Articles | Volume 15, issue 5
https://doi.org/10.5194/gmd-15-2085-2022
© 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-15-2085-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
11 Mar 2022
Model description paper |
| 11 Mar 2022
| 11 Mar 2022
From emission scenarios to spatially resolved projections with a chain of computationally efficient emulators: coupling of MAGICC (v7.5.1) and MESMER (v0.8.3)
Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
Zebedee Nicholls
Climate and Energy College, The University of Melbourne, Parkville, Victoria, Australia
School of Geography, Earth and Atmospheric Sciences, The University of Melbourne, Parkville, Victoria, Australia
Climate Resource, Northcote, Victoria, Australia
Lukas Gudmundsson
Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
Mathias Hauser
Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
Malte Meinshausen
Climate and Energy College, The University of Melbourne, Parkville, Victoria, Australia
School of Geography, Earth and Atmospheric Sciences, The University of Melbourne, Parkville, Victoria, Australia
Climate Resource, Northcote, Victoria, Australia
Sonia I. Seneviratne
Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
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Karina von Schuckmann, Audrey Minière, Flora Gues, Francisco José Cuesta-Valero, Gottfried Kirchengast, Susheel Adusumilli, Fiammetta Straneo, Michaël Ablain, Richard P. Allan, Paul M. Barker, Hugo Beltrami, Alejandro Blazquez, Tim Boyer, Lijing Cheng, John Church, Damien Desbruyeres, Han Dolman, Catia M. Domingues, Almudena García-García, Donata Giglio, John E. Gilson, Maximilian Gorfer, Leopold Haimberger, Maria Z. Hakuba, Stefan Hendricks, Shigeki Hosoda, Gregory C. Johnson, Rachel Killick, Brian King, Nicolas Kolodziejczyk, Anton Korosov, Gerhard Krinner, Mikael Kuusela, Felix W. Landerer, Moritz Langer, Thomas Lavergne, Isobel Lawrence, Yuehua Li, John Lyman, Florence Marti, Ben Marzeion, Michael Mayer, Andrew H. MacDougall, Trevor McDougall, Didier Paolo Monselesan, Jan Nitzbon, Inès Otosaka, Jian Peng, Sarah Purkey, Dean Roemmich, Kanako Sato, Katsunari Sato, Abhishek Savita, Axel Schweiger, Andrew Shepherd, Sonia I. Seneviratne, Leon Simons, Donald A. Slater, Thomas Slater, Andrea K. Steiner, Toshio Suga, Tanguy Szekely, Wim Thiery, Mary-Louise Timmermans, Inne Vanderkelen, Susan E. Wjiffels, Tonghua Wu, and Michael Zemp
Earth Syst. Sci. Data, 15, 1675–1709, https://doi.org/10.5194/essd-15-1675-2023, https://doi.org/10.5194/essd-15-1675-2023, 2023
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Susanne Baur, Alexander Nauels, Zebedee Nicholls, Benjamin M. Sanderson, and Carl-Friedrich Schleussner
Earth Syst. Dynam., 14, 367–381, https://doi.org/10.5194/esd-14-367-2023, https://doi.org/10.5194/esd-14-367-2023, 2023
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Jarmo S. Kikstra, Zebedee R. J. Nicholls, Christopher J. Smith, Jared Lewis, Robin D. Lamboll, Edward Byers, Marit Sandstad, Malte Meinshausen, Matthew J. Gidden, Joeri Rogelj, Elmar Kriegler, Glen P. Peters, Jan S. Fuglestvedt, Ragnhild B. Skeie, Bjørn H. Samset, Laura Wienpahl, Detlef P. van Vuuren, Kaj-Ivar van der Wijst, Alaa Al Khourdajie, Piers M. Forster, Andy Reisinger, Roberto Schaeffer, and Keywan Riahi
Geosci. Model Dev., 15, 9075–9109, https://doi.org/10.5194/gmd-15-9075-2022, https://doi.org/10.5194/gmd-15-9075-2022, 2022
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Sjoukje Y. Philip, Sarah F. Kew, Geert Jan van Oldenborgh, Faron S. Anslow, Sonia I. Seneviratne, Robert Vautard, Dim Coumou, Kristie L. Ebi, Julie Arrighi, Roop Singh, Maarten van Aalst, Carolina Pereira Marghidan, Michael Wehner, Wenchang Yang, Sihan Li, Dominik L. Schumacher, Mathias Hauser, Rémy Bonnet, Linh N. Luu, Flavio Lehner, Nathan Gillett, Jordis S. Tradowsky, Gabriel A. Vecchi, Chris Rodell, Roland B. Stull, Rosie Howard, and Friederike E. L. Otto
Earth Syst. Dynam., 13, 1689–1713, https://doi.org/10.5194/esd-13-1689-2022, https://doi.org/10.5194/esd-13-1689-2022, 2022
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Ryan S. Padrón, Lukas Gudmundsson, Laibao Liu, Vincent Humphrey, and Sonia I. Seneviratne
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Steven J. De Hertog, Felix Havermann, Inne Vanderkelen, Suqi Guo, Fei Luo, Iris Manola, Dim Coumou, Edouard L. Davin, Gregory Duveiller, Quentin Lejeune, Julia Pongratz, Carl-Friedrich Schleussner, Sonia I. Seneviratne, and Wim Thiery
Earth Syst. Dynam., 13, 1305–1350, https://doi.org/10.5194/esd-13-1305-2022, https://doi.org/10.5194/esd-13-1305-2022, 2022
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Kathrin Wehrli, Fei Luo, Mathias Hauser, Hideo Shiogama, Daisuke Tokuda, Hyungjun Kim, Dim Coumou, Wilhelm May, Philippe Le Sager, Frank Selten, Olivia Martius, Robert Vautard, and Sonia I. Seneviratne
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Fei Luo, Frank Selten, Kathrin Wehrli, Kai Kornhuber, Philippe Le Sager, Wilhelm May, Thomas Reerink, Sonia I. Seneviratne, Hideo Shiogama, Daisuke Tokuda, Hyungjun Kim, and Dim Coumou
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Verena Bessenbacher, Sonia Isabelle Seneviratne, and Lukas Gudmundsson
Geosci. Model Dev., 15, 4569–4596, https://doi.org/10.5194/gmd-15-4569-2022, https://doi.org/10.5194/gmd-15-4569-2022, 2022
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Earth observations have many missing values. They are often filled using information from spatial and temporal contexts that mostly ignore information from related observed variables. We propose the gap-filling method CLIMFILL that additionally uses information from related variables. We test CLIMFILL using gap-free reanalysis data of variables related to soil–moisture climate interactions. CLIMFILL creates estimates for the missing values that recover the original dependence structure.
Charles D. Koven, Vivek K. Arora, Patricia Cadule, Rosie A. Fisher, Chris D. Jones, David M. Lawrence, Jared Lewis, Keith Lindsay, Sabine Mathesius, Malte Meinshausen, Michael Mills, Zebedee Nicholls, Benjamin M. Sanderson, Roland Séférian, Neil C. Swart, William R. Wieder, and Kirsten Zickfeld
Earth Syst. Dynam., 13, 885–909, https://doi.org/10.5194/esd-13-885-2022, https://doi.org/10.5194/esd-13-885-2022, 2022
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We explore the long-term dynamics of Earth's climate and carbon cycles under a pair of contrasting scenarios to the year 2300 using six models that include both climate and carbon cycle dynamics. One scenario assumes very high emissions, while the second assumes a peak in emissions, followed by rapid declines to net negative emissions. We show that the models generally agree that warming is roughly proportional to carbon emissions but that many other aspects of the model projections differ.
Shruti Nath, Quentin Lejeune, Lea Beusch, Sonia I. Seneviratne, and Carl-Friedrich Schleussner
Earth Syst. Dynam., 13, 851–877, https://doi.org/10.5194/esd-13-851-2022, https://doi.org/10.5194/esd-13-851-2022, 2022
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Uncertainty within climate model projections on inter-annual timescales is largely affected by natural climate variability. Emulators are valuable tools for approximating climate model runs, allowing for easy exploration of such uncertainty spaces. This study takes a first step at building a spatially resolved, monthly temperature emulator that takes local yearly temperatures as the sole input, thus providing monthly temperature distributions which are of critical value to impact assessments.
Ronny Meier, Edouard L. Davin, Gordon B. Bonan, David M. Lawrence, Xiaolong Hu, Gregory Duveiller, Catherine Prigent, and Sonia I. Seneviratne
Geosci. Model Dev., 15, 2365–2393, https://doi.org/10.5194/gmd-15-2365-2022, https://doi.org/10.5194/gmd-15-2365-2022, 2022
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We revise the roughness of the land surface in the CESM climate model. Guided by observational data, we increase the surface roughness of forests and decrease that of bare soil, snow, ice, and crops. These modifications alter simulated temperatures and wind speeds at and above the land surface considerably, in particular over desert regions. The revised model represents the diurnal variability of the land surface temperature better compared to satellite observations over most regions.
Heye Reemt Bogena, Martin Schrön, Jannis Jakobi, Patrizia Ney, Steffen Zacharias, Mie Andreasen, Roland Baatz, David Boorman, Mustafa Berk Duygu, Miguel Angel Eguibar-Galán, Benjamin Fersch, Till Franke, Josie Geris, María González Sanchis, Yann Kerr, Tobias Korf, Zalalem Mengistu, Arnaud Mialon, Paolo Nasta, Jerzy Nitychoruk, Vassilios Pisinaras, Daniel Rasche, Rafael Rosolem, Hami Said, Paul Schattan, Marek Zreda, Stefan Achleitner, Eduardo Albentosa-Hernández, Zuhal Akyürek, Theresa Blume, Antonio del Campo, Davide Canone, Katya Dimitrova-Petrova, John G. Evans, Stefano Ferraris, Félix Frances, Davide Gisolo, Andreas Güntner, Frank Herrmann, Joost Iwema, Karsten H. Jensen, Harald Kunstmann, Antonio Lidón, Majken Caroline Looms, Sascha Oswald, Andreas Panagopoulos, Amol Patil, Daniel Power, Corinna Rebmann, Nunzio Romano, Lena Scheiffele, Sonia Seneviratne, Georg Weltin, and Harry Vereecken
Earth Syst. Sci. Data, 14, 1125–1151, https://doi.org/10.5194/essd-14-1125-2022, https://doi.org/10.5194/essd-14-1125-2022, 2022
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Monitoring of increasingly frequent droughts is a prerequisite for climate adaptation strategies. This data paper presents long-term soil moisture measurements recorded by 66 cosmic-ray neutron sensors (CRNS) operated by 24 institutions and distributed across major climate zones in Europe. Data processing followed harmonized protocols and state-of-the-art methods to generate consistent and comparable soil moisture products and to facilitate continental-scale analysis of hydrological extremes.
Aine M. Gormley-Gallagher, Sebastian Sterl, Annette L. Hirsch, Sonia I. Seneviratne, Edouard L. Davin, and Wim Thiery
Earth Syst. Dynam., 13, 419–438, https://doi.org/10.5194/esd-13-419-2022, https://doi.org/10.5194/esd-13-419-2022, 2022
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Our results show that agricultural management can impact the local climate and highlight the need to evaluate land management in climate models. We use regression analysis on climate simulations and observations to assess irrigation and conservation agriculture impacts on warming trends. This allowed us to distinguish between the effects of land management and large-scale climate forcings such as rising CO2 concentrations and thus gain insight into the impacts under different climate regimes.
