrough machine learning model in medium-range weather forecasting that considers 3D atmospheric information. We show that using a simpler 2D framework improves robustness, speeds up training, and reduces computational needs by 20 %–30 %. We introduce a training procedure that varies the importance of atmospheric variables over time to speed up training convergence. Decreasing computational demand increases the accessibility of training and working with the model.
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.
Seung H. Baek, Paul A. Ullrich, Bo Dong, and Jiwoo Lee
Geosci. Model Dev., 17, 8665–8681, https://doi.org/10.5194/gmd-17-8665-2024, https://doi.org/10.5194/gmd-17-8665-2024, 2024
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We evaluate downscaled products by examining locally relevant co-variances during precipitation events. Common statistical downscaling techniques preserve expected co-variances during convective precipitation (a stationary phenomenon). However, they dampen future intensification of frontal precipitation (a non-stationary phenomenon) captured in global climate models and dynamical downscaling. Our study quantifies a ramification of the stationarity assumption underlying statistical downscaling.
Emmanuel Nyenah, Petra Döll, Daniel S. Katz, and Robert Reinecke
Geosci. Model Dev., 17, 8593–8611, https://doi.org/10.5194/gmd-17-8593-2024, https://doi.org/10.5194/gmd-17-8593-2024, 2024
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Research software is vital for scientific progress but is often developed by scientists with limited skills, time, and funding, leading to challenges in usability and maintenance. Our study across 10 sectors shows strengths in version control, open-source licensing, and documentation while emphasizing the need for containerization and code quality. We recommend workshops; code quality metrics; funding; and following the findable, accessible, interoperable, and reusable (FAIR) standards.
Chris Smith, Donald P. Cummins, Hege-Beate Fredriksen, Zebedee Nicholls, Malte Meinshausen, Myles Allen, Stuart Jenkins, Nicholas Leach, Camilla Mathison, and Antti-Ilari Partanen
Geosci. Model Dev., 17, 8569–8592, https://doi.org/10.5194/gmd-17-8569-2024, https://doi.org/10.5194/gmd-17-8569-2024, 2024
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Climate projections are only useful if the underlying models that produce them are well calibrated and can reproduce observed climate change. We formalise a software package that calibrates the open-source FaIR simple climate model to full-complexity Earth system models. Observations, including historical warming, and assessments of key climate variables such as that of climate sensitivity are used to constrain the model output.
Jingwei Xie, Xi Wang, Hailong Liu, Pengfei Lin, Jiangfeng Yu, Zipeng Yu, Junlin Wei, and Xiang Han
Geosci. Model Dev., 17, 8469–8493, https://doi.org/10.5194/gmd-17-8469-2024, https://doi.org/10.5194/gmd-17-8469-2024, 2024
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We propose the concept of mesoscale ocean direct numerical simulation (MODNS), which should resolve the first baroclinic deformation radius and ensure the numerical dissipative effects do not directly contaminate the mesoscale motions. It can be a benchmark for testing mesoscale ocean large eddy simulation (MOLES) methods in ocean models. We build an idealized Southern Ocean model using MITgcm to generate a type of MODNS. We also illustrate the diversity of multiscale eddy interactions.
Emily Black, John Ellis, and Ross I. Maidment
Geosci. Model Dev., 17, 8353–8372, https://doi.org/10.5194/gmd-17-8353-2024, https://doi.org/10.5194/gmd-17-8353-2024, 2024
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We present General TAMSAT-ALERT, a computationally lightweight and versatile tool for generating ensemble forecasts from time series data. General TAMSAT-ALERT is capable of combining multiple streams of monitoring and meteorological forecasting data into probabilistic hazard assessments. In this way, it complements existing systems and enhances their utility for actionable hazard assessment.
Sarah Schöngart, Lukas Gudmundsson, Mathias Hauser, Peter Pfleiderer, Quentin Lejeune, Shruti Nath, Sonia Isabelle Seneviratne, and Carl-Friedrich Schleussner
Geosci. Model Dev., 17, 8283–8320, https://doi.org/10.5194/gmd-17-8283-2024, https://doi.org/10.5194/gmd-17-8283-2024, 2024
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Precipitation and temperature are two of the most impact-relevant climatic variables. Yet, projecting future precipitation and temperature data under different emission scenarios relies on complex models that are computationally expensive. In this study, we propose a method that allows us to generate monthly means of local precipitation and temperature at low computational costs. Our modelling framework is particularly useful for all downstream applications of climate model data.
Gang Tang, Zebedee Nicholls, Chris Jones, Thomas Gasser, Alexander Norton, Tilo Ziehn, Alejandro Romero-Prieto, and Malte Meinshausen
EGUsphere, https://doi.org/10.5194/egusphere-2024-3522, https://doi.org/10.5194/egusphere-2024-3522, 2024
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We analyzed carbon and nitrogen mass conservation in data from CMIP6 Earth System Models. Our findings reveal significant discrepancies between flux and pool size data, particularly in nitrogen, where cumulative imbalances can reach hundreds of gigatons. These imbalances appear primarily due to missing or inconsistently reported fluxes – especially for land use and fire emissions. To enhance data quality, we recommend that future climate data protocols address this issue at the reporting stage.
Benjamin M. Sanderson, Ben B. B. Booth, John Dunne, Veronika Eyring, Rosie A. Fisher, Pierre Friedlingstein, Matthew J. Gidden, Tomohiro Hajima, Chris D. Jones, Colin G. Jones, Andrew King, Charles D. Koven, David M. Lawrence, Jason Lowe, Nadine Mengis, Glen P. Peters, Joeri Rogelj, Chris Smith, Abigail C. Snyder, Isla R. Simpson, Abigail L. S. Swann, Claudia Tebaldi, Tatiana Ilyina, Carl-Friedrich Schleussner, Roland Séférian, Bjørn H. Samset, Detlef van Vuuren, and Sönke Zaehle
Geosci. Model Dev., 17, 8141–8172, https://doi.org/10.5194/gmd-17-8141-2024, https://doi.org/10.5194/gmd-17-8141-2024, 2024
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We discuss how, in order to provide more relevant guidance for climate policy, coordinated climate experiments should adopt a greater focus on simulations where Earth system models are provided with carbon emissions from fossil fuels together with land use change instructions, rather than past approaches that have largely focused on experiments with prescribed atmospheric carbon dioxide concentrations. We discuss how these goals might be achieved in coordinated climate modeling experiments.
