Articles | Volume 7, issue 6
https://doi.org/10.5194/gmd-7-3111-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-7-3111-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Development and technical paper
| 
18 Dec 2014
Development and technical paper |
| 18 Dec 2014
A simplified permafrost-carbon model for long-term climate studies with the CLIMBER-2 coupled earth system model
K. A. Crichton
CORRESPONDING AUTHOR
CNRS, LGGE (UMR5183), 38041 Grenoble, France
Univ. Grenoble Alpes, LGGE (UMR5183), 38041 Grenoble, France
D. M. Roche
CEA/INSU-CNRS/UVSQ, LSCE (UMR8212), Centre d'Etudes de Saclay CEA-Orme des Merisiers, bat. 701 91191 Gif-sur-Yvette CEDEX, France
Cluster Earth and Climate, Department of Earth Sciences, Faculty of Earth and Life Sciences, Vrije Universiteit Amsterdam De Boelelaan 1085, 1081 HV Amsterdam, the Netherlands
G. Krinner
CNRS, LGGE (UMR5183), 38041 Grenoble, France
Univ. Grenoble Alpes, LGGE (UMR5183), 38041 Grenoble, France
J. Chappellaz
CNRS, LGGE (UMR5183), 38041 Grenoble, France
Univ. Grenoble Alpes, LGGE (UMR5183), 38041 Grenoble, France
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Eleanor J. Burke, Yu Zhang, and Gerhard Krinner
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Manuscript not accepted for further review
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Lawrence Mudryk, María Santolaria-Otín, Gerhard Krinner, Martin Ménégoz, Chris Derksen, Claire Brutel-Vuilmet, Mike Brady, and Richard Essery
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Brett Metcalfe, Bryan C. Lougheed, Claire Waelbroeck, and Didier M. Roche
Clim. Past, 16, 885–910, https://doi.org/10.5194/cp-16-885-2020, https://doi.org/10.5194/cp-16-885-2020, 2020
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Lise Missiaen, Nathaelle Bouttes, Didier M. Roche, Jean-Claude Dutay, Aurélien Quiquet, Claire Waelbroeck, Sylvain Pichat, and Jean-Yves Peterschmitt
Clim. Past, 16, 867–883, https://doi.org/10.5194/cp-16-867-2020, https://doi.org/10.5194/cp-16-867-2020, 2020
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We present a model that can simulate the dynamics of peatland area extent and the vertical buildup of peat. The model is validated across a range of northern peatland sites and over the Northern Hemisphere (> 30° N). It is able to reproduce the spatial extent of northern peatlands and peat carbon accumulation over the Holocene.
Gerhard Krinner, Chris Derksen, Richard Essery, Mark Flanner, Stefan Hagemann, Martyn Clark, Alex Hall, Helmut Rott, Claire Brutel-Vuilmet, Hyungjun Kim, Cécile B. Ménard, Lawrence Mudryk, Chad Thackeray, Libo Wang, Gabriele Arduini, Gianpaolo Balsamo, Paul Bartlett, Julia Boike, Aaron Boone, Frédérique Chéruy, Jeanne Colin, Matthias Cuntz, Yongjiu Dai, Bertrand Decharme, Jeff Derry, Agnès Ducharne, Emanuel Dutra, Xing Fang, Charles Fierz, Josephine Ghattas, Yeugeniy Gusev, Vanessa Haverd, Anna Kontu, Matthieu Lafaysse, Rachel Law, Dave Lawrence, Weiping Li, Thomas Marke, Danny Marks, Martin Ménégoz, Olga Nasonova, Tomoko Nitta, Masashi Niwano, John Pomeroy, Mark S. Raleigh, Gerd Schaedler, Vladimir Semenov, Tanya G. Smirnova, Tobias Stacke, Ulrich Strasser, Sean Svenson, Dmitry Turkov, Tao Wang, Nander Wever, Hua Yuan, Wenyan Zhou, and Dan Zhu
Geosci. Model Dev., 11, 5027–5049, https://doi.org/10.5194/gmd-11-5027-2018, https://doi.org/10.5194/gmd-11-5027-2018, 2018
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This paper provides an overview of a coordinated international experiment to determine the strengths and weaknesses in how climate models treat snow. The models will be assessed at point locations using high-quality reference measurements and globally using satellite-derived datasets. How well climate models simulate snow-related processes is important because changing snow cover is an important part of the global climate system and provides an important freshwater resource for human use.
Aurélien Quiquet, Christophe Dumas, Catherine Ritz, Vincent Peyaud, and Didier M. Roche
Geosci. Model Dev., 11, 5003–5025, https://doi.org/10.5194/gmd-11-5003-2018, https://doi.org/10.5194/gmd-11-5003-2018, 2018
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This paper presents the GRISLI (Grenoble ice sheet and land ice) model in its newest revision. We present the recent model improvements from its original version (Ritz et al., 2001), together with a discussion of the model performance in reproducing the present-day Antarctic ice sheet geometry and the grounding line advances and retreats during the last 400 000 years. We show that GRISLI is a computationally cheap model, able to reproduce the large-scale behaviour of ice sheets.
Didier M. Roche, Claire Waelbroeck, Brett Metcalfe, and Thibaut Caley
Geosci. Model Dev., 11, 3587–3603, https://doi.org/10.5194/gmd-11-3587-2018, https://doi.org/10.5194/gmd-11-3587-2018, 2018
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The oxygen-18 signal recorded in fossil planktonic foraminifers has been used for over 50 years in many geoscience applications. However, different planktonic foraminifer species from the same sediment core generally yield distinct oxygen-18 signals, as a consequence of their specific living habitat in the water column and along the year. To explicitly take into account this variability for five common planktonic species, we developed the portable module FAME (Foraminifers As Modeled Entities).
