Articles | Volume 11, issue 2
https://doi.org/10.5194/ascmo-11-273-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/ascmo-11-273-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
02 Dec 2025
| 02 Dec 2025
Soil moisture–temperature coupling during extreme warm conditions in 2018 in Sweden: a case study with WRF-CTSM
Center for International Climate Research (CICERO), Oslo, Norway
Department of Geosciences, University of Oslo, Oslo, Norway
Øivind Hodnebrog
Center for International Climate Research (CICERO), Oslo, Norway
Yeliz A. Yilmaz
Department of Geosciences, University of Oslo, Oslo, Norway
Terje K. Berntsen
Department of Geosciences, University of Oslo, Oslo, Norway
Jana Sillmann
Center for International Climate Research (CICERO), Oslo, Norway
Research Unit Sustainability and Climate Risks, Center for Earth System Research and Sustainability (CEN), University of Hamburg, Hamburg, Germany
David M. Lawrence
National Center for Atmospheric Research (NCAR), Boulder, CO, USA
Paul A. Dirmeyer
Atmospheric, Oceanic & Earth Sciences Department, George Mason University, Fairfax, VA, USA
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Victor Brovkin, Benjamin M. Sanderson, Noel G. Brizuela, Tomohiro Hajima, Tatiana Ilyina, Chris D. Jones, Charles Koven, David Lawrence, Peter Lawrence, Hongmei Li, Spencer Liddcoat, Anastasia Romanou, Roland Séférian, Lori T. Sentman, Abigail L. S. Swann, Jerry Tjiputra, Tilo Ziehn, and Alexander J. Winkler
Earth Syst. Dynam., 16, 2021–2034, https://doi.org/10.5194/esd-16-2021-2025, https://doi.org/10.5194/esd-16-2021-2025, 2025
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Idealized experiments with Earth system models provide a basis for understanding the response of the carbon cycle to emissions. We show that most models exhibit a quasi-linear relationship between cumulative carbon uptake on land and in the ocean and hypothesize that this relationship does not depend on emission pathways. We reduce the coupled system to only one differential equation, which represents a powerful simplification of the Earth system dynamics as a function of fossil fuel emissions.
Natalia Castillo Bautista, Marco Gaetani, Leonard F. Borchert, Benjamin Poschlod, Lukas Brunner, Jana Sillmann, and Mario L. V. Martina
EGUsphere, https://doi.org/10.5194/egusphere-2025-5073, https://doi.org/10.5194/egusphere-2025-5073, 2025
This preprint is open for discussion and under review for Weather and Climate Dynamics (WCD).
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When hot temperatures and drought occur together (compound events), they can cause harmful impacts on crops and society. Using six decades of climate data, we show that such compound events repeatedly occurred in three breadbaskets of the Northern Hemisphere. These events are linked to atmospheric circulation patterns that favor heat and dryness, which in turn interact to amplify the impact. Our study contributes to understand the drivers of these events to support climate impact assessment.
Srinath Krishnan, Ragnhild Bieltvedt Skeie, Øivind Hodnebrog, Gunnar Myhre, Maria Sand, Marit Sandstad, Hannah Bryant, Didier A. Hauglustaine, Fabien Paulot, Michael Prather, and David Stevenson
EGUsphere, https://doi.org/10.5194/egusphere-2025-4898, https://doi.org/10.5194/egusphere-2025-4898, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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Hydrogen (H2) is an indirect greenhouse gas that can affect climate through chemical reactions in the atmosphere. To better understand this impact, it is important to constrain the sources and sinks of hydrogen. Using a suite of three-dimensional and one-dimensional models, we find that atmospheric production of hydrogen is 37–60 Tg/yr and that the geological source of H2 is much smaller than suggested. More field and isotopic measurements are needed to improve these estimates.
Junnyeong Han, Eunkyo Seo, and Paul A. Dirmeyer
EGUsphere, https://doi.org/10.5194/egusphere-2025-4163, https://doi.org/10.5194/egusphere-2025-4163, 2025
This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
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Soil moisture sensors often exhibit misleading daytime peaks because they are sensitive to temperature. This study proposes a method to correct the spurious diurnal cycle of SM, using Fourier analysis with land reanalyses. The diurnally adjusted time series better captures realistic soil moisture behavior and provides more reliable insight into land–atmosphere interactions on a diurnal timescale.
Gunnar Myhre, Øivind Hodnebrog, Srinath Krishnan, Maria Sand, Marit Sandstad, Ragnhild B. Skeie, Lieven Clarisse, Bruno Franco, Dylan B. Millet, Kelley C. Wells, Alexander Archibald, Hannah N. Bryant, Alex T. Chaudhri, David S. Stevenson, Didier Hauglustaine, Michael Prather, J. Christopher Kaiser, Dirk J. L. Olivie, Michael Schulz, Oliver Wild, Ye Wang, Thérèse Salameh, Jason E. Williams, Philippe Le Sager, Fabien Paulot, Kostas Tsigaridis, and Haley E. Plaas
EGUsphere, https://doi.org/10.5194/egusphere-2025-3057, https://doi.org/10.5194/egusphere-2025-3057, 2025
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Volatile organic compounds (VOCs) affect air quality and climate, but their behavior in the atmosphere is still uncertain. We launched a global research effort to compare how different models represent these compounds and to improve their accuracy. By analyzing model results alongside observations and satellite data, we aim to better understand the atmospheric composition of these compounds.