Peter Berg, Thomas Bosshard, Denica Bozhinova, Lars Bärring, Joakim Löw, Carolina Nilsson, Gustav Strandberg, Johan Södling, Johan Thuresson, Renate Wilcke, and Wei Yang
Geosci. Model Dev., 17, 8173–8179, https://doi.org/10.5194/gmd-17-8173-2024, https://doi.org/10.5194/gmd-17-8173-2024, 2024
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When bias adjusting climate model data using quantile mapping, one needs to prescribe what to do at the tails of the distribution, where a larger data range is likely encountered outside of the calibration period. The end result is highly dependent on the method used. We show that, to avoid discontinuities in the time series, one needs to exclude data in the calibration range to also activate the extrapolation functionality in that time period.
Philip J. Rasch, Haruki Hirasawa, Mingxuan Wu, Sarah J. Doherty, Robert Wood, Hailong Wang, Andy Jones, James Haywood, and Hansi Singh
Geosci. Model Dev., 17, 7963–7994, https://doi.org/10.5194/gmd-17-7963-2024, https://doi.org/10.5194/gmd-17-7963-2024, 2024
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We introduce a protocol to compare computer climate simulations to better understand a proposed strategy intended to counter warming and climate impacts from greenhouse gas increases. This slightly changes clouds in six ocean regions to reflect more sunlight and cool the Earth. Example changes in clouds and climate are shown for three climate models. Cloud changes differ between the models, but precipitation and surface temperature changes are similar when their cooling effects are made similar.
Trude Eidhammer, Andrew Gettelman, Katherine Thayer-Calder, Duncan Watson-Parris, Gregory Elsaesser, Hugh Morrison, Marcus van Lier-Walqui, Ci Song, and Daniel McCoy
Geosci. Model Dev., 17, 7835–7853, https://doi.org/10.5194/gmd-17-7835-2024, https://doi.org/10.5194/gmd-17-7835-2024, 2024
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We describe a dataset where 45 parameters related to cloud processes in the Community Earth System Model version 2 (CESM2) Community Atmosphere Model version 6 (CAM6) are perturbed. Three sets of perturbed parameter ensembles (263 members) were created: current climate, preindustrial aerosol loading and future climate with sea surface temperature increased by 4 K.
Ha Thi Minh Ho-Hagemann, Vera Maurer, Stefan Poll, and Irina Fast
Geosci. Model Dev., 17, 7815–7834, https://doi.org/10.5194/gmd-17-7815-2024, https://doi.org/10.5194/gmd-17-7815-2024, 2024
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The regional Earth system model GCOAST-AHOI v2.0 that includes the regional climate model ICON-CLM coupled to the ocean model NEMO and the hydrological discharge model HD via the OASIS3-MCT coupler can be a useful tool for conducting long-term regional climate simulations over the EURO-CORDEX domain. The new OASIS3-MCT coupling interface implemented in ICON-CLM makes it more flexible for coupling to an external ocean model and an external hydrological discharge model.
Sandro Vattioni, Rahel Weber, Aryeh Feinberg, Andrea Stenke, John A. Dykema, Beiping Luo, Georgios A. Kelesidis, Christian A. Bruun, Timofei Sukhodolov, Frank N. Keutsch, Thomas Peter, and Gabriel Chiodo
Geosci. Model Dev., 17, 7767–7793, https://doi.org/10.5194/gmd-17-7767-2024, https://doi.org/10.5194/gmd-17-7767-2024, 2024
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We quantified impacts and efficiency of stratospheric solar climate intervention via solid particle injection. Microphysical interactions of solid particles with the sulfur cycle were interactively coupled to the heterogeneous chemistry scheme and the radiative transfer code of an aerosol–chemistry–climate model. Compared to injection of SO2 we only find a stronger cooling efficiency for solid particles when normalizing to the aerosol load but not when normalizing to the injection rate.
Ingo Richter, Ping Chang, Gokhan Danabasoglu, Dietmar Dommenget, Guillaume Gastineau, Aixue Hu, Takahito Kataoka, Noel Keenlyside, Fred Kucharski, Yuko Okumura, Wonsun Park, Malte Stuecker, Andrea Taschetto, Chunzai Wang, Stephen Yeager, and Sang-Wook Yeh
EGUsphere, https://doi.org/10.5194/egusphere-2024-3110, https://doi.org/10.5194/egusphere-2024-3110, 2024
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The tropical ocean basins influence each other through multiple pathways and mechanisms, here referred to as tropical basin interaction (TBI). Many researchers have examined TBI using comprehensive climate models, but have obtained conflicting results. This may be partly due to differences in experiment protocols, and partly due to systematic model errors. TBIMIP aims to address this problem by designing a set of TBI experiments that will be performed by multiple models.
Samuel Rémy, Swen Metzger, Vincent Huijnen, Jason E. Williams, and Johannes Flemming
Geosci. Model Dev., 17, 7539–7567, https://doi.org/10.5194/gmd-17-7539-2024, https://doi.org/10.5194/gmd-17-7539-2024, 2024
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In this paper we describe the development of the future operational cycle 49R1 of the IFS-COMPO system, used for operational forecasts of atmospheric composition in the CAMS project, and focus on the implementation of the thermodynamical model EQSAM4Clim version 12. The implementation of EQSAM4Clim significantly improves the simulated secondary inorganic aerosol surface concentration. The new aerosol and precipitation acidity diagnostics showed good agreement against observational datasets.
Maximillian Van Wyk de Vries, Tom Matthews, L. Baker Perry, Nirakar Thapa, and Rob Wilby
Geosci. Model Dev., 17, 7629–7643, https://doi.org/10.5194/gmd-17-7629-2024, https://doi.org/10.5194/gmd-17-7629-2024, 2024
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This paper introduces the AtsMOS workflow, a new tool for improving weather forecasts in mountainous areas. By combining advanced statistical techniques with local weather data, AtsMOS can provide more accurate predictions of weather conditions. Using data from Mount Everest as an example, AtsMOS has shown promise in better forecasting hazardous weather conditions, making it a valuable tool for communities in mountainous regions and beyond.