Nicholas J. Leach, Stuart Jenkins, Zebedee Nicholls, Christopher J. Smith, John Lynch, Michelle Cain, Tristram Walsh, Bill Wu, Junichi Tsutsui, and Myles R. Allen
Geosci. Model Dev., 14, 3007–3036, https://doi.org/10.5194/gmd-14-3007-2021, https://doi.org/10.5194/gmd-14-3007-2021, 2021
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This paper presents an update of the FaIR simple climate model, which can estimate the impact of anthropogenic greenhouse gas and aerosol emissions on the global climate. This update aims to significantly increase the structural simplicity of the model, making it more understandable and transparent. This simplicity allows it to be implemented in a wide range of environments, including Excel. We suggest that it could be used widely in academia, corporate research, and education.
Johannes Gütschow, M. Louise Jeffery, Annika Günther, and Malte Meinshausen
Earth Syst. Sci. Data, 13, 1005–1040, https://doi.org/10.5194/essd-13-1005-2021, https://doi.org/10.5194/essd-13-1005-2021, 2021
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Climate policy analysis needs scenarios of future greenhouse gas emission to assess countries' emission targets and current trends. The models generating these scenarios work on a regional resolution. Scenarios are often made available only on a very coarse regional resolution. In this paper we use per country projections of gross domestic product (GDP) from the Shared Socio-Economic Pathways (SSPs) to derive country-level data from published regional emission scenarios.
Claudia Tebaldi, Kevin Debeire, Veronika Eyring, Erich Fischer, John Fyfe, Pierre Friedlingstein, Reto Knutti, Jason Lowe, Brian O'Neill, Benjamin Sanderson, Detlef van Vuuren, Keywan Riahi, Malte Meinshausen, Zebedee Nicholls, Katarzyna B. Tokarska, George Hurtt, Elmar Kriegler, Jean-Francois Lamarque, Gerald Meehl, Richard Moss, Susanne E. Bauer, Olivier Boucher, Victor Brovkin, Young-Hwa Byun, Martin Dix, Silvio Gualdi, Huan Guo, Jasmin G. John, Slava Kharin, YoungHo Kim, Tsuyoshi Koshiro, Libin Ma, Dirk Olivié, Swapna Panickal, Fangli Qiao, Xinyao Rong, Nan Rosenbloom, Martin Schupfner, Roland Séférian, Alistair Sellar, Tido Semmler, Xiaoying Shi, Zhenya Song, Christian Steger, Ronald Stouffer, Neil Swart, Kaoru Tachiiri, Qi Tang, Hiroaki Tatebe, Aurore Voldoire, Evgeny Volodin, Klaus Wyser, Xiaoge Xin, Shuting Yang, Yongqiang Yu, and Tilo Ziehn
Earth Syst. Dynam., 12, 253–293, https://doi.org/10.5194/esd-12-253-2021, https://doi.org/10.5194/esd-12-253-2021, 2021
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We present an overview of CMIP6 ScenarioMIP outcomes from up to 38 participating ESMs according to the new SSP-based scenarios. Average temperature and precipitation projections according to a wide range of forcings, spanning a wider range than the CMIP5 projections, are documented as global averages and geographic patterns. Times of crossing various warming levels are computed, together with benefits of mitigation for selected pairs of scenarios. Comparisons with CMIP5 are also discussed.
Sarah F. Kew, Sjoukje Y. Philip, Mathias Hauser, Mike Hobbins, Niko Wanders, Geert Jan van Oldenborgh, Karin van der Wiel, Ted I. E. Veldkamp, Joyce Kimutai, Chris Funk, and Friederike E. L. Otto
Earth Syst. Dynam., 12, 17–35, https://doi.org/10.5194/esd-12-17-2021, https://doi.org/10.5194/esd-12-17-2021, 2021
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Motivated by the possible influence of rising temperatures, this study synthesises results from observations and climate models to explore trends (1900–2018) in eastern African (EA) drought measures. However, no discernible trends are found in annual soil moisture or precipitation. Positive trends in potential evaporation indicate that for irrigated regions more water is now required to counteract increased evaporation. Precipitation deficit is, however, the most useful indicator of EA drought.
Quentin Lejeune, Edouard L. Davin, Grégory Duveiller, Bas Crezee, Ronny Meier, Alessandro Cescatti, and Sonia I. Seneviratne
Earth Syst. Dynam., 11, 1209–1232, https://doi.org/10.5194/esd-11-1209-2020, https://doi.org/10.5194/esd-11-1209-2020, 2020
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Trees are darker than crops or grasses; hence, they absorb more solar radiation. Therefore, land cover changes modify the fraction of solar radiation reflected by the land surface (its albedo), with consequences for the climate. We apply a new statistical method to simulations conducted with 15 recent climate models and find that albedo variations due to land cover changes since 1860 have led to a decrease in the net amount of energy entering the atmosphere by −0.09 W m2 on average.
Maialen Iturbide, José M. Gutiérrez, Lincoln M. Alves, Joaquín Bedia, Ruth Cerezo-Mota, Ezequiel Cimadevilla, Antonio S. Cofiño, Alejandro Di Luca, Sergio Henrique Faria, Irina V. Gorodetskaya, Mathias Hauser, Sixto Herrera, Kevin Hennessy, Helene T. Hewitt, Richard G. Jones, Svitlana Krakovska, Rodrigo Manzanas, Daniel Martínez-Castro, Gemma T. Narisma, Intan S. Nurhati, Izidine Pinto, Sonia I. Seneviratne, Bart van den Hurk, and Carolina S. Vera
Earth Syst. Sci. Data, 12, 2959–2970, https://doi.org/10.5194/essd-12-2959-2020, https://doi.org/10.5194/essd-12-2959-2020, 2020
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We present an update of the IPCC WGI reference regions used in AR5 for the synthesis of climate change information. This revision was guided by the basic principles of climatic consistency and model representativeness (in particular for the new CMIP6 simulations). We also present a new dataset of monthly CMIP5 and CMIP6 spatially aggregated information using the new reference regions and describe a worked example of how to use this dataset to inform regional climate change studies.
Robin D. Lamboll, Zebedee R. J. Nicholls, Jarmo S. Kikstra, Malte Meinshausen, and Joeri Rogelj
Geosci. Model Dev., 13, 5259–5275, https://doi.org/10.5194/gmd-13-5259-2020, https://doi.org/10.5194/gmd-13-5259-2020, 2020
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Many models project how human activity can lead to more or less climate change, but most of these models do not project all climate-relevant emissions, potentially biasing climate projections. This paper outlines a Python package called Silicone, which can add missing emissions in a flexible yet high-throughput manner. It does this
infillingbased on more complete literature projections. It facilitates a more complete understanding of the climate impact of alternative emission pathways.
Zebedee R. J. Nicholls, Malte Meinshausen, Jared Lewis, Robert Gieseke, Dietmar Dommenget, Kalyn Dorheim, Chen-Shuo Fan, Jan S. Fuglestvedt, Thomas Gasser, Ulrich Golüke, Philip Goodwin, Corinne Hartin, Austin P. Hope, Elmar Kriegler, Nicholas J. Leach, Davide Marchegiani, Laura A. McBride, Yann Quilcaille, Joeri Rogelj, Ross J. Salawitch, Bjørn H. Samset, Marit Sandstad, Alexey N. Shiklomanov, Ragnhild B. Skeie, Christopher J. Smith, Steve Smith, Katsumasa Tanaka, Junichi Tsutsui, and Zhiang Xie
Geosci. Model Dev., 13, 5175–5190, https://doi.org/10.5194/gmd-13-5175-2020, https://doi.org/10.5194/gmd-13-5175-2020, 2020
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Computational limits mean that we cannot run our most comprehensive climate models for all applications of interest. In such cases, reduced complexity models (RCMs) are used. Here, researchers working on 15 different models present the first systematic community effort to evaluate and compare RCMs: the Reduced Complexity Model Intercomparison Project (RCMIP). Our research ensures that users of RCMs can more easily evaluate the strengths, weaknesses and limitations of their tools.
Kathrin Wehrli, Mathias Hauser, and Sonia I. Seneviratne
Earth Syst. Dynam., 11, 855–873, https://doi.org/10.5194/esd-11-855-2020, https://doi.org/10.5194/esd-11-855-2020, 2020
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The 2018 summer was unusually hot for large areas in the Northern Hemisphere, and heatwaves on three continents led to major impacts on agriculture and society. This study investigates storylines for the extreme 2018 summer, given the observed atmospheric circulation but different levels of background global warming. The results reveal a strong contribution by the present-day level of global warming and show a dramatic outlook for similar events in a warmer climate.
Karina von Schuckmann, Lijing Cheng, Matthew D. Palmer, James Hansen, Caterina Tassone, Valentin Aich, Susheel Adusumilli, Hugo Beltrami, Tim Boyer, Francisco José Cuesta-Valero, Damien Desbruyères, Catia Domingues, Almudena García-García, Pierre Gentine, John Gilson, Maximilian Gorfer, Leopold Haimberger, Masayoshi Ishii, Gregory C. Johnson, Rachel Killick, Brian A. King, Gottfried Kirchengast, Nicolas Kolodziejczyk, John Lyman, Ben Marzeion, Michael Mayer, Maeva Monier, Didier Paolo Monselesan, Sarah Purkey, Dean Roemmich, Axel Schweiger, Sonia I. Seneviratne, Andrew Shepherd, Donald A. Slater, Andrea K. Steiner, Fiammetta Straneo, Mary-Louise Timmermans, and Susan E. Wijffels
Earth Syst. Sci. Data, 12, 2013–2041, https://doi.org/10.5194/essd-12-2013-2020, https://doi.org/10.5194/essd-12-2013-2020, 2020
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Understanding how much and where the heat is distributed in the Earth system is fundamental to understanding how this affects warming oceans, atmosphere and land, rising temperatures and sea level, and loss of grounded and floating ice, which are fundamental concerns for society. This study is a Global Climate Observing System (GCOS) concerted international effort to obtain the Earth heat inventory over the period 1960–2018.
Malte Meinshausen, Zebedee R. J. Nicholls, Jared Lewis, Matthew J. Gidden, Elisabeth Vogel, Mandy Freund, Urs Beyerle, Claudia Gessner, Alexander Nauels, Nico Bauer, Josep G. Canadell, John S. Daniel, Andrew John, Paul B. Krummel, Gunnar Luderer, Nicolai Meinshausen, Stephen A. Montzka, Peter J. Rayner, Stefan Reimann, Steven J. Smith, Marten van den Berg, Guus J. M. Velders, Martin K. Vollmer, and Ray H. J. Wang
Geosci. Model Dev., 13, 3571–3605, https://doi.org/10.5194/gmd-13-3571-2020, https://doi.org/10.5194/gmd-13-3571-2020, 2020
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This study provides the future greenhouse gas (GHG) concentrations under the new set of so-called SSP scenarios (the successors of the IPCC SRES and previous representative concentration pathway (RCP) scenarios). The projected CO2 concentrations range from 350 ppm for low-emission scenarios by 2150 to more than 2000 ppm under the high-emission scenarios. We also provide concentrations, latitudinal gradients, and seasonality for most of the other 42 considered GHGs.
