Articles | Volume 11, issue 1
https://doi.org/10.5194/esd-11-139-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/esd-11-139-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
17 Feb 2020
Research article |
| 17 Feb 2020
| 17 Feb 2020
Emulating Earth system model temperatures with MESMER: from global mean temperature trajectories to grid-point-level realizations on land
Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
Lukas Gudmundsson
Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
Sonia I. Seneviratne
Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
Related authors
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
Short summary
Short summary
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.
Lea Beusch, Zebedee Nicholls, Lukas Gudmundsson, Mathias Hauser, Malte Meinshausen, and Sonia I. Seneviratne
Geosci. Model Dev., 15, 2085–2103, https://doi.org/10.5194/gmd-15-2085-2022, https://doi.org/10.5194/gmd-15-2085-2022, 2022
Short summary
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.
Sarah Schöngart, Lukas Gudmundsson, Mathias Hauser, Peter Pfleiderer, Quentin Lejeune, Shruti Nath, Sonia Isabelle Seneviratne, and Carl-Friedrich Schleussner
Geosci. Model Dev., 17, 8283–8320, https://doi.org/10.5194/gmd-17-8283-2024, https://doi.org/10.5194/gmd-17-8283-2024, 2024
Short summary
Short summary
Precipitation and temperature are two of the most impact-relevant climatic variables. Yet, projecting future precipitation and temperature data under different emission scenarios relies on complex models that are computationally expensive. In this study, we propose a method that allows us to generate monthly means of local precipitation and temperature at low computational costs. Our modelling framework is particularly useful for all downstream applications of climate model data.
Felix Jäger, Jonas Schwaab, Yann Quilcaille, Michael Windisch, Jonathan Doelman, Stefan Frank, Mykola Gusti, Petr Havlik, Florian Humpenöder, Andrey Lessa Derci Augustynczik, Christoph Müller, Kanishka Balu Narayan, Ryan Sebastian Padrón, Alexander Popp, Detlef van Vuuren, Michael Wögerer, and Sonia Isabelle Seneviratne
Earth Syst. Dynam., 15, 1055–1071, https://doi.org/10.5194/esd-15-1055-2024, https://doi.org/10.5194/esd-15-1055-2024, 2024
Short summary
Short summary
Climate change mitigation strategies developed with socioeconomic models rely on the widespread (re)planting of trees to limit global warming below 2°. However, most of these models neglect climate-driven shifts in forest damage like fires. By assessing existing mitigation scenarios, we show the exposure of projected forestation areas to fire-promoting weather conditions. Our study highlights the problem of ignoring climate-driven shifts in forest damage and ways to address it.
Christoph Nathanael von Matt, Regula Muelchi, Lukas Gudmundsson, and Olivia Martius
Nat. Hazards Earth Syst. Sci., 24, 1975–2001, https://doi.org/10.5194/nhess-24-1975-2024, https://doi.org/10.5194/nhess-24-1975-2024, 2024
Short summary
Short summary
The simultaneous occurrence of meteorological (precipitation), agricultural (soil moisture), and hydrological (streamflow) drought can lead to augmented impacts. By analysing drought indices derived from the newest climate scenarios for Switzerland (CH2018, Hydro-CH2018), we show that with climate change the concurrence of all drought types will increase in all studied regions of Switzerland. Our results stress the benefits of and need for both mitigation and adaptation measures at early stages.
Malte Meinshausen, Carl-Friedrich Schleussner, Kathleen Beyer, Greg Bodeker, Olivier Boucher, Josep G. Canadell, John S. Daniel, Aïda Diongue-Niang, Fatima Driouech, Erich Fischer, Piers Forster, Michael Grose, Gerrit Hansen, Zeke Hausfather, Tatiana Ilyina, Jarmo S. Kikstra, Joyce Kimutai, Andrew D. King, June-Yi Lee, Chris Lennard, Tabea Lissner, Alexander Nauels, Glen P. Peters, Anna Pirani, Gian-Kasper Plattner, Hans Pörtner, Joeri Rogelj, Maisa Rojas, Joyashree Roy, Bjørn H. Samset, Benjamin M. Sanderson, Roland Séférian, Sonia Seneviratne, Christopher J. Smith, Sophie Szopa, Adelle Thomas, Diana Urge-Vorsatz, Guus J. M. Velders, Tokuta Yokohata, Tilo Ziehn, and Zebedee Nicholls
Geosci. Model Dev., 17, 4533–4559, https://doi.org/10.5194/gmd-17-4533-2024, https://doi.org/10.5194/gmd-17-4533-2024, 2024
Short summary
Short summary
The scientific community is considering new scenarios to succeed RCPs and SSPs for the next generation of Earth system model runs to project future climate change. To contribute to that effort, we reflect on relevant policy and scientific research questions and suggest categories for representative emission pathways. These categories are tailored to the Paris Agreement long-term temperature goal, high-risk outcomes in the absence of further climate policy and worlds “that could have been”.
Piers M. Forster, Chris Smith, Tristram Walsh, William F. Lamb, Robin Lamboll, Bradley Hall, Mathias Hauser, Aurélien Ribes, Debbie Rosen, Nathan P. Gillett, Matthew D. Palmer, Joeri Rogelj, Karina von Schuckmann, Blair Trewin, Myles Allen, Robbie Andrew, Richard A. Betts, Alex Borger, Tim Boyer, Jiddu A. Broersma, Carlo Buontempo, Samantha Burgess, Chiara Cagnazzo, Lijing Cheng, Pierre Friedlingstein, Andrew Gettelman, Johannes Gütschow, Masayoshi Ishii, Stuart Jenkins, Xin Lan, Colin Morice, Jens Mühle, Christopher Kadow, John Kennedy, Rachel E. Killick, Paul B. Krummel, Jan C. Minx, Gunnar Myhre, Vaishali Naik, Glen P. Peters, Anna Pirani, Julia Pongratz, Carl-Friedrich Schleussner, Sonia I. Seneviratne, Sophie Szopa, Peter Thorne, Mahesh V. M. Kovilakam, Elisa Majamäki, Jukka-Pekka Jalkanen, Margreet van Marle, Rachel M. Hoesly, Robert Rohde, Dominik Schumacher, Guido van der Werf, Russell Vose, Kirsten Zickfeld, Xuebin Zhang, Valérie Masson-Delmotte, and Panmao Zhai
Earth Syst. Sci. Data, 16, 2625–2658, https://doi.org/10.5194/essd-16-2625-2024, https://doi.org/10.5194/essd-16-2625-2024, 2024
Short summary
Short summary
This paper tracks some key indicators of global warming through time, from 1850 through to the end of 2023. It is designed to give an authoritative estimate of global warming to date and its causes. We find that in 2023, global warming reached 1.3 °C and is increasing at over 0.2 °C per decade. This is caused by all-time-high greenhouse gas emissions.
Basil Kraft, Michael Schirmer, William H. Aeberhard, Massimiliano Zappa, Sonia I. Seneviratne, and Lukas Gudmundsson
EGUsphere, https://doi.org/10.5194/egusphere-2024-993, https://doi.org/10.5194/egusphere-2024-993, 2024
Short summary
Short summary
This study uses deep learning to predict spatially contiguous water runoff in Switzerland from 1962–2023. It outperforms traditional models, requiring less data and computational power. Key findings include increased dry years and summer water scarcity. This method offers significant advancements in water monitoring.
Steven J. De Hertog, Carmen E. Lopez-Fabara, Ruud van der Ent, Jessica Keune, Diego G. Miralles, Raphael Portmann, Sebastian Schemm, Felix Havermann, Suqi Guo, Fei Luo, Iris Manola, Quentin Lejeune, Julia Pongratz, Carl-Friedrich Schleussner, Sonia I. Seneviratne, and Wim Thiery
Earth Syst. Dynam., 15, 265–291, https://doi.org/10.5194/esd-15-265-2024, https://doi.org/10.5194/esd-15-265-2024, 2024
Short summary
Short summary
Changes in land use are crucial to achieve lower global warming. However, despite their importance, the effects of these changes on moisture fluxes are poorly understood. We analyse land cover and management scenarios in three climate models involving cropland expansion, afforestation, and irrigation. Results show largely consistent influences on moisture fluxes, with cropland expansion causing a drying and reduced local moisture recycling, while afforestation and irrigation show the opposite.
Dominik L. Schumacher, Mariam Zachariah, Friederike Otto, Clair Barnes, Sjoukje Philip, Sarah Kew, Maja Vahlberg, Roop Singh, Dorothy Heinrich, Julie Arrighi, Maarten van Aalst, Mathias Hauser, Martin Hirschi, Verena Bessenbacher, Lukas Gudmundsson, Hiroko K. Beaudoing, Matthew Rodell, Sihan Li, Wenchang Yang, Gabriel A. Vecchi, Luke J. Harrington, Flavio Lehner, Gianpaolo Balsamo, and Sonia I. Seneviratne
Earth Syst. Dynam., 15, 131–154, https://doi.org/10.5194/esd-15-131-2024, https://doi.org/10.5194/esd-15-131-2024, 2024
Short summary
Short summary
The 2022 summer was accompanied by widespread soil moisture deficits, including an unprecedented drought in Europe. Combining several observation-based estimates and models, we find that such an event has become at least 5 and 20 times more likely due to human-induced climate change in western Europe and the northern extratropics, respectively. Strong regional warming fuels soil desiccation; hence, projections indicate even more potent future droughts as we progress towards a 2 °C warmer world.