Sofia Allende, Anne Marie Treguier, Camille Lique, Clément de Boyer Montégut, François Massonnet, Thierry Fichefet, and Antoine Barthélemy
Geosci. Model Dev., 17, 7445–7466, https://doi.org/10.5194/gmd-17-7445-2024, https://doi.org/10.5194/gmd-17-7445-2024, 2024
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We study the parameters of the turbulent-kinetic-energy mixed-layer-penetration scheme in the NEMO model with regard to sea-ice-covered regions of the Arctic Ocean. This evaluation reveals the impact of these parameters on mixed-layer depth, sea surface temperature and salinity, and ocean stratification. Our findings demonstrate significant impacts on sea ice thickness and sea ice concentration, emphasizing the need for accurately representing ocean mixing to understand Arctic climate dynamics.
Pengfei Shi, L. Ruby Leung, and Bin Wang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-183, https://doi.org/10.5194/gmd-2024-183, 2024
Revised manuscript accepted for GMD
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Improving climate predictions has significant socio-economic impacts. In this study, we developed and applied a weakly coupled ocean data assimilation (WCODA) system to a coupled climate model. The WCODA system improves simulations of ocean temperature and salinity across many global regions. It also enhances the simulation of interannual precipitation and temperature variability over the southern US. This system is to support future predictability studies.
Sabin I. Taranu, David M. Lawrence, Yoshihide Wada, Ting Tang, Erik Kluzek, Sam Rabin, Yi Yao, Steven J. De Hertog, Inne Vanderkelen, and Wim Thiery
Geosci. Model Dev., 17, 7365–7399, https://doi.org/10.5194/gmd-17-7365-2024, https://doi.org/10.5194/gmd-17-7365-2024, 2024
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In this study, we improved a climate model by adding the representation of water use sectors such as domestic, industry, and agriculture. This new feature helps us understand how water is used and supplied in various areas. We tested our model from 1971 to 2010 and found that it accurately identifies areas with water scarcity. By modelling the competition between sectors when water availability is limited, the model helps estimate the intensity and extent of individual sectors' water shortages.
Yucheng Lin, Robert E. Kopp, Alexander Reedy, Matteo Turilli, Shantenu Jha, and Erica L. Ashe
EGUsphere, https://doi.org/10.5194/egusphere-2024-2183, https://doi.org/10.5194/egusphere-2024-2183, 2024
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PaleoSTeHM v1.0-rc is a state-of-the-art framework designed to reconstruct past environmental conditions using geological data. Built on modern machine learning techniques, it efficiently handles the sparse and noisy nature of paleo records, allowing scientists to make accurate and scalable inferences about past environmental change. By using flexible statistical models, PaleoSTeHM separates different sources of uncertainty, improving the precision of historical climate reconstructions.
Florian Börgel, Sven Karsten, Karoline Rummel, and Ulf Gräwe
EGUsphere, https://doi.org/10.5194/egusphere-2024-2685, https://doi.org/10.5194/egusphere-2024-2685, 2024
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Forecasting river runoff, crucial for managing water resources and understanding climate impacts, can be challenging. This study introduces a new method using Convolutional Long Short-Term Memory (ConvLSTM) networks, a machine learning model that processes spatial and temporal data. Focusing on the Baltic Sea region, our model uses weather data as input to predict daily river runoff for 97 rivers.
Thi Nhu Ngoc Do, Kengo Sudo, Akihiko Ito, Louisa Emmons, Vaishali Naik, Kostas Tsigaridis, Øyvind Seland, Gerd A. Folberth, and Douglas I. Kelley
EGUsphere, https://doi.org/10.5194/egusphere-2024-2313, https://doi.org/10.5194/egusphere-2024-2313, 2024
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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 climate. Future models that refine these factors’ effects on isoprene emissions, along with long-term observations, are essential for better understanding plant-climate interactions.
Cynthia Whaley, Montana Etten-Bohm, Courtney Schumacher, Ayodeji Akingunola, Vivek Arora, Jason Cole, Michael Lazare, David Plummer, Knut von Salzen, and Barbara Winter
Geosci. Model Dev., 17, 7141–7155, https://doi.org/10.5194/gmd-17-7141-2024, https://doi.org/10.5194/gmd-17-7141-2024, 2024
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This paper describes how lightning was added as a process in the Canadian Earth System Model in order to interactively respond to climate changes. As lightning is an important cause of global wildfires, this new model development allows for more realistic projections of how wildfires may change in the future, responding to a changing climate.
