Articles | Volume 29, issue 2
https://doi.org/10.5194/hess-29-397-2025
© 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/hess-29-397-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Potential of long-term satellite observations and reanalysis products for characterising soil drying: trends and drought events
Martin Hirschi
CORRESPONDING AUTHOR
Institute for Atmospheric and Climate Science, ETH Zurich, Universitätstrasse 16, 8092 Zurich, Switzerland
Pietro Stradiotti
Department of Geodesy and Geoinformation, TU Wien, Wiedner Hauptstrasse 8–10, 1040 Vienna, Austria
Bas Crezee
Institute for Atmospheric and Climate Science, ETH Zurich, Universitätstrasse 16, 8092 Zurich, Switzerland
now at: Federal Office of Meteorology and Climatology MeteoSwiss, Operation Center 1, 8058 Zurich-Airport, Switzerland
Wouter Dorigo
Department of Geodesy and Geoinformation, TU Wien, Wiedner Hauptstrasse 8–10, 1040 Vienna, Austria
Sonia I. Seneviratne
Institute for Atmospheric and Climate Science, ETH Zurich, Universitätstrasse 16, 8092 Zurich, Switzerland
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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
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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
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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
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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
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Samuel Scherrer, Gabriëlle De Lannoy, Zdenko Heyvaert, Michel Bechtold, Clement Albergel, Tarek S. El-Madany, and Wouter Dorigo
Hydrol. Earth Syst. Sci., 27, 4087–4114, https://doi.org/10.5194/hess-27-4087-2023, https://doi.org/10.5194/hess-27-4087-2023, 2023
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We explored different options for data assimilation (DA) of the remotely sensed leaf area index (LAI). We found strong biases between LAI predicted by Noah-MP and observations. LAI DA that does not take these biases into account can induce unphysical patterns in the resulting LAI and flux estimates and leads to large changes in the climatology of root zone soil moisture. We tested two bias-correction approaches and explored alternative solutions to treating bias in LAI DA.
Adam Pasik, Alexander Gruber, Wolfgang Preimesberger, Domenico De Santis, and Wouter Dorigo
Geosci. Model Dev., 16, 4957–4976, https://doi.org/10.5194/gmd-16-4957-2023, https://doi.org/10.5194/gmd-16-4957-2023, 2023
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We apply the exponential filter (EF) method to satellite soil moisture retrievals to estimate the water content in the unobserved root zone globally from 2002–2020. Quality assessment against an independent dataset shows satisfactory results. Error characterization is carried out using the standard uncertainty propagation law and empirically estimated values of EF model structural uncertainty and parameter uncertainty. This is followed by analysis of temporal uncertainty variations.
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
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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
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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
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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
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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
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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
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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
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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
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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.
Remi Madelon, Nemesio J. Rodríguez-Fernández, Hassan Bazzi, Nicolas Baghdadi, Clement Albergel, Wouter Dorigo, and Mehrez Zribi
Hydrol. Earth Syst. Sci., 27, 1221–1242, https://doi.org/10.5194/hess-27-1221-2023, https://doi.org/10.5194/hess-27-1221-2023, 2023
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We present an approach to estimate soil moisture (SM) at 1 km resolution using Sentinel-1 and Sentinel-3 satellites. The estimates were compared to other high-resolution (HR) datasets over Europe, northern Africa, Australia, and North America, showing good agreement. However, the discrepancies between the different HR datasets and their lower performances compared with in situ measurements and coarse-resolution datasets show the remaining challenges for large-scale HR SM mapping.
Luisa Schmidt, Matthias Forkel, Ruxandra-Maria Zotta, Samuel Scherrer, Wouter A. Dorigo, Alexander Kuhn-Régnier, Robin van der Schalie, and Marta Yebra
Biogeosciences, 20, 1027–1046, https://doi.org/10.5194/bg-20-1027-2023, https://doi.org/10.5194/bg-20-1027-2023, 2023
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Vegetation attenuates natural microwave emissions from the land surface. The strength of this attenuation is quantified as the vegetation optical depth (VOD) parameter and is influenced by the vegetation mass, structure, water content, and observation wavelength. Here we model the VOD signal as a multi-variate function of several descriptive vegetation variables. The results help in understanding the effects of ecosystem properties on VOD.
Taylor Smith, Ruxandra-Maria Zotta, Chris A. Boulton, Timothy M. Lenton, Wouter Dorigo, and Niklas Boers
Earth Syst. Dynam., 14, 173–183, https://doi.org/10.5194/esd-14-173-2023, https://doi.org/10.5194/esd-14-173-2023, 2023
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Multi-instrument records with varying signal-to-noise ratios are becoming increasingly common as legacy sensors are upgraded, and data sets are modernized. Induced changes in higher-order statistics such as the autocorrelation and variance are not always well captured by cross-calibration schemes. Here we investigate using synthetic examples how strong resulting biases can be and how they can be avoided in order to make reliable statements about changes in the resilience of a system.
Matthias Forkel, Luisa Schmidt, Ruxandra-Maria Zotta, Wouter Dorigo, and Marta Yebra
Hydrol. Earth Syst. Sci., 27, 39–68, https://doi.org/10.5194/hess-27-39-2023, https://doi.org/10.5194/hess-27-39-2023, 2023
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The live fuel moisture content (LFMC) of vegetation canopies is a driver of wildfires. We investigate the relation between LFMC and passive microwave satellite observations of vegetation optical depth (VOD) and develop a method to estimate LFMC from VOD globally. Our global VOD-based estimates of LFMC can be used to investigate drought effects on vegetation and fire risks.
Sjoukje Y. Philip, Sarah F. Kew, Geert Jan van Oldenborgh, Faron S. Anslow, Sonia I. Seneviratne, Robert Vautard, Dim Coumou, Kristie L. Ebi, Julie Arrighi, Roop Singh, Maarten van Aalst, Carolina Pereira Marghidan, Michael Wehner, Wenchang Yang, Sihan Li, Dominik L. Schumacher, Mathias Hauser, Rémy Bonnet, Linh N. Luu, Flavio Lehner, Nathan Gillett, Jordis S. Tradowsky, Gabriel A. Vecchi, Chris Rodell, Roland B. Stull, Rosie Howard, and Friederike E. L. Otto
Earth Syst. Dynam., 13, 1689–1713, https://doi.org/10.5194/esd-13-1689-2022, https://doi.org/10.5194/esd-13-1689-2022, 2022
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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
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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.
Leander Moesinger, Ruxandra-Maria Zotta, Robin van der Schalie, Tracy Scanlon, Richard de Jeu, and Wouter Dorigo
Biogeosciences, 19, 5107–5123, https://doi.org/10.5194/bg-19-5107-2022, https://doi.org/10.5194/bg-19-5107-2022, 2022
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The standardized vegetation optical depth index (SVODI) can be used to monitor the vegetation condition, such as whether the vegetation is unusually dry or wet. SVODI has global coverage, spans the past 3 decades and is derived from multiple spaceborne passive microwave sensors of that period. SVODI is based on a new probabilistic merging method that allows the merging of normally distributed data even if the data are not gap-free.