Chloé Largeron, Gerhard Krinner, Philippe Ciais, and Claire Brutel-Vuilmet
Geosci. Model Dev., 11, 3279–3297, https://doi.org/10.5194/gmd-11-3279-2018, https://doi.org/10.5194/gmd-11-3279-2018, 2018
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Peatlands are widely present in boreal regions and contain large carbon stocks due to their hydrologic properties and high water content. We have enhanced the global land surface model ORCHIDEE by introducing boreal peatlands. These are considered as a new type of vegetation in the model, with specific hydrological properties for peat soil. In this paper, we focus on the representation of the hydrology of northern peatlands and on the evaluation of the hydrological impact of this implementation.
Masa Kageyama, Pascale Braconnot, Sandy P. Harrison, Alan M. Haywood, Johann H. Jungclaus, Bette L. Otto-Bliesner, Jean-Yves Peterschmitt, Ayako Abe-Ouchi, Samuel Albani, Patrick J. Bartlein, Chris Brierley, Michel Crucifix, Aisling Dolan, Laura Fernandez-Donado, Hubertus Fischer, Peter O. Hopcroft, Ruza F. Ivanovic, Fabrice Lambert, Daniel J. Lunt, Natalie M. Mahowald, W. Richard Peltier, Steven J. Phipps, Didier M. Roche, Gavin A. Schmidt, Lev Tarasov, Paul J. Valdes, Qiong Zhang, and Tianjun Zhou
Geosci. Model Dev., 11, 1033–1057, https://doi.org/10.5194/gmd-11-1033-2018, https://doi.org/10.5194/gmd-11-1033-2018, 2018
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The Paleoclimate Modelling Intercomparison Project (PMIP) takes advantage of the existence of past climate states radically different from the recent past to test climate models used for climate projections and to better understand these climates. This paper describes the PMIP contribution to CMIP6 (Coupled Model Intercomparison Project, 6th phase) and possible analyses based on PMIP results, as well as on other CMIP6 projects.
Nathaelle Bouttes, Didier Swingedouw, Didier M. Roche, Maria F. Sanchez-Goni, and Xavier Crosta
Clim. Past, 14, 239–253, https://doi.org/10.5194/cp-14-239-2018, https://doi.org/10.5194/cp-14-239-2018, 2018
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Atmospheric CO2 is key for climate change. CO2 is lower during the oldest warm period of the last million years, the interglacials, than during the most recent ones (since 430 000 years ago). This difference has not been explained yet, but could be due to changes of ocean circulation. We test this hypothesis and the role of vegetation and ice sheets using an intermediate complexity model. We show that only small changes of CO2 can be obtained, underlying missing feedbacks or mechanisms.
Chunjing Qiu, Dan Zhu, Philippe Ciais, Bertrand Guenet, Gerhard Krinner, Shushi Peng, Mika Aurela, Christian Bernhofer, Christian Brümmer, Syndonia Bret-Harte, Housen Chu, Jiquan Chen, Ankur R. Desai, Jiří Dušek, Eugénie S. Euskirchen, Krzysztof Fortuniak, Lawrence B. Flanagan, Thomas Friborg, Mateusz Grygoruk, Sébastien Gogo, Thomas Grünwald, Birger U. Hansen, David Holl, Elyn Humphreys, Miriam Hurkuck, Gerard Kiely, Janina Klatt, Lars Kutzbach, Chloé Largeron, Fatima Laggoun-Défarge, Magnus Lund, Peter M. Lafleur, Xuefei Li, Ivan Mammarella, Lutz Merbold, Mats B. Nilsson, Janusz Olejnik, Mikaell Ottosson-Löfvenius, Walter Oechel, Frans-Jan W. Parmentier, Matthias Peichl, Norbert Pirk, Olli Peltola, Włodzimierz Pawlak, Daniel Rasse, Janne Rinne, Gaius Shaver, Hans Peter Schmid, Matteo Sottocornola, Rainer Steinbrecher, Torsten Sachs, Marek Urbaniak, Donatella Zona, and Klaudia Ziemblinska
Geosci. Model Dev., 11, 497–519, https://doi.org/10.5194/gmd-11-497-2018, https://doi.org/10.5194/gmd-11-497-2018, 2018
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Northern peatlands store large amount of soil carbon and are vulnerable to climate change. We implemented peatland hydrological and carbon accumulation processes into the ORCHIDEE land surface model. The model was evaluated against EC measurements from 30 northern peatland sites. The model generally well reproduced the spatial gradient and temporal variations in GPP and NEE at these sites. Water table depth was not well predicted but had only small influence on simulated NEE.
Aurélien Quiquet, Didier M. Roche, Christophe Dumas, and Didier Paillard
Geosci. Model Dev., 11, 453–466, https://doi.org/10.5194/gmd-11-453-2018, https://doi.org/10.5194/gmd-11-453-2018, 2018
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Earth system models of intermediate complexity generally have a simplified model physics and a coarse model resolution. In this work we present the inclusion of an online dynamical downscaling of temperature and precipitation in such a model. This downscaling explicitly takes into account sub-grid topography. With this new model functionality we are able to simulate temperature and precipitation on a 40 km grid for the whole Northern Hemisphere from the native model resolution.
Matthieu Guimberteau, Dan Zhu, Fabienne Maignan, Ye Huang, Chao Yue, Sarah Dantec-Nédélec, Catherine Ottlé, Albert Jornet-Puig, Ana Bastos, Pierre Laurent, Daniel Goll, Simon Bowring, Jinfeng Chang, Bertrand Guenet, Marwa Tifafi, Shushi Peng, Gerhard Krinner, Agnès Ducharne, Fuxing Wang, Tao Wang, Xuhui Wang, Yilong Wang, Zun Yin, Ronny Lauerwald, Emilie Joetzjer, Chunjing Qiu, Hyungjun Kim, and Philippe Ciais
Geosci. Model Dev., 11, 121–163, https://doi.org/10.5194/gmd-11-121-2018, https://doi.org/10.5194/gmd-11-121-2018, 2018
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Improved projections of future Arctic and boreal ecosystem transformation require improved land surface models that integrate processes specific to these cold biomes. To this end, this study lays out relevant new parameterizations in the ORCHIDEE-MICT land surface model. These describe the interactions between soil carbon, soil temperature and hydrology, and their resulting feedbacks on water and CO2 fluxes, in addition to a recently developed fire module.
