Articles | Volume 14, issue 1
https://doi.org/10.5194/esd-14-173-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/esd-14-173-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
14 Feb 2023
Research article |
| 14 Feb 2023
| 14 Feb 2023
Reliability of resilience estimation based on multi-instrument time series
Institute of Geosciences, Universität Potsdam, Potsdam, Germany
Ruxandra-Maria Zotta
Department of Geodesy and Geo-Information, Vienna University of Technology, Vienna, Austria
Chris A. Boulton
Global Systems Institute, University of Exeter, Exeter, UK
Timothy M. Lenton
Global Systems Institute, University of Exeter, Exeter, UK
Wouter Dorigo
Department of Geodesy and Geo-Information, Vienna University of Technology, Vienna, Austria
Niklas Boers
Global Systems Institute, University of Exeter, Exeter, UK
Earth System Modelling, School of Engineering and Design, Technical University of Munich, Munich, Germany
Potsdam Institute for Climate Impact Research, Potsdam, Germany
Department of Mathematics, University of Exeter, Exeter, UK
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Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2026-620, https://doi.org/10.5194/essd-2026-620, 2026
Preprint under review for ESSD
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Machine learning is increasingly used for soil moisture modelling, but models remain difficult to compare because studies use different data and tests. Here, we present SoMoBench, built from ground measurements at 1,445 locations across diverse climate conditions, covering 2001–2024 and three soil depths. It also provides weather data, site information, baseline model results, and example code. This resource supports more consistent model development and fairer comparisons.
Andrew F. Feldman, William K. Smith, Alexandra G. Konings, Martin J. Baur, Marvin Browne, David Chaparro, Charles Devine, Jen L. Diehl, Arthur Endsley, Thomas Jagdhuber, Kristine M. Larson, Coral del Mar Valle-Rodriguez, Konstantin Schellenberg, Ruxandra-Maria Zotta, and Shawn P. Serbin
Biogeosciences, 23, 8159–8181, https://doi.org/10.5194/bg-23-8159-2026, https://doi.org/10.5194/bg-23-8159-2026, 2026
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Vegetation water observations from 272 field-based microwave Global Navigation Satellite System (GNSS) sensors and satellite-based vegetation optical depth are compared across the western United States. Significant positive correlations are found across sites, with larger seasonal amplitudes, more homogeneous landscapes, and less forest cover increasing the correlations. These field-based GNSS sensors are thus useful tools to evaluate grass and shrub water stress and validate satellite signals.
Roland Hohensinn, Junyang Gou, Ulrich Meyer, Laura Jensen, Vincent Humphrey, Wouter Dorigo, Eva Börgens, Benedikt Soja, Alexander Gruber, Annette Eicker, Michael Rast, and Andreas Güntner
Hydrol. Earth Syst. Sci., 30, 6789–6820, https://doi.org/10.5194/hess-30-6789-2026, https://doi.org/10.5194/hess-30-6789-2026, 2026
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Using 21.5 years of observations from the Gravity Recovery and Climate Experiment and its Follow-On mission, together with the Global Gravity-based Groundwater Product, we quantify groundwater storage change at continental and global scales. Significant losses are concentrated in Asia, while gains in Africa partly offset them globally. Accounting for persistent hydrological variability helps separate long-term change from shorter-term fluctuations.
Andreas Güntner, Ehsan Sharifi, Julian Haas, Eva Boergens, Feifei Cao, Christoph Dahle, Neda Darbeheshti, Henryk Dobslaw, Inés Dussaillant, Wouter Dorigo, Frank Flechtner, Adrian Jäggi, Miriam Kosmale, Martin Lasser, Kari Luojus, Ulrich Meyer, Adam Pasik, Wolfgang Preimesberger, Claudia Ruz Vargas, and Michael Zemp
Earth Syst. Sci. Data, 18, 7787–7816, https://doi.org/10.5194/essd-18-7787-2026, https://doi.org/10.5194/essd-18-7787-2026, 2026
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We provide a data set that illustrates how the amount of water that is stored in the subsurface as groundwater varies in time over the continents of the Earth. An important part of the data comes from satellites that track changes in water by its gravity effect. The data allow for assessing how groundwater as the most important freshwater resource for mankind and ecosystems is affected by climate variability, climate change and withdrawal by human activities.
