Articles | Volume 12, issue 1
https://doi.org/10.5194/ascmo-12-1-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/ascmo-12-1-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
05 Jan 2026
| 05 Jan 2026
Bayesian hierarchical modelling of intensity-duration-frequency curves using a climate model large ensemble
Alexander Lee Rischmuller
CORRESPONDING AUTHOR
Research Unit Sustainability and Climate Risk, Center for Earth System Research and Sustainability (CEN), Universität Hamburg, 20144 Hamburg, Germany
Benjamin Poschlod
Research Unit Sustainability and Climate Risk, Center for Earth System Research and Sustainability (CEN), Universität Hamburg, 20144 Hamburg, Germany
Jana Sillmann
Research Unit Sustainability and Climate Risk, Center for Earth System Research and Sustainability (CEN), Universität Hamburg, 20144 Hamburg, Germany
Center for International Climate Research (CICERO), 0349 Oslo, Norway
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Philip J. Ward, Sophie L. Buijs, Roxana Ciurean, Judith N. Claassen, James Daniell, Kelley De Polt, Melanie Duncan, Stefania Gottardo, Stefan Hochrainer-Stigler, Robert Šakić Trogrlić, Julius Schlumberger, Timothy Tiggeloven, Silvia Torresan, Nicole van Maanen, Andrew Warren, Carmen D. Álvarez-Albelo, Vanessa Banks, Benjamin Blanz, Veronica Casartelli, Jordan Correa, Julia Crummy, Anne Sophie Daloz, Marleen C. de Ruiter, Juan José Díaz-Hernández, Jaime Díaz-Pacheco, Pedro Dorta Antequera, Davide Ferrario, David Geurts, Sara García-González, Joel C. Gill, Raúl Hernández-Martín, Wiebke S. Jäger, Abel López-Díez, Lin Ma, Jaroslav Mysiak, Diep Ngoc Nguyen, Noemi Padrón Fumero, Eva-Cristina Petrescu, Karina Reiter, Jana Sillmann, Lara Smale, and Tristian Stolte
Nat. Hazards Earth Syst. Sci., 26, 1325–1345, https://doi.org/10.5194/nhess-26-1325-2026, https://doi.org/10.5194/nhess-26-1325-2026, 2026
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Disasters often result from interactions between different hazards, like floods triggering landslides, or earthquakes followed by tropical cyclones, so-called multi-hazards. People and societies are increasingly exposed and vulnerable to these multi-hazards. Assessing these aspects is referred to as multi-risk assessment and management. In this paper we synthesise key learnings from the MYRIAD-EU (Multi-hazard and sYstemic framework for enhancing Risk-Informed mAnagement and Decision-making in the E.U.) project, reflecting on progress and challenges faced in addressing multi-hazards and multi-risk.
Benjamin Poschlod, Laura Sailer, Alexander Sasse, Anastasia Vogelbacher, and Ralf Ludwig
Hydrol. Earth Syst. Sci., 30, 1165–1188, https://doi.org/10.5194/hess-30-1165-2026, https://doi.org/10.5194/hess-30-1165-2026, 2026
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Europe was hit by severe droughts in recent years resulting in extreme low flow conditions in rivers. Here, we investigate future climate change effects on river droughts in Bavaria. We find increasing severity for the low peak discharge and low flow duration in a warmer climate. This is caused by hotter and drier summers, where the joint occurrence of heat and drought intensifies. Further, we show that conditions in the year before the drought gain more importance in a warmer climate.
Maša Ann, Jörn Behrens, and Jana Sillmann
Nonlin. Processes Geophys., 33, 85–102, https://doi.org/10.5194/npg-33-85-2026, https://doi.org/10.5194/npg-33-85-2026, 2026
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We present a new framework based on Dynamic Mode Decomposition (DMD) to better detect outliers and model extremes. Unlike standard DMD, which focuses on average system behaviour, our approach targets rare, exceptional dynamics. Applied to climate data, it improves extreme event approximation and reveals meaningful spatiotemporal patterns. The method may generalise to other types of extremes.
Nina Schuhen, Carley E. Iles, Marit Sandstad, Viktor Ananiev, and Jana Sillmann
Nat. Hazards Earth Syst. Sci., 26, 753–773, https://doi.org/10.5194/nhess-26-753-2026, https://doi.org/10.5194/nhess-26-753-2026, 2026
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As climate changes, extremes are becoming increasingly frequent. We investigate the time of emergence for a large range of different extremes, meaning the earliest time when a significant change in these extremes can be detected beyond natural variability, whether in the past or in the future. The results are based on 21 global climate models and show considerable differences between regions, types of indices and emissions scenarios, as well as between temperature and precipitation extremes.