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.
Eleanor J. Burke, Altug Ekici, Ye Huang, Sarah E. Chadburn, Chris Huntingford, Philippe Ciais, Pierre Friedlingstein, Shushi Peng, and Gerhard Krinner
Biogeosciences, 14, 3051–3066, https://doi.org/10.5194/bg-14-3051-2017, https://doi.org/10.5194/bg-14-3051-2017, 2017
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There are large reserves of carbon within the permafrost which might be released to the atmosphere under global warming. Our models suggest this release may cause an additional global temperature increase of 0.005 to 0.2°C by the year 2100 and 0.01 to 0.34°C by the year 2300. Under climate mitigation scenarios this is between 1.5 and 9 % (by 2100) and between 6 and 16 % (by 2300) of the global mean temperature change. There is a large uncertainty associated with these results.
Pierre Burckel, Claire Waelbroeck, Yiming Luo, Didier M. Roche, Sylvain Pichat, Samuel L. Jaccard, Jeanne Gherardi, Aline Govin, Jörg Lippold, and François Thil
Clim. Past, 12, 2061–2075, https://doi.org/10.5194/cp-12-2061-2016, https://doi.org/10.5194/cp-12-2061-2016, 2016
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In this paper, we compare new and published Atlantic sedimentary Pa/Th data with Pa/Th simulated using stream functions generated under various climatic conditions. We show that during Greenland interstadials of the 20–50 ka period, the Atlantic meridional overturning circulation was very different from that of the Holocene. Moreover, southern-sourced waters dominated the Atlantic during Heinrich stadial 2, a slow northern-sourced water mass flowing above 2500 m in the North Atlantic.
Timothé Bolliet, Patrick Brockmann, Valérie Masson-Delmotte, Franck Bassinot, Valérie Daux, Dominique Genty, Amaelle Landais, Marlène Lavrieux, Elisabeth Michel, Pablo Ortega, Camille Risi, Didier M. Roche, Françoise Vimeux, and Claire Waelbroeck
Clim. Past, 12, 1693–1719, https://doi.org/10.5194/cp-12-1693-2016, https://doi.org/10.5194/cp-12-1693-2016, 2016
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This paper presents a new database of past climate proxies which aims to facilitate the distribution of data by using a user-friendly interface. Available data from the last 40 years are often fragmented, with lots of different formats, and online libraries are sometimes nonintuitive. We thus built a new dynamic web portal for data browsing, visualizing, and batch downloading of hundreds of datasets presenting a homogeneous format.
Ruza F. Ivanovic, Lauren J. Gregoire, Masa Kageyama, Didier M. Roche, Paul J. Valdes, Andrea Burke, Rosemarie Drummond, W. Richard Peltier, and Lev Tarasov
Geosci. Model Dev., 9, 2563–2587, https://doi.org/10.5194/gmd-9-2563-2016, https://doi.org/10.5194/gmd-9-2563-2016, 2016
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This manuscript presents the experiment design for the PMIP4 Last Deglaciation Core experiment: a transient simulation of the last deglaciation, 21–9 ka. Specified model boundary conditions include time-varying orbital parameters, greenhouse gases, ice sheets, ice meltwater fluxes and other geographical changes (provided for 26–0 ka). The context of the experiment and the choices for the boundary conditions are explained, along with the future direction of the working group.
Rachael H. Rhodes, Xavier Faïn, Edward J. Brook, Joseph R. McConnell, Olivia J. Maselli, Michael Sigl, Jon Edwards, Christo Buizert, Thomas Blunier, Jérôme Chappellaz, and Johannes Freitag
Clim. Past, 12, 1061–1077, https://doi.org/10.5194/cp-12-1061-2016, https://doi.org/10.5194/cp-12-1061-2016, 2016
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Local artifacts in ice core methane data are superimposed on consistent records of past atmospheric variability. These artifacts are not related to past atmospheric history and care should be taken to avoid interpreting them as such. By investigating five polar ice cores from sites with different conditions, we relate isolated methane spikes to melt layers and decimetre-scale variations as "trapping signal" associated with a difference in timing of air bubble closure in adjacent firn layers.
Marianne Bügelmayer-Blaschek, Didier M. Roche, Hans Renssen, and Claire Waelbroeck
Clim. Past Discuss., https://doi.org/10.5194/cp-2016-31, https://doi.org/10.5194/cp-2016-31, 2016
Revised manuscript has not been submitted
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Using the global isotope-enabled climate – iceberg model iLOVECLIM we performed three experiments to investigate the mechanisms behind the simulated δ18Ocalcite pattern applying a Heinrich event like iceberg forcing. Our model results display two main patterns in the δ18Ocalcite signal. First, we find regions that display almost no response in δ18Ocalcite and second, regions where the δ18Ocalcite pattern closely follows the δ18Oseawater signal.
S. Peng, P. Ciais, G. Krinner, T. Wang, I. Gouttevin, A. D. McGuire, D. Lawrence, E. Burke, X. Chen, B. Decharme, C. Koven, A. MacDougall, A. Rinke, K. Saito, W. Zhang, R. Alkama, T. J. Bohn, C. Delire, T. Hajima, D. Ji, D. P. Lettenmaier, P. A. Miller, J. C. Moore, B. Smith, and T. Sueyoshi
The Cryosphere, 10, 179–192, https://doi.org/10.5194/tc-10-179-2016, https://doi.org/10.5194/tc-10-179-2016, 2016
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Soil temperature change is a key indicator of the dynamics of permafrost. Using nine process-based ecosystem models with permafrost processes, a large spread of soil temperature trends across the models. Air temperature and longwave downward radiation are the main drivers of soil temperature trends. Based on an emerging observation constraint method, the total boreal near-surface permafrost area decrease comprised between 39 ± 14 × 103 and 75 ± 14 × 103 km2 yr−1 from 1960 to 2000.