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EGUsphere, https://doi.org/10.5194/egusphere-2026-6254, https://doi.org/10.5194/egusphere-2026-6254, 2026
This preprint is open for discussion and under review for Biogeosciences (BG).
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We developed a satellite-based method to estimate how much carbon plants take up through photosynthesis worldwide from 2002 to 2020. Using microwave observations, land cover and machine learning, we found that land-cover information improved estimates most, while deeper soil moisture better captured water-related changes in short vegetation. The approach complements existing products, but the total amount of plant carbon uptake remains uncertain.
Chris Huntingford, Jesse F. Abrams, Peter Ashwin, Niklas Boers, Chris A. Boulton, Joshua E. Buxton, Joseph Clarke, Peter M. Cox, Andrew M. Cunliffe, Henk A. Dijkstra, Bahar Emirzade, Darren Ghent, Daniel Giles, Sneha Kachhara, Timothy M. Lenton, Valerio Lucarini, Helen Millman, Robert J. Parker, Sergei Petrovskii, Paul D. L. Ritchie, Cristina Ruiz Villena, Mark S. Williamson, and Niccolò Zagli
EGUsphere, https://doi.org/10.5194/egusphere-2026-5606, https://doi.org/10.5194/egusphere-2026-5606, 2026
This preprint is open for discussion and under review for Earth System Dynamics (ESD).
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Future tipping of key parts of the Earth system, driven by human-induced climate change, poses serious risks to society. These concerns have spurred the development of Early Warning Systems (EWSs) that use data to show how close we are to tipping. However, existing EWSs are often generic statistical forms. We first review current EWS methods, then present a broad set of hypotheses that may help improve them. We argue strongly for process knowledge to guide more refined EWS forms.
Diaa Sheishah, Enas Abdelsamei, Viktoria Blanka-Vegi, Károly Barta, Ahmed M. Ali, Khaldoun Abualhin, Djamil Al-Halbouni, Wouter Dorigo, and Gyorgy Sipos
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2026-563, https://doi.org/10.5194/essd-2026-563, 2026
Preprint under review for ESSD
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Soil moisture controls drought, crop water supply, and groundwater recharge, but it is difficult to monitor below the surface. We used national monitoring data from 117 stations and six soil depths to build an open database that links soil moisture, soil type, water retention, and expected electromagnetic responses. The results identify a key mid-depth buffering zone and provide a practical reference for future drought monitoring, irrigation planning, and non-invasive soil-water surveys.
Xiyuan Chen and Timothy M. Lenton
EGUsphere, https://doi.org/10.5194/egusphere-2026-2949, https://doi.org/10.5194/egusphere-2026-2949, 2026
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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We develop the new TAlkEaSy (Total Alkalinity Earth System) model for exploring Earth’s climate, redox and ocean chemistry over geological time. It is the first forward model coupling carbon, oxygen, nutrients, ocean major ions and carbonate chemistry in one framework. We illustrate the model configuration and test its response to an abrupt carbon dioxide pulse and a longer-term change in tectonic degassing. The model produces reasonable responses.
Jawairia A. Ahmad, Christopher M. Taylor, Bethan L. Harris, Dávid D. Kovács, Seonaid Anderson, Adrià Amell, Colin Moldenhauer, Steven Wells, and Wouter Dorigo
EGUsphere, https://doi.org/10.5194/egusphere-2026-4687, https://doi.org/10.5194/egusphere-2026-4687, 2026
This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
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Evaluating the ability of satellite-observed soil moisture products to represent fine-scale land surface information shows that active microwave radar based product from ASCAT captures spatial variability at fine resolution which passive microwave based products miss. Rainfall dataset evaluation using fine-scale soil moisture information highlights the limitations in ERA5 precipitation. Further, fine-scale soil moisture information improves nowcasting of convective storms over dry regions.