Steven J. De Hertog, Felix Havermann, Inne Vanderkelen, Suqi Guo, Fei Luo, Iris Manola, Dim Coumou, Edouard L. Davin, Gregory Duveiller, Quentin Lejeune, Julia Pongratz, Carl-Friedrich Schleussner, Sonia I. Seneviratne, and Wim Thiery
Earth Syst. Dynam., 13, 1305–1350, https://doi.org/10.5194/esd-13-1305-2022, https://doi.org/10.5194/esd-13-1305-2022, 2022
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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
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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
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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.
Robin van der Schalie, Mendy van der Vliet, Clément Albergel, Wouter Dorigo, Piotr Wolski, and Richard de Jeu
Hydrol. Earth Syst. Sci., 26, 3611–3627, https://doi.org/10.5194/hess-26-3611-2022, https://doi.org/10.5194/hess-26-3611-2022, 2022
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Climate data records of surface soil moisture, vegetation optical depth, and land surface temperature can be derived from passive microwave observations. The ability of these datasets to properly detect anomalies and extremes is very valuable in climate research and can especially help to improve our insight in complex regions where the current climate reanalysis datasets reach their limitations. Here, we present a case study over the Okavango Delta, where we focus on inter-annual variability.
Verena Bessenbacher, Sonia Isabelle Seneviratne, and Lukas Gudmundsson
Geosci. Model Dev., 15, 4569–4596, https://doi.org/10.5194/gmd-15-4569-2022, https://doi.org/10.5194/gmd-15-4569-2022, 2022
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Earth observations have many missing values. They are often filled using information from spatial and temporal contexts that mostly ignore information from related observed variables. We propose the gap-filling method CLIMFILL that additionally uses information from related variables. We test CLIMFILL using gap-free reanalysis data of variables related to soil–moisture climate interactions. CLIMFILL creates estimates for the missing values that recover the original dependence structure.
Shruti Nath, Quentin Lejeune, Lea Beusch, Sonia I. Seneviratne, and Carl-Friedrich Schleussner
Earth Syst. Dynam., 13, 851–877, https://doi.org/10.5194/esd-13-851-2022, https://doi.org/10.5194/esd-13-851-2022, 2022
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Uncertainty within climate model projections on inter-annual timescales is largely affected by natural climate variability. Emulators are valuable tools for approximating climate model runs, allowing for easy exploration of such uncertainty spaces. This study takes a first step at building a spatially resolved, monthly temperature emulator that takes local yearly temperatures as the sole input, thus providing monthly temperature distributions which are of critical value to impact assessments.
Ronny Meier, Edouard L. Davin, Gordon B. Bonan, David M. Lawrence, Xiaolong Hu, Gregory Duveiller, Catherine Prigent, and Sonia I. Seneviratne
Geosci. Model Dev., 15, 2365–2393, https://doi.org/10.5194/gmd-15-2365-2022, https://doi.org/10.5194/gmd-15-2365-2022, 2022
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We revise the roughness of the land surface in the CESM climate model. Guided by observational data, we increase the surface roughness of forests and decrease that of bare soil, snow, ice, and crops. These modifications alter simulated temperatures and wind speeds at and above the land surface considerably, in particular over desert regions. The revised model represents the diurnal variability of the land surface temperature better compared to satellite observations over most regions.
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
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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
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Monitoring of increasingly frequent droughts is a prerequisite for climate adaptation strategies. This data paper presents long-term soil moisture measurements recorded by 66 cosmic-ray neutron sensors (CRNS) operated by 24 institutions and distributed across major climate zones in Europe. Data processing followed harmonized protocols and state-of-the-art methods to generate consistent and comparable soil moisture products and to facilitate continental-scale analysis of hydrological extremes.
Benjamin Wild, Irene Teubner, Leander Moesinger, Ruxandra-Maria Zotta, Matthias Forkel, Robin van der Schalie, Stephen Sitch, and Wouter Dorigo
Earth Syst. Sci. Data, 14, 1063–1085, https://doi.org/10.5194/essd-14-1063-2022, https://doi.org/10.5194/essd-14-1063-2022, 2022
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Gross primary production (GPP) describes the conversion of CO2 to carbohydrates and can be seen as a filter for our atmosphere of the primary greenhouse gas CO2. We developed VODCA2GPP, a GPP dataset that is based on vegetation optical depth from microwave remote sensing and temperature. Thus, it is mostly independent from existing GPP datasets and also available in regions with frequent cloud coverage. Analysis showed that VODCA2GPP is able to complement existing state-of-the-art GPP datasets.
Aine M. Gormley-Gallagher, Sebastian Sterl, Annette L. Hirsch, Sonia I. Seneviratne, Edouard L. Davin, and Wim Thiery
Earth Syst. Dynam., 13, 419–438, https://doi.org/10.5194/esd-13-419-2022, https://doi.org/10.5194/esd-13-419-2022, 2022
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Our results show that agricultural management can impact the local climate and highlight the need to evaluate land management in climate models. We use regression analysis on climate simulations and observations to assess irrigation and conservation agriculture impacts on warming trends. This allowed us to distinguish between the effects of land management and large-scale climate forcings such as rising CO2 concentrations and thus gain insight into the impacts under different climate regimes.
Stefan Schlaffer, Marco Chini, Wouter Dorigo, and Simon Plank
Hydrol. Earth Syst. Sci., 26, 841–860, https://doi.org/10.5194/hess-26-841-2022, https://doi.org/10.5194/hess-26-841-2022, 2022
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Prairie wetlands are important for biodiversity and water availability. Knowledge about their variability and spatial distribution is of great use in conservation and water resources management. In this study, we propose a novel approach for the classification of small water bodies from satellite radar images and apply it to our study area over 6 years. The retrieved dynamics show the different responses of small and large wetlands to dry and wet periods.
Wouter Dorigo, Irene Himmelbauer, Daniel Aberer, Lukas Schremmer, Ivana Petrakovic, Luca Zappa, Wolfgang Preimesberger, Angelika Xaver, Frank Annor, Jonas Ardö, Dennis Baldocchi, Marco Bitelli, Günter Blöschl, Heye Bogena, Luca Brocca, Jean-Christophe Calvet, J. Julio Camarero, Giorgio Capello, Minha Choi, Michael C. Cosh, Nick van de Giesen, Istvan Hajdu, Jaakko Ikonen, Karsten H. Jensen, Kasturi Devi Kanniah, Ileen de Kat, Gottfried Kirchengast, Pankaj Kumar Rai, Jenni Kyrouac, Kristine Larson, Suxia Liu, Alexander Loew, Mahta Moghaddam, José Martínez Fernández, Cristian Mattar Bader, Renato Morbidelli, Jan P. Musial, Elise Osenga, Michael A. Palecki, Thierry Pellarin, George P. Petropoulos, Isabella Pfeil, Jarrett Powers, Alan Robock, Christoph Rüdiger, Udo Rummel, Michael Strobel, Zhongbo Su, Ryan Sullivan, Torbern Tagesson, Andrej Varlagin, Mariette Vreugdenhil, Jeffrey Walker, Jun Wen, Fred Wenger, Jean Pierre Wigneron, Mel Woods, Kun Yang, Yijian Zeng, Xiang Zhang, Marek Zreda, Stephan Dietrich, Alexander Gruber, Peter van Oevelen, Wolfgang Wagner, Klaus Scipal, Matthias Drusch, and Roberto Sabia
Hydrol. Earth Syst. Sci., 25, 5749–5804, https://doi.org/10.5194/hess-25-5749-2021, https://doi.org/10.5194/hess-25-5749-2021, 2021
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The International Soil Moisture Network (ISMN) is a community-based open-access data portal for soil water measurements taken at the ground and is accessible at https://ismn.earth. Over 1000 scientific publications and thousands of users have made use of the ISMN. The scope of this paper is to inform readers about the data and functionality of the ISMN and to provide a review of the scientific progress facilitated through the ISMN with the scope to shape future research and operations.