Hong Xuan Do, Fang Zhao, Seth Westra, Michael Leonard, Lukas Gudmundsson, Julien Eric Stanislas Boulange, Jinfeng Chang, Philippe Ciais, Dieter Gerten, Simon N. Gosling, Hannes Müller Schmied, Tobias Stacke, Camelia-Eliza Telteu, and Yoshihide Wada
Hydrol. Earth Syst. Sci., 24, 1543–1564, https://doi.org/10.5194/hess-24-1543-2020, https://doi.org/10.5194/hess-24-1543-2020, 2020
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We presented a global comparison between observed and simulated trends in a flood index over the 1971–2005 period using the Global Streamflow Indices and Metadata archive and six global hydrological models available through The Inter-Sectoral Impact Model Intercomparison Project. Streamflow simulations over 2006–2099 period robustly project high flood hazard in several regions. These high-flood-risk areas, however, are under-sampled by the current global streamflow databases.
Ryan S. Padrón, Lukas Gudmundsson, Dominik Michel, and Sonia I. Seneviratne
Hydrol. Earth Syst. Sci., 24, 793–807, https://doi.org/10.5194/hess-24-793-2020, https://doi.org/10.5194/hess-24-793-2020, 2020
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We focus on the net exchange of water between land and air via evapotranspiration and dew during the night. We provide, for the first time, an overview of the magnitude and variability of this flux across the globe from observations and climate models. Nocturnal water loss from land is 7 % of total evapotranspiration on average and can be greater than 15 % locally. Our results highlight the relevance of this often overlooked flux, with implications for water resources and climate studies.
Lea Beusch, Lukas Gudmundsson, and Sonia I. Seneviratne
Earth Syst. Dynam., 11, 139–159, https://doi.org/10.5194/esd-11-139-2020, https://doi.org/10.5194/esd-11-139-2020, 2020
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Earth system models (ESMs) are invaluable to study the climate system but expensive to run. Here, we present a statistical tool which emulates ESMs at a negligible computational cost by creating stochastic realizations of yearly land temperature field time series. Thereby, 40 ESMs are considered, and for each ESM, a single simulation is required to train the tool. The resulting ESM-specific realizations closely resemble ESM simulations not employed during training at point to regional scales.
Anders Levermann, Ricarda Winkelmann, Torsten Albrecht, Heiko Goelzer, Nicholas R. Golledge, Ralf Greve, Philippe Huybrechts, Jim Jordan, Gunter Leguy, Daniel Martin, Mathieu Morlighem, Frank Pattyn, David Pollard, Aurelien Quiquet, Christian Rodehacke, Helene Seroussi, Johannes Sutter, Tong Zhang, Jonas Van Breedam, Reinhard Calov, Robert DeConto, Christophe Dumas, Julius Garbe, G. Hilmar Gudmundsson, Matthew J. Hoffman, Angelika Humbert, Thomas Kleiner, William H. Lipscomb, Malte Meinshausen, Esmond Ng, Sophie M. J. Nowicki, Mauro Perego, Stephen F. Price, Fuyuki Saito, Nicole-Jeanne Schlegel, Sainan Sun, and Roderik S. W. van de Wal
Earth Syst. Dynam., 11, 35–76, https://doi.org/10.5194/esd-11-35-2020, https://doi.org/10.5194/esd-11-35-2020, 2020
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We provide an estimate of the future sea level contribution of Antarctica from basal ice shelf melting up to the year 2100. The full uncertainty range in the warming-related forcing of basal melt is estimated and applied to 16 state-of-the-art ice sheet models using a linear response theory approach. The sea level contribution we obtain is very likely below 61 cm under unmitigated climate change until 2100 (RCP8.5) and very likely below 40 cm if the Paris Climate Agreement is kept.
Nicholas James Leach, Zebedee Nicholls, Stuart Jenkins, Christopher J. Smith, John Lynch, Michelle Cain, Bill Wu, Junichi Tsutsui, and Myles R. Allen
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2019-379, https://doi.org/10.5194/gmd-2019-379, 2020
Revised manuscript not accepted
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GIR is a simple climate model designed to make exploration of the impact of greenhouse gas and aerosol emissions on the climate easy and understandable for its users. It uses an intuitive input and output structure, and the model is itself a set of only six equations. This lends the model to applications such as teaching, or as a lowest common denominator model between groups in large-scale climate assessments. It could also be used to investigate more complex models through emulation.
Gionata Ghiggi, Vincent Humphrey, Sonia I. Seneviratne, and Lukas Gudmundsson
Earth Syst. Sci. Data, 11, 1655–1674, https://doi.org/10.5194/essd-11-1655-2019, https://doi.org/10.5194/essd-11-1655-2019, 2019
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Freshwater resources are of high societal relevance and understanding their past variability is vital to water management in the context of current and future climatic change. This study introduces GRUN: the first global gridded monthly reconstruction of runoff covering the period from 1902 to 2014. The dataset agrees on average much better with the streamflow observations than an ensemble of 13 state-of-the-art global hydrological models and will foster the understanding of freshwater dynamics.
Chris D. Jones, Thomas L. Frölicher, Charles Koven, Andrew H. MacDougall, H. Damon Matthews, Kirsten Zickfeld, Joeri Rogelj, Katarzyna B. Tokarska, Nathan P. Gillett, Tatiana Ilyina, Malte Meinshausen, Nadine Mengis, Roland Séférian, Michael Eby, and Friedrich A. Burger
Geosci. Model Dev., 12, 4375–4385, https://doi.org/10.5194/gmd-12-4375-2019, https://doi.org/10.5194/gmd-12-4375-2019, 2019
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Global warming is simply related to the total emission of CO2 allowing us to define a carbon budget. However, information on the Zero Emissions Commitment is a key missing link to assess remaining carbon budgets to achieve the climate targets of the Paris Agreement. It was therefore decided that a small targeted MIP activity to fill this knowledge gap would be extremely valuable. This article formalises the experimental design alongside the other CMIP6 documentation papers.
Inne Vanderkelen, Jakob Zschleischler, Lukas Gudmundsson, Klaus Keuler, Francois Rineau, Natalie Beenaerts, Jaco Vangronsveld, and Wim Thiery
Biogeosciences Discuss., https://doi.org/10.5194/bg-2019-267, https://doi.org/10.5194/bg-2019-267, 2019
Manuscript not accepted for further review
Vincent Humphrey and Lukas Gudmundsson
Earth Syst. Sci. Data, 11, 1153–1170, https://doi.org/10.5194/essd-11-1153-2019, https://doi.org/10.5194/essd-11-1153-2019, 2019
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Because changes in freshwater availability can impact many natural ecosystems and human activities, it is crucial to better understand long-term changes in the water cycle. This dataset is a reconstruction of past changes in land water storage over the last century, obtained by combining satellite observations with historical weather data. It can be used to investigate both regional changes in freshwater availability or drought frequency and long-term changes in the global water cycle.
Mathias Hauser, Wim Thiery, and Sonia Isabelle Seneviratne
Earth Syst. Dynam., 10, 157–169, https://doi.org/10.5194/esd-10-157-2019, https://doi.org/10.5194/esd-10-157-2019, 2019
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We develop a method to keep the amount of water in the soil at the present-day level, using only local water sources in a global climate model. This leads to less drying over many land areas, but also decreases river runoff. We find that temperature extremes in the 21st century decrease substantially using our method. This provides a new perspective on how land water can influence regional climate and introduces land water management as potential tool for local mitigation of climate change.
Ronny Meier, Edouard L. Davin, Quentin Lejeune, Mathias Hauser, Yan Li, Brecht Martens, Natalie M. Schultz, Shannon Sterling, and Wim Thiery
Biogeosciences, 15, 4731–4757, https://doi.org/10.5194/bg-15-4731-2018, https://doi.org/10.5194/bg-15-4731-2018, 2018
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Deforestation not only releases carbon dioxide to the atmosphere but also affects local climatic conditions by altering energy fluxes at the land surface and thereby the local temperature. Here, we evaluate the local impact of deforestation in a widely used land surface model. We find that the model reproduces the daytime warming effect of deforestation well. On the other hand, the warmer temperatures observed during night in forests are not present in this model.
Sonya L. Fiddes, Matthew T. Woodhouse, Zebedee Nicholls, Todd P. Lane, and Robyn Schofield
Atmos. Chem. Phys., 18, 10177–10198, https://doi.org/10.5194/acp-18-10177-2018, https://doi.org/10.5194/acp-18-10177-2018, 2018
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The role of natural aerosol in the climate system is uncertain. A key contributor to marine aerosol is dimethyl sulfide (DMS), released by phytoplankton in the oceans. We study the effect of DMS on clouds and rain using a climate model with a detailed aerosol scheme. We show that DMS acts to reduce rainfall in cloud deck regions, leading to longer lived clouds and a large impact on solar energy reaching the surface. Further study of these areas will improve future climate projections.
Hong Xuan Do, Lukas Gudmundsson, Michael Leonard, and Seth Westra
Earth Syst. Sci. Data, 10, 765–785, https://doi.org/10.5194/essd-10-765-2018, https://doi.org/10.5194/essd-10-765-2018, 2018
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The production of 30 959 daily streamflow time series in the Global Streamflow and Metadata Archive (GSIM) project is presented. The paper also describes the development of three metadata products that are freely available. Having collated an unprecedented number of stations and associated metadata, GSIM can be used to advance large-scale hydrological research and improve understanding of the global water cycle.
Lukas Gudmundsson, Hong Xuan Do, Michael Leonard, and Seth Westra
Earth Syst. Sci. Data, 10, 787–804, https://doi.org/10.5194/essd-10-787-2018, https://doi.org/10.5194/essd-10-787-2018, 2018
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Time-series indices characterizing streamflow at annual, seasonal and monthly resolution at more than 30 000 stations around the world are presented. The data belong to the Global Streamflow and Metadata Archive (GSIM) and allow for an assessment of water balance components, hydrological extremes and the seasonality of water availability. The quality of the data is tested using automated methods to aid potential users to gauge the suitability of the data for specific applications.
Peter Greve, Lukas Gudmundsson, and Sonia I. Seneviratne
Earth Syst. Dynam., 9, 227–240, https://doi.org/10.5194/esd-9-227-2018, https://doi.org/10.5194/esd-9-227-2018, 2018
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Assessing projected hydroclimatological changes is crucial, but associated with large uncertainties. We statistically assess here the response of precipitation and water availability to global temperature change, enabling us to estimate the significance of drying/wetting tendencies under anthropogenic climate change. We further show that opting for a 1.5 K warming target just slightly influences the mean response but could substantially reduce the risk of experiencing extreme changes.