Pierre Laluet, Jacopo Dari, Louise Busschaert, Zdenko Heyvaert, Gabrielle De Lannoy, Pia Langhans, Sara Modanesi, Christian Massari, Luca Brocca, Carla Saltalippi, Renato Morbidelli, Clément Albergel, and Wouter Dorigo
Earth Syst. Sci. Data, 18, 4833–4853, https://doi.org/10.5194/essd-18-4833-2026, https://doi.org/10.5194/essd-18-4833-2026, 2026
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We developed a long-term dataset collection of irrigation water use based on about two decades of satellite observations, three distinct approaches, and many input datasets. The collection provides monthly estimates for major agricultural regions and helps describe how irrigation varies across locations, seasons, and years. It offers a foundation for improving how irrigation is quantified, compared across methods, and integrated into large-scale hydrological and climate studies.
Oscar M. Baez-Villanueva, Alfredo Crespo-Otero, Sara Modanesi, Pierre Laluet, Sergio Vicente-Serrano, Jaap Schellekens, Jacopo Dari, Hylke E. Beck, Wouter Dorigo, Christian Massari, Chiara Corbari, Joppe Massant, Kwint Delbare, Olivier Bonte, Aaron Boone, Diego Fernández-Prieto, and Diego G. Miralles
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We developed a new method to estimate daily land evaporation at high resolution across the Iberian Peninsula, explicitly accounting for irrigation. By combining satellite and meteorological data, we show that irrigation can strongly increase evaporation in agricultural areas. The results better match ground observations and improve understanding of water use. This approach can support farming decisions and water management at the regional scale, and will be extended to global applications.
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EGUsphere, https://doi.org/10.5194/egusphere-2026-1012, https://doi.org/10.5194/egusphere-2026-1012, 2026
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Drought impacts water supply, agriculture, and ecosystems, yet hydrological models often disagree on when and where drought occurs. This study tested whether satellite observations can improve how models represent soil moisture drought in the Rhine River basin. Using several models and major drought events, we show that satellite data improve spatial realism and reveal important differences among models, helping to better understand uncertainty in drought monitoring and early warning.
Pierre Laluet, Chiara Corbari, Oscar Baez-Villanueva, Sophia Walther, Yongqiang Zhang, Joaquín Muñoz-Sabater, Clément Albergel, and Wouter Dorigo
Hydrol. Earth Syst. Sci., 30, 1779–1799, https://doi.org/10.5194/hess-30-1779-2026, https://doi.org/10.5194/hess-30-1779-2026, 2026
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We examined how well global datasets estimate evapotranspiration, the water moving from land to the air, in irrigated areas. We compared six widely used products with irrigation maps, satellite estimates, and field measurements across different climate regions. Some datasets better capture irrigation effects, especially those using temperature and vegetation satellite data. This work helps guide dataset selection and supports better inclusion of irrigation in hydrological and climate models.
Michael Aich, Philipp Hess, Baoxiang Pan, Sebastian Bathiany, Yu Huang, and Niklas Boers
Geosci. Model Dev., 19, 1791–1808, https://doi.org/10.5194/gmd-19-1791-2026, https://doi.org/10.5194/gmd-19-1791-2026, 2026
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Accurately simulating rainfall is essential to understand the impacts of climate change, especially extreme events such as floods and droughts. Climate models simulate the atmosphere at a coarse resolution and often misrepresent precipitation, leading to biased and overly smooth fields. We improve the precipitation using a machine learning model that is data-efficient, preserves key climate signals such as trends and variability, and significantly improves the representation of extreme events.
E. Keith Smith, Carl Folke, Niklas Kitzmann, Manjana Milkoreit, Per Olsson, Ricarda Winkelmann, Anne-Sophie Crépin, Christina Eder, Niklas Harring, Jobst Heitzig, Alexia Katsanidou, Timothy M. Lenton, Franz Mauelshagen, Kelton Minor, Ilona M. Otto, Armon Rezai, Jürgen Scheffran, Isabelle Stadelmann-Steffen, Rick van der Ploeg, Nico Wunderling, and Jonathan F. Donges
EGUsphere, https://doi.org/10.5194/egusphere-2026-177, https://doi.org/10.5194/egusphere-2026-177, 2026
This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
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Achieving climate and sustainability goals requires rapid, large-scale change. We introduce criticality – the likelihood a system is near a social tipping point – and critical agency – the capacity to shape those conditions. Our framework shows how coalitions and policies can trigger desired shifts and avoid harmful ones, linking complex systems theory with evidence to guide policymakers and practitioners.
