Articles | Volume 26, issue 5
https://doi.org/10.5194/nhess-26-2031-2026
© 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/nhess-26-2031-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
08 May 2026
Research article |
| 08 May 2026
| 08 May 2026
Non-stationary dynamics of compound climate extremes: a WRF-CMIP6-GAMLSS framework for southeastern China
Yinchi Zhang
Key Laboratory for Humid Subtropical Eco-geographical Processes of the Ministry of Education, Fujian Normal University, Fuzhou, 350117, China
Institute of Geography, Fujian Normal University, Fuzhou, 350117, China
School of Geographical Science, Fujian Normal University, Fuzhou, 350117, China
Department of Geography and School of Global Studies, University of Sussex, Falmer, Brighton BN1 9RH, UK
Wanling Xu
School of Ocean and Earth Science, Tongji University, Shanghai, 200092, China
Chao Deng
Sichuan Academy of Forestry Sciences, Chengdu, 610081, China
State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing, 100081, China
Miaomiao Ma
China Institute of Water Resources and Hydropower Research, Beijing, 100038, China
Jianhui Wei
Institute of Meteorology and Climate Research (IMKIFU), Karlsruhe Institute of Technology, Campus Alpin, Garmisch-Partenkirchen, Germany
Ying Chen
Key Laboratory for Humid Subtropical Eco-geographical Processes of the Ministry of Education, Fujian Normal University, Fuzhou, 350117, China
Institute of Geography, Fujian Normal University, Fuzhou, 350117, China
School of Geographical Science, Fujian Normal University, Fuzhou, 350117, China
Fujian Provincial Engineering Research Center for Monitoring and Accessing Terrestrial Disasters, Fujian Normal University, Fuzhou, 350117, China
Department of Geography and School of Global Studies, University of Sussex, Falmer, Brighton BN1 9RH, UK
Key Laboratory for Humid Subtropical Eco-geographical Processes of the Ministry of Education, Fujian Normal University, Fuzhou, 350117, China
Institute of Geography, Fujian Normal University, Fuzhou, 350117, China
School of Geographical Science, Fujian Normal University, Fuzhou, 350117, China
Fujian Provincial Engineering Research Center for Monitoring and Accessing Terrestrial Disasters, Fujian Normal University, Fuzhou, 350117, China
Harald Kunstmann
Institute of Meteorology and Climate Research (IMKIFU), Karlsruhe Institute of Technology, Campus Alpin, Garmisch-Partenkirchen, Germany
Institute of Geography, University of Augsburg, Augsburg, 86159, Germany
Centre for Climate Resilience, University of Augsburg, Augsburg, 86159, Germany
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Jan Niklas Weber, Christof Lorenz, Tanja C. Schober, Rebecca Wiegels, and Harald Kunstmann
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2026-166, https://doi.org/10.5194/essd-2026-166, 2026
Preprint under review for ESSD
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Seasonal forecasts can support drought preparedness but are often limited by systematic biases. We present SEAS5-BCSD, a global bias-corrected and downscaled seasonal forecast reference dataset integrating ECMWF’s SEAS5 output with observational data. The dataset provides forecasts for all ensemble members over global land areas at 0.25° resolution from 1981 onward. It enables improved seasonal drought and climate impact applications and is openly available via the World Data Center for Climate.
Yining Zang, Pauline C. Treble, Kei Yoshimura, Jayson Gabriel Pinza, Fengbo Zhang, Kübra Özdemir Çallı, Xiaojun Mei, Admin Husic, Alena Gessert, Andrej Stroj, Bartolomé Andreo, Bernard Ladouche, Christine Stumpp, Diana Mance, Eleni Zagana, Fen Huang, Giuseppe Sappa, Harald Kunstmann, Heike Brielmann, Hong Zhou, Huaying Wu, Jakob Garvelmann, James Berglund, Jean-Baptiste Charlier, Jens Lange, Juan Antonio Barberá Fornell, Junbing Pu, Konstantina Katsanou, Kun Ren, Laura Toran, Laurence Gill, Maria Filippini, Martin Kralik, Matías Mudarra Martínez, Min Zhao, Mingming Luo, Nico Goldscheider, Nikolaos Lambrakis, Pantaleone De Vita, Qiong Xiao, Shi Yu, Silvia Iacurto, Silvio Coda, Ted McCormack, Vincenzo Allocca, W. George Darling, Walter D’Alessandro, Xulei Guo, Yundi Hu, Zhijun Wang, Eva Kaminsky, Jiří Faimon, Marek Lang, Pavel Pracný, and Andreas Hartmann
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-812, https://doi.org/10.5194/essd-2025-812, 2026
Preprint under review for ESSD
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We developed the first global database of water from karst springs and cave drips that records different forms of oxygen and hydrogen, which naturally trace how rainwater moves through rocks. By gathering and checking thousands of measurements from around the globe and linking them with flow and rainfall data, the database provides a comprehensive view of water movement, allows scientists to compare regions, understand groundwater processes, and support sustainable water management worldwide.