Yann Quilcaille, Lukas Gudmundsson, and Sonia I. Seneviratne
Earth Syst. Dynam., 14, 1333–1362, https://doi.org/10.5194/esd-14-1333-2023, https://doi.org/10.5194/esd-14-1333-2023, 2023
Short summary
Short summary
Climate models are powerful tools, but they have high computational costs, hindering their use in exploring future climate extremes. We demonstrate MESMER-X, the only existing emulator for spatial climate extremes (heatwaves, fires, droughts) that mimics all of their relevant properties. Thanks to its negligible computational cost, MESMER-X may greatly accelerate the exploration of future climate extremes or enable the integration of climate extremes in economic and financial models.
Martin Hirschi, Bas Crezee, Pietro Stradiotti, Wouter Dorigo, and Sonia I. Seneviratne
EGUsphere, https://doi.org/10.5194/egusphere-2023-2499, https://doi.org/10.5194/egusphere-2023-2499, 2023
Short summary
Short summary
Based on surface and root-zone soil moisture, we compare the ability of selected long-term reanalysis and merged remote-sensing products to represent major agroecological drought events. While all products capture the investigated droughts, they particularly show differences in the drought magnitudes. Globally, the diverse and regionally contradicting dry-season soil moisture trends of the products is an important factor governing their drought representation and monitoring capability.
Shruti Nath, Lukas Gudmundsson, Jonas Schwaab, Gregory Duveiller, Steven J. De Hertog, Suqi Guo, Felix Havermann, Fei Luo, Iris Manola, Julia Pongratz, Sonia I. Seneviratne, Carl F. Schleussner, Wim Thiery, and Quentin Lejeune
Geosci. Model Dev., 16, 4283–4313, https://doi.org/10.5194/gmd-16-4283-2023, https://doi.org/10.5194/gmd-16-4283-2023, 2023
Short summary
Short summary
Tree cover changes play a significant role in climate mitigation and adaptation. Their regional impacts are key in informing national-level decisions and prioritising areas for conservation efforts. We present a first step towards exploring these regional impacts using a simple statistical device, i.e. emulator. The emulator only needs to train on climate model outputs representing the maximal impacts of aff-, re-, and deforestation, from which it explores plausible in-between outcomes itself.
Piers M. Forster, Christopher J. Smith, Tristram Walsh, William F. Lamb, Robin Lamboll, Mathias Hauser, Aurélien Ribes, Debbie Rosen, Nathan Gillett, Matthew D. Palmer, Joeri Rogelj, Karina von Schuckmann, Sonia I. Seneviratne, Blair Trewin, Xuebin Zhang, Myles Allen, Robbie Andrew, Arlene Birt, Alex Borger, Tim Boyer, Jiddu A. Broersma, Lijing Cheng, Frank Dentener, Pierre Friedlingstein, José M. Gutiérrez, Johannes Gütschow, Bradley Hall, Masayoshi Ishii, Stuart Jenkins, Xin Lan, June-Yi Lee, Colin Morice, Christopher Kadow, John Kennedy, Rachel Killick, Jan C. Minx, Vaishali Naik, Glen P. Peters, Anna Pirani, Julia Pongratz, Carl-Friedrich Schleussner, Sophie Szopa, Peter Thorne, Robert Rohde, Maisa Rojas Corradi, Dominik Schumacher, Russell Vose, Kirsten Zickfeld, Valérie Masson-Delmotte, and Panmao Zhai
Earth Syst. Sci. Data, 15, 2295–2327, https://doi.org/10.5194/essd-15-2295-2023, https://doi.org/10.5194/essd-15-2295-2023, 2023
Short summary
Short summary
This is a critical decade for climate action, but there is no annual tracking of the level of human-induced warming. We build on the Intergovernmental Panel on Climate Change assessment reports that are authoritative but published infrequently to create a set of key global climate indicators that can be tracked through time. Our hope is that this becomes an important annual publication that policymakers, media, scientists and the public can refer to.
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., 14, 629–667, https://doi.org/10.5194/esd-14-629-2023, https://doi.org/10.5194/esd-14-629-2023, 2023
Short summary
Short summary
Land cover and land management changes are important strategies for future land-based mitigation. We investigate the climate effects of cropland expansion, afforestation, irrigation and wood harvesting using three Earth system models. Results show that these have important implications for surface temperature where the land cover and/or management change occur and in remote areas. Idealized afforestation causes global warming, which might offset the cooling effect from enhanced carbon uptake.
Yann Quilcaille, Fulden Batibeniz, Andreia F. S. Ribeiro, Ryan S. Padrón, and Sonia I. Seneviratne
Earth Syst. Sci. Data, 15, 2153–2177, https://doi.org/10.5194/essd-15-2153-2023, https://doi.org/10.5194/essd-15-2153-2023, 2023
Short summary
Short summary
We present a new database of four annual fire weather indicators over 1850–2100 and over all land areas. In a 3°C warmer world with respect to preindustrial times, the mean fire weather would increase on average by at least 66% in both intensity and duration and even triple for 1-in-10-year events. The dataset is a freely available resource for fire danger studies and beyond, highlighting that the best course of action would require limiting global warming as much as possible.
Steven J. De Hertog, Carmen E. Lopez-Fabara, Ruud van der Ent, Jessica Keune, Diego G. Miralles, Raphael Portmann, Sebastian Schemm, Felix Havermann, Suqi Guo, Fei Luo, Iris Manola, Quentin Lejeune, Julia Pongratz, Carl-Friedrich Schleussner, Sonia I. Seneviratne, and Wim Thiery
EGUsphere, https://doi.org/10.5194/egusphere-2023-953, https://doi.org/10.5194/egusphere-2023-953, 2023
Preprint archived
Short summary
Short summary
Land cover and management changes can affect the climate and water availability. In this study we use climate model simulations of extreme global land cover changes (afforestation, deforestation) and land management changes (irrigation) to understand the effects on the global water cycle and local to continental water availability. We show that cropland expansion generally leads to higher evaporation and lower amounts of precipitation and afforestation and irrigation expansion to the opposite.
Francisco José Cuesta-Valero, Hugo Beltrami, Almudena García-García, Gerhard Krinner, Moritz Langer, Andrew H. MacDougall, Jan Nitzbon, Jian Peng, Karina von Schuckmann, Sonia I. Seneviratne, Wim Thiery, Inne Vanderkelen, and Tonghua Wu
Earth Syst. Dynam., 14, 609–627, https://doi.org/10.5194/esd-14-609-2023, https://doi.org/10.5194/esd-14-609-2023, 2023
Short summary
Short summary
Climate change is caused by the accumulated heat in the Earth system, with the land storing the second largest amount of this extra heat. Here, new estimates of continental heat storage are obtained, including changes in inland-water heat storage and permafrost heat storage in addition to changes in ground heat storage. We also argue that heat gains in all three components should be monitored independently of their magnitude due to heat-dependent processes affecting society and ecosystems.
Fulden Batibeniz, Mathias Hauser, and Sonia Isabelle Seneviratne
Earth Syst. Dynam., 14, 485–505, https://doi.org/10.5194/esd-14-485-2023, https://doi.org/10.5194/esd-14-485-2023, 2023
Short summary
Short summary
We study single and concurrent heatwaves, droughts, precipitation, and wind extremes. Globally, these extremes become more frequent and affect larger land areas under future warming, with several countries experiencing extreme events every single month. Concurrent heatwaves–droughts (precipitation–wind) are projected to increase the most in mid–high-latitude countries (tropics). Every mitigation action to avoid further warming will reduce the number of people exposed to extreme weather events.
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
Short summary
Short summary
Earth's climate is out of energy balance, and this study quantifies how much heat has consequently accumulated over the past decades (ocean: 89 %, land: 6 %, cryosphere: 4 %, atmosphere: 1 %). Since 1971, this accumulated heat reached record values at an increasing pace. The Earth heat inventory provides a comprehensive view on the status and expectation of global warming, and we call for an implementation of this global climate indicator into the Paris Agreement’s Global Stocktake.
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
Short summary
Short summary
In June 2021, the Pacific Northwest of the US and Canada saw record temperatures far exceeding those previously observed. This attribution study found such a severe heat wave would have been virtually impossible without human-induced climate change. Assuming no nonlinear interactions, such events have become at least 150 times more common, are about 2 °C hotter and will become even more common as warming continues. Therefore, adaptation and mitigation are urgently needed to prepare society.
Ryan S. Padrón, Lukas Gudmundsson, Laibao Liu, Vincent Humphrey, and Sonia I. Seneviratne
Biogeosciences, 19, 5435–5448, https://doi.org/10.5194/bg-19-5435-2022, https://doi.org/10.5194/bg-19-5435-2022, 2022
Short summary
Short summary
The answer to how much carbon land ecosystems are projected to remove from the atmosphere until 2100 is different for each Earth system model. We find that differences across models are primarily explained by the annual land carbon sink dependence on temperature and soil moisture, followed by the dependence on CO2 air concentration, and by average climate conditions. Our insights on why each model projects a relatively high or low land carbon sink can help to reduce the underlying uncertainty.
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
Short summary
Short summary
Land cover and land management changes are important strategies for future land-based mitigation. We investigate the climate effects of cropland expansion, afforestation, irrigation, and wood harvesting using three Earth system models. Results show that these have important implications for surface temperature where the land cover and/or management change occurs and in remote areas. Idealized afforestation causes global warming, which might offset the cooling effect from enhanced carbon uptake.