Irene E. Teubner, Matthias Forkel, Benjamin Wild, Leander Mösinger, and Wouter Dorigo
Biogeosciences, 18, 3285–3308, https://doi.org/10.5194/bg-18-3285-2021, https://doi.org/10.5194/bg-18-3285-2021, 2021
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Vegetation optical depth (VOD), which contains information on vegetation water content and biomass, has been previously shown to be related to gross primary production (GPP). In this study, we analyzed the impact of adding temperature as model input and investigated if this can reduce the previously observed overestimation of VOD-derived GPP. In addition, we could show that the relationship between VOD and GPP largely holds true along a gradient of dry or wet conditions.
Hylke E. Beck, Ming Pan, Diego G. Miralles, Rolf H. Reichle, Wouter A. Dorigo, Sebastian Hahn, Justin Sheffield, Lanka Karthikeyan, Gianpaolo Balsamo, Robert M. Parinussa, Albert I. J. M. van Dijk, Jinyang Du, John S. Kimball, Noemi Vergopolan, and Eric F. Wood
Hydrol. Earth Syst. Sci., 25, 17–40, https://doi.org/10.5194/hess-25-17-2021, https://doi.org/10.5194/hess-25-17-2021, 2021
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We evaluated the largest and most diverse set of surface soil moisture products ever evaluated in a single study. We found pronounced differences in performance among individual products and product groups. Our results provide guidance to choose the most suitable product for a particular application.
Quentin Lejeune, Edouard L. Davin, Grégory Duveiller, Bas Crezee, Ronny Meier, Alessandro Cescatti, and Sonia I. Seneviratne
Earth Syst. Dynam., 11, 1209–1232, https://doi.org/10.5194/esd-11-1209-2020, https://doi.org/10.5194/esd-11-1209-2020, 2020
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Trees are darker than crops or grasses; hence, they absorb more solar radiation. Therefore, land cover changes modify the fraction of solar radiation reflected by the land surface (its albedo), with consequences for the climate. We apply a new statistical method to simulations conducted with 15 recent climate models and find that albedo variations due to land cover changes since 1860 have led to a decrease in the net amount of energy entering the atmosphere by −0.09 W m2 on average.
Maialen Iturbide, José M. Gutiérrez, Lincoln M. Alves, Joaquín Bedia, Ruth Cerezo-Mota, Ezequiel Cimadevilla, Antonio S. Cofiño, Alejandro Di Luca, Sergio Henrique Faria, Irina V. Gorodetskaya, Mathias Hauser, Sixto Herrera, Kevin Hennessy, Helene T. Hewitt, Richard G. Jones, Svitlana Krakovska, Rodrigo Manzanas, Daniel Martínez-Castro, Gemma T. Narisma, Intan S. Nurhati, Izidine Pinto, Sonia I. Seneviratne, Bart van den Hurk, and Carolina S. Vera
Earth Syst. Sci. Data, 12, 2959–2970, https://doi.org/10.5194/essd-12-2959-2020, https://doi.org/10.5194/essd-12-2959-2020, 2020
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We present an update of the IPCC WGI reference regions used in AR5 for the synthesis of climate change information. This revision was guided by the basic principles of climatic consistency and model representativeness (in particular for the new CMIP6 simulations). We also present a new dataset of monthly CMIP5 and CMIP6 spatially aggregated information using the new reference regions and describe a worked example of how to use this dataset to inform regional climate change studies.
Kathrin Wehrli, Mathias Hauser, and Sonia I. Seneviratne
Earth Syst. Dynam., 11, 855–873, https://doi.org/10.5194/esd-11-855-2020, https://doi.org/10.5194/esd-11-855-2020, 2020
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The 2018 summer was unusually hot for large areas in the Northern Hemisphere, and heatwaves on three continents led to major impacts on agriculture and society. This study investigates storylines for the extreme 2018 summer, given the observed atmospheric circulation but different levels of background global warming. The results reveal a strong contribution by the present-day level of global warming and show a dramatic outlook for similar events in a warmer climate.
Karina von Schuckmann, Lijing Cheng, Matthew D. Palmer, James Hansen, Caterina Tassone, Valentin Aich, Susheel Adusumilli, Hugo Beltrami, Tim Boyer, Francisco José Cuesta-Valero, Damien Desbruyères, Catia Domingues, Almudena García-García, Pierre Gentine, John Gilson, Maximilian Gorfer, Leopold Haimberger, Masayoshi Ishii, Gregory C. Johnson, Rachel Killick, Brian A. King, Gottfried Kirchengast, Nicolas Kolodziejczyk, John Lyman, Ben Marzeion, Michael Mayer, Maeva Monier, Didier Paolo Monselesan, Sarah Purkey, Dean Roemmich, Axel Schweiger, Sonia I. Seneviratne, Andrew Shepherd, Donald A. Slater, Andrea K. Steiner, Fiammetta Straneo, Mary-Louise Timmermans, and Susan E. Wijffels
Earth Syst. Sci. Data, 12, 2013–2041, https://doi.org/10.5194/essd-12-2013-2020, https://doi.org/10.5194/essd-12-2013-2020, 2020
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Understanding how much and where the heat is distributed in the Earth system is fundamental to understanding how this affects warming oceans, atmosphere and land, rising temperatures and sea level, and loss of grounded and floating ice, which are fundamental concerns for society. This study is a Global Climate Observing System (GCOS) concerted international effort to obtain the Earth heat inventory over the period 1960–2018.
Cited articles
Albergel, C., Rüdiger, C., Pellarin, T., Calvet, J.-C., Fritz, N., Froissard, F., Suquia, D., Petitpa, A., Piguet, B., and Martin, E.: From near-surface to root-zone soil moisture using an exponential filter: an assessment of the method based on in-situ observations and model simulations, Hydrol. Earth Syst. Sci., 12, 1323–1337, https://doi.org/10.5194/hess-12-1323-2008, 2008.