S. L. Cornford, D. F. Martin, A. J. Payne, E. G. Ng, A. M. Le Brocq, R. M. Gladstone, T. L. Edwards, S. R. Shannon, C. Agosta, M. R. van den Broeke, H. H. Hellmer, G. Krinner, S. R. M. Ligtenberg, R. Timmermann, and D. G. Vaughan
The Cryosphere, 9, 1579–1600, https://doi.org/10.5194/tc-9-1579-2015, https://doi.org/10.5194/tc-9-1579-2015, 2015
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We used a high-resolution ice sheet model capable of resolving grounding line dynamics (BISICLES) to compute responses of the major West Antarctic ice streams to projections of ocean and atmospheric warming. This is computationally demanding, and although other groups have considered parts of West Antarctica, we think this is the first calculation for the whole region at the sub-kilometer resolution that we show is required.
D. Zhu, S. S. Peng, P. Ciais, N. Viovy, A. Druel, M. Kageyama, G. Krinner, P. Peylin, C. Ottlé, S. L. Piao, B. Poulter, D. Schepaschenko, and A. Shvidenko
Geosci. Model Dev., 8, 2263–2283, https://doi.org/10.5194/gmd-8-2263-2015, https://doi.org/10.5194/gmd-8-2263-2015, 2015
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This study presents a new parameterization of the vegetation dynamics module in the process-based ecosystem model ORCHIDEE for mid- to high-latitude regions, showing significant improvements in the modeled distribution of tree functional types north of 40°N. A new set of metrics is proposed to quantify the performance of ORCHIDEE, which integrates uncertainties in the observational data sets.
M. A. Rawlins, A. D. McGuire, J. S. Kimball, P. Dass, D. Lawrence, E. Burke, X. Chen, C. Delire, C. Koven, A. MacDougall, S. Peng, A. Rinke, K. Saito, W. Zhang, R. Alkama, T. J. Bohn, P. Ciais, B. Decharme, I. Gouttevin, T. Hajima, D. Ji, G. Krinner, D. P. Lettenmaier, P. Miller, J. C. Moore, B. Smith, and T. Sueyoshi
Biogeosciences, 12, 4385–4405, https://doi.org/10.5194/bg-12-4385-2015, https://doi.org/10.5194/bg-12-4385-2015, 2015
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We used outputs from nine models to better understand land-atmosphere CO2 exchanges across Northern Eurasia over the period 1960-1990. Model estimates were assessed against independent ground and satellite measurements. We find that the models show a weakening of the CO2 sink over time; the models tend to overestimate respiration, causing an underestimate in NEP; the model range in regional NEP is twice the multimodel mean. Residence time for soil carbon decreased, amid a gain in carbon storage.
A. Ekici, S. Chadburn, N. Chaudhary, L. H. Hajdu, A. Marmy, S. Peng, J. Boike, E. Burke, A. D. Friend, C. Hauck, G. Krinner, M. Langer, P. A. Miller, and C. Beer
The Cryosphere, 9, 1343–1361, https://doi.org/10.5194/tc-9-1343-2015, https://doi.org/10.5194/tc-9-1343-2015, 2015
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This paper compares the performance of different land models in estimating soil thermal regimes at distinct cold region landscape types. Comparing models with different processes reveal the importance of surface insulation (snow/moss layer) and soil internal processes (heat/water transfer). The importance of model processes also depend on site conditions such as high/low snow cover, dry/wet soil types.
M. Bügelmayer, D. M. Roche, and H. Renssen
Geosci. Model Dev., 8, 2139–2151, https://doi.org/10.5194/gmd-8-2139-2015, https://doi.org/10.5194/gmd-8-2139-2015, 2015
N. Bouttes, D. M. Roche, V. Mariotti, and L. Bopp
Geosci. Model Dev., 8, 1563–1576, https://doi.org/10.5194/gmd-8-1563-2015, https://doi.org/10.5194/gmd-8-1563-2015, 2015
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We describe the development of a relatively simple climate model to include a model of the carbon cycle in the ocean. The carbon cycle consists of the exchange of carbon between the atmosphere, land vegetation and ocean. In the ocean, carbon exists in organic form, such as plankton which grows and dies, and inorganic forms, such as dissolved CO2. With this we will be able to explore long-standing questions such as why the atmospheric CO2 has changed over time during the last million years.