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
Earth Syst. Dynam., 13, 1167–1196, https://doi.org/10.5194/esd-13-1167-2022, https://doi.org/10.5194/esd-13-1167-2022, 2022
Short summary
Short summary
The ExtremeX experiment was designed to unravel the contribution of processes leading to the occurrence of recent weather and climate extremes. Global climate simulations are carried out with three models. The results show that in constrained experiments, temperature anomalies during heatwaves are well represented, although climatological model biases remain. Further, a substantial contribution of both atmospheric circulation and soil moisture to heat extremes is identified.
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
Weather Clim. Dynam., 3, 905–935, https://doi.org/10.5194/wcd-3-905-2022, https://doi.org/10.5194/wcd-3-905-2022, 2022
Short summary
Short summary
Recent studies have identified the weather systems in observational data, where wave patterns with high-magnitude values that circle around the whole globe in either wavenumber 5 or wavenumber 7 are responsible for the extreme events. In conclusion, we find that the climate models are able to reproduce the large-scale atmospheric circulation patterns as well as their associated surface variables such as temperature, precipitation, and sea level pressure.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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.
Lea Beusch, Zebedee Nicholls, Lukas Gudmundsson, Mathias Hauser, Malte Meinshausen, and Sonia I. Seneviratne
Geosci. Model Dev., 15, 2085–2103, https://doi.org/10.5194/gmd-15-2085-2022, https://doi.org/10.5194/gmd-15-2085-2022, 2022
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Related subject area
Dynamics of the Earth system: models
Stable stadial and interstadial states of the last glacial's climate identified in a combined stable water isotope and dust record from Greenland
The modelled climatic response to the 18.6-year lunar nodal cycle and its role in decadal temperature trends
The future of the El Niño–Southern Oscillation: using large ensembles to illuminate time-varying responses and inter-model differences
Regime-oriented causal model evaluation of Atlantic–Pacific teleconnections in CMIP6
Seasonal forecasting skill for the High Mountain Asia region in the Goddard Earth Observing System
Assessing sensitivities of climate model weighting to multiple methods, variables, and domains in the south-central United States
Global and northern-high-latitude net ecosystem production in the 21st century from CMIP6 experiments
Potential for bias in effective climate sensitivity from state-dependent energetic imbalance
Regional dynamical and statistical downscaling temperature, humidity and wind speed for the Beijing region under stratospheric aerosol injection geoengineering
Process-based estimate of global-mean sea-level changes in the Common Era
Present and future European heat wave magnitudes: climatologies, trends, and their associated uncertainties in GCM-RCM model chains
Improving the prediction of the Madden–Julian Oscillation of the ECMWF model by post-processing
Estimating the lateral transfer of organic carbon through the European river network using a land surface model
Effect of the Atlantic Meridional Overturning Circulation on atmospheric pCO2 variations
A methodology for the spatiotemporal identification of compound hazards: wind and precipitation extremes in Great Britain (1979–2019)
MESMER-M: an Earth system model emulator for spatially resolved monthly temperature
Evaluation of convection-permitting extreme precipitation simulations for the south of France
Agricultural management effects on mean and extreme temperature trends
Weakened impact of the Atlantic Niño on the future equatorial Atlantic and Guinea Coast rainfall
The fractional energy balance equation for climate projections through 2100
Climate change in the High Mountain Asia in CMIP6
The sensitivity of the El Niño–Southern Oscillation to volcanic aerosol spatial distribution in the MPI Grand Ensemble
Coupled regional Earth system modeling in the Baltic Sea region
Climate change projections of terrestrial primary productivity over the Hindu Kush Himalayan forests
Bookkeeping estimates of the net land-use change flux – a sensitivity study with the CMIP6 land-use dataset
Climate-controlled root zone parameters show potential to improve water flux simulations by land surface models
Space–time dependence of compound hot–dry events in the United States: assessment using a multi-site multi-variable weather generator
First assessment of the earth heat inventory within CMIP5 historical simulations
The thermal response of small and shallow lakes to climate change: new insights from 3D hindcast modelling
Labrador Sea subsurface density as a precursor of multidecadal variability in the North Atlantic: a multi-model study
How modelling paradigms affect simulated future land use change
Identifying meteorological drivers of extreme impacts: an application to simulated crop yields
Simulating compound weather extremes responsible for critical crop failure with stochastic weather generators
Characterisation of Atlantic meridional overturning hysteresis using Langevin dynamics
Evaluating the dependence structure of compound precipitation and wind speed extremes
Future sea level contribution from Antarctica inferred from CMIP5 model forcing and its dependence on precipitation ansatz
The extremely warm summer of 2018 in Sweden – set in a historical context
Effect of changing ocean circulation on deep ocean temperature in the last millennium
How large does a large ensemble need to be?
Reconstructing coupled time series in climate systems using three kinds of machine-learning methods
An investigation of weighting schemes suitable for incorporating large ensembles into multi-model ensembles
What could we learn about climate sensitivity from variability in the surface temperature record?
Using a nested single-model large ensemble to assess the internal variability of the North Atlantic Oscillation and its climatic implications for central Europe
Climate change in a conceptual atmosphere–phytoplankton model
Variability of surface climate in simulations of past and future
Statistical estimation of global surface temperature response to forcing under the assumption of temporal scaling
A global semi-empirical glacial isostatic adjustment (GIA) model based on Gravity Recovery and Climate Experiment (GRACE) data
Improvement in the decadal prediction skill of the North Atlantic extratropical winter circulation through increased model resolution
Societal breakdown as an emergent property of large-scale behavioural models of land use change
Improving weather and climate predictions by training of supermodels
Keno Riechers, Leonardo Rydin Gorjão, Forough Hassanibesheli, Pedro G. Lind, Dirk Witthaut, and Niklas Boers
Earth Syst. Dynam., 14, 593–607, https://doi.org/10.5194/esd-14-593-2023, https://doi.org/10.5194/esd-14-593-2023, 2023
Short summary
Short summary
Paleoclimate proxy records show that the North Atlantic climate repeatedly transitioned between two regimes during the last glacial interval. This study investigates a bivariate proxy record from a Greenland ice core which reflects past Greenland temperatures and large-scale atmospheric conditions. We reconstruct the underlying deterministic drift by estimating first-order Kramers–Moyal coefficients and identify two separate stable states in agreement with the aforementioned climatic regimes.
Manoj Joshi, Robert A. Hall, David P. Stevens, and Ed Hawkins
Earth Syst. Dynam., 14, 443–455, https://doi.org/10.5194/esd-14-443-2023, https://doi.org/10.5194/esd-14-443-2023, 2023
Short summary
Short summary
The 18.6-year lunar nodal cycle arises from variations in the angle of the Moon's orbital plane and affects ocean tides. In this work we use a climate model to examine the effect of this cycle on the ocean, surface, and atmosphere. The timing of anomalies is consistent with the so-called slowdown in global warming and has implications for when global temperatures will exceed 1.5 ℃ above pre-industrial levels. Regional anomalies have implications for seasonal climate areas such as Europe.
Nicola Maher, Robert C. Jnglin Wills, Pedro DiNezio, Jeremy Klavans, Sebastian Milinski, Sara C. Sanchez, Samantha Stevenson, Malte F. Stuecker, and Xian Wu
Earth Syst. Dynam., 14, 413–431, https://doi.org/10.5194/esd-14-413-2023, https://doi.org/10.5194/esd-14-413-2023, 2023
Short summary
Short summary
Understanding whether the El Niño–Southern Oscillation (ENSO) is likely to change in the future is important due to its widespread impacts. By using large ensembles, we can robustly isolate the time-evolving response of ENSO variability in 14 climate models. We find that ENSO variability evolves in a nonlinear fashion in many models and that there are large differences between models. These nonlinear changes imply that ENSO impacts may vary dramatically throughout the 21st century.
Soufiane Karmouche, Evgenia Galytska, Jakob Runge, Gerald A. Meehl, Adam S. Phillips, Katja Weigel, and Veronika Eyring
Earth Syst. Dynam., 14, 309–344, https://doi.org/10.5194/esd-14-309-2023, https://doi.org/10.5194/esd-14-309-2023, 2023
Short summary
Short summary
This study uses a causal discovery method to evaluate the ability of climate models to represent the interactions between the Atlantic multidecadal variability (AMV) and the Pacific decadal variability (PDV). The approach and findings in this study present a powerful methodology that can be applied to a number of environment-related topics, offering tremendous insights to improve the understanding of the complex Earth system and the state of the art of climate modeling.
Elias C. Massoud, Lauren Andrews, Rolf Reichle, Andrea Molod, Jongmin Park, Sophie Ruehr, and Manuela Girotto
Earth Syst. Dynam., 14, 147–171, https://doi.org/10.5194/esd-14-147-2023, https://doi.org/10.5194/esd-14-147-2023, 2023
Short summary
Short summary
In this study, we benchmark the forecast skill of the NASA’s Goddard Earth Observing System subseasonal-to-seasonal (GEOS-S2S version 2) hydrometeorological forecasts in the High Mountain Asia (HMA) region. Hydrometeorological forecast skill is dependent on the forecast lead time, the memory of the variable within the physical system, and the validation dataset used. Overall, these results benchmark the GEOS-S2S system’s ability to forecast HMA hydrometeorology on the seasonal timescale.