Ling Zhang, Lu Li, Zhongshi Zhang, Joël Arnault, Stefan Sobolowski, Xiaoling Chen, Jianzhong Lu, Anthony Musili Mwanthi, Pratik Kad, Mohammed Abdullahi Hassan, Tanja Portele, Harald Kunstmann, and Zhengkang Zuo
Hydrol. Earth Syst. Sci., 29, 4109–4132, https://doi.org/10.5194/hess-29-4109-2025, https://doi.org/10.5194/hess-29-4109-2025, 2025
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To address challenges related to unreliable hydrological simulations, we present an enhanced hydrological simulation with a refined climate model and a more comprehensive hydrological model. The model with the two parts outperforms that without, especially in migrating bias in peak flow and dry-season flow. Our findings highlight the enhanced hydrological simulation capability, with the refined climate and lake module contributing 24 % and 76 % improvement, respectively.
Ningpeng Dong, Haoran Hao, Mingxiang Yang, Jianhui Wei, Shiqin Xu, and Harald Kunstmann
Hydrol. Earth Syst. Sci., 29, 2023–2042, https://doi.org/10.5194/hess-29-2023-2025, https://doi.org/10.5194/hess-29-2023-2025, 2025
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Hydrometeorological forecasting is crucial for managing water resources and mitigating extreme weather events, yet current long-term forecast products are often embedded with uncertainties. We develop a deep-learning-based modelling framework to improve 30 d rainfall and streamflow forecasts by combining advanced neural networks and physical models. With the flow forecast error reduced by up to 33 %, the framework has the potential to enhance water management and disaster prevention.
Maximilian Graf, Andreas Wagner, Julius Polz, Llorenç Lliso, José Alberto Lahuerta, Harald Kunstmann, and Christian Chwala
Atmos. Meas. Tech., 17, 2165–2182, https://doi.org/10.5194/amt-17-2165-2024, https://doi.org/10.5194/amt-17-2165-2024, 2024
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Commercial microwave links (CMLs) can be used for rainfall retrieval. The detection of rainy periods in their attenuation time series is a crucial processing step. We investigate the usage of rainfall data from MSG SEVIRI for this task, compare this approach with existing methods, and introduce a novel combined approach. The results show certain advantages for SEVIRI-based methods, particularly for CMLs where existing methods perform poorly. Our novel combination yields the best performance.
Patrick Olschewski, Qi Sun, Jianhui Wei, Yu Li, Zhan Tian, Laixiang Sun, Joël Arnault, Tanja C. Schober, Brian Böker, Harald Kunstmann, and Patrick Laux
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-95, https://doi.org/10.5194/hess-2024-95, 2024
Revised manuscript not accepted
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There are indications that typhoon intensities may increase under global warming. However, further research on these projections and their uncertainties is necessary. We study changes in typhoon intensity under SSP5-8.5 for seven events affecting the Pearl River Delta using Pseudo-Global Warming and a storyline approach based on 16 CMIP6 models. Results show intensified wind speed, sea level pressure drop and precipitation levels for six events with amplified increases for individual storylines.