Benjamin M. Sanderson, Victor Brovkin, Rosie A. Fisher, David Hohn, Tatiana Ilyina, Chris D. Jones, Torben Koenigk, Charles Koven, Hongmei Li, David M. Lawrence, Peter Lawrence, Spencer Liddicoat, Andrew H. MacDougall, Nadine Mengis, Zebedee Nicholls, Eleanor O'Rourke, Anastasia Romanou, Marit Sandstad, Jörg Schwinger, Roland Séférian, Lori T. Sentman, Isla R. Simpson, Chris Smith, Norman J. Steinert, Abigail L. S. Swann, Jerry Tjiputra, and Tilo Ziehn
Geosci. Model Dev., 18, 5699–5724, https://doi.org/10.5194/gmd-18-5699-2025, https://doi.org/10.5194/gmd-18-5699-2025, 2025
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This study investigates how climate models warm in response to simplified carbon emissions trajectories, refining the understanding of climate reversibility and commitment. Metrics are defined for warming response to cumulative emissions and for the cessation of emissions or ramp-down to net-zero and net-negative levels. Results indicate that previous concentration-driven experiments may have overstated the Zero Emissions Commitment due to emissions rates exceeding historical levels.
Jon Cranko Page, Martin G. De Kauwe, Andy J. Pitman, Isaac R. Towers, Gabriele Arduini, Martin J. Best, Craig Ferguson, Jürgen Knauer, Hyungjun Kim, David M. Lawrence, Tomoko Nitta, Keith W. Oleson, Catherine Ottlé, Anna Ukkola, Nicholas Vuichard, and Gab Abramowitz
EGUsphere, https://doi.org/10.5194/egusphere-2025-4149, https://doi.org/10.5194/egusphere-2025-4149, 2025
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This paper used a large dataset of observations, machine learning predictions, and computer model simulations to test how well land surface models represent the water, energy, and carbon cycles. We found that the models work well under "normal" weather but do not meet performance expectations during coinciding extreme conditions. Since these extremes are relatively rare, targeted model improvements could deliver major performance gains.
Gabriella Everett, Øivind Hodnebrog, Madhoolika Agrawal, Durgesh Singh Yadav, Connie O'Neill, Chubamenla Jamir, Jo Cook, Pritha Pande, Sam Bland, and Lisa Emberson
Biogeosciences, 22, 4203–4219, https://doi.org/10.5194/bg-22-4203-2025, https://doi.org/10.5194/bg-22-4203-2025, 2025
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Ground-level ozone (O3), heat, and water stress (WS) reduce wheat yields, threatening food security in India. O3, heat, and WS interact as stressed plants close stomata, limiting O3 entry and damage. This study models O3 uptake under rainfed (WS) and irrigated conditions for current and future climates. Results show little O3-related yield loss under WS but higher losses with irrigation. Both climate scenarios increase O3-related losses, highlighting risks to India’s wheat productivity.
William J. Collins, Fiona M. O'Connor, Rachael E. Byrom, Øivind Hodnebrog, Patrick Jöckel, Mariano Mertens, Gunnar Myhre, Matthias Nützel, Dirk Olivié, Ragnhild Bieltvedt Skeie, Laura Stecher, Larry W. Horowitz, Vaishali Naik, Gregory Faluvegi, Ulas Im, Lee T. Murray, Drew Shindell, Kostas Tsigaridis, Nathan Luke Abraham, and James Keeble
Atmos. Chem. Phys., 25, 9031–9060, https://doi.org/10.5194/acp-25-9031-2025, https://doi.org/10.5194/acp-25-9031-2025, 2025
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We used 7 climate models that include atmospheric chemistry and find that in a scenario with weak controls on air quality, the warming effects (over 2015 to 2050) of decreases in ozone-depleting substances and increases in air quality pollutants are approximately equal and would make ozone the second highest contributor to warming over this period. We find that for stratospheric ozone recovery, the standard measure of climate effects underestimates a more comprehensive measure.
Maša Ann, Jörn Behrens, and Jana Sillmann
EGUsphere, https://doi.org/10.5194/egusphere-2025-3505, https://doi.org/10.5194/egusphere-2025-3505, 2025
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We present a new framework based on Dynamic Mode Decomposition (DMD) to better detect outliers and model extremes. Unlike standard DMD, which focuses on average system behavior, our approach targets rare, exceptional dynamics. Applied to climate data, it improves extreme event approximation and reveals meaningful spatio-temporal patterns. The method may generalize to other types of extremes.
Timothy Tiggeloven, Colin Raymond, Marleen C. de Ruiter, Jana Sillmann, Annegret H. Thieken, Sophie L. Buijs, Roxana Ciurean, Emma Cordier, Julia M. Crummy, Lydia Cumiskey, Kelley De Polt, Melanie Duncan, Davide M. Ferrario, Wiebke S. Jäger, Elco E. Koks, Nicole van Maanen, Heather J. Murdock, Jaroslav Mysiak, Sadhana Nirandjan, Benjamin Poschlod, Peter Priesmeier, Nivedita Sairam, Pia-Johanna Schweizer, Tristian R. Stolte, Marie-Luise Zenker, James E. Daniell, Alexander Fekete, Christian M. Geiß, Marc J. C. van den Homberg, Sirkku K. Juhola, Christian Kuhlicke, Karen Lebek, Robert Šakić Trogrlić, Stefan Schneiderbauer, Silvia Torresan, Cees J. van Westen, Judith N. Claassen, Bijan Khazai, Virginia Murray, Julius Schlumberger, and Philip J. Ward
EGUsphere, https://doi.org/10.5194/egusphere-2025-2771, https://doi.org/10.5194/egusphere-2025-2771, 2025
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Natural hazards like floods, earthquakes, and landslides are often interconnected which may create bigger problems than when they occur alone. We studied expert discussions from an international conference to understand how scientists and policymakers can better prepare for these multi-hazards and use new technologies to protect its communities while contributing to dialogues about future international agreements beyond the Sendai Framework and supporting global sustainability goals.