Cited articles
Acero, F. J., García, J. A., and Gallego, M. C.: Peaks-over-Threshold Study of Trends in Extreme Rainfall over the Iberian Peninsula, J. Climate, 24, 1089–1105, https://doi.org/10.1175/2010JCLI3627.1, 2011. a
Ackermann, L., Danek, C., Gierz, P., and Lohmann, G.: AMOC Recovery in a
Multicentennial Scenario Using a Coupled Atmosphere-Ocean-Ice Sheet Model,
Geophys. Res. Lett., 47, e2019GL086810, https://doi.org/10.1029/2019GL086810, 2020. a, b, c
Bador, M., Boé, J., Terray, L., Alexander, L. V., Baker, A., Bellucci, A.,
Haarsma, R., Koenigk, T., Moine, M.-P., Lohmann, K., Putrasahan, D. A.,
Roberts, C., Roberts, M., Scoccimarro, E., Schiemann, R., Seddon, J., Senan, R., Valcke, S., and Vanniere, B.: Impact of Higher Spatial Atmospheric Resolution on Precipitation Extremes Over Land in Global Climate Models, J. Geophys. Res.-Atmos., 125, e2019JD032184,
https://doi.org/10.1029/2019JD032184, 2020a. a, b
Bargaoui, Z. and Bárdossy, A.: Modeling short duration extreme precipitation
patterns using copula and generalized maximum pseudo-likelihood estimation
with censoring, Adv. Water Resour., 84, 1–13,
https://doi.org/10.1016/j.advwatres.2015.07.006, 2015. a
Bernard, E., Naveau, P., Vrac, M., and Mestre, O.: Clustering of Maxima:
Spatial Dependencies among Heavy Rainfall in France, J. Climate, 26, 7929–7937, https://doi.org/10.1175/JCLI-D-12-00836.1, 2013. a, b
Brierley, C. M., Zhao, A., Harrison, S. P., Braconnot, P., Williams, C. J. R., Thornalley, D. J. R., Shi, X., Peterschmitt, J.-Y., Ohgaito, R., Kaufman, D. S., Kageyama, M., Hargreaves, J. C., Erb, M. P., Emile-Geay, J., D'Agostino, R., Chandan, D., Carré, M., Bartlein, P. J., Zheng, W., Zhang, Z., Zhang, Q., Yang, H., Volodin, E. M., Tomas, R. A., Routson, C., Peltier, W. R., Otto-Bliesner, B., Morozova, P. A., McKay, N. P., Lohmann, G., Legrande, A. N., Guo, C., Cao, J., Brady, E., Annan, J. D., and Abe-Ouchi, A.: Large-scale features and evaluation of the PMIP4-CMIP6 midHolocene simulations, Clim. Past, 16, 1847–1872, https://doi.org/10.5194/cp-16-1847-2020, 2020. a
Brown, J. R., Brierley, C. M., An, S.-I., Guarino, M.-V., Stevenson, S., Williams, C. J. R., Zhang, Q., Zhao, A., Abe-Ouchi, A., Braconnot, P., Brady, E. C., Chandan, D., D'Agostino, R., Guo, C., LeGrande, A. N., Lohmann, G., Morozova, P. A., Ohgaito, R., O'ishi, R., Otto-Bliesner, B. L., Peltier, W. R., Shi, X., Sime, L., Volodin, E. M., Zhang, Z., and Zheng, W.: Comparison of past and future simulations of ENSO in CMIP5/PMIP3 and CMIP6/PMIP4 models, Clim. Past, 16, 1777–1805, https://doi.org/10.5194/cp-16-1777-2020, 2020. a
Carvalho, M., Melo-Gonçalves, P., Teixeira, J., and Rocha, A.: Regionalization of Europe based on a K-Means Cluster Analysis of the climate change of temperatures and precipitation, Phys. Chem. Earth, 94, 22–28, https://doi.org/10.1016/j.pce.2016.05.001, 2016. a
Castro-Camilo, D. and Huser, R.: Local Likelihood Estimation of Complex Tail
Dependence Structures, Applied to U.S. Precipitation Extremes, J. Am. Stat.
Assoc., 115, 1037–1054, https://doi.org/10.1080/01621459.2019.1647842, 2020. a
Ciais, P., Reichstein, M., Viovy, N., Granier, A., Ogée, J., Allard, V., Aubinet, M., Buchmann, N., Bernhofer, C., Carrara, A., Chevallier, F., De Noblet, N., Friend, A. D., Friedlingstein, P., Grünwald, T., Heinesch, B., Keronen, P., Knohl, A., Krinner, G., Loustau, D., Manca, G., Matteucci, G., Miglietta, F., Ourcival, J. M., Papale, D., Pilegaard, K., Rambal, S., Seufert, G., Soussana, J. F., Sanz, M. J., Schulze, E. D., Vesala T., and Valentini, R.: Europe-wide reduction in primary
productivity caused by the heat and drought in 2003, Nature, 437, 529–533,
https://doi.org/10.1038/nature03972, 2005. a
Cinquini, L., Crichton, D., Mattmann, C., Harney, J., Shipman, G., Wang, F.,
Ananthakrishnan, R., Miller, N., Denvil, S., Morgan, M., Pobre, Z., Bell,
G. M., Doutriaux, C., Drach, R., Williams, D., Kershaw, P., Pascoe, S.,
Gonzalez, E., Fiore, S., and Schweitzer, R.: The Earth System Grid
Federation: An open infrastructure for access to distributed geospatial data, Future Gener. Comp. Sy., 36, 400–417,
https://doi.org/10.1016/j.future.2013.07.002, 2014. a
Cleveland, R., Cleveland, W., McRae, J., and Terpenning, I.: STL: A
seasonal-trend decomposition procedure based on loess, J. Off. Stat., 6, 3–33, 1990. a
Coles, S., Pericchi, L. R., and Sisson, S.: A fully probabilistic approach to
extreme rainfall modeling, J. Hydrol., 273, 35–50,
https://doi.org/10.1016/S0022-1694(02)00353-0, 2003. a
Cooley, D., Naveau, P., and Poncet, P.: Variograms for spatial max-stable
random fields, in: Dependence in Probability and Statistics, edited by:
Bertail, P., Soulier, P., and Doukhan, P., Springer, New York, 373–390, https://doi.org/10.1007/0-387-36062-X, 2006. a, b
Danek, C., Shi, X., Stepanek, C., Yang, H., Barbi, D., Hegewald, J., and
Lohmann, G.: AWI AWI-ESM1.1LR model output prepared for CMIP6 CMIP
historical, Version 20200212, Earth System Grid Federation [data set],, https://doi.org/10.22033/ESGF/CMIP6.9328, 2020. a, b
de Bono, A., Giuliani, G., Kluser, S., and Peduzzi, P.: Impacts of summer
2003 heat wave in Europe, UNEP/DEWA/GRID, Europ. Environ. Alert.