Patrick Olschewski, Mame Diarra Bousso Dieng, Hassane Moutahir, Brian Böker, Edwin Haas, Harald Kunstmann, and Patrick Laux
Nat. Hazards Earth Syst. Sci., 24, 1099–1134, https://doi.org/10.5194/nhess-24-1099-2024, https://doi.org/10.5194/nhess-24-1099-2024, 2024
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We applied a multivariate and dependency-preserving bias correction method to climate model output for the Greater Mediterranean Region and investigated potential changes in false-spring events (FSEs) and heat–drought compound events (HDCEs). Results project an increase in the frequency of FSEs in middle and late spring as well as increases in frequency, intensity, and duration for HDCEs. This will potentially aggravate the risk of crop loss and failure and negatively impact food security.
Qi Sun, Patrick Olschewski, Jianhui Wei, Zhan Tian, Laixiang Sun, Harald Kunstmann, and Patrick Laux
Hydrol. Earth Syst. Sci., 28, 761–780, https://doi.org/10.5194/hess-28-761-2024, https://doi.org/10.5194/hess-28-761-2024, 2024
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Tropical cyclones (TCs) often cause high economic loss due to heavy winds and rainfall, particularly in densely populated regions such as the Pearl River Delta (China). This study provides a reference to set up regional climate models for TC simulations. They contribute to a better TC process understanding and assess the potential changes and risks of TCs in the future. This lays the foundation for hydrodynamical modelling, from which the cities' disaster management and defence could benefit.
Dragan Petrovic, Benjamin Fersch, and Harald Kunstmann
Nat. Hazards Earth Syst. Sci., 24, 265–289, https://doi.org/10.5194/nhess-24-265-2024, https://doi.org/10.5194/nhess-24-265-2024, 2024
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The influence of model resolution and settings on the reproduction of heat waves in Germany between 1980–2009 is analyzed. Outputs from a high-resolution model with settings tailored to the target region are compared to those from coarser-resolution models with more general settings. Neither the increased resolution nor the tailored model settings are found to add significant value to the heat wave simulation. The models exhibit a large spread, indicating that the choice of model can be crucial.
Mohsen Soltani, Bert Hamelers, Abbas Mofidi, Christopher G. Fletcher, Arie Staal, Stefan C. Dekker, Patrick Laux, Joel Arnault, Harald Kunstmann, Ties van der Hoeven, and Maarten Lanters
Earth Syst. Dynam., 14, 931–953, https://doi.org/10.5194/esd-14-931-2023, https://doi.org/10.5194/esd-14-931-2023, 2023
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The temporal changes and spatial patterns in precipitation events do not show a homogeneous tendency across the Sinai Peninsula. Mediterranean cyclones accompanied by the Red Sea and Persian troughs are responsible for the majority of Sinai's extreme rainfall events. Cyclone tracking captures 156 cyclones (rainfall ≥10 mm d-1) either formed within or transferred to the Mediterranean basin precipitating over Sinai.
Efi Rousi, Andreas H. Fink, Lauren S. Andersen, Florian N. Becker, Goratz Beobide-Arsuaga, Marcus Breil, Giacomo Cozzi, Jens Heinke, Lisa Jach, Deborah Niermann, Dragan Petrovic, Andy Richling, Johannes Riebold, Stella Steidl, Laura Suarez-Gutierrez, Jordis S. Tradowsky, Dim Coumou, André Düsterhus, Florian Ellsäßer, Georgios Fragkoulidis, Daniel Gliksman, Dörthe Handorf, Karsten Haustein, Kai Kornhuber, Harald Kunstmann, Joaquim G. Pinto, Kirsten Warrach-Sagi, and Elena Xoplaki
Nat. Hazards Earth Syst. Sci., 23, 1699–1718, https://doi.org/10.5194/nhess-23-1699-2023, https://doi.org/10.5194/nhess-23-1699-2023, 2023
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The objective of this study was to perform a comprehensive, multi-faceted analysis of the 2018 extreme summer in terms of heat and drought in central and northern Europe, with a particular focus on Germany. A combination of favorable large-scale conditions and locally dry soils were related with the intensity and persistence of the events. We also showed that such extremes have become more likely due to anthropogenic climate change and might occur almost every year under +2 °C of global warming.