Johann H. Jungclaus, Edouard Bard, Mélanie Baroni, Pascale Braconnot, Jian Cao, Louise P. Chini, Tania Egorova, Michael Evans, J. Fidel González-Rouco, Hugues Goosse, George C. Hurtt, Fortunat Joos, Jed O. Kaplan, Myriam Khodri, Kees Klein Goldewijk, Natalie Krivova, Allegra N. LeGrande, Stephan J. Lorenz, Jürg Luterbacher, Wenmin Man, Amanda C. Maycock, Malte Meinshausen, Anders Moberg, Raimund Muscheler, Christoph Nehrbass-Ahles, Bette I. Otto-Bliesner, Steven J. Phipps, Julia Pongratz, Eugene Rozanov, Gavin A. Schmidt, Hauke Schmidt, Werner Schmutz, Andrew Schurer, Alexander I. Shapiro, Michael Sigl, Jason E. Smerdon, Sami K. Solanki, Claudia Timmreck, Matthew Toohey, Ilya G. Usoskin, Sebastian Wagner, Chi-Ju Wu, Kok Leng Yeo, Davide Zanchettin, Qiong Zhang, and Eduardo Zorita
Geosci. Model Dev., 10, 4005–4033, https://doi.org/10.5194/gmd-10-4005-2017, https://doi.org/10.5194/gmd-10-4005-2017, 2017
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Climate model simulations covering the last millennium provide context for the evolution of the modern climate and for the expected changes during the coming centuries. They can help identify plausible mechanisms underlying palaeoclimatic reconstructions. Here, we describe the forcing boundary conditions and the experimental protocol for simulations covering the pre-industrial millennium. We describe the PMIP4 past1000 simulations as contributions to CMIP6 and additional sensitivity experiments.
Jakob Zscheischler, Rene Orth, and Sonia I. Seneviratne
Biogeosciences, 14, 3309–3320, https://doi.org/10.5194/bg-14-3309-2017, https://doi.org/10.5194/bg-14-3309-2017, 2017
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We use newly established methods to compute bivariate return periods of temperature and precipitation and relate those to crop yield variability in Europe. Most often, crop yields are lower when it is hot and dry and higher when it is cold and wet. The variability in crop yields along a specific climate gradient can be captured well by return periods aligned with these gradients. This study provides new possibilities for investigating the relationship between crop yield variability and climate.
Alexander Nauels, Malte Meinshausen, Matthias Mengel, Katja Lorbacher, and Tom M. L. Wigley
Geosci. Model Dev., 10, 2495–2524, https://doi.org/10.5194/gmd-10-2495-2017, https://doi.org/10.5194/gmd-10-2495-2017, 2017
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The MAGICC sea level model projects global sea level rise by emulating process-based estimates for all major sea level drivers and applying them to available climate scenarios and their extensions to 2300. The MAGICC sea level projections are well within the ranges of the fifth IPCC assessment report. Due to its efficient structure, this emulator is a powerful tool for exploring sea level uncertainties and investigating sea level responses for a wide range of climate mitigation pathways.
Richard J. Millar, Zebedee R. Nicholls, Pierre Friedlingstein, and Myles R. Allen
Atmos. Chem. Phys., 17, 7213–7228, https://doi.org/10.5194/acp-17-7213-2017, https://doi.org/10.5194/acp-17-7213-2017, 2017
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Simple representations of the global coupled climate–carbon-cycle system are required for climate policy analysis. Existing models have often failed to capture important physical dependencies of the climate response to carbon dioxide emissions. In this paper we propose a simple but novel modification to impulse-response climate–carbon-cycle models to capture these physical dependencies. This simple model creates an important tool for both climate policy and climate science analysis.
Malte Meinshausen, Elisabeth Vogel, Alexander Nauels, Katja Lorbacher, Nicolai Meinshausen, David M. Etheridge, Paul J. Fraser, Stephen A. Montzka, Peter J. Rayner, Cathy M. Trudinger, Paul B. Krummel, Urs Beyerle, Josep G. Canadell, John S. Daniel, Ian G. Enting, Rachel M. Law, Chris R. Lunder, Simon O'Doherty, Ron G. Prinn, Stefan Reimann, Mauro Rubino, Guus J. M. Velders, Martin K. Vollmer, Ray H. J. Wang, and Ray Weiss
Geosci. Model Dev., 10, 2057–2116, https://doi.org/10.5194/gmd-10-2057-2017, https://doi.org/10.5194/gmd-10-2057-2017, 2017
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Climate change is primarily driven by human-induced increases of greenhouse gas (GHG) concentrations. Based on ongoing community efforts (e.g. AGAGE and NOAA networks, ice cores), this study presents historical concentrations of CO2, CH4, N2O and 40 other GHGs from year 0 to year 2014. The data is recommended as input for climate models for pre-industrial, historical runs under CMIP6. Global means, but also latitudinal by monthly surface concentration fields are provided.
Mathias Hauser, René Orth, and Sonia I. Seneviratne
Geosci. Model Dev., 10, 1665–1677, https://doi.org/10.5194/gmd-10-1665-2017, https://doi.org/10.5194/gmd-10-1665-2017, 2017
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Water in the soil can influence temperature and precipitation of the atmosphere. However, the atmosphere also alters the soil moisture content. Climate model simulations prescribing soil moisture are a means to decouple these relationships. We find that the atmospheric response depends strongly on the method used to fix the soil moisture, as well as on the employed soil moisture data set.
Martin Hirschi, Dominik Michel, Irene Lehner, and Sonia I. Seneviratne
Hydrol. Earth Syst. Sci., 21, 1809–1825, https://doi.org/10.5194/hess-21-1809-2017, https://doi.org/10.5194/hess-21-1809-2017, 2017
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We compare lysimeter and eddy covariance (EC) flux measurements of evapotranspiration at a research catchment in Switzerland. The measurements are compared on various timescales, and with respect to a 40-year long-term lysimeter time series. Overall, the lysimeter and EC measurements agree well, especially on the annual timescale. Furthermore, we identify that lack of reliable EC data during/after rainfall events significantly contributes to an underestimation of EC evapotranspiration.
David M. Lawrence, George C. Hurtt, Almut Arneth, Victor Brovkin, Kate V. Calvin, Andrew D. Jones, Chris D. Jones, Peter J. Lawrence, Nathalie de Noblet-Ducoudré, Julia Pongratz, Sonia I. Seneviratne, and Elena Shevliakova
Geosci. Model Dev., 9, 2973–2998, https://doi.org/10.5194/gmd-9-2973-2016, https://doi.org/10.5194/gmd-9-2973-2016, 2016
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Human land-use activities have resulted in large changes to the Earth's surface, with resulting implications for climate. In the future, land-use activities are likely to expand and intensify further to meet growing demands for food, fiber, and energy. The goal of LUMIP is to take the next steps in land-use change science, and enable, coordinate, and ultimately address the most important land-use science questions in more depth and sophistication than possible in a multi-model context to date.
Lukas Gudmundsson and Sonia I. Seneviratne
Earth Syst. Sci. Data, 8, 279–295, https://doi.org/10.5194/essd-8-279-2016, https://doi.org/10.5194/essd-8-279-2016, 2016
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Despite the scientific and societal relevance of freshwater, there are to date no observation-based pan-European runoff estimates available. Here we employ state-of-the-art techniques to estimate monthly runoff rates in Europe. The new data product is based on an unprecedented collection of river flow observations which are combined with atmospheric variables using machine learning. Potential applications of the presented product include climatological assessments and drought monitoring.
Peter Greve, Lukas Gudmundsson, Boris Orlowsky, and Sonia I. Seneviratne
Hydrol. Earth Syst. Sci., 20, 2195–2205, https://doi.org/10.5194/hess-20-2195-2016, https://doi.org/10.5194/hess-20-2195-2016, 2016
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The widely used Budyko framework is by definition limited to steady-state conditions. In this study we analytically derive a new, two-parameter formulation of the Budyko framework that represents conditions under which evapotranspiration exceeds precipitation. This is technically achieved by rotating the water supply limit within the Budyko space. The new formulation is shown to be capable to represent first-order seasonal dynamics within the hydroclimatological system.
D. Michel, C. Jiménez, D. G. Miralles, M. Jung, M. Hirschi, A. Ershadi, B. Martens, M. F. McCabe, J. B. Fisher, Q. Mu, S. I. Seneviratne, E. F. Wood, and D. Fernández-Prieto
Hydrol. Earth Syst. Sci., 20, 803–822, https://doi.org/10.5194/hess-20-803-2016, https://doi.org/10.5194/hess-20-803-2016, 2016
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In this study a common reference input data set from satellite and in situ data is used to run four established evapotranspiration (ET) algorithms using sub-daily and daily input on a tower scale as a testbed for a global ET product. The PT-JPL model and GLEAM provide the best performance for satellite and in situ forcing as well as for the different temporal resolutions. PM-MOD and SEBS perform less well: the PM-MOD model generally underestimates, while SEBS generally overestimates ET.
L. Gudmundsson and S. I. Seneviratne
Hydrol. Earth Syst. Sci., 19, 2859–2879, https://doi.org/10.5194/hess-19-2859-2015, https://doi.org/10.5194/hess-19-2859-2015, 2015
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Water storages and fluxes on land are key variables in the Earth system. To provide context for local investigations and to understand phenomena that emerge at large spatial scales, information on continental freshwater dynamics is needed. This paper presents a methodology to estimate continental-scale runoff on a 0.5° spatial grid, which combines the advantages of in situ observations with the power of machine learning regression. The resulting runoff estimates compare well with observations.
L. Gudmundsson and S. I. Seneviratne
Proc. IAHS, 369, 75–79, https://doi.org/10.5194/piahs-369-75-2015, https://doi.org/10.5194/piahs-369-75-2015, 2015
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Recent climate projections suggest changes in European drought frequency, indicating increased drought risk in the south and less droughts in the north. Here we show that a similar change pattern can be identified in the observed record. The results raise the question whether observed changes in European drought frequency are a consequence of anthropogenic climate change.
T. Schneider von Deimling, G. Grosse, J. Strauss, L. Schirrmeister, A. Morgenstern, S. Schaphoff, M. Meinshausen, and J. Boike
Biogeosciences, 12, 3469–3488, https://doi.org/10.5194/bg-12-3469-2015, https://doi.org/10.5194/bg-12-3469-2015, 2015
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We have modelled the carbon release from thawing permafrost soils under various scenarios of future warming. Our results suggests that up to about 140Pg of carbon could be released under strong warming by end of the century. We have shown that abrupt thaw processes under thermokarst lakes can unlock large amounts of perennially frozen carbon stored in deep deposits (which extend many metres into the soil).