Yue Li, Gang Tang, Eleanor O’Rourke, Samar Minallah, Martim Mas e Braga, Sophie Nowicki, Robin S. Smith, David M. Lawrence, George C. Hurtt, Daniele Peano, Gesa Meyer, Birgit Hassler, Jiafu Mao, Yongkang Xue, and Martin Juckes
EGUsphere, https://doi.org/10.5194/egusphere-2025-3207, https://doi.org/10.5194/egusphere-2025-3207, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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Land and Land Ice Theme Opportunities describe a list that contains 25 variable groups with 716 variables, which are potentially available to the broad scientific audience for performing analysis in land-atmosphere coupling, hydrological processes and freshwater systems, glacier and ice sheet mass balance and their influence on the sea levels, land use, and plant phenology.
Nina Schuhen, Carley E. Iles, Marit Sandstad, Viktor Ananiev, and Jana Sillmann
EGUsphere, https://doi.org/10.5194/egusphere-2025-3331, https://doi.org/10.5194/egusphere-2025-3331, 2025
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As climate changes, extremes are becoming increasingly frequent. We investigate the time of emergence for a large range of different extremes, meaning the earliest time when a significant change in these extremes can be detected beyond natural variability, whether in the past or in the future. The results based on 21 global climate models show considerable differences between regions, types of indices and emissions scenarios, as well as between temperature and precipitation extremes.
Inne Vanderkelen, Marie-Estelle Demoury, Sean Swenson, David M. Lawrence, Benjamin D. Stocker, Myke Koopmans, and Édouard L. Davin
EGUsphere, https://doi.org/10.5194/egusphere-2025-2637, https://doi.org/10.5194/egusphere-2025-2637, 2025
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Soil carbon sequestration supports climate mitigation and may enhance water availability. Using a global land model, we show that increased soil organic carbon improves water retention in the root zone and reduces runoff, particularly in dry, sandy regions. Although hydrological changes are modest, they are systematic and suggest co-benefits for vegetation productivity and ecosystem resilience in water-limited areas.
Rachael E. Byrom, Gunnar Myhre, Øivind Hodnebrog, Dirk Olivié, and Michael Schulz
Atmos. Chem. Phys., 25, 5683–5693, https://doi.org/10.5194/acp-25-5683-2025, https://doi.org/10.5194/acp-25-5683-2025, 2025
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Addressing the cause of model spread in CO2 effective radiative forcing (ERF) is important for reducing uncertainty in climate change. We investigate stratospheric O3 as a driver of this spread by altering its concentration by 50 % and analysing the impact on CO2 forcing. Our experiments show a significant effect on stratospheric temperature that impacts instantaneous radiative forcing, primarily due to the influence on longwave emission. However, the impact on ERF is minimal.
Amali A. Amali, Clemens Schwingshackl, Akihiko Ito, Alina Barbu, Christine Delire, Daniele Peano, David M. Lawrence, David Wårlind, Eddy Robertson, Edouard L. Davin, Elena Shevliakova, Ian N. Harman, Nicolas Vuichard, Paul A. Miller, Peter J. Lawrence, Tilo Ziehn, Tomohiro Hajima, Victor Brovkin, Yanwu Zhang, Vivek K. Arora, and Julia Pongratz
Earth Syst. Dynam., 16, 803–840, https://doi.org/10.5194/esd-16-803-2025, https://doi.org/10.5194/esd-16-803-2025, 2025
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Our study explored the impact of anthropogenic land-use change (LUC) on climate dynamics, focusing on biogeophysical (BGP) and biogeochemical (BGC) effects using data from the Land Use Model Intercomparison Project (LUMIP) and the Coupled Model Intercomparison Project Phase 6 (CMIP6). We found that LUC-induced carbon emissions contribute to a BGC warming of 0.21 °C, with BGC effects dominating globally over BGP effects, which show regional variability. Our findings highlight discrepancies in model simulations and emphasize the need for improved representations of LUC processes.
Danny M. Leung, Jasper F. Kok, Longlei Li, David M. Lawrence, Natalie M. Mahowald, Simone Tilmes, and Erik Kluzek
Atmos. Chem. Phys., 25, 2311–2331, https://doi.org/10.5194/acp-25-2311-2025, https://doi.org/10.5194/acp-25-2311-2025, 2025
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This study derives a gridded dust emission dataset for 1841–2000 by employing a combination of observed dust from core records and reanalyzed global dust cycle constraints. We evaluate the ability of global models to replicate the observed historical dust variability by using the emission dataset to force a historical simulation in an Earth system model. We show that prescribing our emissions forces the model to better match observations than other mechanistic models.