Dragan Petrovic, Benjamin Fersch, and Harald Kunstmann
Nat. Hazards Earth Syst. Sci., 22, 3875–3895, https://doi.org/10.5194/nhess-22-3875-2022, https://doi.org/10.5194/nhess-22-3875-2022, 2022
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The influence of model resolution and settings on drought reproduction in Germany between 1980–2009 is investigated here. Outputs from a high-resolution model with settings tailored to the target region are compared to those from coarser-resolution models with more general settings. Gridded observational data sets serve as reference. Regarding the reproduction of drought characteristics, all models perform on a similar level, while for trends, only the modified model produces reliable outputs.
Benjamin Fersch, Andreas Wagner, Bettina Kamm, Endrit Shehaj, Andreas Schenk, Peng Yuan, Alain Geiger, Gregor Moeller, Bernhard Heck, Stefan Hinz, Hansjörg Kutterer, and Harald Kunstmann
Earth Syst. Sci. Data, 14, 5287–5307, https://doi.org/10.5194/essd-14-5287-2022, https://doi.org/10.5194/essd-14-5287-2022, 2022
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In this study, a comprehensive multi-disciplinary dataset for tropospheric water vapor was developed. Geodetic, photogrammetric, and atmospheric modeling and data fusion techniques were used to obtain maps of water vapor in a high spatial and temporal resolution. It could be shown that regional weather simulations for different seasons benefit from assimilating these maps and that the combination of the different observation techniques led to positive synergies.
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.
Lu Gao, Haijun Deng, Xiangyong Lei, Jianhui Wei, Yaning Chen, Zhongqin Li, Miaomiao Ma, Xingwei Chen, Ying Chen, Meibing Liu, and Jianyun Gao
The Cryosphere, 15, 5765–5783, https://doi.org/10.5194/tc-15-5765-2021, https://doi.org/10.5194/tc-15-5765-2021, 2021
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There is a widespread controversy on the existence of the elevation-dependent warming (EDW) phenomenon due to the limited observations in high mountains. This study provides new evidence of EDW from the Chinese Tian Shan based on a high-resolution (1 km, 6-hourly) air temperature dataset. The result reveals the significant EDW on a monthly scale. The warming rate of the minimum temperature in winter showed a significant elevation dependence (p < 0.01), especially above 3000 m.
Bernd Schalge, Gabriele Baroni, Barbara Haese, Daniel Erdal, Gernot Geppert, Pablo Saavedra, Vincent Haefliger, Harry Vereecken, Sabine Attinger, Harald Kunstmann, Olaf A. Cirpka, Felix Ament, Stefan Kollet, Insa Neuweiler, Harrie-Jan Hendricks Franssen, and Clemens Simmer
Earth Syst. Sci. Data, 13, 4437–4464, https://doi.org/10.5194/essd-13-4437-2021, https://doi.org/10.5194/essd-13-4437-2021, 2021
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In this study, a 9-year simulation of complete model output of a coupled atmosphere–land-surface–subsurface model on the catchment scale is discussed. We used the Neckar catchment in SW Germany as the basis of this simulation. Since the dataset includes the full model output, it is not only possible to investigate model behavior and interactions between the component models but also use it as a virtual truth for comparison of, for example, data assimilation experiments.
Christof Lorenz, Tanja C. Portele, Patrick Laux, and Harald Kunstmann
Earth Syst. Sci. Data, 13, 2701–2722, https://doi.org/10.5194/essd-13-2701-2021, https://doi.org/10.5194/essd-13-2701-2021, 2021
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Semi-arid regions depend on the freshwater resources from the rainy seasons as they are crucial for ensuring security for drinking water, food and electricity. Thus, forecasting the conditions for the next season is crucial for proactive water management. We hence present a seasonal forecast product for four semi-arid domains in Iran, Brazil, Sudan/Ethiopia and Ecuador/Peru. It provides a benchmark for seasonal forecasts and, finally, a crucial contribution for improved disaster preparedness.
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Short summary
Most studies of compound extremes assume stationary climate conditions. Here, we combine high-resolution regional climate modeling with non-stationary statistical methods to assess future changes in compound extremes over southeastern China. Our results demonstrate that non-stationary models more accurately capture shifts in the evolution of these events, suggesting that conventional approaches may systematically underestimate future risks.
Most studies of compound extremes assume stationary climate conditions. Here, we combine...
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