Bethan L. Harris, Christopher M. Taylor, Wouter Dorigo, Ruxandra-Maria Zotta, Darren Ghent, and Iván Noguera
Hydrol. Earth Syst. Sci., 29, 6917–6933, https://doi.org/10.5194/hess-29-6917-2025, https://doi.org/10.5194/hess-29-6917-2025, 2025
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An improved understanding of land-atmosphere coupling processes during flash (rapid-onset) droughts is needed to aid the development of forecasts for these events. We use satellite observations to investigate the surface energy budget during flash droughts globally. The most intense events show a perturbed surface energy budget months before onset. In some regions, vegetation observations 1–2 months before onset provide information on the likelihood of heat extremes during an event.
Clara Hummel, Niklas Boers, and Martin Rypdal
Earth Syst. Dynam., 16, 2035–2062, https://doi.org/10.5194/esd-16-2035-2025, https://doi.org/10.5194/esd-16-2035-2025, 2025
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We revisit early warning signals (EWS) for past abrupt climate changes known as Dansgaard-Oeschger (DO) events. Using advanced statistical methods, we find fewer significant EWS than previously reported. While some signals appear consistent across Greenland ice core records, they are not enough to identify the still unknown mechanisms behind DO events. This study highlights the complexity of predicting climate changes and urges caution in interpreting (paleo-)climate data.
Fenna Blomsma, Mila K.-C. F. Ong, and Timothy M. Lenton
Earth Syst. Dynam., 16, 1865–1886, https://doi.org/10.5194/esd-16-1865-2025, https://doi.org/10.5194/esd-16-1865-2025, 2025
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We investigate the initially successful transition from regional bottle reuse for mineral water to a widespread bottle reuse system in Germany, its subsequent destabilisation, and what this teaches us about tipping dynamics in packaging systems. Our findings demonstrate opportunities to create an enabling environment for change and the role of feedback loops and interventions in accelerating or impeding sustainable transitions.
Antony Philip Emenyu, Thomas Pienkowski, Andrew M. Cunliffe, Timothy M. Lenton, and Tom W. R. Powell
Earth Syst. Dynam., 16, 1699–1710, https://doi.org/10.5194/esd-16-1699-2025, https://doi.org/10.5194/esd-16-1699-2025, 2025
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This paper proposes a new framework combining scaling theory with positive tipping points to explain how regenerative agriculture can scale rapidly. Drawing on the TIST programme (The International Small group and Tree planting programme) in East Africa, it shows that enabling conditions – like affordability, accessibility, and social trust – can trigger feedback loops such as social contagion and network effects. However, outcomes remain highly context-specific, requiring tailored approaches for sustained adoption.
Takahito Mitsui, Peter Ditlevsen, Niklas Boers, and Michel Crucifix
Earth Syst. Dynam., 16, 1569–1584, https://doi.org/10.5194/esd-16-1569-2025, https://doi.org/10.5194/esd-16-1569-2025, 2025
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The late Pleistocene glacial cycles are dominated by a 100-kyr periodicity, rather than other major astronomical periods like 19, 23, 41, or 400 kyr. Various models propose distinct mechanisms to explain this, but their diversity may obscure the key factor behind the 100-kyr periodicity. We propose a timescale-matching hypothesis, suggesting that the ice-sheet climate system responds to astronomical forcing at ∼100 kyr because its intrinsic timescale is closer to 100 kyr than to other periods.
Wolfgang Preimesberger, Pietro Stradiotti, and Wouter Dorigo
Earth Syst. Sci. Data, 17, 4305–4329, https://doi.org/10.5194/essd-17-4305-2025, https://doi.org/10.5194/essd-17-4305-2025, 2025
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We introduce the official ESA CCI Soil Moisture GAPFILLED climate data record. A univariate interpolation algorithm is applied to predict missing data points without relying on ancillary variables. The dataset includes gap-free uncertainty estimates for all predictions and was validated with independent in situ reference measurements. Our data record is recommended for applications which require global long-term gap-free satellite soil moisture data.