Detlef van Vuuren, Brian O'Neill, Claudia Tebaldi, Louise Chini, Pierre Friedlingstein, Tomoko Hasegawa, Keywan Riahi, Benjamin Sanderson, Bala Govindasamy, Nico Bauer, Veronika Eyring, Cheikh Fall, Katja Frieler, Matthew Gidden, Laila Gohar, Andrew Jones, Andrew King, Reto Knutti, Elmar Kriegler, Peter Lawrence, Chris Lennard, Jason Lowe, Camila Mathison, Shahbaz Mehmood, Luciana Prado, Qiang Zhang, Steven Rose, Alexander Ruane, Carl-Friederich Schleussner, Roland Seferian, Jana Sillmann, Chris Smith, Anna Sörensson, Swapna Panickal, Kaoru Tachiiri, Naomi Vaughan, Saritha Vishwanathan, Tokuta Yokohata, and Tilo Ziehn
EGUsphere, https://doi.org/10.5194/egusphere-2024-3765, https://doi.org/10.5194/egusphere-2024-3765, 2025
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We propose a set of six plausible 21st century emission scenarios, and their multi-century extensions, that will be used by the international community of climate modeling centers to produce the next generation of climate projections. These projections will support climate, impact and mitigation researchers, provide information to practitioners to address future risks from climate change, and contribute to policymakers’ considerations of the trade-offs among various levels of mitigation.
Gab Abramowitz, Anna Ukkola, Sanaa Hobeichi, Jon Cranko Page, Mathew Lipson, Martin G. De Kauwe, Samuel Green, Claire Brenner, Jonathan Frame, Grey Nearing, Martyn Clark, Martin Best, Peter Anthoni, Gabriele Arduini, Souhail Boussetta, Silvia Caldararu, Kyeungwoo Cho, Matthias Cuntz, David Fairbairn, Craig R. Ferguson, Hyungjun Kim, Yeonjoo Kim, Jürgen Knauer, David Lawrence, Xiangzhong Luo, Sergey Malyshev, Tomoko Nitta, Jerome Ogee, Keith Oleson, Catherine Ottlé, Phillipe Peylin, Patricia de Rosnay, Heather Rumbold, Bob Su, Nicolas Vuichard, Anthony P. Walker, Xiaoni Wang-Faivre, Yunfei Wang, and Yijian Zeng
Biogeosciences, 21, 5517–5538, https://doi.org/10.5194/bg-21-5517-2024, https://doi.org/10.5194/bg-21-5517-2024, 2024
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This paper evaluates land models – computer-based models that simulate ecosystem dynamics; land carbon, water, and energy cycles; and the role of land in the climate system. It uses machine learning and AI approaches to show that, despite the complexity of land models, they do not perform nearly as well as they could given the amount of information they are provided with about the prediction problem.
Ragnhild Bieltvedt Skeie, Rachael Byrom, Øivind Hodnebrog, Caroline Jouan, and Gunnar Myhre
Atmos. Chem. Phys., 24, 13361–13370, https://doi.org/10.5194/acp-24-13361-2024, https://doi.org/10.5194/acp-24-13361-2024, 2024
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In 2020, new regulations by the International Maritime Organization regarding sulfur emissions came into force, reducing emissions of SO2 from the shipping sector by approximately 80 %. In this study, we use multiple models to calculate how much the Earth energy balance changed due to the emission reduction or the so-called effective radiative forcing. The calculated effective radiative forcing is weak, comparable to the effect of the increase in CO2 over the last 2 to 3 years.
Benjamin M. Sanderson, Ben B. B. Booth, John Dunne, Veronika Eyring, Rosie A. Fisher, Pierre Friedlingstein, Matthew J. Gidden, Tomohiro Hajima, Chris D. Jones, Colin G. Jones, Andrew King, Charles D. Koven, David M. Lawrence, Jason Lowe, Nadine Mengis, Glen P. Peters, Joeri Rogelj, Chris Smith, Abigail C. Snyder, Isla R. Simpson, Abigail L. S. Swann, Claudia Tebaldi, Tatiana Ilyina, Carl-Friedrich Schleussner, Roland Séférian, Bjørn H. Samset, Detlef van Vuuren, and Sönke Zaehle
Geosci. Model Dev., 17, 8141–8172, https://doi.org/10.5194/gmd-17-8141-2024, https://doi.org/10.5194/gmd-17-8141-2024, 2024
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We discuss how, in order to provide more relevant guidance for climate policy, coordinated climate experiments should adopt a greater focus on simulations where Earth system models are provided with carbon emissions from fossil fuels together with land use change instructions, rather than past approaches that have largely focused on experiments with prescribed atmospheric carbon dioxide concentrations. We discuss how these goals might be achieved in coordinated climate modeling experiments.
Ragnhild Bieltvedt Skeie, Magne Aldrin, Terje K. Berntsen, Marit Holden, Ragnar Bang Huseby, Gunnar Myhre, and Trude Storelvmo
Earth Syst. Dynam., 15, 1435–1458, https://doi.org/10.5194/esd-15-1435-2024, https://doi.org/10.5194/esd-15-1435-2024, 2024
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Climate sensitivity and aerosol forcing are central quantities in climate science that are uncertain and contribute to the spread in climate projections. To constrain them, we use observations of temperature and ocean heat content as well as prior knowledge of radiative forcings over the industrialized period. The estimates are sensitive to how aerosol cooling evolved over the latter part of the 20th century, and a strong aerosol forcing trend in the 1960s–1970s is not supported by our analysis.