Bull., 2, 1–4, 2004. a
Dombry, C., Ribatet, M., and Stoev, S.: Probabilities of Concurrent Extremes, J. Am. Stat. Assoc., 113, 1565–1582, https://doi.org/10.1080/01621459.2017.1356318, 2018. a
Dong, B., Sutton, R. T., and Shaffrey, L.: Understanding the rapid summer
warming and changes in temperature extremes since the mid-1990s over Western Europe, Clim. Dynam., 48, 1537–1554, https://doi.org/10.1007/s00382-016-3158-8, 2017. a
EC-Earth Consortium: EC-Earth-Consortium EC-Earth3-Veg-LR model output
prepared for CMIP6 CMIP historical, EC-Earth [data set], Version 20200217,
https://doi.org/10.22033/ESGF/CMIP6.4707, 2020. a
EC-Earth Consortium: EC-Earth-Consortium EC-Earth-3-CC model output prepared for CMIP6 CMIP historical, EC-Earth [data set], Earth System Grid Federation, https://doi.org/10.22033/ESGF/CMIP6.4702, 2021. 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
Fischer, E. and Knutti, R.: Observed heavy precipitation increase confirms
theory and early models, Nat. Clim. Change, 6, 986–991,
https://doi.org/10.1038/nclimate3110, 2016. a
Fisher, R. A. and Tippett, L. H. C.: Limiting forms of the frequency
distribution of the largest or smallest member of a sample, Math. Proc. Cambridge, 24, 180–190, https://doi.org/10.1017/S0305004100015681, 1928. a
Fovell, R. G. and Fovell, M.-Y. C.: Climate zones of the Conterminous United
States defined using cluster analysis, J. Climate, 6, 2103–2135,
https://doi.org/10.1175/1520-0442(1993)006<2103:CZOTCU>2.0.CO;2, 1993. a
Fowler, H. J. and Kilsby, C. G.: Implications of changes in seasonal and annual extreme rainfall, Geophys. Res. Lett., 30, 1720, https://doi.org/10.1029/2003GL017327, 2003. a
Fréchet, M.: Sur la loi de probabilité de l'écart maximum, Ann. Soc. Polon. Math., 6, 93–116, 1927. a
Gnedenko, B.: Sur la distribution limite du terme maximum d'une série
aléatoire, Ann. Math., 44, 423–453, https://doi.org/10.2307/1968974, 1943. a
Hagemann, S. and Dümenil, L.: A parametrization of the lateral waterflow for
the global scale, Clim. Dynam., 14, 17–31, 1997. a
Harris, I. C., Jones, P. D., and Osborn, T.: CRU TS4.04: Climatic Research Unit (CRU) Time-Series (TS) version 4.04 of high-resolution gridded data of month-by-month variation in climate (January 1901–December 2019), University of East Anglia Climatic Research Unit, Centre for Environmental Data Analysis [data set], https://catalogue.ceda.ac.uk/uuid/89e1e34ec3554dc98594a5732622bce9 (last access:12 June 2021), 2020a. a
Harris, I., Osborn, T., Jones, P., and Lister, D.: Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset, Sci. Data, 7, 2052–4463, https://doi.org/10.1038/s41597-020-0453-3, 2020b. a, b
Horton, R., Mankin, J., Lesk, C., Coffel, E., and Raymond, C.: A review of
recent advances in research on extreme heat events, Curr. Clim. Change Rep., 2, 242–259, https://doi.org/10.1007/s40641-016-0042-x, 2016. a
Hosking, J.: Algorithm AS 215: Maximum-likelihood estimation of the parameters
of the generalized extreme-value distribution, J. Roy. Stat. Soc. C-App., 34, 301–310, https://doi.org/10.2307/2347483, 1985. a
Hosking, J., Wallis, J., and Wood, E.: Estimation of the generalized
extreme-value distribution by the method of probability-weighted moments,
Technometrics, 27, 251–261, https://doi.org/10.1080/00401706.1985.10488049, 1985. a, b
Ionita, M., Caldarescu, D. E., and Nagavciuc, V.: Compound Hot and Dry Events
in Europe: Variability and Large-Scale Drivers, Front. Climate, 3, 58, https://doi.org/10.3389/fclim.2021.688991, 2021a. a
Ionita, M., Dima, M., Nagavciuc, V., and Lohmann, G.: Past megadroughts in
central Europe were longer, more severe and less warm than modern droughts,
Commun. Earth Environ., 2, 61, https://doi.org/10.1038/s43247-021-00130-w,
2021b. a
IPCC: Managing the risks of extreme events and disasters to advance climate
change adaptation, A special report of working groups I and II of the
Intergovernmental Panel on Climate Change, edited by: Field, C. B., Barros, V., Stocker, T. F., Qin, D., Dokken, D. J., Ebi, K. L., Mastrandrea, M. D., Mach, K. J., Plattner, G.-K., Allen, S. K., Tignor, M., and Midgley, P. M., Cambridge University Press, Cambridge, UK, and New York, NY, USA, https://doi.org/10.13140/2.1.3117.9529, 2012. a, b
Jongman, B., Hochrainer-Stigler, S., Feyen, L., Aerts, J., Mechler, R., Botzen, W., Bouwer, L., Pflug, G., Rojas, R., and Ward, P.: Increasing stress on disaster-risk finance due to large floods, Nat. Clim. Change, 4, 264–268,
https://doi.org/10.1038/NCLIMATE2124, 2014. a
Kageyama, M., Harrison, S. P., Kapsch, M.-L., Lofverstrom, M., Lora, J. M., Mikolajewicz, U., Sherriff-Tadano, S., Vadsaria, T., Abe-Ouchi, A., Bouttes, N., Chandan, D., Gregoire, L. J., Ivanovic, R. F., Izumi, K., LeGrande, A. N., Lhardy, F., Lohmann, G., Morozova, P. A., Ohgaito, R., Paul, A., Peltier, W. R., Poulsen, C. J., Quiquet, A., Roche, D. M., Shi, X., Tierney, J. E., Valdes, P. J., Volodin, E., and Zhu, J.: The PMIP4 Last Glacial Maximum experiments: preliminary results and comparison with the PMIP3 simulations, Clim. Past, 17, 1065–1089, https://doi.org/10.5194/cp-17-1065-2021, 2021a. a