Adrienne M. Wootten, Elias C. Massoud, Duane E. Waliser, and Huikyo Lee
Earth Syst. Dynam., 14, 121–145, https://doi.org/10.5194/esd-14-121-2023, https://doi.org/10.5194/esd-14-121-2023, 2023
Short summary
Short summary
Climate projections and multi-model ensemble weighting are increasingly used for climate assessments. This study examines the sensitivity of projections to multi-model ensemble weighting strategies in the south-central United States. Model weighting and ensemble means are sensitive to the domain and variable used. There are numerous findings regarding the improvement in skill with model weighting and the sensitivity associated with various strategies.
Han Qiu, Dalei Hao, Yelu Zeng, Xuesong Zhang, and Min Chen
Earth Syst. Dynam., 14, 1–16, https://doi.org/10.5194/esd-14-1-2023, https://doi.org/10.5194/esd-14-1-2023, 2023
Short summary
Short summary
The carbon cycling in terrestrial ecosystems is complex. In our analyses, we found that both the global and the northern-high-latitude (NHL) ecosystems will continue to have positive net ecosystem production (NEP) in the next few decades under four global change scenarios but with large uncertainties. NHL ecosystems will experience faster climate warming but steadily contribute a small fraction of the global NEP. However, the relative uncertainty of NHL NEP is much larger than the global values.
Benjamin M. Sanderson and Maria Rugenstein
Earth Syst. Dynam., 13, 1715–1736, https://doi.org/10.5194/esd-13-1715-2022, https://doi.org/10.5194/esd-13-1715-2022, 2022
Short summary
Short summary
Equilibrium climate sensitivity (ECS) is a measure of how much long-term warming should be expected in response to a change in greenhouse gas concentrations. It is generally calculated in climate models by extrapolating global average temperatures to a point of where the planet is no longer a net absorber of energy. Here we show that some climate models experience energy leaks which change as the planet warms, undermining the standard approach and biasing some existing model estimates of ECS.
Jun Wang, John C. Moore, Liyun Zhao, Chao Yue, and Zhenhua Di
Earth Syst. Dynam., 13, 1625–1640, https://doi.org/10.5194/esd-13-1625-2022, https://doi.org/10.5194/esd-13-1625-2022, 2022
Short summary
Short summary
We examine how geoengineering using aerosols in the atmosphere might impact urban climate in the greater Beijing region containing over 50 million people. Climate models have too coarse resolutions to resolve regional variations well, so we compare two workarounds for this – an expensive physical model and a cheaper statistical method. The statistical method generally gives a reasonable representation of climate and has limited resolution and a different seasonality from the physical model.
Nidheesh Gangadharan, Hugues Goosse, David Parkes, Heiko Goelzer, Fabien Maussion, and Ben Marzeion
Earth Syst. Dynam., 13, 1417–1435, https://doi.org/10.5194/esd-13-1417-2022, https://doi.org/10.5194/esd-13-1417-2022, 2022
Short summary
Short summary
We describe the contributions of ocean thermal expansion and land-ice melting (ice sheets and glaciers) to global-mean sea-level (GMSL) changes in the Common Era. The mass contributions are the major sources of GMSL changes in the pre-industrial Common Era and glaciers are the largest contributor. The paper also describes the current state of climate modelling, uncertainties and knowledge gaps along with the potential implications of the past variabilities in the contemporary sea-level rise.
Changgui Lin, Erik Kjellström, Renate Anna Irma Wilcke, and Deliang Chen
Earth Syst. Dynam., 13, 1197–1214, https://doi.org/10.5194/esd-13-1197-2022, https://doi.org/10.5194/esd-13-1197-2022, 2022
Short summary
Short summary
This study endorses RCMs' added value on the driving GCMs in representing observed heat wave magnitudes. The future increase of heat wave magnitudes projected by GCMs is attenuated when downscaled by RCMs. Within the downscaling, uncertainties can be attributed almost equally to choice of RCMs and to the driving data associated with different GCMs. Uncertainties of GCMs in simulating heat wave magnitudes are transformed by RCMs in a complex manner rather than simply inherited.
Riccardo Silini, Sebastian Lerch, Nikolaos Mastrantonas, Holger Kantz, Marcelo Barreiro, and Cristina Masoller
Earth Syst. Dynam., 13, 1157–1165, https://doi.org/10.5194/esd-13-1157-2022, https://doi.org/10.5194/esd-13-1157-2022, 2022
Short summary
Short summary
The Madden–Julian Oscillation (MJO) has important socioeconomic impacts due to its influence on both tropical and extratropical weather extremes. In this study, we use machine learning (ML) to correct the predictions of the weather model holding the best performance, developed by the European Centre for Medium-Range Weather Forecasts (ECMWF). We show that the ML post-processing leads to an improved prediction of the MJO geographical location and intensity.
Haicheng Zhang, Ronny Lauerwald, Pierre Regnier, Philippe Ciais, Kristof Van Oost, Victoria Naipal, Bertrand Guenet, and Wenping Yuan
Earth Syst. Dynam., 13, 1119–1144, https://doi.org/10.5194/esd-13-1119-2022, https://doi.org/10.5194/esd-13-1119-2022, 2022
Short summary
Short summary
We present a land surface model which can simulate the complete lateral transfer of sediment and carbon from land to ocean through rivers. Our model captures the water, sediment, and organic carbon discharges in European rivers well. Application of our model in Europe indicates that lateral carbon transfer can strongly change regional land carbon budgets by affecting organic carbon distribution and soil moisture.
Amber Boot, Anna S. von der Heydt, and Henk A. Dijkstra
Earth Syst. Dynam., 13, 1041–1058, https://doi.org/10.5194/esd-13-1041-2022, https://doi.org/10.5194/esd-13-1041-2022, 2022
Short summary
Short summary
Atmospheric pCO2 of the past shows large variability on different timescales. We focus on the effect of the strength of Atlantic Meridional Overturning Circulation (AMOC) on this variability and on the AMOC–pCO2 relationship. We find that climatic boundary conditions and the representation of biology in our model are most important for this relationship. Under certain conditions, we find internal oscillations, which can be relevant for atmospheric pCO2 variability during glacial cycles.
Aloïs Tilloy, Bruce D. Malamud, and Amélie Joly-Laugel
Earth Syst. Dynam., 13, 993–1020, https://doi.org/10.5194/esd-13-993-2022, https://doi.org/10.5194/esd-13-993-2022, 2022
Short summary
Short summary
Compound hazards occur when two different natural hazards impact the same time period and spatial area. This article presents a methodology for the spatiotemporal identification of compound hazards (SI–CH). The methodology is applied to compound precipitation and wind extremes in Great Britain for the period 1979–2019. The study finds that the SI–CH approach can accurately identify single and compound hazard events and represent their spatial and temporal properties.
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
Short summary
Short summary
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.
Linh N. Luu, Robert Vautard, Pascal Yiou, and Jean-Michel Soubeyroux
Earth Syst. Dynam., 13, 687–702, https://doi.org/10.5194/esd-13-687-2022, https://doi.org/10.5194/esd-13-687-2022, 2022
Short summary
Short summary
This study downscales climate information from EURO-CORDEX (approx. 12 km) output to a higher horizontal resolution (approx. 3 km) for the south of France. We also propose a matrix of different indices to evaluate the high-resolution precipitation output. We find that a higher resolution reproduces more realistic extreme precipitation events at both daily and sub-daily timescales. Our results and approach are promising to apply to other Mediterranean regions and climate impact studies.
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
Short summary
Short summary
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.
Koffi Worou, Hugues Goosse, Thierry Fichefet, and Fred Kucharski
Earth Syst. Dynam., 13, 231–249, https://doi.org/10.5194/esd-13-231-2022, https://doi.org/10.5194/esd-13-231-2022, 2022
Short summary
Short summary
Over the Guinea Coast, the increased rainfall associated with warm phases of the Atlantic Niño is reasonably well simulated by 24 climate models out of 31, for the present-day conditions. In a warmer climate, general circulation models project a gradual decrease with time of the rainfall magnitude associated with the Atlantic Niño for the 2015–2039, 2040–2069 and 2070–2099 periods. There is a higher confidence in these changes over the equatorial Atlantic than over the Guinea Coast.
Roman Procyk, Shaun Lovejoy, and Raphael Hébert
Earth Syst. Dynam., 13, 81–107, https://doi.org/10.5194/esd-13-81-2022, https://doi.org/10.5194/esd-13-81-2022, 2022
Short summary
Short summary
This paper presents a new class of energy balance model that accounts for the long memory within the Earth's energy storage. The model is calibrated on instrumental temperature records and the historical energy budget of the Earth using an error model predicted by the model itself. Our equilibrium climate sensitivity and future temperature projection estimates are consistent with those estimated by complex climate models.
Mickaël Lalande, Martin Ménégoz, Gerhard Krinner, Kathrin Naegeli, and Stefan Wunderle
Earth Syst. Dynam., 12, 1061–1098, https://doi.org/10.5194/esd-12-1061-2021, https://doi.org/10.5194/esd-12-1061-2021, 2021
Short summary
Short summary
Climate change over High Mountain Asia is investigated with CMIP6 climate models. A general cold bias is found in this area, often related to a snow cover overestimation in the models. Ensemble experiments generally encompass the past observed trends, suggesting that even biased models can reproduce the trends. Depending on the future scenario, a warming from 1.9 to 6.5 °C, associated with a snow cover decrease and precipitation increase, is expected at the end of the 21st century.