Anastasia Vogelbacher, Malte von Szombathely, Marc Lennartz, Benjamin Poschlod, and Jana Sillmann
EGUsphere, https://doi.org/10.5194/egusphere-2025-6362, https://doi.org/10.5194/egusphere-2025-6362, 2026
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In this study we address risk to pluvial floods by following the risk definition of the Intergovernmental Panel on Climate Change (IPCC), developed in co-operation with stakeholders. We identify buildings in urban areas where residents face higher flood risk due to greater social vulnerability, increased exposure, or elevated flood hazard. We present the development and application of a Python-based ArcGIS toolbox for estimating pluvial flood risk at building scale.
Marc Lennartz, Benjamin Poschlod, and Bruno Merz
EGUsphere, https://doi.org/10.5194/egusphere-2025-6419, https://doi.org/10.5194/egusphere-2025-6419, 2026
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Predicting hourly rainfall extremes under climate change is crucial yet highly uncertain. Using convection-permitting climate model data over Germany, we compare stationary and non-stationary GEV and sMEV methods. Results show that the sMEV approach exhibits lower uncertainty across return periods. Moreover, the non-stationary sMEV better captures climate-change-induced changes, though care is needed when projecting future extremes.
Iris Mužić, Øivind Hodnebrog, Yeliz A. Yilmaz, Terje K. Berntsen, Jana Sillmann, David M. Lawrence, and Paul A. Dirmeyer
Adv. Stat. Clim. Meteorol. Oceanogr., 11, 273–292, https://doi.org/10.5194/ascmo-11-273-2025, https://doi.org/10.5194/ascmo-11-273-2025, 2025
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This study investigates soil moisture–temperature coupling during the extreme warm conditions in May–August 2018 in southern and central Sweden using the merged GLEAM-E-OBS dataset and four simulations from the Weather Research and Forecasting model coupled with the Community Terrestrial Systems Model (WRF-CTSM). Based on changes in surface soil moisture, evaporative fraction, and daily maximum 2 m temperature, on average across the region and five datasets, the coupling lasted for 22 d.
Kai Kornuber, Emanuele Bevacqua, Mariana Madruga de Brito, Wiebke S. Jäger, Pauline Rivoire, Cassandra D. W. Rogers, Fabiola Banfi, Fulden Batibeniz, James Carruthers, Carlo de Michele, Silvia de Angeli, Cristina Deidda, Marleen C. de Ruiter, Andreas H. Fink, Henrique M. D. Goulart, Katharina Küpfer, Patrick Ludwig, Douglas Maraun, Gabriele Messori, Shruti Nath, Fiachra O’Loughlin, Joaquim G. Pinto, Benjamin Poschlod, Alexandre M. Ramos, Colin Raymond, Andreia F. S. Ribeiro, Deepti Singh, Laura Suarez Gutierrez, Philip J. Ward, and Christopher J. White
EGUsphere, https://doi.org/10.5194/egusphere-2025-4683, https://doi.org/10.5194/egusphere-2025-4683, 2025
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Impacts from extreme weather events are becoming increasingly severe under global warming, in particular when events occur simultaneously or successively. While these complex event combinations are often difficult to analyse as impact data, early warning schemes or modelling frameworks might not be fit for purpose. In this perspective we reflect on the usability of compound event research to bridge the gap between academic research and real-world applications, by formulating a set of guidelines.
Natalia Castillo Bautista, Marco Gaetani, Leonard F. Borchert, Benjamin Poschlod, Lukas Brunner, Jana Sillmann, and Mario L. V. Martina
EGUsphere, https://doi.org/10.5194/egusphere-2025-5073, https://doi.org/10.5194/egusphere-2025-5073, 2025
This preprint is open for discussion and under review for Weather and Climate Dynamics (WCD).
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When hot temperatures and drought occur together (compound events), they can cause harmful impacts on crops and society. Using six decades of climate data, we show that such compound events repeatedly occurred in three breadbaskets of the Northern Hemisphere. These events are linked to atmospheric circulation patterns that favor heat and dryness, which in turn interact to amplify the impact. Our study contributes to understand the drivers of these events to support climate impact assessment.