Albergel, C., Dorigo, W., Reichle, R. H., Balsamo, G., de Rosnay, P., Munoz-Sabater, J., Isaksen, L., de Jeu, R., and Wagner, W.: Skill and Global Trend Analysis of Soil Moisture from Reanalyses and Microwave Remote Sensing, J. Hydrometeorol., 14, 1259–1277, https://doi.org/10.1175/jhm-d-12-0161.1, 2013.
An, R., Zhang, L., Wang, Z., Quaye-Ballard, J. A., You, J. J., Shen, X. J., Gao, W., Huang, L. J., Zhao, Y. H., and Ke, Z. Y.: Validation of the ESA CCI soil moisture product in China, Int. J. Appl. Earth Obs., 48, 28–36, https://doi.org/10.1016/j.jag.2015.09.009, 2016.
Balsamo, G., Viterbo, P., Beljaars, A., van den Hurk, B., Hirschi, M., Betts, A. K., and Scipal, K.: A Revised Hydrology for the ECMWF Model: Verification from Field Site to Terrestrial Water Storage and Impact in the Integrated Forecast System, J. Hydrometeorol., 10, 623–643, https://doi.org/10.1175/2008jhm1068.1, 2009.
Beck, H. E., Pan, M., Miralles, D. G., Reichle, R. H., Dorigo, W. A., Hahn, S., Sheffield, J., Karthikeyan, L., Balsamo, G., Parinussa, R. M., van Dijk, A. I. J. M., Du, J., Kimball, J. S., Vergopolan, N., and Wood, E. F.: Evaluation of 18 satellite- and model-based soil moisture products using in situ measurements from 826 sensors, Hydrol. Earth Syst. Sci., 25, 17–40, https://doi.org/10.5194/hess-25-17-2021, 2021.
Bosilovich, M. G., Akella, S., Coy, L., Cullather, R., Draper, C., Gelaro, R., Kovach, R., Liu, Q., Molod, A., Norris, P., Wargan, K., Chao, W., Reichle, R., Takacs, L., Vikhliaev, Y., Bloom, S., Collow, A., Firth, S., Labow, G., Partyka, G., Pawson, S., Reale, O., Schubert, S. D., and Suarez, M.: MERRA-2: Initial evaluation of the climate, National Aeronautics and Space Administration, Goddard Space Flight Center, Greenbelt, Maryland, https://gmao.gsfc.nasa.gov/pubs/docs/Bosilovich803.pdf (last access: 10 January 2025), 2015.
Bueechi, E., Fischer, M., Crocetti, L., Trnka, M., Grlj, A., Zappa, L., and Dorigo, W.: Crop yield anomaly forecasting in the Pannonian basin using gradient boosting and its performance in years of severe drought, Agr. Forest Meteorol., 340, 109596, https://doi.org/10.1016/j.agrformet.2023.109596, 2023.
Champagne, C., White, J., Berg, A., Belair, S., and Carrera, M.: Impact of Soil Moisture Data Characteristics on the Sensitivity to Crop Yields Under Drought and Excess Moisture Conditions, Remote Sens.-Basel, 11, 372, https://doi.org/10.3390/rs11040372, 2019.
Cheng, S. J., Guan, X. D., Huang, J. P., Ji, F., and Guo, R. X.: Long-term trend and variability of soil moisture over East Asia, J. Geophys. Res.-Atmos., 120, 8658–8670, https://doi.org/10.1002/2015jd023206, 2015.
Crezee, B., Hirschi, M., Thorne, P., Coll, J., Müller, B., Yang, C., Pisano, A., and Hassler, B.: Deliverable D511.1.5: Data catalogue for extreme events and extreme event metrics, 54 pp., https://drive.google.com/file/d/13KlOW-1xq82LuMKLvbS2MmOtCDMMpYWO/view (last access: 10 January 2025), 2019.
C3S: Land cover classification gridded maps from 1992 to present derived from satellite observation, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.006f2c9a, 2019.
de Rosnay, P., Drusch, M., Vasiljevic, D., Balsamo, G., Albergel, C., and Isaksen, L.: A simplified Extended Kalman Filter for the global operational soil moisture analysis at ECMWF, Q. J. Roy. Meteor. Soc., 139, 1199–1213, https://doi.org/10.1002/qj.2023, 2013.
de Rosnay, P., Balsamo, G., Albergel, C., Munoz-Sabater, J., and Isaksen, L.: Initialisation of Land Surface Variables for Numerical Weather Prediction, Surv. Geophys., 35, 607–621, https://doi.org/10.1007/s10712-012-9207-x, 2014.
Dirmeyer, P. A., Wu, J. X., Norton, H. E., Dorigo, W. A., Quiring, S. M., Ford, T. W., Santanello, J. A., Bosilovich, M. G., Ek, M. B., Koster, R. D., Balsamo, G., and Lawrence, D. M.: Confronting Weather and Climate Models with Observational Data from Soil Moisture Networks over the United States, J. Hydrometeorol., 17, 1049–1067, https://doi.org/10.1175/Jhm-D-15-0196.1, 2016.
Dorigo, W., de Jeu, R., Chung, D., Parinussa, R., Liu, Y., Wagner, W., and Fernandez-Prieto, D.: Evaluating global trends (1988–2010) in harmonized multi-satellite surface soil moisture, Geophys. Res. Lett., 39, L18405, https://doi.org/10.1029/2012gl052988, 2012.
Dorigo, W., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, P. D., Hirschi, M., Ikonen, J., de Jeu, R., Kidd, R., Lahoz, W., Liu, Y. Y., Miralles, D., Mistelbauer, T., Nicolai-Shaw, N., Parinussa, R., Pratola, C., Reimer, C., van der Schalie, R., Seneviratne, S. I., Smolander, T., and Lecomte, P.: ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions, Remote Sens. Environ., 203, 185–215, https://doi.org/10.1016/j.rse.2017.07.001, 2017.
Dorigo, W., Himmelbauer, I., Aberer, D., Schremmer, L., Petrakovic, I., Zappa, L., Preimesberger, W., Xaver, A., Annor, F., Ardö, J., Baldocchi, D., Bitelli, M., Blöschl, G., Bogena, H., Brocca, L., Calvet, J.-C., Camarero, J. J., Capello, G., Choi, M., Cosh, M. C., van de Giesen, N., Hajdu, I., Ikonen, J., Jensen, K. H., Kanniah, K. D., de Kat, I., Kirchengast, G., Kumar Rai, P., Kyrouac, J., Larson, K., Liu, S., Loew, A., Moghaddam, M., Martínez Fernández, J., Mattar Bader, C., Morbidelli, R., Musial, J. P., Osenga, E., Palecki, M. A., Pellarin, T., Petropoulos, G. P., Pfeil, I., Powers, J., Robock, A., Rüdiger, C., Rummel, U., Strobel, M., Su, Z., Sullivan, R., Tagesson, T., Varlagin, A., Vreugdenhil, M., Walker, J., Wen, J., Wenger, F., Wigneron, J. P., Woods, M., Yang, K., Zeng, Y., Zhang, X., Zreda, M., Dietrich, S., Gruber, A., van Oevelen, P., Wagner, W., Scipal, K., Drusch, M., and Sabia, R.: The International Soil Moisture Network: serving Earth system science for over a decade, Hydrol. Earth Syst. Sci., 25, 5749–5804, https://doi.org/10.5194/hess-25-5749-2021, 2021a.