Benjamin Ward, Francesco S. R. Pausata, and Nicola Maher
Earth Syst. Dynam., 12, 975–996, https://doi.org/10.5194/esd-12-975-2021, https://doi.org/10.5194/esd-12-975-2021, 2021
Short summary
Short summary
Using the largest ensemble of a climate model currently available, the Max Planck Institute Grand Ensemble (MPI-GE), we investigated the impact of the spatial distribution of volcanic aerosols on the El Niño–Southern Oscillation (ENSO) response. By selecting three eruptions with different aerosol distributions, we found that the shift of the Intertropical Convergence Zone (ITCZ) is the main driver of the ENSO response, while other mechanisms commonly invoked seem less important in our model.
Matthias Gröger, Christian Dieterich, Jari Haapala, Ha Thi Minh Ho-Hagemann, Stefan Hagemann, Jaromir Jakacki, Wilhelm May, H. E. Markus Meier, Paul A. Miller, Anna Rutgersson, and Lichuan Wu
Earth Syst. Dynam., 12, 939–973, https://doi.org/10.5194/esd-12-939-2021, https://doi.org/10.5194/esd-12-939-2021, 2021
Short summary
Short summary
Regional climate studies are typically pursued by single Earth system component models (e.g., ocean models and atmosphere models). These models are driven by prescribed data which hamper the simulation of feedbacks between Earth system components. To overcome this, models were developed that interactively couple model components and allow an adequate simulation of Earth system interactions important for climate. This article reviews recent developments of such models for the Baltic Sea region.
Halima Usman, Thomas A. M. Pugh, Anders Ahlström, and Sofia Baig
Earth Syst. Dynam., 12, 857–870, https://doi.org/10.5194/esd-12-857-2021, https://doi.org/10.5194/esd-12-857-2021, 2021
Short summary
Short summary
The study assesses the impacts of climate change on forest productivity in the Hindu Kush Himalayan region. LPJ-GUESS was simulated from 1851 to 2100. In first approach, the model was compared with observational estimates. The comparison showed a moderate agreement. In the second approach, the model was assessed for the temporal and spatial trends of net biome productivity and its components along with carbon pool. Increases in both variables were predicted in 2100.
Kerstin Hartung, Ana Bastos, Louise Chini, Raphael Ganzenmüller, Felix Havermann, George C. Hurtt, Tammas Loughran, Julia E. M. S. Nabel, Tobias Nützel, Wolfgang A. Obermeier, and Julia Pongratz
Earth Syst. Dynam., 12, 763–782, https://doi.org/10.5194/esd-12-763-2021, https://doi.org/10.5194/esd-12-763-2021, 2021
Short summary
Short summary
In this study, we model the relative importance of several contributors to the land-use and land-cover change (LULCC) flux based on a LULCC dataset including uncertainty estimates. The uncertainty of LULCC is as relevant as applying wood harvest and gross transitions for the cumulative LULCC flux over the industrial period. However, LULCC uncertainty matters less than the other two factors for the LULCC flux in 2014; historical LULCC uncertainty is negligible for estimates of future scenarios.
Fransje van Oorschot, Ruud J. van der Ent, Markus Hrachowitz, and Andrea Alessandri
Earth Syst. Dynam., 12, 725–743, https://doi.org/10.5194/esd-12-725-2021, https://doi.org/10.5194/esd-12-725-2021, 2021
Short summary
Short summary
The roots of vegetation largely control the Earth's water cycle by transporting water from the subsurface to the atmosphere but are not adequately represented in land surface models, causing uncertainties in modeled water fluxes. We replaced the root parameters in an existing model with more realistic ones that account for a climate control on root development and found improved timing of modeled river discharge. Further extension of our approach could improve modeled water fluxes globally.
Manuela I. Brunner, Eric Gilleland, and Andrew W. Wood
Earth Syst. Dynam., 12, 621–634, https://doi.org/10.5194/esd-12-621-2021, https://doi.org/10.5194/esd-12-621-2021, 2021
Short summary
Short summary
Compound hot and dry events can lead to severe impacts whose severity may depend on their timescale and spatial extent. Here, we show that the spatial extent and timescale of compound hot–dry events are strongly related, spatial compound event extents are largest at
sub-seasonal timescales, and short events are driven more by high temperatures, while longer events are more driven by low precipitation. Future climate impact studies should therefore be performed at different timescales.
Francisco José Cuesta-Valero, Almudena García-García, Hugo Beltrami, and Joel Finnis
Earth Syst. Dynam., 12, 581–600, https://doi.org/10.5194/esd-12-581-2021, https://doi.org/10.5194/esd-12-581-2021, 2021
Short summary
Short summary
The current radiative imbalance at the top of the atmosphere is increasing the heat stored in the oceans, atmosphere, continental subsurface and cryosphere, with consequences for societies and ecosystems (e.g. sea level rise). We performed the first assessment of the ability of global climate models to represent such heat storage in the climate subsystems. Models are able to reproduce the observed atmosphere heat content, with biases in the simulation of heat content in the rest of components.
Francesco Piccioni, Céline Casenave, Bruno Jacques Lemaire, Patrick Le Moigne, Philippe Dubois, and Brigitte Vinçon-Leite
Earth Syst. Dynam., 12, 439–456, https://doi.org/10.5194/esd-12-439-2021, https://doi.org/10.5194/esd-12-439-2021, 2021
Short summary
Short summary
Small lakes are ecosystems highly impacted by climate change. Here, the thermal regime of a small, shallow lake over the past six decades was reconstructed via 3D modelling. Significant changes were found: strong water warming in spring and summer (0.7 °C/decade) as well as increased stratification and thermal energy for cyanobacteria growth, especially in spring. The strong spatial patterns detected for stratification might create local conditions particularly favourable to cyanobacteria bloom.
Pablo Ortega, Jon I. Robson, Matthew Menary, Rowan T. Sutton, Adam Blaker, Agathe Germe, Jöel J.-M. Hirschi, Bablu Sinha, Leon Hermanson, and Stephen Yeager
Earth Syst. Dynam., 12, 419–438, https://doi.org/10.5194/esd-12-419-2021, https://doi.org/10.5194/esd-12-419-2021, 2021
Short summary
Short summary
Deep Labrador Sea densities are receiving increasing attention because of their link to many of the processes that govern decadal climate oscillations in the North Atlantic and their potential use as a precursor of those changes. This article explores those links and how they are represented in global climate models, documenting the main differences across models. Models are finally compared with observational products to identify the ones that reproduce the links more realistically.
Calum Brown, Ian Holman, and Mark Rounsevell
Earth Syst. Dynam., 12, 211–231, https://doi.org/10.5194/esd-12-211-2021, https://doi.org/10.5194/esd-12-211-2021, 2021
Short summary
Short summary
The variety of human and natural processes in the land system can be modelled in many different ways. However, little is known about how and why basic model assumptions affect model results. We compared two models that represent land use in completely distinct ways and found several results that differed greatly. We identify the main assumptions that caused these differences and therefore key issues that need to be addressed for more robust model development.
Johannes Vogel, Pauline Rivoire, Cristina Deidda, Leila Rahimi, Christoph A. Sauter, Elisabeth Tschumi, Karin van der Wiel, Tianyi Zhang, and Jakob Zscheischler
Earth Syst. Dynam., 12, 151–172, https://doi.org/10.5194/esd-12-151-2021, https://doi.org/10.5194/esd-12-151-2021, 2021
Short summary
Short summary
We present a statistical approach for automatically identifying multiple drivers of extreme impacts based on LASSO regression. We apply the approach to simulated crop failure in the Northern Hemisphere and identify which meteorological variables including climate extreme indices and which seasons are relevant to predict crop failure. The presented approach can help unravel compounding drivers in high-impact events and could be applied to other impacts such as wildfires or flooding.
Peter Pfleiderer, Aglaé Jézéquel, Juliette Legrand, Natacha Legrix, Iason Markantonis, Edoardo Vignotto, and Pascal Yiou
Earth Syst. Dynam., 12, 103–120, https://doi.org/10.5194/esd-12-103-2021, https://doi.org/10.5194/esd-12-103-2021, 2021
Short summary
Short summary
In 2016, northern France experienced an unprecedented wheat crop loss. This crop loss was likely due to an extremely warm December 2015 and abnormally high precipitation during the following spring season. Using stochastic weather generators we investigate how severe the metrological conditions leading to the crop loss could be in current climate conditions. We find that December temperatures were close to the plausible maximum but that considerably wetter springs would be possible.
Jelle van den Berk, Sybren Drijfhout, and Wilco Hazeleger
Earth Syst. Dynam., 12, 69–81, https://doi.org/10.5194/esd-12-69-2021, https://doi.org/10.5194/esd-12-69-2021, 2021
Short summary
Short summary
A collapse of the Atlantic Meridional Overturning Circulation can be described by six parameters and Langevin dynamics. These parameters can be determined from collapses seen in climate models of intermediate complexity. With this parameterisation, it might be possible to estimate how much fresh water is needed to observe a collapse in more complicated models and reality.
Jakob Zscheischler, Philippe Naveau, Olivia Martius, Sebastian Engelke, and Christoph C. Raible
Earth Syst. Dynam., 12, 1–16, https://doi.org/10.5194/esd-12-1-2021, https://doi.org/10.5194/esd-12-1-2021, 2021
Short summary
Short summary
Compound extremes such as heavy precipitation and extreme winds can lead to large damage. To date it is unclear how well climate models represent such compound extremes. Here we present a new measure to assess differences in the dependence structure of bivariate extremes. This measure is applied to assess differences in the dependence of compound precipitation and wind extremes between three model simulations and one reanalysis dataset in a domain in central Europe.