D. C. Kitover, R. van Balen, D. M. Roche, J. Vandenberghe, and H. Renssen
Geosci. Model Dev., 8, 1445–1460, https://doi.org/10.5194/gmd-8-1445-2015, https://doi.org/10.5194/gmd-8-1445-2015, 2015
M. Bügelmayer, D. M. Roche, and H. Renssen
The Cryosphere, 9, 821–835, https://doi.org/10.5194/tc-9-821-2015, https://doi.org/10.5194/tc-9-821-2015, 2015
T. Caley, D. M. Roche, C. Waelbroeck, and E. Michel
Clim. Past, 10, 1939–1955, https://doi.org/10.5194/cp-10-1939-2014, https://doi.org/10.5194/cp-10-1939-2014, 2014
D. M. Roche, C. Dumas, M. Bügelmayer, S. Charbit, and C. Ritz
Geosci. Model Dev., 7, 1377–1394, https://doi.org/10.5194/gmd-7-1377-2014, https://doi.org/10.5194/gmd-7-1377-2014, 2014
P. Beghin, S. Charbit, C. Dumas, M. Kageyama, D. M. Roche, and C. Ritz
Clim. Past, 10, 345–358, https://doi.org/10.5194/cp-10-345-2014, https://doi.org/10.5194/cp-10-345-2014, 2014
S. Hou, J. Chappellaz, D. Raynaud, V. Masson-Delmotte, J. Jouzel, P. Bousquet, and D. Hauglustaine
Clim. Past, 9, 2549–2554, https://doi.org/10.5194/cp-9-2549-2013, https://doi.org/10.5194/cp-9-2549-2013, 2013
D. M. Roche
Geosci. Model Dev., 6, 1481–1491, https://doi.org/10.5194/gmd-6-1481-2013, https://doi.org/10.5194/gmd-6-1481-2013, 2013
D. M. Roche and T. Caley
Geosci. Model Dev., 6, 1493–1504, https://doi.org/10.5194/gmd-6-1493-2013, https://doi.org/10.5194/gmd-6-1493-2013, 2013
T. Caley and D. M. Roche
Geosci. Model Dev., 6, 1505–1516, https://doi.org/10.5194/gmd-6-1505-2013, https://doi.org/10.5194/gmd-6-1505-2013, 2013
I. Gouttevin, A. Bartsch, G. Krinner, and V. Naeimi
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-10-11241-2013, https://doi.org/10.5194/hessd-10-11241-2013, 2013
Manuscript not accepted for further review
S. Charbit, C. Dumas, M. Kageyama, D. M. Roche, and C. Ritz
The Cryosphere, 7, 681–698, https://doi.org/10.5194/tc-7-681-2013, https://doi.org/10.5194/tc-7-681-2013, 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
V. Favier, C. Agosta, S. Parouty, G. Durand, G. Delaygue, H. Gallée, A.-S. Drouet, A. Trouvilliez, and G. Krinner
The Cryosphere, 7, 583–597, https://doi.org/10.5194/tc-7-583-2013, https://doi.org/10.5194/tc-7-583-2013, 2013
M. Ménégoz, G. Krinner, Y. Balkanski, A. Cozic, O. Boucher, and P. Ciais
The Cryosphere, 7, 537–554, https://doi.org/10.5194/tc-7-537-2013, https://doi.org/10.5194/tc-7-537-2013, 2013
M.-N. Woillez, M. Kageyama, N. Combourieu-Nebout, and G. Krinner
Biogeosciences, 10, 1561–1582, https://doi.org/10.5194/bg-10-1561-2013, https://doi.org/10.5194/bg-10-1561-2013, 2013
C. Brutel-Vuilmet, M. Ménégoz, and G. Krinner
The Cryosphere, 7, 67–80, https://doi.org/10.5194/tc-7-67-2013, https://doi.org/10.5194/tc-7-67-2013, 2013
J. Zumaque, F. Eynaud, S. Zaragosi, F. Marret, K. M. Matsuzaki, C. Kissel, D. M. Roche, B. Malaizé, E. Michel, I. Billy, T. Richter, and E. Palis
Clim. Past, 8, 1997–2017, https://doi.org/10.5194/cp-8-1997-2012, https://doi.org/10.5194/cp-8-1997-2012, 2012
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Using feature importance as exploratory data analysis tool on earth system models
CropSuite – 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)
Split-explicit external mode solver in the finite volume sea ice–ocean model FESOM2
Applying double cropping and interactive irrigation in the North China Plain using WRF4.5
The sea ice component of GC5: coupling SI3 to HadGEM3 using conductive fluxes
CICE on a C-grid: new momentum, stress, and transport schemes for CICEv6.5
HyPhAICC v1.0: a hybrid physics–AI approach for probability fields advection shown through an application to cloud cover nowcasting
CICERO Simple Climate Model (CICERO-SCM v1.1.1) – an improved simple climate model with a parameter calibration tool
A non-intrusive, multi-scale, and flexible coupling interface in WRF
T&C-CROP: Representing mechanistic crop growth with a terrestrial biosphere model (T&C, v1.5): Model formulation and validation
Development of a plant carbon–nitrogen interface coupling framework in a coupled biophysical-ecosystem–biogeochemical model (SSiB5/TRIFFID/DayCent-SOM v1.0)
The Earth Science Box Modeling Toolkit (ESBMTK)
High Resolution Model Intercomparison Project phase 2 (HighResMIP2) towards CMIP7
Dynamical Madden–Julian Oscillation forecasts using an ensemble subseasonal-to-seasonal forecast system of the IAP-CAS model
Baseline Climate Variables for Earth System Modelling
The DOE E3SM Version 2.1: Overview and Assessment of the Impacts of Parameterized Ocean Submesoscales
Evaluation of atmospheric rivers in reanalyses and climate models in a new metrics framework
Implementation of a brittle sea ice rheology in an Eulerian, finite-difference, C-grid modeling framework: impact on the simulated deformation of sea ice in the Arctic
HSW-V v1.0: localized injections of interactive volcanic aerosols and their climate impacts in a simple general circulation model
A 3D-Var assimilation scheme for vertical velocity with CMA-MESO v5.0
Updating the radiation infrastructure in MESSy (based on MESSy version 2.55)
An urban module coupled with the Variable Infiltration Capacity model to improve hydrothermal simulations in urban systems
Bayesian hierarchical model for bias-correcting climate models
Evaluation of the coupling of EMACv2.55 to the land surface and vegetation model JSBACHv4
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.
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.
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.
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.
Michael Nole, Jonah Bartrand, Fawz Naim, and Glenn Hammond
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-162, https://doi.org/10.5194/gmd-2024-162, 2024
Revised manuscript accepted for GMD
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Safe carbon dioxide (CO2) storage is likely to be critical for mitigating some of the most dangerous 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 sub-sea CO2 injection.
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.