Dorigo, W., Preimesberger, W., Moesinger, L., Pasik, A., Scanlon, T., Hahn, S., Van der Schalie, R., Van der Vliet, M., De Jeu, R., Kidd, R., Rodriguez-Fernandez, N., and Hirschi, M.: ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): Version 06.1 data collection [data set], https://doi.org/10.5285/28935552223242ca97953a8db99c2821, 2021b.
Dorigo, W., Preimesberger, W., Hahn, S., Van der Schalie, R., De Jeu, R., Kidd, R., Rodriguez-Fernandez, N., Hirschi, M., Stradiotti, P., Frederikse, T., Gruber, A., and Madelon, R.: ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): Version 08.1 data collection, NERC EDS Centre for Environmental Data Analysis [data set], http://catalogue.ceda.ac.uk/uuid/ff890589c21f4033803aa550f52c980c (last access: 10 January 2025), 2023.
Dorigo, W. A., Wagner, W., Hohensinn, R., Hahn, S., Paulik, C., Xaver, A., Gruber, A., Drusch, M., Mecklenburg, S., van Oevelen, P., Robock, A., and Jackson, T.: The International Soil Moisture Network: a data hosting facility for global in situ soil moisture measurements, Hydrol. Earth Syst. Sci., 15, 1675–1698, https://doi.org/10.5194/hess-15-1675-2011, 2011.
Dorigo, W. A., Gruber, A., De Jeu, R. A. M., Wagner, W., Stacke, T., Loew, A., Albergel, C., Brocca, L., Chung, D., Parinussa, R. M., and Kidd, R.: Evaluation of the ESA CCI soil moisture product using ground-based observations, Remote Sens. Environ., 162, 380–395, https://doi.org/10.1016/j.rse.2014.07.023, 2015.
Douville, H., Raghavan, K., Renwick, J., Allan, R. P., Arias, P. A., Barlow, M., Cerezo-Mota, R., Cherchi, A., Gan, T. Y., Gergis, J., Jiang, D., Khan, A., Mba, W. P., Rosenfeld, D., Tierney, J., and Zolina, O.: Water Cycle Changes, in: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Masson-Delmotte, V., Zhai, P., Pirani, A., Connors, S. L., Péan, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., Gomis, M. I., Huang, M., Leitzell, K., Lonnoy, E., Matthews, J. B. R., Maycock, T. K., Waterfield, T., Yelekçi, O., Yu, R., and Zhou, B., Cambridge University Press, 1055–1210, https://doi.org/10.1017/9781009157896.010, 2021.
Fairbairn, D., de Rosnay, P., and Browne, P. A.: The New Stand-Alone Surface Analysis at ECMWF: Implications for Land-Atmosphere DA Coupling, J. Hydrometeorol., 20, 2023–2042, https://doi.org/10.1175/Jhm-D-19-0074.1, 2019.
Feng, H. H. and Zhang, M. Y.: Global land moisture trends: drier in dry and wetter in wet over land, Sci. Rep.-UK, 5, 18018, https://doi.org/10.1038/srep18018, 2015.
Fennig, K., Schröder, M., Andersson, A., and Hollmann, R.: A Fundamental Climate Data Record of SMMR, SSM/I, and SSMIS brightness temperatures, Earth Syst. Sci. Data, 12, 647–681, https://doi.org/10.5194/essd-12-647-2020, 2020.
GCOS: The global observing system for climate: Implementation needs, GCOS-200, https://library.wmo.int/idurl/4/55469 (last access: 10 January 2025), 2016.
Gelaro, R., McCarty, W., Suarez, M. J., Todling, R., Molod, A., Takacs, L., Randles, C. A., Darmenov, A., Bosilovich, M. G., Reichle, R., Wargan, K., Coy, L., Cullather, R., Draper, C., Akella, S., Buchard, V., Conaty, A., da Silva, A. M., Gu, W., Kim, G.-K., Koster, R., Lucchesi, R., Merkova, D., Nielsen, J. E., Partyka, G., Pawson, S., Putman, W., Rienecker, M., Schubert, S. D., Sienkiewicz, M., and Zhao, B.: The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2), J. Climate, 30, 5419–5454, https://doi.org/10.1175/jcli-d-16-0758.1, 2017.
GMAO: MERRA-2 tavg1_2d_lnd_Nx: 2d,1-Hourly,Time-Averaged,Single-Level,Assimilation,Land Surface Diagnostics V5.12.4, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], https://doi.org/10.5067/RKPHT8KC1Y1T, 2015.
Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W.: Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology, Earth Syst. Sci. Data, 11, 717–739, https://doi.org/10.5194/essd-11-717-2019, 2019.
Gu, X. H., Li, J. F., Chen, Y. D., Kong, D. D., and Liu, J. Y.: Consistency and Discrepancy of Global Surface Soil Moisture Changes From Multiple Model-Based Data Sets Against Satellite Observations, J. Geophys. Res.-Atmos., 124, 1474–1495, https://doi.org/10.1029/2018jd029304, 2019.
Gudmundsson, L., Rego, F. C., Rocha, M., and Seneviratne, S. I.: Predicting above normal wildfire activity in southern Europe as a function of meteorological drought, Environ. Res. Lett., 9, 084008, https://doi.org/10.1088/1748-9326/9/8/084008, 2014.
Hahn, S., Wagner, W., Alves, O., Muguda Sanjeevamurthy, P., Vreugdenhil, M., and Melzer, T.: Metop ASCAT soil moisture trends: Mitigating the effects of long-term land cover changes, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-16205, https://doi.org/10.5194/egusphere-egu23-16205, 2023.
Hanel, M., Rakovec, O., Markonis, Y., Maca, P., Samaniego, L., Kysely, J., and Kumar, R.: Revisiting the recent European droughts from a long-term perspective, Sci. Rep., 8, 9499, https://doi.org/10.1038/s41598-018-27464-4, 2018.
Harris, I., Osborn, T. J., Jones, P., and Lister, D.: Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset, Scientific Data, 7, 109, https://doi.org/10.1038/s41597-020-0453-3, 2020.
Harris, I. C., Jones, P. D., and Osborn, T.: CRU TS4.07: Climatic Research Unit (CRU) Time-Series (TS) version 4.07 of high-resolution gridded data of month-by-month variation in climate (Jan. 1901–Dec. 2022), NERC EDS Centre for Environmental Data Analysis [data set], https://catalogue.ceda.ac.uk/uuid/5fda109ab71947b6b7724077bf7eb753 (last access: 10 January 2025), 2023.
He, Q., Lu, H., and Yang, K.: Soil Moisture Memory of Land Surface Models Utilized in Major Reanalyses Differ Significantly From SMAP Observation, Earths Future, 11, e2022EF003215, https://doi.org/10.1029/2022EF003215, 2023.
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.-N.: The ERA5 Global Reanalysis, Q. J. Roy. Meteor. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020.