Kageyama, M., Sime, L. C., Sicard, M., Guarino, M.-V., de Vernal, A., Stein, R., Schroeder, D., Malmierca-Vallet, I., Abe-Ouchi, A., Bitz, C., Braconnot, P., Brady, E. C., Cao, J., Chamberlain, M. A., Feltham, D., Guo, C., LeGrande, A. N., Lohmann, G., Meissner, K. J., Menviel, L., Morozova, P., Nisancioglu, K. H., Otto-Bliesner, B. L., O'ishi, R., Ramos Buarque, S., Salas y Melia, D., Sherriff-Tadano, S., Stroeve, J., Shi, X., Sun, B., Tomas, R. A., Volodin, E., Yeung, N. K. H., Zhang, Q., Zhang, Z., Zheng, W., and Ziehn, T.: A multi-model CMIP6-PMIP4 study of Arctic sea ice at 127 ka: sea ice data compilation and model differences, Clim. Past, 17, 37–62, https://doi.org/10.5194/cp-17-37-2021, 2021b. a
Katz, R. and Brown, B.: Extreme events in a changing climate: Variability is
more important than averages, Clim. Change, 21, 289–302,
https://doi.org/10.1007/BF00139728, 1992. a
Keeble, J., Hassler, B., Banerjee, A., Checa-Garcia, R., Chiodo, G., Davis, S., Eyring, V., Griffiths, P. T., Morgenstern, O., Nowack, P., Zeng, G., Zhang, J., Bodeker, G., Burrows, S., Cameron-Smith, P., Cugnet, D., Danek, C., Deushi, M., Horowitz, L. W., Kubin, A., Li, L., Lohmann, G., Michou, M., Mills, M. J., Nabat, P., Olivié, D., Park, S., Seland, Ø., Stoll, J., Wieners, K.-H., and Wu, T.: Evaluating stratospheric ozone and water vapour changes in CMIP6 models from 1850 to 2100, Atmos. Chem. Phys., 21, 5015–5061, https://doi.org/10.5194/acp-21-5015-2021, 2021. a
Kiriliouk, A., Rootzén, H., Segers, J., and Wadsworth, J. L.: Peaks Over
Thresholds Modeling With Multivariate Generalized Pareto Distributions,
Technometrics, 61, 123–135, https://doi.org/10.1080/00401706.2018.1462738, 2019. a
Kornhuber, K., Coumou, D., Vogel, E., Lesk, C., Donges, J. F., Lehmann, J., and
Horton, R.: Amplified Rossby waves enhance risk of concurrent heatwaves in
major breadbasket regions, Nat. Clim. Change, 10, 48–53,
https://doi.org/10.1038/s41558-019-0637-z, 2020. a
Kovats, R. S. and Kristie, L. E.: Heatwaves and public health in Europe, Eur. J. Public Health, 16, 592–599, https://doi.org/10.1093/eurpub/ckl049, 2006. a
Lohmann, G.: ESD Ideas: The stochastic climate model shows that underestimated Holocene trends and variability represent two sides of the same coin, Earth Syst. Dynam., 9, 1279–1281, https://doi.org/10.5194/esd-9-1279-2018, 2018. a
Lohmann, G., Butzin, M., Eissner, N., Shi, X., and Stepanek, C.: Abrupt Climate
and Weather Changes Across Time Scales, Paleoceanography and
Paleoclimatology, 35, e2019PA003782,
https://doi.org/10.1029/2019PA003782, 2020. a, b, c
Mahajan, S., Evans, K., Branstetter, M., Anantharaj, V., and Leifeld, J.:
Fidelity of Precipitation Extremes in High Resolution Global Climate
Simulations, Procedia Comput. Sci., 51, 2178–2187,
https://doi.org/10.1016/j.procs.2015.05.492, 2015. a
Marcon, G., Padoan, S., Naveau, P., and Muliere, P.: Multivariate nonparametric
estimation of the Pickands Dependence Function using Bernstein Polynomials, J. Stat. Plan. Infer., 183, 1–14, https://doi.org/10.1016/j.jspi.2016.10.004, 2014. a, b
Millard, S. and Kowarik, A.: EnvStats, an R Package for Environmental Statistics, EnvStats, https://cran.r-project.org/web/packages/EnvStats/index.html (last access: 12 February 2021), 2013. a
Mills, E.: Insurance in a climate of change, Science, 309, 1040–1044,
https://doi.org/10.1126/science.1112121, 2005. a
Mishra, V., Kumar, D., Ganguly, A. R., Sanjay, J., Mujumdar, M., Krishnan, R., and Shah, R. D.: Reliability of regional and global climate models to
simulate precipitation extremes over India, J. Geophys. Res.-Atmos., 119,
9301–9323, https://doi.org/10.1002/2014JD021636, 2014. a
Murtagh, F. and Contreras, P.: Algorithms for hierarchical clustering: an
overview, WIREs Data Min. Knowl., 2, 86–97, https://doi.org/10.1002/widm.53, 2012. a
Myhre, G., Alterskjær, K., Stjern, C. W., Hodnebrog, Ø., Marelle, L., Samset, B., Sillmann, J., Schaller, N., Fischer, E., Schulz, M., and Stohl, A.: Frequency of extreme precipitation increases extensively with event rareness under global warming, Sci. Rep.-UK, 9, 16063, https://doi.org/10.1038/s41598-019-52277-4, 2019. a
Nazeri Tahroudi, M., Ramezani, Y., de Michele, C., and Mirabbasi, R.:
Multivariate analysis of rainfall and its deficiency signatures using vine
copulas, Int. J. Climatol., 1–14, https://doi.org/10.1002/joc.7349, 2021. a
Neumann, A., Bodnar, T., Pfeifer, D., and Dickhaus, T.: Multivariate multiple
test procedures based on nonparametric copula estimation, Biometrical J., 61, 40–61, https://doi.org/10.1002/bimj.201700205, 2019. a
Niu, L., Lohmann, G., Gierz, P., Gowan, E. J., and Knorr, G.: Coupled
climate-ice sheet modelling of MIS-13 reveals a sensitive Cordilleran Ice
Sheet, Global Planet. Change, 200, 103474,
https://doi.org/10.1016/j.gloplacha.2021.103474, 2021. a
Onwuegbuche, F., Kenyatta, A., Affognon, S. B., Enock, E., and Akinade, M.:
Application of extreme value theory in predicting climate change induced
extreme rainfall in Kenya, Int. J. Stat. Probab., 8, 85–94, https://doi.org/10.5539/ijsp.v8n4p85, 2019. a