Sabin I. Taranu, David M. Lawrence, Yoshihide Wada, Ting Tang, Erik Kluzek, Sam Rabin, Yi Yao, Steven J. De Hertog, Inne Vanderkelen, and Wim Thiery
Geosci. Model Dev., 17, 7365–7399, https://doi.org/10.5194/gmd-17-7365-2024, https://doi.org/10.5194/gmd-17-7365-2024, 2024
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In this study, we improved a climate model by adding the representation of water use sectors such as domestic, industry, and agriculture. This new feature helps us understand how water is used and supplied in various areas. We tested our model from 1971 to 2010 and found that it accurately identifies areas with water scarcity. By modelling the competition between sectors when water availability is limited, the model helps estimate the intensity and extent of individual sectors' water shortages.
Cecile B. Menard, Sirpa Rasmus, Ioanna Merkouriadi, Gianpaolo Balsamo, Annett Bartsch, Chris Derksen, Florent Domine, Marie Dumont, Dorothee Ehrich, Richard Essery, Bruce C. Forbes, Gerhard Krinner, David Lawrence, Glen Liston, Heidrun Matthes, Nick Rutter, Melody Sandells, Martin Schneebeli, and Sari Stark
The Cryosphere, 18, 4671–4686, https://doi.org/10.5194/tc-18-4671-2024, https://doi.org/10.5194/tc-18-4671-2024, 2024
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Computer models, like those used in climate change studies, are written by modellers who have to decide how best to construct the models in order to satisfy the purpose they serve. Using snow modelling as an example, we examine the process behind the decisions to understand what motivates or limits modellers in their decision-making. We find that the context in which research is undertaken is often more crucial than scientific limitations. We argue for more transparency in our research practice.
Viktoria Spaiser, Sirkku Juhola, Sara M. Constantino, Weisi Guo, Tabitha Watson, Jana Sillmann, Alessandro Craparo, Ashleigh Basel, John T. Bruun, Krishna Krishnamurthy, Jürgen Scheffran, Patricia Pinho, Uche T. Okpara, Jonathan F. Donges, Avit Bhowmik, Taha Yasseri, Ricardo Safra de Campos, Graeme S. Cumming, Hugues Chenet, Florian Krampe, Jesse F. Abrams, James G. Dyke, Stefanie Rynders, Yevgeny Aksenov, and Bryan M. Spears
Earth Syst. Dynam., 15, 1179–1206, https://doi.org/10.5194/esd-15-1179-2024, https://doi.org/10.5194/esd-15-1179-2024, 2024
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In this paper, we identify potential negative social tipping points linked to Earth system destabilization and draw on related research to understand the drivers and likelihood of these negative social tipping dynamics, their potential effects on human societies and the Earth system, and the potential for cascading interactions and contribution to systemic risks.
Elin Ristorp Aas, Inge Althuizen, Hui Tang, Sonya Geange, Eva Lieungh, Vigdis Vandvik, and Terje Koren Berntsen
Biogeosciences, 21, 3789–3817, https://doi.org/10.5194/bg-21-3789-2024, https://doi.org/10.5194/bg-21-3789-2024, 2024
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We used a soil model to replicate two litterbag decomposition experiments to examine the implications of climate, litter quality, and soil microclimate representation. We found that macroclimate was more important than litter quality for modeled mass loss. By comparing different representations of soil temperature and moisture we found that using observed data did not improve model results. We discuss causes for this and suggest possible improvements to both the model and experimental design.
Eunkyo Seo and Paul A. Dirmeyer
EGUsphere, https://doi.org/10.5194/egusphere-2024-1066, https://doi.org/10.5194/egusphere-2024-1066, 2024
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This study examines the impact of using a multi-layer snow scheme in seasonal forecasts. Compared to single-layer schemes, multi-layer schemes better represent snow's insulating effect, improving forecast accuracy for temperature, soil moisture, and precipitation. These enhancements lead to more realistic simulations of land-atmosphere interactions, mitigating biases and improving model performance over mid- and high-latitude regions of the Northern Hemisphere.
Elin Ristorp Aas, Heleen A. de Wit, and Terje K. Berntsen
Geosci. Model Dev., 17, 2929–2959, https://doi.org/10.5194/gmd-17-2929-2024, https://doi.org/10.5194/gmd-17-2929-2024, 2024
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By including microbial processes in soil models, we learn how the soil system interacts with its environment and responds to climate change. We present a soil process model, MIMICS+, which is able to reproduce carbon stocks found in boreal forest soils better than a conventional land model. With the model we also find that when adding nitrogen, the relationship between soil microbes changes notably. Coupling the model to a vegetation model will allow for further study of these mechanisms.
Gaoyun Wang, Rong Fu, Yizhou Zhuang, Paul A. Dirmeyer, Joseph A. Santanello, Guiling Wang, Kun Yang, and Kaighin McColl
Atmos. Chem. Phys., 24, 3857–3868, https://doi.org/10.5194/acp-24-3857-2024, https://doi.org/10.5194/acp-24-3857-2024, 2024
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This study investigates the influence of lower-tropospheric humidity on land–atmosphere coupling (LAC) during warm seasons in the US Southern Great Plains. Using radiosonde data and a buoyancy model, we find that elevated LT humidity is crucial for generating afternoon precipitation events under dry soil conditions not accounted for by conventional LAC indices. This underscores the importance of considering LT humidity in understanding LAC over dry soil during droughts in the SGP.
Kirsten L. Findell, Zun Yin, Eunkyo Seo, Paul A. Dirmeyer, Nathan P. Arnold, Nathaniel Chaney, Megan D. Fowler, Meng Huang, David M. Lawrence, Po-Lun Ma, and Joseph A. Santanello Jr.