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., and Thépaut, J.-N.: ERA5 hourly data on single levels from 1940 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.adbb2d47, 2023.
Hirschi, M., Seneviratne, S. I., Alexandrov, V., Boberg, F., Boroneant, C., Christensen, O. B., Formayer, H., Orlowsky, B., and Stepanek, P.: Observational evidence for soil-moisture impact on hot extremes in southeastern Europe, Nat. Geosci., 4, 17–21, https://doi.org/10.1038/Ngeo1032, 2011.
Hirschi, M., Mueller, B., Dorigo, W., and Seneviratne, S. I.: Using remotely sensed soil moisture for land-atmosphere coupling diagnostics: The role of surface vs. root-zone soil moisture variability, Remote Sens. Environ., 154, 246–252, https://doi.org/10.1016/j.rse.2014.08.030, 2014.
Hirschi, M., Stradiotti, P., Preimesberger, W., Dorigo, W., and Kidd, R.: Product Validation and Intercomparison Report (PVIR): Supporting Product version v08.1. Deliverable D4.1 Version 1, ESA Climate Change Initiative Plus – Soil Moisture, https://doi.org/10.5281/zenodo.8320930, 2023.
H SAF: Algorithm Theoretical Baseline Document (ATBD) Metop ASCAT Surface Soil Moisture Climate Data Record v7 12.5 km sampling (H119) and extension (H120), v0.1, 2021.
Jia, B. H., Liu, J. G., Xie, Z. H., and Shi, C. X.: Interannual Variations and Trends in Remotely Sensed and Modeled Soil Moisture in China, J. Hydrometeorol., 19, 831–847, https://doi.org/10.1175/Jhm-D-18-0003.1, 2018.
Koster, R. D., Suarez, M. J., Ducharne, A., Stieglitz, M., and Kumar, P.: A catchment-based approach to modeling land surface processes in a general circulation model: 1. Model structure, J. Geophys. Res.-Atmos., 105, 24809–24822, https://doi.org/10.1029/2000jd900327, 2000.
Koster, R. D., Guo, Z., Yang, R., Dirmeyer, P. A., Mitchell, K., and Puma, M. J.: On the Nature of Soil Moisture in Land Surface Models, J. Climate, 22, 4322–4335, https://doi.org/10.1175/2009jcli2832.1, 2009.
Koster, R. D., Mahanama, S. P. P., Livneh, B., Lettenmaier, D. P., and Reichle, R. H.: Skill in streamflow forecasts derived from large-scale estimates of soil moisture and snow, Nat. Geosci., 3, 613–616, https://doi.org/10.1038/Ngeo944, 2010.
Li, M., Wu, P., and Ma, Z.: A comprehensive evaluation of soil moisture and soil temperature from third-generation atmospheric and land reanalysis data sets, Int. J. Climatol., 40, 5744–5766, https://doi.org/10.1002/joc.6549, 2020.
Li, X. W., Gao, X. Z., Wang, J. K., and Guoa, H. D.: Microwave soil moisture dynamics and response to climate change in Central Asia and Xinjiang Province, China, over the last 30 years, J. Appl. Remote Sens., 9, 096012, https://doi.org/10.1117/1.Jrs.9.096012, 2015.
Liu, L. B., Gudmundsson, L., Hauser, M., Qin, D. H., Li, S. C., and Seneviratne, S. I.: Soil moisture dominates dryness stress on ecosystem production globally, Nat. Commun., 11, 4892, https://doi.org/10.1038/s41467-020-18631-1, 2020.
Lloyd-Hughes, B. and Saunders, M. A.: A drought climatology for Europe, Int. J. Climatol., 22, 1571–1592, https://doi.org/10.1002/joc.846, 2002.
Loew, A., Stacke, T., Dorigo, W., de Jeu, R., and Hagemann, S.: Potential and limitations of multidecadal satellite soil moisture observations for selected climate model evaluation studies, Hydrol. Earth Syst. Sci., 17, 3523–3542, https://doi.org/10.5194/hess-17-3523-2013, 2013.
Lyons, D. S., Dobrowski, S. Z., Holden, Z. A., Maneta, M. P., and Sala, A.: Soil moisture variation drives canopy water content dynamics across the western US, Remote Sens. Environ., 253, 112233, https://doi.org/10.1016/j.rse.2020.112233, 2021.
McKee, T. B., Doesken, N. J., and Kleist, J.: The relationship of drought frequency and duration to time scales, in: Eighth Conference on Applied Climatology, 17–22 January 1993, Anaheim, California, USA, 179–184,1993.
Miralles, D. G., Teuling, A. J., van Heerwaarden, C. C., and Vila-Guerau de Arellano, J.: Mega-heatwave temperatures due to combined soil desiccation and atmospheric heat accumulation, Nat. Geosci., 7, 345–349, https://doi.org/10.1038/ngeo2141, 2014.
Moravec, V., Markonis, Y., Rakovec, O., Kumar, R., and Hanel, M.: A 250-Year European Drought Inventory Derived From Ensemble Hydrologic Modeling, Geophys. Res. Lett., 46, 5909–5917, https://doi.org/10.1029/2019gl082783, 2019.
Mueller, B. and Seneviratne, S. I.: Hot days induced by precipitation deficits at the global scale, P. Natl. Acad. Sci. USA, 109, 12398–12403, https://doi.org/10.1073/pnas.1204330109, 2012.
Muñoz Sabater, J.: ERA5-Land hourly data from 1950 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.e2161bac, 2019.
Muñoz-Sabater, J., Dutra, E., Agustí-Panareda, A., Albergel, C., Arduini, G., Balsamo, G., Boussetta, S., Choulga, M., Harrigan, S., Hersbach, H., Martens, B., Miralles, D. G., Piles, M., Rodríguez-Fernández, N. J., Zsoter, E., Buontempo, C., and Thépaut, J.-N.: ERA5-Land: a state-of-the-art global reanalysis dataset for land applications, Earth Syst. Sci. Data, 13, 4349–4383, https://doi.org/10.5194/essd-13-4349-2021, 2021.
Naeimi, V., Scipal, K., Bartalis, Z., Hasenauer, S., and Wagner, W.: An Improved Soil Moisture Retrieval Algorithm for ERS and METOP Scatterometer Observations, IEEE T. Geosci. Remote, 47, 1999–2013, https://doi.org/10.1109/Tgrs.2008.2011617, 2009.
Orlowsky, B. and Seneviratne, S. I.: Elusive drought: uncertainty in observed trends and short- and long-term CMIP5 projections, Hydrol. Earth Syst. Sci., 17, 1765–1781, https://doi.org/10.5194/hess-17-1765-2013, 2013.
Padron, R. S., Gudmundsson, L., Decharme, B., Ducharne, A., Lawrence, D. M., Mao, J. F., Peano, D., Krinner, G., Kim, H., and Seneviratne, S. I.: Observed changes in dry-season water availability attributed to human-induced climate change, Nat. Geosci., 13, 477–481, https://doi.org/10.1038/s41561-020-0594-1, 2020.