Timothy Tiggeloven, Colin Raymond, Marleen C. de Ruiter, Jana Sillmann, Annegret H. Thieken, Sophie L. Buijs, Roxana Ciurean, Emma Cordier, Julia M. Crummy, Lydia Cumiskey, Kelley De Polt, Melanie Duncan, Davide M. Ferrario, Wiebke S. Jäger, Elco E. Koks, Nicole van Maanen, Heather J. Murdock, Jaroslav Mysiak, Sadhana Nirandjan, Benjamin Poschlod, Peter Priesmeier, Nivedita Sairam, Pia-Johanna Schweizer, Tristian R. Stolte, Marie-Luise Zenker, James E. Daniell, Alexander Fekete, Christian M. Geiß, Marc J. C. van den Homberg, Sirkku K. Juhola, Christian Kuhlicke, Karen Lebek, Robert Šakić Trogrlić, Stefan Schneiderbauer, Silvia Torresan, Cees J. van Westen, Judith N. Claassen, Bijan Khazai, Virginia Murray, Julius Schlumberger, and Philip J. Ward
EGUsphere, https://doi.org/10.5194/egusphere-2025-2771, https://doi.org/10.5194/egusphere-2025-2771, 2025
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Natural hazards like floods, earthquakes, and landslides are often interconnected which may create bigger problems than when they occur alone. We studied expert discussions from an international conference to understand how scientists and policymakers can better prepare for these multi-hazards and use new technologies to protect its communities while contributing to dialogues about future international agreements beyond the Sendai Framework and supporting global sustainability goals.
Florian Zabel, Matthias Knüttel, and Benjamin Poschlod
Geosci. Model Dev., 18, 1067–1087, https://doi.org/10.5194/gmd-18-1067-2025, https://doi.org/10.5194/gmd-18-1067-2025, 2025
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CropSuite is a new open-source crop suitability model. It provides a GUI and a wide range of options, including a spatial downscaling of climate data. We apply CropSuite to 48 staple and opportunity crops at a 1 km spatial resolution in Africa. We find that climate variability significantly impacts suitable areas but also affects optimal sowing dates and multiple cropping potential. The results provide valuable information for climate impact assessments, adaptation, and land-use planning.
Detlef van Vuuren, Brian O'Neill, Claudia Tebaldi, Louise Chini, Pierre Friedlingstein, Tomoko Hasegawa, Keywan Riahi, Benjamin Sanderson, Bala Govindasamy, Nico Bauer, Veronika Eyring, Cheikh Fall, Katja Frieler, Matthew Gidden, Laila Gohar, Andrew Jones, Andrew King, Reto Knutti, Elmar Kriegler, Peter Lawrence, Chris Lennard, Jason Lowe, Camila Mathison, Shahbaz Mehmood, Luciana Prado, Qiang Zhang, Steven Rose, Alexander Ruane, Carl-Friederich Schleussner, Roland Seferian, Jana Sillmann, Chris Smith, Anna Sörensson, Swapna Panickal, Kaoru Tachiiri, Naomi Vaughan, Saritha Vishwanathan, Tokuta Yokohata, and Tilo Ziehn
EGUsphere, https://doi.org/10.5194/egusphere-2024-3765, https://doi.org/10.5194/egusphere-2024-3765, 2025
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We propose a set of six plausible 21st century emission scenarios, and their multi-century extensions, that will be used by the international community of climate modeling centers to produce the next generation of climate projections. These projections will support climate, impact and mitigation researchers, provide information to practitioners to address future risks from climate change, and contribute to policymakers’ considerations of the trade-offs among various levels of mitigation.
Viktoria Spaiser, Sirkku Juhola, Sara M. Constantino, Weisi Guo, Tabitha Watson, Jana Sillmann, Alessandro Craparo, Ashleigh Basel, John T. Bruun, Krishna Krishnamurthy, Jürgen Scheffran, Patricia Pinho, Uche T. Okpara, Jonathan F. Donges, Avit Bhowmik, Taha Yasseri, Ricardo Safra de Campos, Graeme S. Cumming, Hugues Chenet, Florian Krampe, Jesse F. Abrams, James G. Dyke, Stefanie Rynders, Yevgeny Aksenov, and Bryan M. Spears
Earth Syst. Dynam., 15, 1179–1206, https://doi.org/10.5194/esd-15-1179-2024, https://doi.org/10.5194/esd-15-1179-2024, 2024
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In this paper, we identify potential negative social tipping points linked to Earth system destabilization and draw on related research to understand the drivers and likelihood of these negative social tipping dynamics, their potential effects on human societies and the Earth system, and the potential for cascading interactions and contribution to systemic risks.