B. P. Guillod, B. Orlowsky, D. Miralles, A. J. Teuling, P. D. Blanken, N. Buchmann, P. Ciais, M. Ek, K. L. Findell, P. Gentine, B. R. Lintner, R. L. Scott, B. Van den Hurk, and S. I. Seneviratne
Atmos. Chem. Phys., 14, 8343–8367, https://doi.org/10.5194/acp-14-8343-2014, https://doi.org/10.5194/acp-14-8343-2014, 2014
S. J. Sutanto, B. van den Hurk, P. A. Dirmeyer, S. I. Seneviratne, T. Röckmann, K. E. Trenberth, E. M. Blyth, J. Wenninger, and G. Hoffmann
Hydrol. Earth Syst. Sci., 18, 2815–2827, https://doi.org/10.5194/hess-18-2815-2014, https://doi.org/10.5194/hess-18-2815-2014, 2014
F. Aemisegger, S. Pfahl, H. Sodemann, I. Lehner, S. I. Seneviratne, and H. Wernli
Atmos. Chem. Phys., 14, 4029–4054, https://doi.org/10.5194/acp-14-4029-2014, https://doi.org/10.5194/acp-14-4029-2014, 2014
L. Gudmundsson and S. I. Seneviratne
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-10-13191-2013, https://doi.org/10.5194/hessd-10-13191-2013, 2013
Manuscript not accepted for further review
R. Orth and S. I. Seneviratne
Hydrol. Earth Syst. Sci., 17, 3895–3911, https://doi.org/10.5194/hess-17-3895-2013, https://doi.org/10.5194/hess-17-3895-2013, 2013
B. Mueller, M. Hirschi, C. Jimenez, P. Ciais, P. A. Dirmeyer, A. J. Dolman, J. B. Fisher, M. Jung, F. Ludwig, F. Maignan, D. G. Miralles, M. F. McCabe, M. Reichstein, J. Sheffield, K. Wang, E. F. Wood, Y. Zhang, and S. I. Seneviratne
Hydrol. Earth Syst. Sci., 17, 3707–3720, https://doi.org/10.5194/hess-17-3707-2013, https://doi.org/10.5194/hess-17-3707-2013, 2013
B. Orlowsky and S. I. Seneviratne
Hydrol. Earth Syst. Sci., 17, 1765–1781, https://doi.org/10.5194/hess-17-1765-2013, https://doi.org/10.5194/hess-17-1765-2013, 2013
T. Egorova, E. Rozanov, J. Gröbner, M. Hauser, and W. Schmutz
Atmos. Chem. Phys., 13, 3811–3823, https://doi.org/10.5194/acp-13-3811-2013, https://doi.org/10.5194/acp-13-3811-2013, 2013
Related subject area
Climate and Earth system modeling
An overview of cloud–radiation denial experiments for the Energy Exascale Earth System Model version 1
The computational and energy cost of simulation and storage for climate science: lessons from CMIP6
Subgrid-scale variability of cloud ice in the ICON-AES 1.3.00
INFERNO-peat v1.0.0: a representation of northern high-latitude peat fires in the JULES-INFERNO global fire model
The 4DEnVar-based weakly coupled land data assimilation system for E3SM version 2
Continental-scale bias-corrected climate and hydrological projections for Australia
G6-1.5K-SAI: a new Geoengineering Model Intercomparison Project (GeoMIP) experiment integrating recent advances in solar radiation modification studies
Modeling the effects of tropospheric ozone on the growth and yield of global staple crops with DSSAT v4.8.0
A one-dimensional urban flow model with an eddy-diffusivity mass-flux (EDMF) scheme and refined turbulent transport (MLUCM v3.0)
DCMIP2016: the tropical cyclone test case
Interactions between atmospheric composition and climate change – progress in understanding and future opportunities from AerChemMIP, PDRMIP, and RFMIP
CD-type discretization for sea ice dynamics in FESOM version 2
CSDMS Data Components: data–model integration tools for Earth surface processes modeling
A generic algorithm to automatically classify urban fabric according to the local climate zone system: implementation in GeoClimate 0.0.1 and application to French cities
Modelling water isotopologues (1H2H16O, 1H217O) in the coupled numerical climate model iLOVECLIM (version 1.1.5)
Accurate assessment of land–atmosphere coupling in climate models requires high-frequency data output
Towards variance-conserving reconstructions of climate indices with Gaussian process regression in an embedding space
A diatom extension to the cGEnIE Earth system model – EcoGEnIE 1.1
Carbon isotopes in the marine biogeochemistry model FESOM2.1-REcoM3
Flux coupling approach on an exchange grid for the IOW Earth System Model (version 1.04.00) of the Baltic Sea region
Using EUREC4A/ATOMIC field campaign data to improve trade wind regimes in the Community Atmosphere Model
New model ensemble reveals how forcing uncertainty and model structure alter climate simulated across CMIP generations of the Community Earth System Model
Quantifying wildfire drivers and predictability in boreal peatlands using a two-step error-correcting machine learning framework in TeFire v1.0
Benchmarking GOCART-2G in the Goddard Earth Observing System (GEOS)
Energy-conserving physics for nonhydrostatic dynamics in mass coordinate models
Evaluation and optimisation of the soil carbon turnover routine in the MONICA model (version 3.3.1)
Assessing the sensitivity of aerosol mass budget and effective radiative forcing to horizontal grid spacing in E3SMv1 using a regional refinement approach
Towards the definition of a solar forcing dataset for CMIP7
ibicus: a new open-source Python package and comprehensive interface for statistical bias adjustment and evaluation in climate modelling (v1.0.1)
Disentangling the hydrological and hydraulic controls on streamflow variability in Energy Exascale Earth System Model (E3SM) V2 – a case study in the Pantanal region
Constraining the carbon cycle in JULES-ES-1.0
The utility of simulated ocean chlorophyll observations: a case study with the Chlorophyll Observation Simulator Package (version 1) in CESMv2.2
GeoPDNN 1.0: a semi-supervised deep learning neural network using pseudo-labels for three-dimensional shallow strata modelling and uncertainty analysis in urban areas from borehole data
The prototype NOAA Aerosol Reanalysis version 1.0: description of the modeling system and its evaluation
Performance and process-based evaluation of the BARPA-R Australasian regional climate model version 1
Monsoon Mission Coupled Forecast System version 2.0: model description and Indian monsoon simulations
Exploring the ocean mesoscale at reduced computational cost with FESOM 2.5: efficient modeling strategies applied to the Southern Ocean
Implementing detailed nucleation predictions in the Earth system model EC-Earth3.3.4: sulfuric acid-ammonia nucleation
Truly conserving with conservative remapping methods
High-resolution downscaling of CMIP6 Earth system and global climate models using deep learning for Iberia
Earth system modeling on modular supercomputing architecture: coupled atmosphere–ocean simulations with ICON 2.6.6-rc
Global Downscaled Projections for Climate Impacts Research (GDPCIR): preserving quantile trends for modeling future climate impacts
Understanding changes in cloud simulations from E3SM version 1 to version 2
WRF (v4.0)–SUEWS (v2018c) coupled system: development, evaluation and application
Scenario setup and forcing data for impact model evaluation and impact attribution within the third round of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP3a)
Deep learning model based on multi-scale feature fusion for precipitation nowcasting
The Framework for Assessing Changes To Sea-level (FACTS) v1.0: a platform for characterizing parametric and structural uncertainty in future global, relative, and extreme sea-level change
Getting the leaves right matters for estimating temperature extremes
The Southern Ocean Freshwater Input from Antarctica (SOFIA) Initiative: scientific objectives and experimental design
Modeling and evaluating the effects of irrigation on land–atmosphere interaction in southwestern Europe with the regional climate model REMO2020–iMOVE using a newly developed parameterization
Bryce E. Harrop, Jian Lu, L. Ruby Leung, William K. M. Lau, Kyu-Myong Kim, Brian Medeiros, Brian J. Soden, Gabriel A. Vecchi, Bosong Zhang, and Balwinder Singh
Geosci. Model Dev., 17, 3111–3135, https://doi.org/10.5194/gmd-17-3111-2024, https://doi.org/10.5194/gmd-17-3111-2024, 2024
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Seven new experimental setups designed to interfere with cloud radiative heating have been added to the Energy Exascale Earth System Model (E3SM). These experiments include both those that test the mean impact of cloud radiative heating and those examining its covariance with circulations. This paper documents the code changes and steps needed to run these experiments. Results corroborate prior findings for how cloud radiative heating impacts circulations and rainfall patterns.
Mario C. Acosta, Sergi Palomas, Stella V. Paronuzzi Ticco, Gladys Utrera, Joachim Biercamp, Pierre-Antoine Bretonniere, Reinhard Budich, Miguel Castrillo, Arnaud Caubel, Francisco Doblas-Reyes, Italo Epicoco, Uwe Fladrich, Sylvie Joussaume, Alok Kumar Gupta, Bryan Lawrence, Philippe Le Sager, Grenville Lister, Marie-Pierre Moine, Jean-Christophe Rioual, Sophie Valcke, Niki Zadeh, and Venkatramani Balaji
Geosci. Model Dev., 17, 3081–3098, https://doi.org/10.5194/gmd-17-3081-2024, https://doi.org/10.5194/gmd-17-3081-2024, 2024
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We present a collection of performance metrics gathered during the Coupled Model Intercomparison Project Phase 6 (CMIP6), a worldwide initiative to study climate change. We analyse the metrics that resulted from collaboration efforts among many partners and models and describe our findings to demonstrate the utility of our study for the scientific community. The research contributes to understanding climate modelling performance on the current high-performance computing (HPC) architectures.
Sabine Doktorowski, Jan Kretzschmar, Johannes Quaas, Marc Salzmann, and Odran Sourdeval
Geosci. Model Dev., 17, 3099–3110, https://doi.org/10.5194/gmd-17-3099-2024, https://doi.org/10.5194/gmd-17-3099-2024, 2024
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Especially over the midlatitudes, precipitation is mainly formed via the ice phase. In this study we focus on the initial snow formation process in the ICON-AES, the aggregation process. We use a stochastical approach for the aggregation parameterization and investigate the influence in the ICON-AES. Therefore, a distribution function of cloud ice is created, which is evaluated with satellite data. The new approach leads to cloud ice loss and an improvement in the process rate bias.
Katie R. Blackford, Matthew Kasoar, Chantelle Burton, Eleanor Burke, Iain Colin Prentice, and Apostolos Voulgarakis
Geosci. Model Dev., 17, 3063–3079, https://doi.org/10.5194/gmd-17-3063-2024, https://doi.org/10.5194/gmd-17-3063-2024, 2024
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Peatlands are globally important stores of carbon which are being increasingly threatened by wildfires with knock-on effects on the climate system. Here we introduce a novel peat fire parameterization in the northern high latitudes to the INFERNO global fire model. Representing peat fires increases annual burnt area across the high latitudes, alongside improvements in how we capture year-to-year variation in burning and emissions.
Pengfei Shi, L. Ruby Leung, Bin Wang, Kai Zhang, Samson M. Hagos, and Shixuan Zhang
Geosci. Model Dev., 17, 3025–3040, https://doi.org/10.5194/gmd-17-3025-2024, https://doi.org/10.5194/gmd-17-3025-2024, 2024
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Improving climate predictions have profound socio-economic impacts. This study introduces a new weakly coupled land data assimilation (WCLDA) system for a coupled climate model. We demonstrate improved simulation of soil moisture and temperature in many global regions and throughout the soil layers. Furthermore, significant improvements are also found in reproducing the time evolution of the 2012 US Midwest drought. The WCLDA system provides the groundwork for future predictability studies.
Justin Peter, Elisabeth Vogel, Wendy Sharples, Ulrike Bende-Michl, Louise Wilson, Pandora Hope, Andrew Dowdy, Greg Kociuba, Sri Srikanthan, Vi Co Duong, Jake Roussis, Vjekoslav Matic, Zaved Khan, Alison Oke, Margot Turner, Stuart Baron-Hay, Fiona Johnson, Raj Mehrotra, Ashish Sharma, Marcus Thatcher, Ali Azarvinand, Steven Thomas, Ghyslaine Boschat, Chantal Donnelly, and Robert Argent
Geosci. Model Dev., 17, 2755–2781, https://doi.org/10.5194/gmd-17-2755-2024, https://doi.org/10.5194/gmd-17-2755-2024, 2024
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We detail the production of datasets and communication to end users of high-resolution projections of rainfall, runoff, and soil moisture for the entire Australian continent. This is important as previous projections for Australia were for small regions and used differing techniques for their projections, making comparisons difficult across Australia's varied climate zones. The data will be beneficial for research purposes and to aid adaptation to climate change.