Christian B. Rodehacke, Madlene Pfeiffer, Tido Semmler, Özgür Gurses, and Thomas Kleiner
Earth Syst. Dynam., 11, 1153–1194, https://doi.org/10.5194/esd-11-1153-2020, https://doi.org/10.5194/esd-11-1153-2020, 2020
Short summary
Short summary
In the warmer future, Antarctica's ice sheet will lose more ice due to enhanced iceberg calving and a warming ocean that melts more floating ice from below. However, the hydrological cycle is also stronger in a warmer world. Hence, more snowfall will precipitate on Antarctica and may balance the amplified ice loss. We have used future climate scenarios from various global climate models to perform numerous ice sheet simulations to show that precipitation may counteract mass loss.
Renate Anna Irma Wilcke, Erik Kjellström, Changgui Lin, Daniela Matei, Anders Moberg, and Evangelos Tyrlis
Earth Syst. Dynam., 11, 1107–1121, https://doi.org/10.5194/esd-11-1107-2020, https://doi.org/10.5194/esd-11-1107-2020, 2020
Short summary
Short summary
Two long-lasting high-pressure systems in summer 2018 led to heat waves over Scandinavia and an extended summer period with devastating impacts on both agriculture and human life. Using five climate model ensembles, the unique 263-year Stockholm temperature time series and a composite 150-year time series for the whole of Sweden, we found that anthropogenic climate change has strongly increased the probability of a warm summer, such as the one observed in 2018, occurring in Sweden.
Jeemijn Scheen and Thomas F. Stocker
Earth Syst. Dynam., 11, 925–951, https://doi.org/10.5194/esd-11-925-2020, https://doi.org/10.5194/esd-11-925-2020, 2020
Short summary
Short summary
Variability of sea surface temperatures (SST) in 1200–2000 CE is quite well-known, but the history of deep ocean temperatures is not. Forcing an ocean model with these SSTs, we simulate temperatures in the ocean interior. The circulation changes alter the amplitude and timing of deep ocean temperature fluctuations below 2 km depth, e.g. delaying the atmospheric signal by ~ 200 years in the deep Atlantic. Thus ocean circulation changes are shown to be as important as SST changes at these depths.
Sebastian Milinski, Nicola Maher, and Dirk Olonscheck
Earth Syst. Dynam., 11, 885–901, https://doi.org/10.5194/esd-11-885-2020, https://doi.org/10.5194/esd-11-885-2020, 2020
Short summary
Short summary
Initial-condition large ensembles with ensemble sizes ranging from 30 to 100 members have become a commonly used tool to quantify the forced response and internal variability in various components of the climate system, but there is no established method to determine the required ensemble size for a given problem. We propose a new framework that can be used to estimate the required ensemble size from a model's control run or an existing large ensemble.
Yu Huang, Lichao Yang, and Zuntao Fu
Earth Syst. Dynam., 11, 835–853, https://doi.org/10.5194/esd-11-835-2020, https://doi.org/10.5194/esd-11-835-2020, 2020
Short summary
Short summary
We investigate the applicability of machine learning (ML) on time series reconstruction and find that the dynamical coupling relation and nonlinear causality are crucial for the application of ML. Our results could provide insights into causality and ML approaches for paleoclimate reconstruction, parameterization schemes, and prediction in climate studies.
Anna Louise Merrifield, Lukas Brunner, Ruth Lorenz, Iselin Medhaug, and Reto Knutti
Earth Syst. Dynam., 11, 807–834, https://doi.org/10.5194/esd-11-807-2020, https://doi.org/10.5194/esd-11-807-2020, 2020
Short summary
Short summary
Justifiable uncertainty estimates of future change in northern European winter and Mediterranean summer temperature can be obtained by weighting a multi-model ensemble comprised of projections from different climate models and multiple projections from the same climate model. Weights reduce the influence of model biases and handle dependence by identifying a projection's model of origin from historical characteristics; contributions from the same model are scaled by the number of members.
James D. Annan, Julia C. Hargreaves, Thorsten Mauritsen, and Bjorn Stevens
Earth Syst. Dynam., 11, 709–719, https://doi.org/10.5194/esd-11-709-2020, https://doi.org/10.5194/esd-11-709-2020, 2020
Short summary
Short summary
In this paper we explore the potential of variability for constraining the equilibrium response of the climate system to external forcing. We show that the constraint is inherently skewed, with a long tail to high sensitivity, and that while the variability may contain some useful information, it is unlikely to generate a tight constraint.
Andrea Böhnisch, Ralf Ludwig, and Martin Leduc
Earth Syst. Dynam., 11, 617–640, https://doi.org/10.5194/esd-11-617-2020, https://doi.org/10.5194/esd-11-617-2020, 2020
Short summary
Short summary
North Atlantic air pressure variations influencing European climate variables are simulated in coarse-resolution global climate models (GCMs). As single-model runs do not sufficiently describe variations of their patterns, several model runs with slightly diverging initial conditions are analyzed. The study shows that GCM and regional climate model (RCM) patterns vary in a similar range over the same domain, while RCMs add consistent fine-scale information due to their higher spatial resolution.
György Károlyi, Rudolf Dániel Prokaj, István Scheuring, and Tamás Tél
Earth Syst. Dynam., 11, 603–615, https://doi.org/10.5194/esd-11-603-2020, https://doi.org/10.5194/esd-11-603-2020, 2020
Short summary
Short summary
We construct a conceptual model to understand the interplay between the atmosphere and the ocean biosphere in a climate change framework, including couplings between extraction of carbon dioxide by phytoplankton and climate change, temperature and carrying capacity of phytoplankton, and wind energy and phytoplankton production. We find that sufficiently strong mixing can result in decaying global phytoplankton content.
Kira Rehfeld, Raphaël Hébert, Juan M. Lora, Marcus Lofverstrom, and Chris M. Brierley
Earth Syst. Dynam., 11, 447–468, https://doi.org/10.5194/esd-11-447-2020, https://doi.org/10.5194/esd-11-447-2020, 2020
Short summary
Short summary
Under continued anthropogenic greenhouse gas emissions, it is likely that global mean surface temperature will continue to increase. Little is known about changes in climate variability. We analyze surface climate variability and compare it to mean change in colder- and warmer-than-present climate model simulations. In most locations, but not on subtropical land, simulated temperature variability up to decadal timescales decreases with mean temperature, and precipitation variability increases.
Eirik Myrvoll-Nilsen, Sigrunn Holbek Sørbye, Hege-Beate Fredriksen, Håvard Rue, and Martin Rypdal
Earth Syst. Dynam., 11, 329–345, https://doi.org/10.5194/esd-11-329-2020, https://doi.org/10.5194/esd-11-329-2020, 2020
Short summary
Short summary
This paper presents efficient Bayesian methods for linear response models of global mean surface temperature that take into account long-range dependence. We apply the methods to the instrumental temperature record and historical model runs in the CMIP5 ensemble to provide estimates of the transient climate response and temperature projections under the Representative Concentration Pathways.
Yu Sun and Riccardo E. M. Riva
Earth Syst. Dynam., 11, 129–137, https://doi.org/10.5194/esd-11-129-2020, https://doi.org/10.5194/esd-11-129-2020, 2020
Short summary
Short summary
The solid Earth is still deforming because of the effect of past ice sheets through glacial isostatic adjustment (GIA). Satellite gravity observations by the Gravity Recovery and Climate Experiment (GRACE) mission are sensitive to those signals but are superimposed on the redistribution effect of water masses by the hydrological cycle. We propose a method separating the two signals, providing new constraints for forward GIA models and estimating the global water cycle's patterns and magnitude.
Mareike Schuster, Jens Grieger, Andy Richling, Thomas Schartner, Sebastian Illing, Christopher Kadow, Wolfgang A. Müller, Holger Pohlmann, Stephan Pfahl, and Uwe Ulbrich
Earth Syst. Dynam., 10, 901–917, https://doi.org/10.5194/esd-10-901-2019, https://doi.org/10.5194/esd-10-901-2019, 2019
Short summary
Short summary
Decadal climate predictions are valuable to society as they allow us to estimate climate conditions several years in advance. We analyze the latest version of the German MiKlip prediction system (https://www.fona-miklip.de) and assess the effect of the model resolution on the skill of the system. The increase in the resolution of the system reduces the bias and significantly improves the forecast skill for North Atlantic extratropical winter dynamics for lead times of two to five winters.
Calum Brown, Bumsuk Seo, and Mark Rounsevell
Earth Syst. Dynam., 10, 809–845, https://doi.org/10.5194/esd-10-809-2019, https://doi.org/10.5194/esd-10-809-2019, 2019
Short summary
Short summary
Concerns are growing that human activity will lead to social and environmental breakdown, but it is hard to anticipate when and where such breakdowns might occur. We developed a new model of land management decisions in Europe to explore possible future changes and found that decision-making that takes into account social and environmental conditions can produce unexpected outcomes that include societal breakdown in challenging conditions.
Francine Schevenhoven, Frank Selten, Alberto Carrassi, and Noel Keenlyside
Earth Syst. Dynam., 10, 789–807, https://doi.org/10.5194/esd-10-789-2019, https://doi.org/10.5194/esd-10-789-2019, 2019
Short summary
Short summary
Weather and climate predictions potentially improve by dynamically combining different models into a
supermodel. A crucial step is to train the supermodel on the basis of observations. Here, we apply two different training methods to the global atmosphere–ocean–land model SPEEDO. We demonstrate that both training methods yield climate and weather predictions of superior quality compared to the individual models. Supermodel predictions can also outperform the commonly used multi-model mean.