Ricarda Winkelmann, Donovan P. Dennis, Jonathan F. Donges, Sina Loriani, Ann Kristin Klose, Jesse F. Abrams, Jorge Alvarez-Solas, Torsten Albrecht, David Armstrong McKay, Sebastian Bathiany, Javier Blasco Navarro, Victor Brovkin, Eleanor Burke, Gokhan Danabasoglu, Reik V. Donner, Markus Drüke, Goran Georgievski, Heiko Goelzer, Anna B. Harper, Gabriele Hegerl, Marina Hirota, Aixue Hu, Laura C. Jackson, Colin Jones, Hyungjun Kim, Torben Koenigk, Peter Lawrence, Timothy M. Lenton, Hannah Liddy, José Licón-Saláiz, Maxence Menthon, Marisa Montoya, Jan Nitzbon, Sophie Nowicki, Bette Otto-Bliesner, Francesco Pausata, Stefan Rahmstorf, Karoline Ramin, Alexander Robinson, Johan Rockström, Anastasia Romanou, Boris Sakschewski, Christina Schädel, Steven Sherwood, Robin S. Smith, Norman J. Steinert, Didier Swingedouw, Matteo Willeit, Wilbert Weijer, Richard Wood, Klaus Wyser, and Shuting Yang
EGUsphere, https://doi.org/10.5194/egusphere-2025-1899, https://doi.org/10.5194/egusphere-2025-1899, 2025
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The Tipping Points Modelling Intercomparison Project (TIPMIP) is an international collaborative effort to systematically assess tipping point risks in the Earth system using state-of-the-art coupled and stand-alone domain models. TIPMIP will provide a first global atlas of potential tipping dynamics, respective critical thresholds and key uncertainties, generating an important building block towards a comprehensive scientific basis for policy- and decision-making.
Jakob Deutloff, Hermann Held, and Timothy M. Lenton
Earth Syst. Dynam., 16, 565–583, https://doi.org/10.5194/esd-16-565-2025, https://doi.org/10.5194/esd-16-565-2025, 2025
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We investigate the probabilities of triggering climate tipping points under various emission scenarios and how they are altered by additional carbon emissions from the tipping of the Amazon and permafrost. We find that there is a high risk for triggering climate tipping points under a scenario comparable to current policies. However, the additional warming and hence the additional risk of triggering other climate tipping points from the tipping of the Amazon and permafrost remain small.
Wolfgang Knorr, Matthew Williams, Tea Thum, Thomas Kaminski, Michael Voßbeck, Marko Scholze, Tristan Quaife, T. Luke Smallman, Susan C. Steele-Dunne, Mariette Vreugdenhil, Tim Green, Sönke Zaehle, Mika Aurela, Alexandre Bouvet, Emanuel Bueechi, Wouter Dorigo, Tarek S. El-Madany, Mirco Migliavacca, Marika Honkanen, Yann H. Kerr, Anna Kontu, Juha Lemmetyinen, Hannakaisa Lindqvist, Arnaud Mialon, Tuuli Miinalainen, Gaétan Pique, Amanda Ojasalo, Shaun Quegan, Peter J. Rayner, Pablo Reyes-Muñoz, Nemesio Rodríguez-Fernández, Mike Schwank, Jochem Verrelst, Songyan Zhu, Dirk Schüttemeyer, and Matthias Drusch
Geosci. Model Dev., 18, 2137–2159, https://doi.org/10.5194/gmd-18-2137-2025, https://doi.org/10.5194/gmd-18-2137-2025, 2025
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When it comes to climate change, the land surface is where the vast majority of impacts happen. The task of monitoring those impacts across the globe is formidable and must necessarily rely on satellites – at a significant cost: the measurements are only indirect and require comprehensive physical understanding. We have created a comprehensive modelling system that we offer to the research community to explore how satellite data can be better exploited to help us capture the changes that happen on our lands.
Chris A. Boulton, Joshua E. Buxton, and Timothy M. Lenton
Earth Syst. Dynam., 16, 411–421, https://doi.org/10.5194/esd-16-411-2025, https://doi.org/10.5194/esd-16-411-2025, 2025
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Early warning signals used to detect tipping points are tested on a dataset of daily views of online electric vehicle (EV) adverts. The attention given to EV adverts spikes upwards after specific events before returning to normality more slowly over time. Alongside increases in autocorrelation and variance, these results are consistent with the movement towards a tipping point to an EV-dominated market, highlighting the ability of these signals to work in previously untested social systems.