Daniele Visioni, Alan Robock, Jim Haywood, Matthew Henry, Simone Tilmes, Douglas G. MacMartin, Ben Kravitz, Sarah J. Doherty, John Moore, Chris Lennard, Shingo Watanabe, Helene Muri, Ulrike Niemeier, Olivier Boucher, Abu Syed, Temitope S. Egbebiyi, Roland Séférian, and Ilaria Quaglia
Geosci. Model Dev., 17, 2583–2596, https://doi.org/10.5194/gmd-17-2583-2024, https://doi.org/10.5194/gmd-17-2583-2024, 2024
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This paper describes a new experimental protocol for the Geoengineering Model Intercomparison Project (GeoMIP). In it, we describe the details of a new simulation of sunlight reflection using the stratospheric aerosols that climate models are supposed to run, and we explain the reasons behind each choice we made when defining the protocol.
Jose Rafael Guarin, Jonas Jägermeyr, Elizabeth A. Ainsworth, Fabio A. A. Oliveira, Senthold Asseng, Kenneth Boote, Joshua Elliott, Lisa Emberson, Ian Foster, Gerrit Hoogenboom, David Kelly, Alex C. Ruane, and Katrina Sharps
Geosci. Model Dev., 17, 2547–2567, https://doi.org/10.5194/gmd-17-2547-2024, https://doi.org/10.5194/gmd-17-2547-2024, 2024
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The effects of ozone (O3) stress on crop photosynthesis and leaf senescence were added to maize, rice, soybean, and wheat crop models. The modified models reproduced growth and yields under different O3 levels measured in field experiments and reported in the literature. The combined interactions between O3 and additional stresses were reproduced with the new models. These updated crop models can be used to simulate impacts of O3 stress under future climate change and air pollution scenarios.
Jiachen Lu, Negin Nazarian, Melissa Anne Hart, E. Scott Krayenhoff, and Alberto Martilli
Geosci. Model Dev., 17, 2525–2545, https://doi.org/10.5194/gmd-17-2525-2024, https://doi.org/10.5194/gmd-17-2525-2024, 2024
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This study enhances urban canopy models by refining key assumptions. Simulations for various urban scenarios indicate discrepancies in turbulent transport efficiency for flow properties. We propose two modifications that involve characterizing diffusion coefficients for momentum and turbulent kinetic energy separately and introducing a physics-based
mass-fluxterm. These adjustments enhance the model's performance, offering more reliable temperature and surface flux estimates.
Justin L. Willson, Kevin A. Reed, Christiane Jablonowski, James Kent, Peter H. Lauritzen, Ramachandran Nair, Mark A. Taylor, Paul A. Ullrich, Colin M. Zarzycki, David M. Hall, Don Dazlich, Ross Heikes, Celal Konor, David Randall, Thomas Dubos, Yann Meurdesoif, Xi Chen, Lucas Harris, Christian Kühnlein, Vivian Lee, Abdessamad Qaddouri, Claude Girard, Marco Giorgetta, Daniel Reinert, Hiroaki Miura, Tomoki Ohno, and Ryuji Yoshida
Geosci. Model Dev., 17, 2493–2507, https://doi.org/10.5194/gmd-17-2493-2024, https://doi.org/10.5194/gmd-17-2493-2024, 2024
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Accurate simulation of tropical cyclones (TCs) is essential to understanding their behavior in a changing climate. One way this is accomplished is through model intercomparison projects, where results from multiple climate models are analyzed to provide benchmark solutions for the wider climate modeling community. This study describes and analyzes the previously developed TC test case for nine climate models in an intercomparison project, providing solutions that aid in model development.
Stephanie Fiedler, Vaishali Naik, Fiona M. O'Connor, Christopher J. Smith, Paul Griffiths, Ryan J. Kramer, Toshihiko Takemura, Robert J. Allen, Ulas Im, Matthew Kasoar, Angshuman Modak, Steven Turnock, Apostolos Voulgarakis, Duncan Watson-Parris, Daniel M. Westervelt, Laura J. Wilcox, Alcide Zhao, William J. Collins, Michael Schulz, Gunnar Myhre, and Piers M. Forster
Geosci. Model Dev., 17, 2387–2417, https://doi.org/10.5194/gmd-17-2387-2024, https://doi.org/10.5194/gmd-17-2387-2024, 2024
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Climate scientists want to better understand modern climate change. Thus, climate model experiments are performed and compared. The results of climate model experiments differ, as assessed in the latest Intergovernmental Panel on Climate Change (IPCC) assessment report. This article gives insights into the challenges and outlines opportunities for further improving the understanding of climate change. It is based on views of a group of experts in atmospheric composition–climate interactions.
Sergey Danilov, Carolin Mehlmann, Dmitry Sidorenko, and Qiang Wang
Geosci. Model Dev., 17, 2287–2297, https://doi.org/10.5194/gmd-17-2287-2024, https://doi.org/10.5194/gmd-17-2287-2024, 2024
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Sea ice models are a necessary component of climate models. At very high resolution they are capable of simulating linear kinematic features, such as leads, which are important for better prediction of heat exchanges between the ocean and atmosphere. Two new discretizations are described which improve the sea ice component of the Finite volumE Sea ice–Ocean Model (FESOM version 2) by allowing simulations of finer scales.
Tian Gan, Gregory E. Tucker, Eric W. H. Hutton, Mark D. Piper, Irina Overeem, Albert J. Kettner, Benjamin Campforts, Julia M. Moriarty, Brianna Undzis, Ethan Pierce, and Lynn McCready
Geosci. Model Dev., 17, 2165–2185, https://doi.org/10.5194/gmd-17-2165-2024, https://doi.org/10.5194/gmd-17-2165-2024, 2024
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This study presents the design, implementation, and application of the CSDMS Data Components. The case studies demonstrate that the Data Components provide a consistent way to access heterogeneous datasets from multiple sources, and to seamlessly integrate them with various models for Earth surface process modeling. The Data Components support the creation of open data–model integration workflows to improve the research transparency and reproducibility.
Jérémy Bernard, Erwan Bocher, Matthieu Gousseff, François Leconte, and Elisabeth Le Saux Wiederhold
Geosci. Model Dev., 17, 2077–2116, https://doi.org/10.5194/gmd-17-2077-2024, https://doi.org/10.5194/gmd-17-2077-2024, 2024
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Geographical features may have a considerable effect on local climate. The local climate zone (LCZ) system proposed by Stewart and Oke (2012) is seen as a standard approach for classifying any zone according to a set of geographic indicators. While many methods already exist to map the LCZ, only a few tools are openly and freely available. We present the algorithm implemented in GeoClimate software to identify the LCZ of any place in the world using OpenStreetMap data.
Thomas Extier, Thibaut Caley, and Didier M. Roche
Geosci. Model Dev., 17, 2117–2139, https://doi.org/10.5194/gmd-17-2117-2024, https://doi.org/10.5194/gmd-17-2117-2024, 2024
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Stable water isotopes are used to infer changes in the hydrological cycle for different time periods in climatic archive and climate models. We present the implementation of the δ2H and δ17O water isotopes in the coupled climate model iLOVECLIM and calculate the d- and 17O-excess. Results of a simulation under preindustrial conditions show that the model correctly reproduces the water isotope distribution in the atmosphere and ocean in comparison to data and other global circulation models.
Kirsten L. Findell, Zun Yin, Eunkyo Seo, Paul A. Dirmeyer, Nathan P. Arnold, Nathaniel Chaney, Megan D. Fowler, Meng Huang, David M. Lawrence, Po-Lun Ma, and Joseph A. Santanello Jr.
Geosci. Model Dev., 17, 1869–1883, https://doi.org/10.5194/gmd-17-1869-2024, https://doi.org/10.5194/gmd-17-1869-2024, 2024
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We outline a request for sub-daily data to accurately capture the process-level connections between land states, surface fluxes, and the boundary layer response. This high-frequency model output will allow for more direct comparison with observational field campaigns on process-relevant timescales, enable demonstration of inter-model spread in land–atmosphere coupling processes, and aid in targeted identification of sources of deficiencies and opportunities for improvement of the models.
Marlene Klockmann, Udo von Toussaint, and Eduardo Zorita
Geosci. Model Dev., 17, 1765–1787, https://doi.org/10.5194/gmd-17-1765-2024, https://doi.org/10.5194/gmd-17-1765-2024, 2024
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Reconstructions of climate variability before the observational period rely on climate proxies and sophisticated statistical models to link the proxy information and climate variability. Existing models tend to underestimate the true magnitude of variability, especially if the proxies contain non-climatic noise. We present and test a promising new framework for climate-index reconstructions, based on Gaussian processes, which reconstructs robust variability estimates from noisy and sparse data.
Aaron A. Naidoo-Bagwell, Fanny M. Monteiro, Katharine R. Hendry, Scott Burgan, Jamie D. Wilson, Ben A. Ward, Andy Ridgwell, and Daniel J. Conley
Geosci. Model Dev., 17, 1729–1748, https://doi.org/10.5194/gmd-17-1729-2024, https://doi.org/10.5194/gmd-17-1729-2024, 2024
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As an extension to the EcoGEnIE 1.0 Earth system model that features a diverse plankton community, EcoGEnIE 1.1 includes siliceous plankton diatoms and also considers their impact on biogeochemical cycles. With updates to existing nutrient cycles and the introduction of the silicon cycle, we see improved model performance relative to observational data. Through a more functionally diverse plankton community, the new model enables more comprehensive future study of ocean ecology.
Martin Butzin, Ying Ye, Christoph Völker, Özgür Gürses, Judith Hauck, and Peter Köhler
Geosci. Model Dev., 17, 1709–1727, https://doi.org/10.5194/gmd-17-1709-2024, https://doi.org/10.5194/gmd-17-1709-2024, 2024
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In this paper we describe the implementation of the carbon isotopes 13C and 14C into the marine biogeochemistry model FESOM2.1-REcoM3 and present results of long-term test simulations. Our model results are largely consistent with marine carbon isotope reconstructions for the pre-anthropogenic period, but also exhibit some discrepancies.
Sven Karsten, Hagen Radtke, Matthias Gröger, Ha T. M. Ho-Hagemann, Hossein Mashayekh, Thomas Neumann, and H. E. Markus Meier
Geosci. Model Dev., 17, 1689–1708, https://doi.org/10.5194/gmd-17-1689-2024, https://doi.org/10.5194/gmd-17-1689-2024, 2024
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This paper describes the development of a regional Earth System Model for the Baltic Sea region. In contrast to conventional coupling approaches, the presented model includes a flux calculator operating on a common exchange grid. This approach automatically ensures a locally consistent treatment of fluxes and simplifies the exchange of model components. The presented model can be used for various scientific questions, such as studies of natural variability and ocean–atmosphere interactions.
Skyler Graap and Colin M. Zarzycki
Geosci. Model Dev., 17, 1627–1650, https://doi.org/10.5194/gmd-17-1627-2024, https://doi.org/10.5194/gmd-17-1627-2024, 2024
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A key target for improving climate models is how low, bright clouds are predicted over tropical oceans, since they have important consequences for the Earth's energy budget. A climate model has been updated to improve the physical realism of the treatment of how momentum is moved up and down in the atmosphere. By comparing this updated model to real-world observations from balloon launches, it can be shown to more accurately depict atmospheric structure in trade-wind areas close to the Equator.