Benjamin Poschlod and Anne Sophie Daloz
The Cryosphere, 18, 1959–1981, https://doi.org/10.5194/tc-18-1959-2024, https://doi.org/10.5194/tc-18-1959-2024, 2024
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Information about snow depth is important within climate research but also many other sectors, such as tourism, mobility, civil engineering, and ecology. Climate models often feature a spatial resolution which is too coarse to investigate snow depth. Here, we analyse high-resolution simulations and identify added value compared to a coarser-resolution state-of-the-art product. Also, daily snow depth extremes are well reproduced by two models.
Clemens Schwingshackl, Anne Sophie Daloz, Carley Iles, Kristin Aunan, and Jana Sillmann
Nat. Hazards Earth Syst. Sci., 24, 331–354, https://doi.org/10.5194/nhess-24-331-2024, https://doi.org/10.5194/nhess-24-331-2024, 2024
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Ambient heat in European cities will substantially increase under global warming, as projected by three heat metrics calculated from high-resolution climate model simulations. While the heat metrics consistently project high levels of ambient heat for several cities, in other cities the projected heat levels vary considerably across the three heat metrics. Using complementary heat metrics for projections of ambient heat is thus important for assessments of future risks from heat stress.
Florian Zabel and Benjamin Poschlod
Geosci. Model Dev., 16, 5383–5399, https://doi.org/10.5194/gmd-16-5383-2023, https://doi.org/10.5194/gmd-16-5383-2023, 2023
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Today, most climate model data are provided at daily time steps. However, more and more models from different sectors, such as energy, water, agriculture, and health, require climate information at a sub-daily temporal resolution for a more robust and reliable climate impact assessment. Here we describe and validate the Teddy tool, a new model for the temporal disaggregation of daily climate model data for climate impact analysis.
Philip J. Ward, James Daniell, Melanie Duncan, Anna Dunne, Cédric Hananel, Stefan Hochrainer-Stigler, Annegien Tijssen, Silvia Torresan, Roxana Ciurean, Joel C. Gill, Jana Sillmann, Anaïs Couasnon, Elco Koks, Noemi Padrón-Fumero, Sharon Tatman, Marianne Tronstad Lund, Adewole Adesiyun, Jeroen C. J. H. Aerts, Alexander Alabaster, Bernard Bulder, Carlos Campillo Torres, Andrea Critto, Raúl Hernández-Martín, Marta Machado, Jaroslav Mysiak, Rene Orth, Irene Palomino Antolín, Eva-Cristina Petrescu, Markus Reichstein, Timothy Tiggeloven, Anne F. Van Loon, Hung Vuong Pham, and Marleen C. de Ruiter
Nat. Hazards Earth Syst. Sci., 22, 1487–1497, https://doi.org/10.5194/nhess-22-1487-2022, https://doi.org/10.5194/nhess-22-1487-2022, 2022
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The majority of natural-hazard risk research focuses on single hazards (a flood, a drought, a volcanic eruption, an earthquake, etc.). In the international research and policy community it is recognised that risk management could benefit from a more systemic approach. In this perspective paper, we argue for an approach that addresses multi-hazard, multi-risk management through the lens of sustainability challenges that cut across sectors, regions, and hazards.
Katja Weigel, Lisa Bock, Bettina K. Gier, Axel Lauer, Mattia Righi, Manuel Schlund, Kemisola Adeniyi, Bouwe Andela, Enrico Arnone, Peter Berg, Louis-Philippe Caron, Irene Cionni, Susanna Corti, Niels Drost, Alasdair Hunter, Llorenç Lledó, Christian Wilhelm Mohr, Aytaç Paçal, Núria Pérez-Zanón, Valeriu Predoi, Marit Sandstad, Jana Sillmann, Andreas Sterl, Javier Vegas-Regidor, Jost von Hardenberg, and Veronika Eyring
Geosci. Model Dev., 14, 3159–3184, https://doi.org/10.5194/gmd-14-3159-2021, https://doi.org/10.5194/gmd-14-3159-2021, 2021
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This work presents new diagnostics for the Earth System Model Evaluation Tool (ESMValTool) v2.0 on the hydrological cycle, extreme events, impact assessment, regional evaluations, and ensemble member selection. The ESMValTool v2.0 diagnostics are developed by a large community of scientists aiming to facilitate the evaluation and comparison of Earth system models (ESMs) with a focus on the ESMs participating in the Coupled Model Intercomparison Project (CMIP).
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Short summary
Extreme precipitation probability estimation is vital for hazard protection design but has high uncertainty. We tested six statistical models using 2000 years of climate data. Our Bayesian hierarchical duration-dependent Generalized Extreme Value model shows the highest accuracy and robustness for sample sizes between 30 and 100 years, making it highly promising for use with limited observational records.
Extreme precipitation probability estimation is vital for hazard protection design but has high...