Pasik, A., Gruber, A., Preimesberger, W., De Santis, D., and Dorigo, W.: Uncertainty estimation for a new exponential-filter-based long-term root-zone soil moisture dataset from Copernicus Climate Change Service (C3S) surface observations, Geosci. Model Dev., 16, 4957–4976, https://doi.org/10.5194/gmd-16-4957-2023, 2023.
Preimesberger, W., Scanlon, T., Su, C.-H., Gruber, A., and Dorigo, W.: Homogenization of Structural Breaks in the Global ESA CCI Soil Moisture Multisatellite Climate Data Record, IEEE T. Geosci. Remote, 59, 2845–2862, https://doi.org/10.1109/tgrs.2020.3012896, 2021.
Qiu, J. X., Gao, Q. Z., Wang, S., and Su, Z. R.: Comparison of temporal trends from multiple soil moisture data sets and precipitation: The implication of irrigation on regional soil moisture trend, Int. J. Appl. Earth Obs., 48, 17–27, https://doi.org/10.1016/j.jag.2015.11.012, 2016.
Rahmani, A., Golian, S., and Brocca, L.: Multiyear monitoring of soil moisture over Iran through satellite and reanalysis soil moisture products, Int. J. Appl. Earth Obs., 48, 85–95, https://doi.org/10.1016/j.jag.2015.06.009, 2016.
Reichle, R. H., Draper, C. S., Liu, Q., Girotto, M., Mahanama, S. P. P., Koster, R. D., and De Lannoy, G. J. M.: Assessment of MERRA-2 Land Surface Hydrology Estimates, J. Climate, 30, 2937–2960, https://doi.org/10.1175/jcli-d-16-0720.1, 2017a.
Reichle, R. H., Liu, Q., Koster, R. D., Draper, C. S., Mahanama, S. P. P., and Partyka, G. S.: Land Surface Precipitation in MERRA-2, J. Climate, 30, 1643–1664, https://doi.org/10.1175/jcli-d-16-0570.1, 2017b.
Rodell, M., Houser, P. R., Jambor, U., Gottschalck, J., Mitchell, K., Meng, C. J., Arsenault, K., Cosgrove, B., Radakovich, J., Bosilovich, M., Entin, J. K., Walker, J. P., Lohmann, D., and Toll, D.: The global land data assimilation system, B. Am. Meteorol. Soc., 85, 381–394, https://doi.org/10.1175/Bams-85-3-381, 2004.
Saxton, K. E. and Rawls, W. J.: Soil water characteristic estimates by texture and organic matter for hydrologic solutions, Soil Sci. Soc. Am. J., 70, 1569–1578, https://doi.org/10.2136/sssaj2005.0117, 2006.
Scherrer, S. C., Hirschi, M., Spirig, C., Maurer, F., and Kotlarski, S.: Trends and drivers of recent summer drying in Switzerland, Environmental Research Communications, 4, 025004, https://doi.org/10.1088/2515-7620/ac4fb9, 2022.
Schumacher, D. L., Zachariah, M., Otto, F., Barnes, C., Philip, S., Kew, S., Vahlberg, M., Singh, R., Heinrich, D., Arrighi, J., van Aalst, M., Thalheimer, L., Raju, E., Hauser, M., Hirschi, M., Gudmundsson, L., Beaudoing, H. K., Rodell, M., Li, S., Yang, W., Vecchi, G. A., Vautard, R., Harrington, L. J., and Seneviratne, S. I.: High temperatures exacerbated by climate change made 2022 Northern Hemisphere soil moisture droughts more likely, World Weather Attribution, https://www.worldweatherattribution.org/wp-content/uploads/WCE-NH-drought-scientific-report.pdf (last access: 10 January 2025), 2022.
Schumacher, D. L., Zachariah, M., Otto, F., Barnes, C., Philip, S., Kew, S., Vahlberg, M., Singh, R., Heinrich, D., Arrighi, J., van Aalst, M., Hauser, M., Hirschi, M., Bessenbacher, V., Gudmundsson, L., Beaudoing, H. K., Rodell, M., Li, S., Yang, W., Vecchi, G. A., Harrington, L. J., Lehner, F., Balsamo, G., and Seneviratne, S. I.: Detecting the human fingerprint in the summer 2022 western–central European soil drought, Earth Syst. Dynam., 15, 131–154, https://doi.org/10.5194/esd-15-131-2024, 2024.
Schwingshackl, C., Hirschi, M., and Seneviratne, S. I.: Quantifying Spatiotemporal Variations of Soil Moisture Control on Surface Energy Balance and Near-Surface Air Temperature, J. Climate, 30, 7105–7124, https://doi.org/10.1175/Jcli-D-16-0727.1, 2017.
Seneviratne, S. I.: Climate science: Historical drought trends revisited, Nature, 491, 338–339, https://doi.org/10.1038/491338a, 2012.
Seneviratne, S. I., Corti, T., Davin, E. L., Hirschi, M., Jaeger, E. B., Lehner, I., Orlowsky, B., and Teuling, A. J.: Investigating soil moisture-climate interactions in a changing climate: A review, Earth-Sci. Rev., 99, 125–161, https://doi.org/10.1016/j.earscirev.2010.02.004, 2010.
Seneviratne, S. I., Zhang, X., Adnan, M., Badi, W., Dereczynski, C., Luca, A. D., Ghosh, S., Iskandar, I., Kossin, J., Lewis, S., Otto, F., Pinto, I., Satoh, M., Vicente-Serrano, S. M., Wehner, M., and Zhou, B.: Weather and Climate Extreme Events in a Changing Climate, in: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Masson-Delmotte, V., Zhai, P., Pirani, A., Connors, S. L., Péan, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., Gomis, M. I., Huang, M., Leitzell, K., Lonnoy, E., Matthews, J. B. R., Maycock, T. K., Waterfield, T., Yelekçi, O., Yu, R., and Zhou, B., Cambridge University Press, 1513–1766, https://doi.org/10.1017/9781009157896.013, 2021.
Simmons, A. J., Berrisford, P., Dee, D. P., Hersbach, H., Hirahara, S., and Thepaut, J. N.: A reassessment of temperature variations and trends from global reanalyses and monthly surface climatological datasets, Q. J. Roy. Meteor. Soc., 143, 101–119, https://doi.org/10.1002/qj.2949, 2017.
Stahl, K., Kohn, I., Blauhut, V., Urquijo, J., De Stefano, L., Acácio, V., Dias, S., Stagge, J. H., Tallaksen, L. M., Kampragou, E., Van Loon, A. F., Barker, L. J., Melsen, L. A., Bifulco, C., Musolino, D., de Carli, A., Massarutto, A., Assimacopoulos, D., and Van Lanen, H. A. J.: Impacts of European drought events: insights from an international database of text-based reports, Nat. Hazards Earth Syst. Sci., 16, 801–819, https://doi.org/10.5194/nhess-16-801-2016, 2016.