Cited articles
Abramowitz, G., Herger, N., Gutmann, E., Hammerling, D., Knutti, R., Leduc, M., Lorenz, R., Pincus, R., and Schmidt, G. A.: ESD Reviews: Model dependence in multi-model climate ensembles: weighting, sub-selection and out-of-sample testing, Earth Syst. Dynam., 10, 91–105, https://doi.org/10.5194/esd-10-91-2019, 2019. a
Allen, M. R. and Stott, P. A.: Estimating signal amplitudes in optimal
fingerprinting, part I: Theory, Clim. Dynam., 21, 477–491,
https://doi.org/10.1007/s00382-003-0313-9, 2003. a
Bao, J., McInerney, D. J., and Stein, M. L.: A spatial-dependent model for
climate emulation, Environmetrics, 27, 396–408, https://doi.org/10.1002/env.2412,
2016. a, b, c
Beusch, L., Gudmundsson, L., and Seneviratne, S. I.: Emulating Earth System
Model Temperatures, in: Proceedings of the 8th International Workshop on
Climate Informatics: CI 2018, 19–21 September 2018, Boulder, CO, USA, edited by: Chen, C., Cooley, D., Runge, J., and
Szekely, E., NCAR Technical Note, Boulder, 41–44,
https://doi.org/10.5065/D6BZ64XQ, 2018. a
Bishop, C. H. and Abramowitz, G.: Climate model dependence and the replicate
Earth paradigm, Clim. Dynam., 41, 885–900,
https://doi.org/10.1007/s00382-012-1610-y, 2013. a
Brown, P. T., Li, W., Cordero, E. C., and Mauget, S. A.: Comparing the
model-simulated global warming signal to observations using empirical
estimates of unforced noise, Sci. Rep., 5, 1–9,
https://doi.org/10.1038/srep09957, 2015. a
Carrassi, A., Bocquet, M., Bertino, L., and Evensen, G.: Data assimilation in the geosciences: An overview of methods, issues, and perspectives, WIRES Clim. Change, 9, 1–79, https://doi.org/10.1002/wcc.535,
2018. a
Castruccio, S. and Genton, M. G.: Compressing an Ensemble With Statistical
Models: An Algorithm for Global 3D Spatio-Temporal Temperature,
Technometrics, 58, 319–328, https://doi.org/10.1080/00401706.2015.1027068, 2016. a, b, c, d
Castruccio, S., McInerney, D. J., Stein, M. L., Crouch, F. L., Jacob, R. L.,
and Moyer, E. J.: Statistical emulation of climate model projections based
on precomputed GCM runs, J. Climate, 27, 1829–1844,
https://doi.org/10.1175/JCLI-D-13-00099.1, 2014. a, b, c
Deser, C., Phillips, A., Bourdette, V., and Teng, H.: Uncertainty in climate
change projections: The role of internal variability, Clim. Dynam., 38,
527–546, https://doi.org/10.1007/s00382-010-0977-x, 2012. a, b, c
Eyring, V., Bony, S., Meehl, G. A., Senior, C. A., Stevens, B., Stouffer, R. J., and Taylor, K. E.: Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization, Geosci. Model Dev., 9, 1937–1958, https://doi.org/10.5194/gmd-9-1937-2016, 2016. a, b
Eyring, V., Cox, P. M., Flato, G. M., Gleckler, P. J., Abramowitz, G.,
Caldwell, P., Collins, W. D., Gier, B. K., Hall, A. D., Hoffman, F. M.,
Hurtt, G. C., Jahn, A., Jones, C. D., Klein, S. A., Krasting, J. P.,
Kwiatkowski, L., Lorenz, R., Maloney, E., Meehl, G. A., Pendergrass, A. G.,
Pincus, R., Ruane, A. C., Russell, J. L., Sanderson, B. M., Santer, B. D.,
Sherwood, S. C., Simpson, I. R., Stouffer, R. J., and Williamson, M. S.:
Taking climate model evaluation to the next level, Nat. Clim. Change,
9, 102–110, https://doi.org/10.1038/s41558-018-0355-y, 2019. a
Fischer, E. M., Beyerle, U., and Knutti, R.: Robust spatially aggregated
projections of climate extremes, Nat. Clim. Change, 3, 1033–1038,
https://doi.org/10.1038/nclimate2051, 2013. a, b
Frieler, K., Meinshausen, M., Mengel, M., Braun, N., and Hare, W.: A scaling
approach to probabilistic assessment of regional climate change, J.
Climate, 25, 3117–3144, https://doi.org/10.1175/JCLI-D-11-00199.1, 2012. a
Gaspari, G. and Cohn, S. E.: Construction of correlation functions in two and
three dimensions, Q. J. Roy. Meteor. Soc.,
125, 723–757, https://doi.org/10.1256/smsqj.55416, 1999. a
Goodwin, P.: How historic simulation–observation discrepancy affects future
warming projections in a very large model ensemble, Clim. Dynam., 47,
2219–2233, https://doi.org/10.1007/s00382-015-2960-z, 2016. a, b
Hall, A. and Qu, X.: Using the current seasonal cycle to constrain snow albedo
feedback in future climate change, Geophys. Res. Lett., 33,
L03502, https://doi.org/10.1029/2005GL025127, 2006. a
Hartmann, D., Klein Tank, A., Rusticucci, M., Alexander, L., Brönnimann,
S., Charabi, Y., Dentener, F., Dlugokencky, E., Easterling, D., Kaplan, A.,
Soden, B., Thorne, P., Wild, M., and Zhai, P.: Observations: Atmosphere and
Surface, in: Climate Change 2013: The Physical Science Basis. Contribution
of Working Group I to the Fifth Assessment Report of the Intergovernmental
Panel on Climate Change, edited by: Stocker, T. F., Qin, D., Plattner, G.-K.,
Tignor, M., Allen, S., Boschung, J., Nauels, A., Xia, Y., Bex, V., and
Midgle, P., chap. 2, Cambridge, UK and New York,
NY, USA, 159–254, https://doi.org/10.1017/CBO9781107415324.008, 2013. a
Hawkins, E. and Sutton, R.: The potential to narrow uncertainty in regional
climate predictions, B. Am. Meteorol. Soc., 90,
1095–1107, https://doi.org/10.1175/2009BAMS2607.1, 2009. a, b
Herger, N., Sanderson, B. M., and Knutti, R.: Improved pattern scaling
approaches for the use in climate impact studies, Geophys. Res.
Lett., 42, 3486–3494, https://doi.org/10.1002/2015GL063569, 2015. a
Holden, P. B. and Edwards, N. R.: Dimensionally reduced emulation of an AOGCM
for application to integrated assessment modelling, Geophys. Res.
Lett., 37, 1–5, https://doi.org/10.1029/2010GL045137, 2010. a, b
Holden, P. B., Edwards, N. R., Garthwaite, P. H., Fraedrich, K., Lunkeit, F., Kirk, E., Labriet, M., Kanudia, A., and Babonneau, F.: PLASIM-ENTSem v1.0: a spatio-temporal emulator of future climate change for impacts assessment, Geosci. Model Dev., 7, 433–451, https://doi.org/10.5194/gmd-7-433-2014, 2014. a
Humphrey, V. and Gudmundsson, L.: GRACE-REC: a reconstruction of climate-driven water storage changes over the last century, Earth Syst. Sci. Data, 11, 1153–1170, https://doi.org/10.5194/essd-11-1153-2019, 2019. a
Kay, J. E., Deser, C., Phillips, A., Mai, A., Hannay, C., Strand, G.,
Arblaster, J. M., Bates, S. C., Danabasoglu, G., Edwards, J., Holland, M.,
Kushner, P., Lamarque, J. F., Lawrence, D., Lindsay, K., Middleton, A.,
Munoz, E., Neale, R., Oleson, K., Polvani, L., and Vertenstein, M.: The
community earth system model (CESM) large ensemble project: A community
resource for studying climate change in the presence of internal climate
variability, B. Am. Meteorol. Soc., 96,
1333–1349, https://doi.org/10.1175/BAMS-D-13-00255.1, 2015. a, b
King, A. D., Karoly, D. J., and Henley, B. J.: Australian climate extremes at
1.5 ∘C and 2 ∘C of global warming, Nat. Clim.