Geosci. Model Dev., 17, 1869–1883, https://doi.org/10.5194/gmd-17-1869-2024, https://doi.org/10.5194/gmd-17-1869-2024, 2024
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We outline a request for sub-daily data to accurately capture the process-level connections between land states, surface fluxes, and the boundary layer response. This high-frequency model output will allow for more direct comparison with observational field campaigns on process-relevant timescales, enable demonstration of inter-model spread in land–atmosphere coupling processes, and aid in targeted identification of sources of deficiencies and opportunities for improvement of the models.
Danny M. Leung, Jasper F. Kok, Longlei Li, Natalie M. Mahowald, David M. Lawrence, Simone Tilmes, Erik Kluzek, Martina Klose, and Carlos Pérez García-Pando
Atmos. Chem. Phys., 24, 2287–2318, https://doi.org/10.5194/acp-24-2287-2024, https://doi.org/10.5194/acp-24-2287-2024, 2024
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This study uses a premier Earth system model to evaluate a new desert dust emission scheme proposed in our companion paper. We show that our scheme accounts for more dust emission physics, hence matching better against observations than other existing dust emission schemes do. Our scheme's dust emissions also couple tightly with meteorology, hence likely improving the modeled dust sensitivity to climate change. We believe this work is vital for improving dust representation in climate models.
Clemens Schwingshackl, Anne Sophie Daloz, Carley Iles, Kristin Aunan, and Jana Sillmann
Nat. Hazards Earth Syst. Sci., 24, 331–354, https://doi.org/10.5194/nhess-24-331-2024, https://doi.org/10.5194/nhess-24-331-2024, 2024
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Ambient heat in European cities will substantially increase under global warming, as projected by three heat metrics calculated from high-resolution climate model simulations. While the heat metrics consistently project high levels of ambient heat for several cities, in other cities the projected heat levels vary considerably across the three heat metrics. Using complementary heat metrics for projections of ambient heat is thus important for assessments of future risks from heat stress.
Danny M. Leung, Jasper F. Kok, Longlei Li, Gregory S. Okin, Catherine Prigent, Martina Klose, Carlos Pérez García-Pando, Laurent Menut, Natalie M. Mahowald, David M. Lawrence, and Marcelo Chamecki
Atmos. Chem. Phys., 23, 6487–6523, https://doi.org/10.5194/acp-23-6487-2023, https://doi.org/10.5194/acp-23-6487-2023, 2023
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Desert dust modeling is important for understanding climate change, as dust regulates the atmosphere's greenhouse effect and radiation. This study formulates and proposes a more physical and realistic desert dust emission scheme for global and regional climate models. By considering more aeolian processes in our emission scheme, our simulations match better against dust observations than existing schemes. We believe this work is vital in improving dust representation in climate models.
Norbert Pirk, Kristoffer Aalstad, Yeliz A. Yilmaz, Astrid Vatne, Andrea L. Popp, Peter Horvath, Anders Bryn, Ane Victoria Vollsnes, Sebastian Westermann, Terje Koren Berntsen, Frode Stordal, and Lena Merete Tallaksen
Biogeosciences, 20, 2031–2047, https://doi.org/10.5194/bg-20-2031-2023, https://doi.org/10.5194/bg-20-2031-2023, 2023
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We measured the land–atmosphere exchange of CO2 and water vapor in alpine Norway over 3 years. The extremely snow-rich conditions in 2020 reduced the total annual evapotranspiration to 50 % and reduced the growing-season carbon assimilation to turn the ecosystem from a moderate annual carbon sink to an even stronger source. Our analysis suggests that snow cover anomalies are driving the most consequential short-term responses in this ecosystem’s functioning.
Wenfu Tang, Simone Tilmes, David M. Lawrence, Fang Li, Cenlin He, Louisa K. Emmons, Rebecca R. Buchholz, and Lili Xia
Atmos. Chem. Phys., 23, 5467–5486, https://doi.org/10.5194/acp-23-5467-2023, https://doi.org/10.5194/acp-23-5467-2023, 2023
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Globally, total wildfire burned area is projected to increase over the 21st century under scenarios without geoengineering and decrease under the two geoengineering scenarios. Geoengineering reduces fire by decreasing surface temperature and wind speed and increasing relative humidity and soil water. However, geoengineering also yields reductions in precipitation, which offset some of the fire reduction.
Zun Yin, Kirsten L. Findell, Paul Dirmeyer, Elena Shevliakova, Sergey Malyshev, Khaled Ghannam, Nina Raoult, and Zhihong Tan
Hydrol. Earth Syst. Sci., 27, 861–872, https://doi.org/10.5194/hess-27-861-2023, https://doi.org/10.5194/hess-27-861-2023, 2023
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Land–atmosphere (L–A) interactions typically focus on daytime processes connecting the land state with the overlying atmospheric boundary layer. However, much prior L–A work used monthly or daily means due to the lack of daytime-only data products. Here we show that monthly smoothing can significantly obscure the L–A coupling signal, and including nighttime information can mute or mask the daytime processes of interest. We propose diagnosing L–A coupling within models or archiving subdaily data.
Eunkyo Seo and Paul A. Dirmeyer
Hydrol. Earth Syst. Sci., 26, 5411–5429, https://doi.org/10.5194/hess-26-5411-2022, https://doi.org/10.5194/hess-26-5411-2022, 2022
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This study presents the climatology of the observed land–atmosphere interactions on a subdaily timescale during the warm season from flux site observations. Multivariate metrics are employed to examine the land, atmosphere, and combined couplings, and a mixing diagram is adopted to understand the coevolution of the moist and thermal energy budget within the atmospheric mixed layer. The diurnal cycles of both mixing diagrams and hourly land–atmosphere couplings exhibit hysteresis.