Marika M. Holland, Cecile Hannay, John Fasullo, Alexandra Jahn, Jennifer E. Kay, Michael Mills, Isla R. Simpson, William Wieder, Peter Lawrence, Erik Kluzek, and David Bailey
Geosci. Model Dev., 17, 1585–1602, https://doi.org/10.5194/gmd-17-1585-2024, https://doi.org/10.5194/gmd-17-1585-2024, 2024
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Climate evolves in response to changing forcings, as prescribed in simulations. Models and forcings are updated over time to reflect new understanding. This makes it difficult to attribute simulation differences to either model or forcing changes. Here we present new simulations which enable the separation of model structure and forcing influence between two widely used simulation sets. Results indicate a strong influence of aerosol emission uncertainty on historical climate.
Rongyun Tang, Mingzhou Jin, Jiafu Mao, Daniel M. Ricciuto, Anping Chen, and Yulong Zhang
Geosci. Model Dev., 17, 1525–1542, https://doi.org/10.5194/gmd-17-1525-2024, https://doi.org/10.5194/gmd-17-1525-2024, 2024
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Carbon-rich boreal peatlands are at risk of burning. The reproducibility and predictability of rare peatland fire events are investigated by constructing a two-step error-correcting machine learning framework to tackle such complex systems. Fire occurrence and impacts are highly predictable with our approach. Factor-controlling simulations revealed that temperature, moisture, and freeze–thaw cycles control boreal peatland fires, indicating thermal impacts on causing peat fires.
Allison B. Collow, Peter R. Colarco, Arlindo M. da Silva, Virginie Buchard, Huisheng Bian, Mian Chin, Sampa Das, Ravi Govindaraju, Dongchul Kim, and Valentina Aquila
Geosci. Model Dev., 17, 1443–1468, https://doi.org/10.5194/gmd-17-1443-2024, https://doi.org/10.5194/gmd-17-1443-2024, 2024
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The GOCART aerosol module within the Goddard Earth Observing System recently underwent a major refactoring and update to the representation of physical processes. Code changes that were included in GOCART Second Generation (GOCART-2G) are documented, and we establish a benchmark simulation that is to be used for future development of the system. The 4-year benchmark simulation was evaluated using in situ and spaceborne measurements to develop a baseline and prioritize future development.
Oksana Guba, Mark A. Taylor, Peter A. Bosler, Christopher Eldred, and Peter H. Lauritzen
Geosci. Model Dev., 17, 1429–1442, https://doi.org/10.5194/gmd-17-1429-2024, https://doi.org/10.5194/gmd-17-1429-2024, 2024
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We want to reduce errors in the moist energy budget in numerical atmospheric models. We study a few common assumptions and mechanisms that are used for the moist physics. Some mechanisms are more consistent with the underlying equations. Separately, we study how assumptions about models' thermodynamics affect the modeled energy of precipitation. We also explain how to conserve energy in the moist physics for nonhydrostatic models.
Konstantin Aiteew, Jarno Rouhiainen, Claas Nendel, and René Dechow
Geosci. Model Dev., 17, 1349–1385, https://doi.org/10.5194/gmd-17-1349-2024, https://doi.org/10.5194/gmd-17-1349-2024, 2024
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This study evaluated the biogeochemical model MONICA and its performance in simulating soil organic carbon changes. MONICA can reproduce plant growth, carbon and nitrogen dynamics, soil water and temperature. The model results were compared with five established carbon turnover models. With the exception of certain sites, adequate reproduction of soil organic carbon stock change rates was achieved. The MONICA model was capable of performing similar to or even better than the other models.
Jianfeng Li, Kai Zhang, Taufiq Hassan, Shixuan Zhang, Po-Lun Ma, Balwinder Singh, Qiyang Yan, and Huilin Huang
Geosci. Model Dev., 17, 1327–1347, https://doi.org/10.5194/gmd-17-1327-2024, https://doi.org/10.5194/gmd-17-1327-2024, 2024
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By comparing E3SM simulations with and without regional refinement, we find that model horizontal grid spacing considerably affects the simulated aerosol mass budget, aerosol–cloud interactions, and the effective radiative forcing of anthropogenic aerosols. The study identifies the critical physical processes strongly influenced by model resolution. It also highlights the benefit of applying regional refinement in future modeling studies at higher or even convection-permitting resolutions.
Bernd Funke, Thierry Dudok de Wit, Ilaria Ermolli, Margit Haberreiter, Doug Kinnison, Daniel Marsh, Hilde Nesse, Annika Seppälä, Miriam Sinnhuber, and Ilya Usoskin
Geosci. Model Dev., 17, 1217–1227, https://doi.org/10.5194/gmd-17-1217-2024, https://doi.org/10.5194/gmd-17-1217-2024, 2024
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We outline a road map for the preparation of a solar forcing dataset for the upcoming Phase 7 of the Coupled Model Intercomparison Project (CMIP7), considering the latest scientific advances made in the reconstruction of solar forcing and in the understanding of climate response while also addressing the issues that were raised during CMIP6.
Fiona Raphaela Spuler, Jakob Benjamin Wessel, Edward Comyn-Platt, James Varndell, and Chiara Cagnazzo
Geosci. Model Dev., 17, 1249–1269, https://doi.org/10.5194/gmd-17-1249-2024, https://doi.org/10.5194/gmd-17-1249-2024, 2024
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Before using climate models to study the impacts of climate change, bias adjustment is commonly applied to the models to ensure that they correspond with observations at a local scale. However, this can introduce undesirable distortions into the climate model. In this paper, we present an open-source python package called ibicus to enable the comparison and detailed evaluation of bias adjustment methods, facilitating their transparent and rigorous application.
Donghui Xu, Gautam Bisht, Zeli Tan, Chang Liao, Tian Zhou, Hong-Yi Li, and L. Ruby Leung
Geosci. Model Dev., 17, 1197–1215, https://doi.org/10.5194/gmd-17-1197-2024, https://doi.org/10.5194/gmd-17-1197-2024, 2024
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We aim to disentangle the hydrological and hydraulic controls on streamflow variability in a fully coupled earth system model. We found that calibrating only one process (i.e., traditional calibration procedure) will result in unrealistic parameter values and poor performance of the water cycle, while the simulated streamflow is improved. To address this issue, we further proposed a two-step calibration procedure to reconcile the impacts from hydrological and hydraulic processes on streamflow.
Douglas McNeall, Eddy Robertson, and Andy Wiltshire
Geosci. Model Dev., 17, 1059–1089, https://doi.org/10.5194/gmd-17-1059-2024, https://doi.org/10.5194/gmd-17-1059-2024, 2024
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We can run simulations of the land surface and carbon cycle, using computer models to help us understand and predict climate change and its impacts. These simulations are not perfect reproductions of the real land surface, and that can make them less effective tools. We use new statistical and computational techniques to help us understand how different our models are from the real land surface, how to make them more realistic, and how well we can simulate past and future climate.
Genevieve L. Clow, Nicole S. Lovenduski, Michael N. Levy, Keith Lindsay, and Jennifer E. Kay
Geosci. Model Dev., 17, 975–995, https://doi.org/10.5194/gmd-17-975-2024, https://doi.org/10.5194/gmd-17-975-2024, 2024
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Satellite observations of chlorophyll allow us to study marine phytoplankton on a global scale; yet some of these observations are missing due to clouds and other issues. To investigate the impact of missing data, we developed a satellite simulator for chlorophyll in an Earth system model. We found that missing data can impact the global mean chlorophyll by nearly 20 %. The simulated observations provide a more direct comparison to real-world data and can be used to improve model validation.
Jiateng Guo, Xuechuang Xu, Luyuan Wang, Xulei Wang, Lixin Wu, Mark Jessell, Vitaliy Ogarko, Zhibin Liu, and Yufei Zheng
Geosci. Model Dev., 17, 957–973, https://doi.org/10.5194/gmd-17-957-2024, https://doi.org/10.5194/gmd-17-957-2024, 2024
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This study proposes a semi-supervised learning algorithm using pseudo-labels for 3D geological modelling. We establish a 3D geological model using borehole data from a complex real urban local survey area in Shenyang and make an uncertainty analysis of this model. The method effectively expands the sample space, which is suitable for geomodelling and uncertainty analysis from boreholes. The modelling results perform well in terms of spatial morphology and geological semantics.
Shih-Wei Wei, Mariusz Pagowski, Arlindo da Silva, Cheng-Hsuan Lu, and Bo Huang
Geosci. Model Dev., 17, 795–813, https://doi.org/10.5194/gmd-17-795-2024, https://doi.org/10.5194/gmd-17-795-2024, 2024
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This study describes the modeling system and the evaluation results for the first prototype version of a global aerosol reanalysis product at NOAA, prototype NOAA Aerosol ReAnalysis version 1.0 (pNARA v1.0). We evaluated pNARA v1.0 against independent datasets and compared it with other reanalyses. We identified deficiencies in the system (both in the forecast model and in the data assimilation system) and the uncertainties that exist in our reanalysis.
Emma Howard, Chun-Hsu Su, Christian Stassen, Rajashree Naha, Harvey Ye, Acacia Pepler, Samuel S. Bell, Andrew J. Dowdy, Simon O. Tucker, and Charmaine Franklin
Geosci. Model Dev., 17, 731–757, https://doi.org/10.5194/gmd-17-731-2024, https://doi.org/10.5194/gmd-17-731-2024, 2024
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The BARPA-R modelling configuration has been developed to produce high-resolution climate hazard projections within the Australian region. When using boundary driving data from quasi-observed historical conditions, BARPA-R shows good performance with errors generally on par with reanalysis products. BARPA-R also captures trends, known modes of climate variability, large-scale weather processes, and multivariate relationships.
Deepeshkumar Jain, Suryachandra A. Rao, Ramu A. Dandi, Prasanth A. Pillai, Ankur Srivastava, Maheswar Pradhan, and Kiran V. Gangadharan
Geosci. Model Dev., 17, 709–729, https://doi.org/10.5194/gmd-17-709-2024, https://doi.org/10.5194/gmd-17-709-2024, 2024
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The present paper discusses and evaluates the new Monsoon Mission Coupled Forecast System model (MMCFS) version 2.0 which upgrades the currently operational MMCFS v1.0 at the Indian Meteorological Department, India. The individual model components have been substantially upgraded independently by their respective scientific groups. MMCFS v2.0 includes these upgrades in the operational coupled model. The new model shows significant skill improvement in simulating the Indian monsoon.
Nathan Beech, Thomas Rackow, Tido Semmler, and Thomas Jung
Geosci. Model Dev., 17, 529–543, https://doi.org/10.5194/gmd-17-529-2024, https://doi.org/10.5194/gmd-17-529-2024, 2024
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Cost-reducing modeling strategies are applied to high-resolution simulations of the Southern Ocean in a changing climate. They are evaluated with respect to observations and traditional, lower-resolution modeling methods. The simulations effectively reproduce small-scale ocean flows seen in satellite data and are largely consistent with traditional model simulations after 4 °C of warming. Small-scale flows are found to intensify near bathymetric features and to become more variable.