Opitz, T.: Extremal t-processes: Elliptical domain of attraction and a spectral representation, J. Multivariate Anal., 122, 409–413,
https://doi.org/10.1016/j.jmva.2013.08.008, 2013. a
Otto-Bliesner, B. L., Brady, E. C., Zhao, A., Brierley, C. M., Axford, Y., Capron, E., Govin, A., Hoffman, J. S., Isaacs, E., Kageyama, M., Scussolini, P., Tzedakis, P. C., Williams, C. J. R., Wolff, E., Abe-Ouchi, A., Braconnot, P., Ramos Buarque, S., Cao, J., de Vernal, A., Guarino, M. V., Guo, C., LeGrande, A. N., Lohmann, G., Meissner, K. J., Menviel, L., Morozova, P. A., Nisancioglu, K. H., O'ishi, R., Salas y Mélia, D., Shi, X., Sicard, M., Sime, L., Stepanek, C., Tomas, R., Volodin, E., Yeung, N. K. H., Zhang, Q., Zhang, Z., and Zheng, W.: Large-scale features of Last Interglacial climate: results from evaluating the lig127k simulations for the Coupled Model Intercomparison Project (CMIP6)–Paleoclimate Modeling Intercomparison Project (PMIP4), Clim. Past, 17, 63–94, https://doi.org/10.5194/cp-17-63-2021, 2021. a
Pickands, J.: Multivariate extreme value distributions, in: Proceedings of the 43rd Session of the International Statistical Institute, Vol. 2 (Buenos
Aires, 1981), International Statistical Institute, 49, 859–878, 894–902, 1981. a
Qian, L., Wang, H., Dang, S., Wang, C., Jiao, Z., and Zhao, Y.: Modelling
bivariate extreme precipitation distribution for data-scarce regions using
Gumbel–Hougaard copula with maximum entropy estimation, Hydrol. Process., 32, 212–227, https://doi.org/10.1002/hyp.11406, 2018. a
Rackow, T., Goessling, H., Jung, T., Sidorenko, D., Semmler, T., Barbi, D., and Handorf, D.: Towards multi-resolution global climate modeling with
ECHAM6-FESOM, Part II: climate variability, Clim. Dynam., 50, 2369–2394,
https://doi.org/10.1007/s00382-016-3192-6, 2018. a
Rahmstorf, S. and Coumou, D.: Increase of extreme events in a warming world, P. Natl. Acad. Sci. USA, 108, 17905–17909, https://doi.org/10.1073/pnas.1101766108,
2011. a
Reick, C. H., Raddatz, T., Brovkin, V., and Gayler, V.: Representation of
natural and anthropogenic land cover change in MPI-ESM, J. Adv. Model. Earth Sy., 5, 459–482, https://doi.org/10.1002/jame.20022, 2013. a
Ribatet, M.: Modelling spatial extremes using max-stable processes, in:
Nonlinear and Stochastic Climate Dynamics, edited by: Franzke, C. L. E. and
O'Kane, T. J., Cambridge University Press, 369–391,
https://doi.org/10.1017/9781316339251.014, 2017. a
Ribatet, M., Dombry, C., and Oesting, M.: Spatial extremes and max-stable
processes, in: Extreme Value Modeling and Risk Analysis: Methods and
Applications, 179–194, https://doi.org/10.1201/b19721-10, 2015. a, b, c
Salvador, S. and Chan, P.: Determining the number of clusters/segments in
hierarchical clustering/segmentation algorithms, in: 16th IEEE International Conference on Tools with Artificial Intelligence, 576–584,
https://doi.org/10.1109/ICTAI.2004.50, 2004. a, b
Schär, C., Vidale, P., Lüthi, D., Frei, C., Häberli, C., Liniger, M., and
Appenzeller, C.: The role of increasing temperature variability in European
summer heatwaves, Nature, 427, 332–336, https://doi.org/10.1038/nature02300, 2004. a
Schlather, M.: Models for stationary max-stable random fields, Extremes, 5,
33–44, https://doi.org/10.1023/A:1020977924878, 2002. a
Shaby, B. A. and Reich, B. J.: Bayesian spatial extreme value analysis to
assess the changing risk of concurrent high temperatures across large
portions of European cropland, Environmetrics, 23, 638–648,
https://doi.org/10.1002/env.2178, 2012. a
Shi, X., Lohmann, G., Sidorenko, D., and Yang, H.: Early-Holocene simulations
using different forcings and resolutions in AWI-ESM, The Holocene, 30,
996–1015, https://doi.org/10.1177/0959683620908634, 2020. a, b
Sidorenko, D., Rackow, T., Jung, T., Semmler, T., Barbi, D., Danilov, S., Dethloff, K., Dorn, W., Fieg, K., Gößling, H. F., Horf, D., Harig, S., Hiller, W., Juricke, S., Losch, M., Schröter, J., Sein, D., and Wang, Q.: Towards multi-resolution global climate modeling with ECHAM6-FESOM. Part I: Model formulation and mean climate, Clim. Dynam., 44, 757–780, https://doi.org/10.1007/s00382-014-2290-6,
2015. a
Sillmann, J., Kharin, V. V., Zwiers, F. W., Zhang, X., and Bronaugh, D.:
Climate extremes indices in the CMIP5 multimodel ensemble: Part 2, Future
climate projections, J. Geophys. Res.-Atmos., 118, 2473–2493,
https://doi.org/10.1002/jgrd.50188, 2013. a
Smith, R. L.: Max-stable processes and spatial extremes, Unpublished
Manuscript, University of Surrey, Guildford GU25XH, England, https://www.rls.sites.oasis.unc.edu/postscript/rs/spatex.pdf (last access: 28 April 2021), 1990. a
Stevens, B., Giorgetta, M., Esch, M., Mauritsen, T., Crueger, T., Rast, S., Salzmann, M., Schmidt, H., Bader, J., Block, K., Brokopf, R., Fast, I., Kinne, S., Kornblueh, L., Lohmann, U., Pincus, R., Reichler, T., and Roeckner, E.: Atmospheric component of the
MPI-M Earth System Model: ECHAM6, J. Adv. Model. Earth Sy., 5, 146–172,
https://doi.org/10.1002/jame.20015, 2013. a