Inne Vanderkelen, Shervan Gharari, Naoki Mizukami, Martyn P. Clark, David M. Lawrence, Sean Swenson, Yadu Pokhrel, Naota Hanasaki, Ann van Griensven, and Wim Thiery
Geosci. Model Dev., 15, 4163–4192, https://doi.org/10.5194/gmd-15-4163-2022, https://doi.org/10.5194/gmd-15-4163-2022, 2022
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Human-controlled reservoirs have a large influence on the global water cycle. However, dam operations are rarely represented in Earth system models. We implement and evaluate a widely used reservoir parametrization in a global river-routing model. Using observations of individual reservoirs, the reservoir scheme outperforms the natural lake scheme. However, both schemes show a similar performance due to biases in runoff timing and magnitude when using simulated runoff.
Charles D. Koven, Vivek K. Arora, Patricia Cadule, Rosie A. Fisher, Chris D. Jones, David M. Lawrence, Jared Lewis, Keith Lindsay, Sabine Mathesius, Malte Meinshausen, Michael Mills, Zebedee Nicholls, Benjamin M. Sanderson, Roland Séférian, Neil C. Swart, William R. Wieder, and Kirsten Zickfeld
Earth Syst. Dynam., 13, 885–909, https://doi.org/10.5194/esd-13-885-2022, https://doi.org/10.5194/esd-13-885-2022, 2022
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We explore the long-term dynamics of Earth's climate and carbon cycles under a pair of contrasting scenarios to the year 2300 using six models that include both climate and carbon cycle dynamics. One scenario assumes very high emissions, while the second assumes a peak in emissions, followed by rapid declines to net negative emissions. We show that the models generally agree that warming is roughly proportional to carbon emissions but that many other aspects of the model projections differ.
Philip J. Ward, James Daniell, Melanie Duncan, Anna Dunne, Cédric Hananel, Stefan Hochrainer-Stigler, Annegien Tijssen, Silvia Torresan, Roxana Ciurean, Joel C. Gill, Jana Sillmann, Anaïs Couasnon, Elco Koks, Noemi Padrón-Fumero, Sharon Tatman, Marianne Tronstad Lund, Adewole Adesiyun, Jeroen C. J. H. Aerts, Alexander Alabaster, Bernard Bulder, Carlos Campillo Torres, Andrea Critto, Raúl Hernández-Martín, Marta Machado, Jaroslav Mysiak, Rene Orth, Irene Palomino Antolín, Eva-Cristina Petrescu, Markus Reichstein, Timothy Tiggeloven, Anne F. Van Loon, Hung Vuong Pham, and Marleen C. de Ruiter
Nat. Hazards Earth Syst. Sci., 22, 1487–1497, https://doi.org/10.5194/nhess-22-1487-2022, https://doi.org/10.5194/nhess-22-1487-2022, 2022
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The majority of natural-hazard risk research focuses on single hazards (a flood, a drought, a volcanic eruption, an earthquake, etc.). In the international research and policy community it is recognised that risk management could benefit from a more systemic approach. In this perspective paper, we argue for an approach that addresses multi-hazard, multi-risk management through the lens of sustainability challenges that cut across sectors, regions, and hazards.
Ronny Meier, Edouard L. Davin, Gordon B. Bonan, David M. Lawrence, Xiaolong Hu, Gregory Duveiller, Catherine Prigent, and Sonia I. Seneviratne
Geosci. Model Dev., 15, 2365–2393, https://doi.org/10.5194/gmd-15-2365-2022, https://doi.org/10.5194/gmd-15-2365-2022, 2022
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We revise the roughness of the land surface in the CESM climate model. Guided by observational data, we increase the surface roughness of forests and decrease that of bare soil, snow, ice, and crops. These modifications alter simulated temperatures and wind speeds at and above the land surface considerably, in particular over desert regions. The revised model represents the diurnal variability of the land surface temperature better compared to satellite observations over most regions.
Sara Marie Blichner, Moa Kristina Sporre, and Terje Koren Berntsen
Atmos. Chem. Phys., 21, 17243–17265, https://doi.org/10.5194/acp-21-17243-2021, https://doi.org/10.5194/acp-21-17243-2021, 2021
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In this study we quantify how a new way of modeling the formation of new particles in the atmosphere affects the estimated cooling from aerosol–cloud interactions since pre-industrial times. Our improved scheme merges two common approaches to aerosol modeling: a sectional scheme for treating early growth and the pre-existing modal scheme in NorESM. We find that the cooling from aerosol–cloud interactions since pre-industrial times is reduced by 10 % when the new scheme is used.
Stefanie Falk, Ane V. Vollsnes, Aud B. Eriksen, Lisa Emberson, Connie O'Neill, Frode Stordal, and Terje Koren Berntsen
Biogeosciences Discuss., https://doi.org/10.5194/bg-2021-260, https://doi.org/10.5194/bg-2021-260, 2021
Revised manuscript not accepted
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Subarctic vegetation is threatened by climate change and ozone. We assess essential climate variables in 2018/19. 2018 was warmer and brighter than usual in Spring with forest fires and elevated ozone in summer. Visible damage was observed on plant species in 2018. We find that generic parameterizations used in modeling ozone dose do not suffice. We propose a method to acclimate these parameterizations and find an ozone-induced biomass loss of 2.5 to 17.4 % (up to 6 % larger than default).