Martin Hirschi, Pietro Stradiotti, Bas Crezee, Wouter Dorigo, and Sonia I. Seneviratne
Hydrol. Earth Syst. Sci., 29, 397–425, https://doi.org/10.5194/hess-29-397-2025, https://doi.org/10.5194/hess-29-397-2025, 2025
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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.
Nils Bochow, Anna Poltronieri, and Niklas Boers
The Cryosphere, 18, 5825–5863, https://doi.org/10.5194/tc-18-5825-2024, https://doi.org/10.5194/tc-18-5825-2024, 2024
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Using the latest climate models, we update the understanding of how the Greenland ice sheet responds to climate changes. We found that precipitation and temperature changes in Greenland vary across different regions. Our findings suggest that using uniform estimates for temperature and precipitation for modelling the response of the ice sheet can overestimate ice loss in Greenland. Therefore, this study highlights the need for spatially resolved data in predicting the ice sheet's future.
Mark S. Williamson and Timothy M. Lenton
Earth Syst. Dynam., 15, 1483–1508, https://doi.org/10.5194/esd-15-1483-2024, https://doi.org/10.5194/esd-15-1483-2024, 2024
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Climate models have transitioned to a superrotating atmospheric state under a broad range of warm climates. Such a transition would change global weather patterns should it occur. Here we simulate this transition using an idealized climate model and look for any early warnings of the superrotating state before it happens. We find several early warning indicators that we attribute to an oscillating pattern in the windfield fluctuations.
Ruxandra-Maria Zotta, Leander Moesinger, Robin van der Schalie, Mariette Vreugdenhil, Wolfgang Preimesberger, Thomas Frederikse, Richard de Jeu, and Wouter Dorigo
Earth Syst. Sci. Data, 16, 4573–4617, https://doi.org/10.5194/essd-16-4573-2024, https://doi.org/10.5194/essd-16-4573-2024, 2024
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VODCA v2 is a dataset providing vegetation indicators for long-term ecosystem monitoring. VODCA v2 comprises two products: VODCA CXKu, spanning 34 years of observations (1987–2021), suitable for monitoring upper canopy dynamics, and VODCA L (2010–2021), for above-ground biomass monitoring. VODCA v2 has lower noise levels than the previous product version and provides valuable insights into plant water dynamics and biomass changes, even in areas where optical data are limited.
Vasilis Dakos, Chris A. Boulton, Joshua E. Buxton, Jesse F. Abrams, Beatriz Arellano-Nava, David I. Armstrong McKay, Sebastian Bathiany, Lana Blaschke, Niklas Boers, Daniel Dylewsky, Carlos López-Martínez, Isobel Parry, Paul Ritchie, Bregje van der Bolt, Larissa van der Laan, Els Weinans, and Sonia Kéfi
Earth Syst. Dynam., 15, 1117–1135, https://doi.org/10.5194/esd-15-1117-2024, https://doi.org/10.5194/esd-15-1117-2024, 2024
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Tipping points are abrupt, rapid, and sometimes irreversible changes, and numerous approaches have been proposed to detect them in advance. Such approaches have been termed early warning signals and represent a set of methods for identifying changes in the underlying behaviour of a system across time or space that might indicate an approaching tipping point. Here, we review the literature to explore where, how, and which early warnings have been used in real-world case studies so far.
Sibel Eker, Timothy M. Lenton, Tom Powell, Jürgen Scheffran, Steven R. Smith, Deepthi Swamy, and Caroline Zimm
Earth Syst. Dynam., 15, 789–800, https://doi.org/10.5194/esd-15-789-2024, https://doi.org/10.5194/esd-15-789-2024, 2024
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Cascading effects through cross-system interactions are one of the biggest promises of positive tipping points to create rapid climate and sustainability action. Here, we review these in terms of their interactions with sociotechnical systems such as energy, transport, agriculture, society, and policy.