Erik Gustafsson, Bo G. Gustafsson, Martijn Hermans, Christoph Humborg, and Christian Stranne
Geosci. Model Dev., 17, 7157–7179, https://doi.org/10.5194/gmd-17-7157-2024, https://doi.org/10.5194/gmd-17-7157-2024, 2024
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Methane (CH4) cycling in the Baltic Proper is studied through model simulations, enabling a first estimate of key CH4 fluxes. A preliminary budget identifies benthic CH4 release as the dominant source and two main sinks: CH4 oxidation in the water (92 % of sinks) and outgassing to the atmosphere (8 % of sinks). This study addresses CH4 emissions from coastal seas and is a first step toward understanding the relative importance of open-water outgassing compared with local coastal hotspots.
Daniel Ries, Katherine Goode, Kellie McClernon, and Benjamin Hillman
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-133, https://doi.org/10.5194/gmd-2024-133, 2024
Revised manuscript accepted for GMD
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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.
Florian Zabel, Matthias Knüttel, and Benjamin Poschlod
EGUsphere, https://doi.org/10.5194/egusphere-2024-2526, https://doi.org/10.5194/egusphere-2024-2526, 2024
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CropSuite is a fuzzy-logic based high resolution open-source crop suitability model considering the impact of climate variability. We apply CropSuite for 48 important staple and cash crops at 1 km spatial resolution for Africa. We find that climate variability significantly impacts on suitable areas, but also affects optimal sowing dates, and multiple cropping potentials. The results provide information that can be used 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. Discuss., https://doi.org/10.5194/gmd-2024-135, https://doi.org/10.5194/gmd-2024-135, 2024
Revised manuscript accepted for GMD
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The Icosahedral Nonhydrostatic (ICON) Model 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.
Tridib Banerjee, Patrick Scholz, Sergey Danilov, Knut Klingbeil, and Dmitry Sidorenko
Geosci. Model Dev., 17, 7051–7065, https://doi.org/10.5194/gmd-17-7051-2024, https://doi.org/10.5194/gmd-17-7051-2024, 2024
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In this paper we propose a new alternative to one of the functionalities of the sea ice model FESOM2. The alternative we propose allows the model to capture and simulate fast changes in quantities like sea surface elevation more accurately. We also demonstrate that the new alternative is faster and more adept at taking advantages of highly parallelized computing infrastructure. We therefore show that this new alternative is a great addition to the sea ice model FESOM2.
Yuwen Fan, Zhao Yang, Min-Hui Lo, Jina Hur, and Eun-Soon Im
Geosci. Model Dev., 17, 6929–6947, https://doi.org/10.5194/gmd-17-6929-2024, https://doi.org/10.5194/gmd-17-6929-2024, 2024
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Irrigated agriculture in the North China Plain (NCP) has a significant impact on the local climate. To better understand this impact, we developed a specialized model specifically for the NCP region. This model allows us to simulate the double-cropping vegetation and the dynamic irrigation practices that are commonly employed in the NCP. This model shows improved performance in capturing the general crop growth, such as crop stages, biomass, crop yield, and vegetation greenness.
Ed Blockley, Emma Fiedler, Jeff Ridley, Luke Roberts, Alex West, Dan Copsey, Daniel Feltham, Tim Graham, David Livings, Clement Rousset, David Schroeder, and Martin Vancoppenolle
Geosci. Model Dev., 17, 6799–6817, https://doi.org/10.5194/gmd-17-6799-2024, https://doi.org/10.5194/gmd-17-6799-2024, 2024
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This paper documents the sea ice model component of the latest Met Office coupled model configuration, which will be used as the physical basis for UK contributions to CMIP7. Documentation of science options used in the configuration are given along with a brief model evaluation. This is the first UK configuration to use NEMO’s new SI3 sea ice model. We provide details on how SI3 was adapted to work with Met Office coupling methodology and documentation of coupling processes in the model.
Jean-François Lemieux, William H. Lipscomb, Anthony Craig, David A. Bailey, Elizabeth C. Hunke, Philippe Blain, Till A. S. Rasmussen, Mats Bentsen, Frédéric Dupont, David Hebert, and Richard Allard
Geosci. Model Dev., 17, 6703–6724, https://doi.org/10.5194/gmd-17-6703-2024, https://doi.org/10.5194/gmd-17-6703-2024, 2024
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We present the latest version of the CICE model. It solves equations that describe the dynamics and the growth and melt of sea ice. To do so, the domain is divided into grid cells and variables are positioned at specific locations in the cells. A new implementation (C-grid) is presented, with the velocity located on cell edges. Compared to the previous B-grid, the C-grid allows for a natural coupling with some oceanic and atmospheric models. It also allows for ice transport in narrow channels.
Rachid El Montassir, Olivier Pannekoucke, and Corentin Lapeyre
Geosci. Model Dev., 17, 6657–6681, https://doi.org/10.5194/gmd-17-6657-2024, https://doi.org/10.5194/gmd-17-6657-2024, 2024
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This study introduces a novel approach that combines physics and artificial intelligence (AI) for improved cloud cover forecasting. This approach outperforms traditional deep learning (DL) methods in producing realistic and physically consistent results while requiring less training data. This architecture provides a promising solution to overcome the limitations of classical AI methods and contributes to open up new possibilities for combining physical knowledge with deep learning models.
Marit Sandstad, Borgar Aamaas, Ane Nordlie Johansen, Marianne Tronstad Lund, Glen Philip Peters, Bjørn Hallvard Samset, Benjamin Mark Sanderson, and Ragnhild Bieltvedt Skeie
Geosci. Model Dev., 17, 6589–6625, https://doi.org/10.5194/gmd-17-6589-2024, https://doi.org/10.5194/gmd-17-6589-2024, 2024
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The CICERO-SCM has existed as a Fortran model since 1999 that calculates the radiative forcing and concentrations from emissions and is an upwelling diffusion energy balance model of the ocean that calculates temperature change. In this paper, we describe an updated version ported to Python and publicly available at https://github.com/ciceroOslo/ciceroscm (https://doi.org/10.5281/zenodo.10548720). This version contains functionality for parallel runs and automatic calibration.