Carl Svenhag, Moa Kristina Sporre, Tinja Olenius, Daniel Yazgi, Sara Marie Blichner, Lars Peter Nieradzik, and Pontus Roldin
EGUsphere, https://doi.org/10.5194/egusphere-2023-2665, https://doi.org/10.5194/egusphere-2023-2665, 2024
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Our research shows the importance of modeling new particle formation (NPF) and growth of particles in the atmosphere on a global scale, as they influence the outcomes of clouds and our climate. With the global model EC-Earth3 we showed that using a new method for NPF modeling, which includes new detailed processes with NH3 and H2SO4, significantly impacted the number of particles in the air and clouds. It also changed the radiation balance in the same magnitude as man-made greenhouse emissions.
Karl E. Taylor
Geosci. Model Dev., 17, 415–430, https://doi.org/10.5194/gmd-17-415-2024, https://doi.org/10.5194/gmd-17-415-2024, 2024
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Remapping gridded data in a way that preserves the conservative properties of the climate system can be essential in coupling model components and for accurate assessment of the system’s energy and mass constituents. Remapping packages capable of handling a wide variety of grids can, for some common grids, calculate remapping weights that are somewhat inaccurate. Correcting for these errors, guidelines are provided to ensure conservation when the weights are used in practice.
Pedro M. M. Soares, Frederico Johannsen, Daniela C. A. Lima, Gil Lemos, Virgílio A. Bento, and Angelina Bushenkova
Geosci. Model Dev., 17, 229–259, https://doi.org/10.5194/gmd-17-229-2024, https://doi.org/10.5194/gmd-17-229-2024, 2024
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This study uses deep learning (DL) to downscale global climate models for the Iberian Peninsula. Four DL architectures were evaluated and trained using historical climate data and then used to downscale future projections from the global models. These show agreement with the original models and reveal a warming of 2 ºC to 6 ºC, along with decreasing precipitation in western Iberia after 2040. This approach offers key regional climate change information for adaptation strategies in the region.
Abhiraj Bishnoi, Olaf Stein, Catrin I. Meyer, René Redler, Norbert Eicker, Helmuth Haak, Lars Hoffmann, Daniel Klocke, Luis Kornblueh, and Estela Suarez
Geosci. Model Dev., 17, 261–273, https://doi.org/10.5194/gmd-17-261-2024, https://doi.org/10.5194/gmd-17-261-2024, 2024
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We enabled the weather and climate model ICON to run in a high-resolution coupled atmosphere–ocean setup on the JUWELS supercomputer, where the ocean and the model I/O runs on the CPU Cluster, while the atmosphere is running simultaneously on GPUs. Compared to a simulation performed on CPUs only, our approach reduces energy consumption by 45 % with comparable runtimes. The experiments serve as preparation for efficient computing of kilometer-scale climate models on future supercomputing systems.
Diana R. Gergel, Steven B. Malevich, Kelly E. McCusker, Emile Tenezakis, Michael T. Delgado, Meredith A. Fish, and Robert E. Kopp
Geosci. Model Dev., 17, 191–227, https://doi.org/10.5194/gmd-17-191-2024, https://doi.org/10.5194/gmd-17-191-2024, 2024
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The freely available Global Downscaled Projections for Climate Impacts Research (GDPCIR) dataset gives researchers a new tool for studying how future climate will evolve at a local or regional level, corresponding to the latest global climate model simulations prepared as part of the UN Intergovernmental Panel on Climate Change’s Sixth Assessment Report. Those simulations represent an enormous advance in quality, detail, and scope that GDPCIR translates to the local level.
Yuying Zhang, Shaocheng Xie, Yi Qin, Wuyin Lin, Jean-Christophe Golaz, Xue Zheng, Po-Lun Ma, Yun Qian, Qi Tang, Christopher R. Terai, and Meng Zhang
Geosci. Model Dev., 17, 169–189, https://doi.org/10.5194/gmd-17-169-2024, https://doi.org/10.5194/gmd-17-169-2024, 2024
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We performed systematic evaluation of clouds simulated in the Energy
Exascale Earth System Model (E3SMv2) to document model performance and understand what updates in E3SMv2 have caused changes in clouds from E3SMv1 to E3SMv2. We find that stratocumulus clouds along the subtropical west coast of continents are dramatically improved, primarily due to the retuning done in CLUBB. This study offers additional insights into clouds simulated in E3SMv2 and will benefit future E3SM developments.
Exascale Earth System Model (E3SMv2) to document model performance and understand what updates in E3SMv2 have caused changes in clouds from E3SMv1 to E3SMv2. We find that stratocumulus clouds along the subtropical west coast of continents are dramatically improved, primarily due to the retuning done in CLUBB. This study offers additional insights into clouds simulated in E3SMv2 and will benefit future E3SM developments.
Ting Sun, Hamidreza Omidvar, Zhenkun Li, Ning Zhang, Wenjuan Huang, Simone Kotthaus, Helen C. Ward, Zhiwen Luo, and Sue Grimmond
Geosci. Model Dev., 17, 91–116, https://doi.org/10.5194/gmd-17-91-2024, https://doi.org/10.5194/gmd-17-91-2024, 2024
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For the first time, we coupled a state-of-the-art urban land surface model – Surface Urban Energy and Water Scheme (SUEWS) – with the widely-used Weather Research and Forecasting (WRF) model, creating an open-source tool that may benefit multiple applications. We tested our new system at two UK sites and demonstrated its potential by examining how human activities in various areas of Greater London influence local weather conditions.
Katja Frieler, Jan Volkholz, Stefan Lange, Jacob Schewe, Matthias Mengel, María del Rocío Rivas López, Christian Otto, Christopher P. O. Reyer, Dirk Nikolaus Karger, Johanna T. Malle, Simon Treu, Christoph Menz, Julia L. Blanchard, Cheryl S. Harrison, Colleen M. Petrik, Tyler D. Eddy, Kelly Ortega-Cisneros, Camilla Novaglio, Yannick Rousseau, Reg A. Watson, Charles Stock, Xiao Liu, Ryan Heneghan, Derek Tittensor, Olivier Maury, Matthias Büchner, Thomas Vogt, Tingting Wang, Fubao Sun, Inga J. Sauer, Johannes Koch, Inne Vanderkelen, Jonas Jägermeyr, Christoph Müller, Sam Rabin, Jochen Klar, Iliusi D. Vega del Valle, Gitta Lasslop, Sarah Chadburn, Eleanor Burke, Angela Gallego-Sala, Noah Smith, Jinfeng Chang, Stijn Hantson, Chantelle Burton, Anne Gädeke, Fang Li, Simon N. Gosling, Hannes Müller Schmied, Fred Hattermann, Jida Wang, Fangfang Yao, Thomas Hickler, Rafael Marcé, Don Pierson, Wim Thiery, Daniel Mercado-Bettín, Robert Ladwig, Ana Isabel Ayala-Zamora, Matthew Forrest, and Michel Bechtold
Geosci. Model Dev., 17, 1–51, https://doi.org/10.5194/gmd-17-1-2024, https://doi.org/10.5194/gmd-17-1-2024, 2024
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Our paper provides an overview of all observational climate-related and socioeconomic forcing data used as input for the impact model evaluation and impact attribution experiments within the third round of the Inter-Sectoral Impact Model Intercomparison Project. The experiments are designed to test our understanding of observed changes in natural and human systems and to quantify to what degree these changes have already been induced by climate change.
Jinkai Tan, Qiqiao Huang, and Sheng Chen
Geosci. Model Dev., 17, 53–69, https://doi.org/10.5194/gmd-17-53-2024, https://doi.org/10.5194/gmd-17-53-2024, 2024
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This study presents a deep learning architecture, multi-scale feature fusion (MFF), to improve the forecast skills of precipitations especially for heavy precipitations. MFF uses multi-scale receptive fields so that the movement features of precipitation systems are well captured. MFF uses the mechanism of discrete probability to reduce uncertainties and forecast errors so that heavy precipitations are produced.
Robert E. Kopp, Gregory G. Garner, Tim H. J. Hermans, Shantenu Jha, Praveen Kumar, Alexander Reedy, Aimée B. A. Slangen, Matteo Turilli, Tamsin L. Edwards, Jonathan M. Gregory, George Koubbe, Anders Levermann, Andre Merzky, Sophie Nowicki, Matthew D. Palmer, and Chris Smith
Geosci. Model Dev., 16, 7461–7489, https://doi.org/10.5194/gmd-16-7461-2023, https://doi.org/10.5194/gmd-16-7461-2023, 2023
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Future sea-level rise projections exhibit multiple forms of uncertainty, all of which must be considered by scientific assessments intended to inform decision-making. The Framework for Assessing Changes To Sea-level (FACTS) is a new software package intended to support assessments of global mean, regional, and extreme sea-level rise. An early version of FACTS supported the development of the IPCC Sixth Assessment Report sea-level projections.
Gregory Duveiller, Mark Pickering, Joaquin Muñoz-Sabater, Luca Caporaso, Souhail Boussetta, Gianpaolo Balsamo, and Alessandro Cescatti
Geosci. Model Dev., 16, 7357–7373, https://doi.org/10.5194/gmd-16-7357-2023, https://doi.org/10.5194/gmd-16-7357-2023, 2023
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Some of our best tools to describe the state of the land system, including the intensity of heat waves, have a problem. The model currently assumes that the number of leaves in ecosystems always follows the same cycle. By using satellite observations of when leaves are present, we show that capturing the yearly changes in this cycle is important to avoid errors in estimating surface temperature. We show that this has strong implications for our capacity to describe heat waves across Europe.
Neil C. Swart, Torge Martin, Rebecca Beadling, Jia-Jia Chen, Christopher Danek, Matthew H. England, Riccardo Farneti, Stephen M. Griffies, Tore Hattermann, Judith Hauck, F. Alexander Haumann, André Jüling, Qian Li, John Marshall, Morven Muilwijk, Andrew G. Pauling, Ariaan Purich, Inga J. Smith, and Max Thomas
Geosci. Model Dev., 16, 7289–7309, https://doi.org/10.5194/gmd-16-7289-2023, https://doi.org/10.5194/gmd-16-7289-2023, 2023
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Current climate models typically do not include full representation of ice sheets. As the climate warms and the ice sheets melt, they add freshwater to the ocean. This freshwater can influence climate change, for example by causing more sea ice to form. In this paper we propose a set of experiments to test the influence of this missing meltwater from Antarctica using multiple different climate models.
Christina Asmus, Peter Hoffmann, Joni-Pekka Pietikäinen, Jürgen Böhner, and Diana Rechid
Geosci. Model Dev., 16, 7311–7337, https://doi.org/10.5194/gmd-16-7311-2023, https://doi.org/10.5194/gmd-16-7311-2023, 2023
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Irrigation modifies the land surface and soil conditions. The effects can be quantified using numerical climate models. Our study introduces a new irrigation parameterization, which simulates the effects of irrigation on land, atmosphere, and vegetation. We applied the parameterization and evaluated the results in terms of their physical consistency. We found an improvement in the model results in the 2 m temperature representation in comparison with observational data for our study.
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Short summary
We introduce the first chain of computationally efficient Earth system model (ESM) emulators to translate user-defined greenhouse gas emission pathways into regional temperature change time series accounting for all major sources of climate change projection uncertainty. By combining the global mean emulator MAGICC with the spatially resolved emulator MESMER, we can derive ESM-specific and constrained probabilistic emulations to rapidly provide targeted climate information at the local scale.
We introduce the first chain of computationally efficient Earth system model (ESM) emulators to...