Maya Ben-Yami, Lana Blaschke, Sebastian Bathiany, and Niklas Boers
EGUsphere, https://doi.org/10.5194/egusphere-2024-1106, https://doi.org/10.5194/egusphere-2024-1106, 2024
Preprint archived
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Recent work has used observations to find statistical signs that the Atlantic Meridional Overturning Circulation (AMOC) may be approaching a collapse. We find that in complex climate models in which the AMOC does not collapse before 2100, the statistical signs that are present in the observations are not found in the 1850–2014 equivalent model time series. This indicates that the observed statistical signs are not prone to false positives.
Takahito Mitsui and Niklas Boers
Clim. Past, 20, 683–699, https://doi.org/10.5194/cp-20-683-2024, https://doi.org/10.5194/cp-20-683-2024, 2024
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In general, the variance and short-lag autocorrelations of the fluctuations increase in a system approaching a critical transition. Using these indicators, we identify statistical precursor signals for the Dansgaard–Oeschger cooling events recorded in two climatic proxies of three Greenland ice core records. We then provide a dynamical systems theory that bridges the gap between observing statistical precursor signals and the physical precursor signs empirically known in paleoclimate research.
Takahito Mitsui, Matteo Willeit, and Niklas Boers
Earth Syst. Dynam., 14, 1277–1294, https://doi.org/10.5194/esd-14-1277-2023, https://doi.org/10.5194/esd-14-1277-2023, 2023
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The glacial–interglacial cycles of the Quaternary exhibit 41 kyr periodicity before the Mid-Pleistocene Transition (MPT) around 1.2–0.8 Myr ago and ~100 kyr periodicity after that. The mechanism generating these periodicities remains elusive. Through an analysis of an Earth system model of intermediate complexity, CLIMBER-2, we show that the dominant periodicities of glacial cycles can be explained from the viewpoint of synchronization theory.
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.
Stephen P. Hesselbo, Aisha Al-Suwaidi, Sarah J. Baker, Giorgia Ballabio, Claire M. Belcher, Andrew Bond, Ian Boomer, Remco Bos, Christian J. Bjerrum, Kara Bogus, Richard Boyle, James V. Browning, Alan R. Butcher, Daniel J. Condon, Philip Copestake, Stuart Daines, Christopher Dalby, Magret Damaschke, Susana E. Damborenea, Jean-Francois Deconinck, Alexander J. Dickson, Isabel M. Fendley, Calum P. Fox, Angela Fraguas, Joost Frieling, Thomas A. Gibson, Tianchen He, Kat Hickey, Linda A. Hinnov, Teuntje P. Hollaar, Chunju Huang, Alexander J. L. Hudson, Hugh C. Jenkyns, Erdem Idiz, Mengjie Jiang, Wout Krijgsman, Christoph Korte, Melanie J. Leng, Timothy M. Lenton, Katharina Leu, Crispin T. S. Little, Conall MacNiocaill, Miguel O. Manceñido, Tamsin A. Mather, Emanuela Mattioli, Kenneth G. Miller, Robert J. Newton, Kevin N. Page, József Pálfy, Gregory Pieńkowski, Richard J. Porter, Simon W. Poulton, Alberto C. Riccardi, James B. Riding, Ailsa Roper, Micha Ruhl, Ricardo L. Silva, Marisa S. Storm, Guillaume Suan, Dominika Szűcs, Nicolas Thibault, Alfred Uchman, James N. Stanley, Clemens V. Ullmann, Bas van de Schootbrugge, Madeleine L. Vickers, Sonja Wadas, Jessica H. Whiteside, Paul B. Wignall, Thomas Wonik, Weimu Xu, Christian Zeeden, and Ke Zhao
Sci. Dril., 32, 1–25, https://doi.org/10.5194/sd-32-1-2023, https://doi.org/10.5194/sd-32-1-2023, 2023
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We present initial results from a 650 m long core of Late Triasssic to Early Jurassic (190–202 Myr) sedimentary strata from the Cheshire Basin, UK, which is shown to be an exceptional record of Earth evolution for the time of break-up of the supercontinent Pangaea. Further work will determine periodic changes in depositional environments caused by solar system dynamics and used to reconstruct orbital history.