Sébastien Masson, Swen Jullien, Eric Maisonnave, David Gill, Guillaume Samson, Mathieu Le Corre, and Lionel Renault
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-140, https://doi.org/10.5194/gmd-2024-140, 2024
Revised manuscript accepted for GMD
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This article details a new feature we implemented in the most popular regional atmospheric model (WRF). This feature allows data to be exchanged 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.
Jordi Buckley Paules, Simone Fatichi, Bonnie Warring, and Athanasios Paschalis
EGUsphere, https://doi.org/10.5194/egusphere-2024-2072, https://doi.org/10.5194/egusphere-2024-2072, 2024
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We outline and validate developments to the pre-existing process-based model T&C to better represent cropland processes. Foreseen applications of T&C-CROP include hydrological and carbon storage implications of land-use transitions involving crop, forest, and pasture conversion, as well as studies on optimal irrigation and fertilization under a changing climate.
Zheng Xiang, Yongkang Xue, Weidong Guo, Melannie D. Hartman, Ye Liu, and William J. Parton
Geosci. Model Dev., 17, 6437–6464, https://doi.org/10.5194/gmd-17-6437-2024, https://doi.org/10.5194/gmd-17-6437-2024, 2024
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A process-based plant carbon (C)–nitrogen (N) interface coupling framework has been developed which mainly focuses on plant resistance and N-limitation effects on photosynthesis, plant respiration, and plant phenology. A dynamic C / N ratio is introduced to represent plant resistance and self-adjustment. The framework has been implemented in a coupled biophysical-ecosystem–biogeochemical model, and testing results show a general improvement in simulating plant properties with this framework.
Ulrich Georg Wortmann, Tina Tsan, Mahrukh Niazi, Ruben Navasardyan, Magnus-Roland Marun, Bernardo S. Chede, Jingwen Zhong, and Morgan Wolfe
EGUsphere, https://doi.org/10.5194/egusphere-2024-1864, https://doi.org/10.5194/egusphere-2024-1864, 2024
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The Earth Science Box Modeling Toolkit (ESBMTK) is a Python library designed to separate model description from numerical implementation. This approach results in well-documented, easily readable, and maintainable model code, allowing students and researchers to concentrate on conceptual challenges rather than mathematical intricacies.
Malcolm John 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
EGUsphere, https://doi.org/10.5194/egusphere-2024-2582, https://doi.org/10.5194/egusphere-2024-2582, 2024
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HighResMIP2 is a model intercomparison project focussing on high resolution global climate models, that is those with grid spacings of 25 km or less in atmosphere and ocean, using simulations of decades to a century or so 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.
Yangke Liu, Qing Bao, Bian He, Xiaofei Wu, Jing Yang, Yimin Liu, Guoxiong Wu, Tao Zhu, Siyuan Zhou, Yao Tang, Ankang Qu, Yalan Fan, Anling Liu, Dandan Chen, Zhaoming Luo, Xing Hu, and Tongwen Wu
Geosci. Model Dev., 17, 6249–6275, https://doi.org/10.5194/gmd-17-6249-2024, https://doi.org/10.5194/gmd-17-6249-2024, 2024
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We give an overview of the Institute of Atmospheric Physics–Chinese Academy of Sciences subseasonal-to-seasonal ensemble forecasting system and Madden–Julian Oscillation forecast evaluation of the system. Compared to other S2S models, the IAP-CAS model has its benefits but also biases, i.e., underdispersive ensemble, overestimated amplitude, and faster propagation speed when forecasting MJO. We provide a reason for these biases and prospects for further improvement of this system in the future.
Martin Juckes, Karl E. Taylor, Fabrizio Antonio, David Brayshaw, Carlo Buontempo, Jian Cao, Paul J. Durack, Michio Kawamiya, Hyungjun Kim, Tomas Lovato, Chloe Mackallah, Matthew Mizielinski, Alessandra Nuzzo, Martina Stockhause, Daniele Visioni, Jeremy Walton, Briony Turner, Eleanor O’Rourke, and Beth Dingley
EGUsphere, https://doi.org/10.5194/egusphere-2024-2363, https://doi.org/10.5194/egusphere-2024-2363, 2024
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The Baseline Climate Variables for Earth System Modelling (ESM-BCVs) are defined as a list of 132 variables which have high utility for the evaluation and exploitation of climate simulations. The list reflects the most heavily used variables from Earth System Models, based on an assessment of data publication and download records from the largest archive of global climate projects.
Katherine Smith, Alice M. Barthel, LeAnn M. Conlon, Luke P. Van Roekel, Anthony Bartoletti, Jean-Christophe Golez, Chengzhu Zhang, Carolyn Branecky Begeman, James J. Benedict, Gautum Bisht, Yan Feng, Walter Hannah, Bryce E. Harrop, Nicole Jeffery, Wuyin Lin, Po-Lun Ma, Mathew E. Maltrud, Mark R. Petersen, Balwinder Singh, Qi Tang, Teklu Tesfa, Jonathan D. Wolfe, Shaocheng Xie, Xue Zheng, Karthik Balaguru, Oluwayemi Garuba, Peter Gleckler, Aixue Hu, Jiwoo Lee, Ben Moore-Maley, and Ana C. Ordonez
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-149, https://doi.org/10.5194/gmd-2024-149, 2024
Revised manuscript accepted for GMD
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Version 2.1 of the U.S. Department of Energy's Energy Exascale Earth System Model (E3SM) adds the Fox-Kemper et al. (2011) mixed layer eddy parameterization, which restratifies the ocean surface layer through an overturning streamfunction. Results include surface layer biases reduction in temperature, salinity, and sea-ice extent in the North Atlantic, a small strengthening of the Atlantic Meridional Overturning Circulation, and improvements in many atmospheric climatological variables.