Change, 7, 412–416, https://doi.org/10.1038/nclimate3296, 2017. a
Knutti, R.: The end of model democracy?, Climatic Change, 102, 395–404,
https://doi.org/10.1007/s10584-010-9800-2, 2010. a
Knutti, R., Masson, D., and Gettelman, A.: Climate model genealogy: Generation
CMIP5 and how we got there, Geophys. Res. Lett., 40, 1194–1199,
https://doi.org/10.1002/grl.50256, 2013. a
Leduc, M., Mailhot, A., Frigon, A., Martel, J.-L., Ludwig, R., Brietzke, G. B., Giguére, M., Brissette, F., Turcotte, R., Braun, M., and Scinocca, J.: The ClimEx project: a 50-member ensemble of climate change projections at 12-km resolution over Europe and northeastern North America with the Canadian Regional Climate Model (CRCM5), J. Appl. Meteorol. Clim., 58, 663–693, https://doi.org/10.1175/jamc-d-18-0021.1, 2019. a, b
Levy, H., Horowitz, L. W., Schwarzkopf, M. D., Ming, Y., Golaz, J.-C., Naik,
V., and Ramaswamy, V.: The roles of aerosol direct and indirect effects in
past and future climate change, J. Geophys. Res.-Atmos., 118, 4521–4532, https://doi.org/10.1002/jgrd.50192, 2013. a
Link, R., Snyder, A., Lynch, C., Hartin, C., Kravitz, B., and Bond-Lamberty, B.: Fldgen v1.0: an emulator with internal variability and space–time correlation for Earth system models, Geosci. Model Dev., 12, 1477–1489, https://doi.org/10.5194/gmd-12-1477-2019, 2019. a, b, c, d
Lopez, A., Suckling, E. B., and Smith, L. A.: Robustness of pattern scaled
climate change scenarios for adaptation decision support, Climatic Change,
122, 555–566, https://doi.org/10.1007/s10584-013-1022-y, 2014. a
Lynch, C., Hartin, C., Bond-Lamberty, B., and Kravitz, B.: An open-access CMIP5 pattern library for temperature and precipitation: description and methodology, Earth Syst. Sci. Data, 9, 281–292, https://doi.org/10.5194/essd-9-281-2017, 2017. a, b
Maher, N., Milinski, S., Suarez-Gutierrez, L., Botzet, M., Kornblueh, L.,
Takano, Y., Kröger, J., Ghosh, R., Hedemann, C., Li, C., Li, H.,
Manzini, E., Notz, D., Putrasahan, D., Boysen, L., Claussen, M., Ilyina, T.,
Olonscheck, D., Raddatz, T., Stevens, B., and Marotzke, J.: The Max Planck
Institute Grand Ensemble – Enabling the Exploration of Climate System
Variability, J. Adv. Model. Earth Syst., 11, 1–21,
https://doi.org/10.1029/2019MS001639, 2019. a
May, W.: Assessing the strength of regional changes in near-surface climate
associated with a global warming of 2 ∘C, Climatic Change, 110,
619–644, https://doi.org/10.1007/s10584-011-0076-y, 2012. a
McKinnon, K. A. and Deser, C.: Internal variability and regional climate
trends in an observational large ensemble, J. Climate, 31,
6783–6802, https://doi.org/10.1175/JCLI-D-17-0901.1, 2018. a, b, c, d
McKinnon, K. A., Poppick, A., Dunn-Sigouin, E., and Deser, C.: An
“observational large ensemble” to compare observed and modeled temperature
trend uncertainty due to internal variability, J. Climate, 30,
7585–7598, https://doi.org/10.1175/JCLI-D-16-0905.1, 2017. a, b, c
Meehl, G. A., Covey, C., Delworth, T., Latif, M., McAvaney, B., Mitchell, J.
F. B., Stouffer, R. J., and Taylor, K. E.: The WCRP CMIP3 multi-model
dataset: a new era in climate change research, B. Am.
Meteorol. Soc., 88, 1383–1394, https://doi.org/10.1175/BAMS-88-9-1383, 2007. a, b
Meinshausen, M., Raper, S. C. B., and Wigley, T. M. L.: Emulating coupled atmosphere-ocean and carbon cycle models with a simpler model, MAGICC6 – Part 1: Model description and calibration, Atmos. Chem. Phys., 11, 1417–1456, https://doi.org/10.5194/acp-11-1417-2011, 2011. a, b, c, d
Mitchell, T. D.: Pattern Scaling. An Examination of the Accuracy of the
Technique for Describing Future Climates, Climatic Change, 60, 217–242,
https://doi.org/10.1023/A:1026035305597, 2003. a, b, c, d
Nychka, D., Hammerling, D., Krock, M., and Wiens, A.: Modeling and emulation
of nonstationary Gaussian fields, Spat. Stat., 28, 21–38,
https://doi.org/10.1016/j.spasta.2018.08.006, 2018. a
Olonscheck, D. and Notz, D.: Consistently estimating internal climate
variability from climate model simulations, J. Climate, 30,
9555–9573, https://doi.org/10.1175/JCLI-D-16-0428.1, 2017. a, b
Osborn, T. J., Wallace, C. J., Harris, I. C., and Melvin, T. M.: Pattern
scaling using ClimGen: monthly-resolution future climate scenarios including
changes in the variability of precipitation, Climatic Change, 134, 353–369,
https://doi.org/10.1007/s10584-015-1509-9, 2016. a, b, c, d
Osborn, T. J., Wallace, C. J., Lowea, J. A., and Bernie, D.: Performance of
pattern-scaled climate projections under high-end warming. Part I: Surface
air temperature over land, J. Climate, 31, 5667–5680,
https://doi.org/10.1175/JCLI-D-17-0780.1, 2018. a, b
Riahi, K., Rao, S., Krey, V., Cho, C., Chirkov, V., Fischer, G., Kindermann,
G., Nakicenovic, N., and Rafaj, P.: RCP 8.5-A scenario of comparatively high
greenhouse gas emissions, Climatic Change, 109, 33–57,
https://doi.org/10.1007/s10584-011-0149-y, 2011. a
Rougier, J., Sexton, D. M. H., Murphy, J. M., and Stainforth, D.: Analyzing
the climate sensitivity of the HadSM3 climate model using ensembles from
different but related experiments, J. Climate, 22, 3540–3557,
https://doi.org/10.1175/2008JCLI2533.1, 2009. a
Sanderson, B. M., Knutti, R., and Caldwell, P.: Addressing interdependency in a multimodel ensemble by interpolation of model properties, J.
Climate, 28, 5150–5170, https://doi.org/10.1175/JCLI-D-14-00361.1, 2015. a
Sato, M., Hansen, J. E., McCormick, M. P., and Pollack, J. B.: Stratospheric
aerosol optical depths, 1850–1990, J. Geophys. Res., 98,
22987–22994, https://doi.org/10.1029/93JD02553, 1993. a
Scher, S.: Toward Data-Driven Weather and Climate Forecasting: Approximating a Simple General Circulation Model With Deep Learning, Geophys. Res.
Lett., 45, 12616–12622, https://doi.org/10.1029/2018GL080704, 2018. a
Scher, S. and Messori, G.: Weather and climate forecasting with neural networks: using general circulation models (GCMs) with different complexity as a study ground, Geosci. Model Dev., 12, 2797–2809, https://doi.org/10.5194/gmd-12-2797-2019, 2019. a
Seneviratne, S. I., Nicholls, N., Easterling, D., Goodess, C., Kanae, S.,
Kossin, J., Luo, Y., Marengo, J., McInnes, K., Rahimi, M., Reichstein, M.,
Sorteberg, A., Vera, C., and Zhang, X.: Changes in climate extremes and
their impacts on the natural physical environment, in: Managing the Risk of
Extreme Events and Disasters to Advance Climate Change Adaptation. A Special
Report of Working Groups I and II of the Intergovernmental Panel on Climate
Change (IPCC), edited by: Field, C. B., Barros, V., Stocker, T. F., Qin, D.,
Dokken, D. J., Ebi, K. L., Mastrandrea, M. D., Mach, K. J., Plattner, G.-K.,
Allen, S. K., Tignor, M., and Midgley, P. M., chap. 3,
Cambridge University Press, Cambridge, UK, and New York, NY, USA, 109–230, 2012. a
Serreze, M. C. and Barry, R. G.: Processes and impacts of Arctic
amplification: A research synthesis, Global Planet. Change, 77,
85–96, https://doi.org/10.1016/j.gloplacha.2011.03.004, 2011. a
Sutton, R. T., Dong, B., and Gregory, J. M.: Land/sea warming ratio in
response to climate change: IPCC AR4 model results and comparison with
observations, Geophys. Res. Lett., 34, L02701,
https://doi.org/10.1029/2006GL028164, 2007. a
Tebaldi, C. and Knutti, R.: Evaluating the accuracy of climate change pattern
emulation for low warming targets, Environ. Res. Lett., 13,
55006, https://doi.org/10.1088/1748-9326/aabef2, 2018. a
Trenberth, K. E.: The Definition of El Niño, B. Am.
Meteorol. Soc., 78, 2771–2778,
https://doi.org/10.1175/1520-0477(1997)078<2771:TDOENO>2.0.CO;2, 1997. a
Wartenburger, R., Hirschi, M., Donat, M. G., Greve, P., Pitman, A. J., and Seneviratne, S. I.: Changes in regional climate extremes as a function of global mean temperature: an interactive plotting framework, Geosci. Model Dev., 10, 3609–3634, https://doi.org/10.5194/gmd-10-3609-2017, 2017. a, b, c, d
Weigel, A. P.: Ensemble Forecasts, in: Forecast Verification: A
Practitioner's Guide in Atmospheric Science, edited by: Jolliffe, I. T. and
Stephenson, D. B., chap. 8, John Wiley & Sons, Chichester,
UK, 2nd edn., 141–166, https://doi.org/10.1002/9781119960003.ch8, 2012. a
Williamson, D., Goldstein, M., Allison, L., Blaker, A., Challenor, P., Jackson,
L., and Yamazaki, K.: History matching for exploring and reducing climate
model parameter space using observations and a large perturbed physics
ensemble, Clim. Dynam., 41, 1703–1729, https://doi.org/10.1007/s00382-013-1896-4,
2013. a
Download
The requested paper has a corresponding corrigendum published. Please read the corrigendum first before downloading the article.
- Article
(8215 KB) - Full-text XML
- Corrigendum
-
Supplement
(12579 KB) - BibTeX
- EndNote
Short summary
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.
Earth system models (ESMs) are invaluable to study the climate system but expensive to run....
Altmetrics
Final-revised paper
Preprint