Stradiotti, P. and Preimesberger, W.: ESA CCI SM RZSM Long-term Climate Record of Root-Zone Soil Moisture from merged multi-satellite observations (9.1), TU Wien [data set], https://doi.org/10.48436/v8cwj-jk556, 2024.
Su, C.-H., Ryu, D., Dorigo, W., Zwieback, S., Gruber, A., Albergel, C., Reichle, R. H., and Wagner, W.: Homogeneity of a global multisatellite soil moisture climate data record, Geophys. Res. Lett., 43, 11245–11252, https://doi.org/10.1002/2016gl070458, 2016.
Teuling, A. J., Van Loon, A. F., Seneviratne, S. I., Lehner, I., Aubinet, M., Heinesch, B., Bernhofer, C., Grunwald, T., Prasse, H., and Spank, U.: Evapotranspiration amplifies European summer drought, Geophys. Res. Lett., 40, 2071–2075, https://doi.org/10.1002/grl.50495, 2013.
Trnka, M., Brazdil, R., Mozny, M., Stepanek, P., Dobrovolny, P., Zahradnicek, P., Balek, J., Semeradova, D., Dubrovsky, M., Hlavinka, P., Eitzinger, J., Wardlow, B., Svoboda, M., Hayesi, M., and Zalud, Z.: Soil moisture trends in the Czech Republic between 1961 and 2012, Int. J. Climatol., 35, 3733–3747, https://doi.org/10.1002/joc.4242, 2015.
Vreugdenhil, M., Dorigo, W. A., Wagner, W., de Jeu, R. A. M., Hahn, S., and van Marle, M. J. E.: Analyzing the Vegetation Parameterization in the TU-Wien ASCAT Soil Moisture Retrieval, IEEE T. Geosci. Remote, 54, 3513–3531, https://doi.org/10.1109/Tgrs.2016.2519842, 2016.
Vroege, W., Bucheli, J., Dalhaus, T., Hirschi, M., and Finger, R.: Insuring crops from space: the potential of satellite-retrieved soil moisture to reduce farmers' drought risk exposure, Eur. Rev. Agric. Econ., 48, 266–314, https://doi.org/10.1093/erae/jbab010, 2021.
Wagner, W., Lemoine, G., and Rott, H.: A method for estimating soil moisture from ERS scatterometer and soil data, Remote Sens. Environ., 70, 191–207, https://doi.org/10.1016/S0034-4257(99)00036-X, 1999.
Wagner, W., Lindorfer, R., Melzer, T., Hahn, S., Bauer-Marschallinger, B., Morrison, K., Calvet, J. C., Hobbs, S., Quast, R., Greimeister-Pfeil, I., and Vreugdenhil, M.: Widespread occurrence of anomalous C-band backscatter signals in arid environments caused by subsurface scattering, Remote Sens. Environ., 276, 113025, https://doi.org/10.1016/j.rse.2022.113025, 2022.
Wang, S. S., Mo, X. G., Liu, S. X., Lin, Z. H., and Hu, S.: Validation and trend analysis of ECV soil moisture data on cropland in North China Plain during 1981–2010, Int. J. Appl. Earth Obs., 48, 110–121, https://doi.org/10.1016/j.jag.2015.10.010, 2016.
Wen, J., Wu, X., You, D., Ma, X., Ma, D., Wang, J., and Xiao, Q.: The main inherent uncertainty sources in trend estimation based on satellite remote sensing data, Theor. Appl. Climatol., 151, 915–934, https://doi.org/10.1007/s00704-022-04312-0, 2022.
WMO: Guidelines on the Definition and Characterization of Extreme Weather and Climate Events, WMO-No. 1310, https://library.wmo.int/idurl/4/58396 (last access: 10 January 2025), 2023.
Wouters, H.: Global bioclimatic indicators from 1979 to 2018 derived from reanalysis [data set], https://doi.org/10.24381/cds.bce175f0, 2021.
Yang, C. X., Cagnazzo, C., Artale, V., Nardelli, B. B., Buontempo, C., Busatto, J., Caporaso, L., Cesarini, C., Cionni, I., Coll, J., Crezee, B., Cristofanelli, P., de Toma, V., Essa, Y. H., Eyring, V., Fierli, F., Grant, L., Hassler, B., Hirschi, M., Huybrechts, P., Le Merle, E., Leonelli, F. E., Lin, X., Madonna, F., Mason, E., Massonnet, F., Marcos, M., Marullo, S., Muller, B., Obregon, A., Organelli, E., Palacz, A., Pascual, A., Pisano, A., Putero, D., Rana, A., Sanchez-Roman, A., Seneviratne, S. I., Serva, F., Storto, A., Thiery, W., Throne, P., Van Tricht, L., Verhaegen, Y., Volpe, G., and Santoleri, R.: Independent Quality Assessment of Essential Climate Variables: Lessons Learned from the Copernicus Climate Change Service, B. Am. Meteorol. Soc., 103, E2032–E2049, https://doi.org/10.1175/Bams-D-21-0109.1, 2022.
Yang, J., Gong, P., Fu, R., Zhang, M. H., Chen, J. M., Liang, S. L., Xu, B., Shi, J. C., and Dickinson, R.: The role of satellite remote sensing in climate change studies, Nat. Clim. Change, 3, 875–883, https://doi.org/10.1038/Nclimate1908, 2013.
Zaitchik, B. F., Rodell, M., Biasutti, M., and Seneviratne, S. I.: Wetting and drying trends under climate change, Nature Water, 1, 502–513, https://doi.org/10.1038/s44221-023-00073-w, 2023.
Zheng, X. M., Zhao, K., Ding, Y. L., Jiang, T., Zhang, S. Y., and Jin, M. J.: The spatiotemporal patterns of surface soil moisture in Northeast China based on remote sensing products, J. Water Clim. Change, 7, 708–720, https://doi.org/10.2166/wcc.2016.106, 2016.
Zheng, Y., Coxon, G., Woods, R., Power, D., Rico-Ramirez, M. A., McJannet, D., Rosolem, R., Li, J., and Feng, P.: Evaluation of reanalysis soil moisture products using cosmic ray neutron sensor observations across the globe, Hydrol. Earth Syst. Sci., 28, 1999–2022, https://doi.org/10.5194/hess-28-1999-2024, 2024.
Zotta, R.-M., Moesinger, L., van der Schalie, R., Vreugdenhil, M., Preimesberger, W., Frederikse, T., de Jeu, R., and Dorigo, W.: VODCA v2: multi-sensor, multi-frequency vegetation optical depth data for long-term canopy dynamics and biomass monitoring, Earth Syst. Sci. Data, 16, 4573–4617, https://doi.org/10.5194/essd-16-4573-2024, 2024.
Short summary
We investigate the potential of long-term satellite and reanalysis products for characterising soil drying by analysing their 2000–2022 soil moisture trends and their representation of agroecological drought events of this period. Soil moisture trends are globally diverse and partly contradictory between products. This also affects the products' drought-detection capacity. Based on the best-estimate products, consistent soil drying is observed over more than 40 % of the land area covered.
We investigate the potential of long-term satellite and reanalysis products for characterising...