Bo Dong, Paul Ullrich, Jiwoo Lee, Peter Gleckler, Kristin Chang, and Travis O'Brien
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-142, https://doi.org/10.5194/gmd-2024-142, 2024
Revised manuscript accepted for GMD
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1. A metrics package designed for easy analysis of AR characteristics and statistics is presented. 2. The tool is efficient for diagnosing systematic AR bias in climate models, and useful for evaluating new AR characteristics in model simulations. 3. 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).
Laurent Brodeau, Pierre Rampal, Einar Ólason, and Véronique Dansereau
Geosci. Model Dev., 17, 6051–6082, https://doi.org/10.5194/gmd-17-6051-2024, https://doi.org/10.5194/gmd-17-6051-2024, 2024
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A new brittle sea ice rheology, BBM, has been implemented into the sea ice component of NEMO. We describe how a new spatial discretization framework was introduced to achieve this. A set of idealized and realistic ocean and sea ice simulations of the Arctic have been performed using BBM and the standard viscous–plastic rheology of NEMO. When compared to satellite data, our simulations show that our implementation of BBM leads to a fairly good representation of sea ice deformations.
Joseph P. Hollowed, Christiane Jablonowski, Hunter Y. Brown, Benjamin R. Hillman, Diana L. Bull, and Joseph L. Hart
Geosci. Model Dev., 17, 5913–5938, https://doi.org/10.5194/gmd-17-5913-2024, https://doi.org/10.5194/gmd-17-5913-2024, 2024
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Large volcanic eruptions deposit material in the upper atmosphere, which is capable of altering temperature and wind patterns of Earth's atmosphere for subsequent years. This research describes a new method of simulating these effects in an idealized, efficient atmospheric model. A volcanic eruption of sulfur dioxide is described with a simplified set of physical rules, which eventually cools the planetary surface. This model has been designed as a test bed for climate attribution studies.
Hong Li, Yi Yang, Jian Sun, Yuan Jiang, Ruhui Gan, and Qian Xie
Geosci. Model Dev., 17, 5883–5896, https://doi.org/10.5194/gmd-17-5883-2024, https://doi.org/10.5194/gmd-17-5883-2024, 2024
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Vertical atmospheric motions play a vital role in convective-scale precipitation forecasts by connecting atmospheric dynamics with cloud development. A three-dimensional variational vertical velocity assimilation scheme is developed within the high-resolution CMA-MESO model, utilizing the adiabatic Richardson equation as the observation operator. A 10 d continuous run and an individual case study demonstrate improved forecasts, confirming the scheme's effectiveness.
Matthias Nützel, Laura Stecher, Patrick Jöckel, Franziska Winterstein, Martin Dameris, Michael Ponater, Phoebe Graf, and Markus Kunze
Geosci. Model Dev., 17, 5821–5849, https://doi.org/10.5194/gmd-17-5821-2024, https://doi.org/10.5194/gmd-17-5821-2024, 2024
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We extended the infrastructure of our modelling system to enable the use of an additional radiation scheme. After calibrating the model setups to the old and the new radiation scheme, we find that the simulation with the new scheme shows considerable improvements, e.g. concerning the cold-point temperature and stratospheric water vapour. Furthermore, perturbations of radiative fluxes associated with greenhouse gas changes, e.g. of methane, tend to be improved when the new scheme is employed.
Yibing Wang, Xianhong Xie, Bowen Zhu, Arken Tursun, Fuxiao Jiang, Yao Liu, Dawei Peng, and Buyun Zheng
Geosci. Model Dev., 17, 5803–5819, https://doi.org/10.5194/gmd-17-5803-2024, https://doi.org/10.5194/gmd-17-5803-2024, 2024
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Urban expansion intensifies challenges like urban heat and urban dry islands. To address this, we developed an urban module, VIC-urban, in the Variable Infiltration Capacity (VIC) model. Tested in Beijing, VIC-urban accurately simulated turbulent heat fluxes, runoff, and land surface temperature. We provide a reliable tool for large-scale simulations considering urban environment and a systematic urban modelling framework within VIC, offering crucial insights for urban planners and designers.
Jeremy Carter, Erick A. Chacón-Montalván, and Amber Leeson
Geosci. Model Dev., 17, 5733–5757, https://doi.org/10.5194/gmd-17-5733-2024, https://doi.org/10.5194/gmd-17-5733-2024, 2024
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Climate models are essential tools in the study of climate change and its wide-ranging impacts on life on Earth. However, the output is often afflicted with some bias. In this paper, a novel model is developed to predict and correct bias in the output of climate models. The model captures uncertainty in the correction and explicitly models underlying spatial correlation between points. These features are of key importance for climate change impact assessments and resulting decision-making.
Anna Martin, Veronika Gayler, Benedikt Steil, Klaus Klingmüller, Patrick Jöckel, Holger Tost, Jos Lelieveld, and Andrea Pozzer
Geosci. Model Dev., 17, 5705–5732, https://doi.org/10.5194/gmd-17-5705-2024, https://doi.org/10.5194/gmd-17-5705-2024, 2024
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The study evaluates the land surface and vegetation model JSBACHv4 as a replacement for the simplified submodel SURFACE in EMAC. JSBACH mitigates earlier problems of soil dryness, which are critical for vegetation modelling. When analysed using different datasets, the coupled model shows strong correlations of key variables, such as land surface temperature, surface albedo and radiation flux. The versatility of the model increases significantly, while the overall performance does not degrade.
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Short summary
Permafrost is ground that remains frozen for two or more consecutive years. An estimated 50% of the global below-ground organic carbon is stored in soils of the permafrost zone. This study presents the development and validation of a simplified permafrost-carbon mechanism for the CLIMBER-2 model. Our model development allows, for the first time, the study of the role of permafrost soils in the global carbon cycle for long timescales and for coupled palaeoclimate Earth system modelling studies.
Permafrost is ground that remains frozen for two or more consecutive years. An estimated 50% of...