Stefanie Falk, Ane V. Vollsnes, Aud B. Eriksen, Frode Stordal, and Terje Koren Berntsen
Atmos. Chem. Phys., 21, 15647–15661, https://doi.org/10.5194/acp-21-15647-2021, https://doi.org/10.5194/acp-21-15647-2021, 2021
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We evaluate regional and global models for ozone modeling and damage risk mapping of vegetation over subarctic Europe. Our analysis suggests that low-resolution global models do not reproduce the observed ozone seasonal cycle at ground level, underestimating ozone by 30–50 %. High-resolution regional models capture the seasonal cycle well, still underestimating ozone by up to 20 %. Our proposed gap-filling method for site observations shows a 76 % accuracy compared to the regional model (80 %).
Sara M. Blichner, Moa K. Sporre, Risto Makkonen, and Terje K. Berntsen
Geosci. Model Dev., 14, 3335–3359, https://doi.org/10.5194/gmd-14-3335-2021, https://doi.org/10.5194/gmd-14-3335-2021, 2021
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Aerosol–cloud interactions are the largest contributor to climate forcing uncertainty. In this study we combine two common approaches to aerosol representation in global models: a sectional scheme, which is closer to first principals, for the smallest particles forming in the atmosphere and a log-modal scheme, which is faster, for the larger particles. With this approach, we improve the aerosol representation compared to observations, while only increasing the computational cost by 15 %.
Katja Weigel, Lisa Bock, Bettina K. Gier, Axel Lauer, Mattia Righi, Manuel Schlund, Kemisola Adeniyi, Bouwe Andela, Enrico Arnone, Peter Berg, Louis-Philippe Caron, Irene Cionni, Susanna Corti, Niels Drost, Alasdair Hunter, Llorenç Lledó, Christian Wilhelm Mohr, Aytaç Paçal, Núria Pérez-Zanón, Valeriu Predoi, Marit Sandstad, Jana Sillmann, Andreas Sterl, Javier Vegas-Regidor, Jost von Hardenberg, and Veronika Eyring
Geosci. Model Dev., 14, 3159–3184, https://doi.org/10.5194/gmd-14-3159-2021, https://doi.org/10.5194/gmd-14-3159-2021, 2021
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This work presents new diagnostics for the Earth System Model Evaluation Tool (ESMValTool) v2.0 on the hydrological cycle, extreme events, impact assessment, regional evaluations, and ensemble member selection. The ESMValTool v2.0 diagnostics are developed by a large community of scientists aiming to facilitate the evaluation and comparison of Earth system models (ESMs) with a focus on the ESMs participating in the Coupled Model Intercomparison Project (CMIP).
Benjamin Poschlod, Ralf Ludwig, and Jana Sillmann
Earth Syst. Sci. Data, 13, 983–1003, https://doi.org/10.5194/essd-13-983-2021, https://doi.org/10.5194/essd-13-983-2021, 2021
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This study provides a homogeneous data set of 10-year rainfall return levels based on 50 simulations of the Canadian Regional Climate Model v5 (CRCM5). In order to evaluate its quality, the return levels are compared to those of observation-based rainfall of 16 European countries from 32 different sources. The CRCM5 is able to capture the general spatial pattern of observed extreme precipitation, and also the intensity is reproduced in 77 % of the area for rainfall durations of 3 h and longer.
Peter Horvath, Hui Tang, Rune Halvorsen, Frode Stordal, Lena Merete Tallaksen, Terje Koren Berntsen, and Anders Bryn
Biogeosciences, 18, 95–112, https://doi.org/10.5194/bg-18-95-2021, https://doi.org/10.5194/bg-18-95-2021, 2021
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We evaluated the performance of three methods for representing vegetation cover. Remote sensing provided the best match to a reference dataset, closely followed by distribution modelling (DM), whereas the dynamic global vegetation model (DGVM) in CLM4.5BGCDV deviated strongly from the reference. Sensitivity tests show that use of threshold values for predictors identified by DM may improve DGVM performance. The results highlight the potential of using DM in the development of DGVMs.
Katherine Dagon, Benjamin M. Sanderson, Rosie A. Fisher, and David M. Lawrence
Adv. Stat. Clim. Meteorol. Oceanogr., 6, 223–244, https://doi.org/10.5194/ascmo-6-223-2020, https://doi.org/10.5194/ascmo-6-223-2020, 2020
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Uncertainties in land model projections are important to understand in order to build confidence in Earth system modeling. In this paper, we introduce a framework for estimating uncertain land model parameters with machine learning. This method increases the computational efficiency of this process relative to traditional hand tuning approaches and provides objective methods to assess the results. We further identify key processes and parameters that are important for accurate land modeling.
Cited articles
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Barriopedro, D., García-Herrera, R., Ordóñez, C., Miralles, D. G., and Salcedo-Sanz, S.: Heat Waves: Physical Understanding and Scientific Challenges, Reviews of Geophysics, 61, e2022RG000780, https://doi.org/10.1029/2022RG000780, 2023.
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Short summary
This study investigates soil moisture–temperature coupling during the extreme warm conditions in May–August 2018 in southern and central Sweden using the merged GLEAM-E-OBS dataset and four simulations from the Weather Research and Forecasting model coupled with the Community Terrestrial Systems Model (WRF-CTSM). Based on changes in surface soil moisture, evaporative fraction, and daily maximum 2 m temperature, on average across the region and five datasets, the coupling lasted for 22 d.
This study investigates soil moisture–temperature coupling during the extreme warm conditions in...