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.
Sara M. Vallejo-Bernal, Frederik Wolf, Niklas Boers, Dominik Traxl, Norbert Marwan, and Jürgen Kurths
Hydrol. Earth Syst. Sci., 27, 2645–2660, https://doi.org/10.5194/hess-27-2645-2023, https://doi.org/10.5194/hess-27-2645-2023, 2023
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Employing event synchronization and complex networks analysis, we reveal a cascade of heavy rainfall events, related to intense atmospheric rivers (ARs): heavy precipitation events (HPEs) in western North America (NA) that occur in the aftermath of land-falling ARs are synchronized with HPEs in central and eastern Canada with a delay of up to 12 d. Understanding the effects of ARs in the rainfall over NA will lead to better anticipating the evolution of the climate dynamics in the region.
Maximilian Gelbrecht, Alistair White, Sebastian Bathiany, and Niklas Boers
Geosci. Model Dev., 16, 3123–3135, https://doi.org/10.5194/gmd-16-3123-2023, https://doi.org/10.5194/gmd-16-3123-2023, 2023
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Differential programming is a technique that enables the automatic computation of derivatives of the output of models with respect to model parameters. Applying these techniques to Earth system modeling leverages the increasing availability of high-quality data to improve the models themselves. This can be done by either using calibration techniques that use gradient-based optimization or incorporating machine learning methods that can learn previously unresolved influences directly from data.
Keno Riechers, Leonardo Rydin Gorjão, Forough Hassanibesheli, Pedro G. Lind, Dirk Witthaut, and Niklas Boers
Earth Syst. Dynam., 14, 593–607, https://doi.org/10.5194/esd-14-593-2023, https://doi.org/10.5194/esd-14-593-2023, 2023
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Paleoclimate proxy records show that the North Atlantic climate repeatedly transitioned between two regimes during the last glacial interval. This study investigates a bivariate proxy record from a Greenland ice core which reflects past Greenland temperatures and large-scale atmospheric conditions. We reconstruct the underlying deterministic drift by estimating first-order Kramers–Moyal coefficients and identify two separate stable states in agreement with the aforementioned climatic regimes.
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.
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.
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.
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.
Eirik Myrvoll-Nilsen, Keno Riechers, Martin Wibe Rypdal, and Niklas Boers
Clim. Past, 18, 1275–1294, https://doi.org/10.5194/cp-18-1275-2022, https://doi.org/10.5194/cp-18-1275-2022, 2022
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In layer counted proxy records each measurement is accompanied by a timestamp typically measured by counting periodic layers. Knowledge of the uncertainty of this timestamp is important for a rigorous propagation to further analyses. By assuming a Bayesian regression model to the layer increments we express the dating uncertainty by the posterior distribution, from which chronologies can be sampled efficiently. We apply our framework to dating abrupt warming transitions during the last glacial.
Keno Riechers, Takahito Mitsui, Niklas Boers, and Michael Ghil
Clim. Past, 18, 863–893, https://doi.org/10.5194/cp-18-863-2022, https://doi.org/10.5194/cp-18-863-2022, 2022
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Building upon Milancovic's theory of orbital forcing, this paper reviews the interplay between intrinsic variability and external forcing in the emergence of glacial interglacial cycles. It provides the reader with historical background information and with basic theoretical concepts used in recent paleoclimate research. Moreover, it presents new results which confirm the reduced stability of glacial-cycle dynamics after the mid-Pleistocene transition.
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.
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.
Thomas S. Ball, Naomi E. Vaughan, Thomas W. Powell, Andrew Lovett, and Timothy M. Lenton
Geosci. Model Dev., 15, 929–949, https://doi.org/10.5194/gmd-15-929-2022, https://doi.org/10.5194/gmd-15-929-2022, 2022
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C-LLAMA is a simple model of the global food system operating at a country level from 2013 to 2050. The model begins with projections of diet composition and populations for each country, producing a demand for each food commodity and finally an agricultural land use in each country. The model can be used to explore the sensitivity of agricultural land use to various drivers within the food system at country, regional, and continental spatial aggregations.
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Short summary
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.
Multi-instrument records with varying signal-to-noise ratios are becoming increasingly common as...
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