Tabari, H., De Troch, R., Giot, O., Hamdi, R., Termonia, P., Saeed, S., Brisson, E., Van Lipzig, N., and Willems, P.: Local impact analysis of climate change on precipitation extremes: are high-resolution climate models needed for realistic simulations?, Hydrol. Earth Syst. Sci., 20, 3843–3857, https://doi.org/10.5194/hess-20-3843-2016, 2016. a
Tapiador, F. J., Turk, F., Petersen, W., Hou, A. Y., García-Ortega, E., Machado, L. A. T., Angelis, C. F., Salio, P., Kidd, C., Huffman, G. J., and de Castro, M.: Global precipitation
measurement: Methods, datasets and applications, Atmos. Res., 104–105, 70–97, https://doi.org/10.1016/j.atmosres.2011.10.021, 2012. a
Timmermans, B., Wehner, M., Cooley, D., O’Brien, T., and Krishnan, H.: An
evaluation of the consistency of extremes in gridded precipitation data sets, Clim. Dynam., 52, 1–20, https://doi.org/10.1007/s00382-018-4537-0, 2019. a
Toreti, A., Cronie, O., and Zampieri, M.: Concurrent climate extremes in the
key wheat producing regions of the world, Sci. Rep.-UK, 9, 5493,
https://doi.org/10.1038/s41598-019-41932-5, 2019. a
Trenberth, K. E. and Fasullo, J. T.: An apparent hiatus in global warming?,
Earths Future, 1, 19–32, https://doi.org/10.1002/2013EF000165, 2013. a
University of East Anglia Climatic Research Unit: Harris, I. C., Jones,
P. D., and Osborn, T.: CRU TS4.04: Climatic Research Unit (CRU) Time-Series
(TS) version 4.04 of high-resolution gridded data of month-by-month variation
in climate (January 1901 – December 2019), Centre for Environmental Data Analysis [data set], https://catalogue.ceda.ac.uk/uuid/89e1e34ec3554dc98594a5732622bce9 (last access: 25 May 2021), 2020. a
Vandentorren, S., Suzan, F., Medina, S., Pascal, M., Maulpoix, A., Cohen,
J.-C., and Ledrans, M.: Mortality in 13 French cities during the August 2003 heat wave, Am. J. Public Health, 94, 1518–1520, https://doi.org/10.2105/AJPH.94.9.1518, 2004. a
Vernieuwe, H., Vandenberghe, S., De Baets, B., and Verhoest, N. E. C.: A continuous rainfall model based on vine copulas, Hydrol. Earth Syst. Sci., 19, 2685–2699, https://doi.org/10.5194/hess-19-2685-2015, 2015. a
Villarini, G., Smith, J. A., Ntelekos, A. A., and Schwarz, U.: Annual maximum
and peaks-over-threshold analyses of daily rainfall accumulations for
Austria, J. Geophys. Res.-Atmos., 116, D05103, https://doi.org/10.1029/2010JD015038, 2011.
a
Wang, Q., Danilov, S., Sidorenko, D., Timmermann, R., Wekerle, C., Wang, X., Jung, T., and Schröter, J.: The Finite Element Sea Ice-Ocean Model (FESOM) v.1.4: formulation of an ocean general circulation model, Geosci. Model Dev., 7, 663–693, https://doi.org/10.5194/gmd-7-663-2014, 2014. a
Weigel, K., Bock, L., Gier, B. K., Lauer, A., Righi, M., Schlund, M., Adeniyi, K., Andela, B., Arnone, E., Berg, P., Caron, L.-P., Cionni, I., Corti, S., Drost, N., Hunter, A., Lledó, L., Mohr, C. W., Paçal, A., Pérez-Zanón, N., Predoi, V., Sandstad, M., Sillmann, J., Sterl, A., Vegas-Regidor, J., von Hardenberg, J., and Eyring, V.: Earth System Model Evaluation Tool (ESMValTool) v2.0 – diagnostics for extreme events, regional and impact evaluation, and analysis of Earth system models in CMIP, Geosci. Model Dev., 14, 3159–3184, https://doi.org/10.5194/gmd-14-3159-2021, 2021. a
Zhang, Q., Li, J., Singh, V. P., and Xu, C.-Y.: Copula-based spatio-temporal
patterns of precipitation extremes in China, Int. J. Climatol., 33, 1140–1152, https://doi.org/10.1002/joc.3499, 2013. a
Zhang, X., Alexander, L., Hegerl, G. C., Jones, P., Tank, A. K., Peterson,
T. C., Trewin, B., and Zwiers, F. W.: Indices for monitoring changes in
extremes based on daily temperature and precipitation data, WIREs Clim.
Change, 2, 851–870, https://doi.org/10.1002/wcc.147, 2011. a, b
Zscheischler, J., Mahecha, M. D., and Harmeling, S.: Climate classifications:
the value of unsupervised clustering, proceedings of the International
Conference on Computational Science, ICCS 2012, Procedia Comput. Sci., 9, 897–906, https://doi.org/10.1016/j.procs.2012.04.096, 2012. a
Zscheischler, J., Michalak, A. M., Schwalm, C., Mahecha, M. D., Huntzinger, D. N., Reichstein, M., Berthier, G., Ciais, P., Cook, R. B., El-Masri, B., Huang, M., Ito, A., Jain, A., King, A., Lei, H., Lu, C., Mao, J., Peng, S., Poulter, B., Ricciuto, D., Shi, X., Tao, B., Tian, H., Viovy, N., Wang, W., Wei, Y., Yang, J., and Zeng, N.: Impact of large-scale climate extremes on biospheric carbon fluxes: An intercomparison based on MsTMIP data, Global Biogeochem. Cy., 28, 585–600,
https://doi.org/10.1002/2014GB004826, 2014. a
Short summary
Climate models are of paramount importance to predict future climate changes. Since many severe consequences of climate change are due to extreme events, the accurate behaviour of models in terms of extremes needs to be validated thoroughly. We present a method for model validation in terms of climate extremes and an algorithm to detect regions in which extremes tend to occur at the same time. These methods are applied to data from different climate models and to observational data.
Climate models are of paramount importance to predict future climate changes. Since many severe...
