Articles | Volume 18, issue 2
https://doi.org/10.5194/nhess-18-491-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/nhess-18-491-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Brief communication
| 
14 Feb 2018
Brief communication |
| 14 Feb 2018
Brief communication: Drought likelihood for East Africa
Hui Yang
CORRESPONDING AUTHOR
Department of Ecology, School of Urban and Environmental Sciences,
Peking University, Beijing, 100871, PR China
Centre for Ecology and Hydrology, Wallingford, Oxfordshire, OX10 8BB,
UK
Chris Huntingford
Centre for Ecology and Hydrology, Wallingford, Oxfordshire, OX10 8BB,
UK
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Guohua Liu, Philippe Ciais, Shengli Tao, Hui Yang, and Ana Bastos
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-330, https://doi.org/10.5194/essd-2025-330, 2025
Preprint under review for ESSD
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We have developed a long-term and high-resolution global map of above-ground biomass changes from 1993 to 2020 using radar data and machine learning approach. This dataset can help understand the effects of disturbances, land-use changes, and extreme events on global carbon cycle, and enhance the representation of these processes in Earth System Models.
Lei Zhu, Philippe Ciais, Yitong Yao, Daniel Goll, Sebastiaan Luyssaert, Isabel Martínez Cano, Arthur Fendrich, Laurent Li, Hui Yang, Sassan Saatchi, and Wei Li
EGUsphere, https://doi.org/10.5194/egusphere-2025-397, https://doi.org/10.5194/egusphere-2025-397, 2025
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This study enhances the accuracy of modeling the carbon dynamics of Amazon rainforest by optimizing key model parameters based on satellite data. Using spatially varying parameters for tree mortality and photosynthesis, we improved predictions of biomass, productivity, and tree mortality. Our findings highlight the critical role of wood density and water availability in forest processes, offering insights to refine global carbon cycle models.
Chris Huntingford, Hui Yang, Anna Harper, Peter M. Cox, Nicola Gedney, Eleanor J. Burke, Jason A. Lowe, Garry Hayman, William J. Collins, Stephen M. Smith, and Edward Comyn-Platt
Earth Syst. Dynam., 8, 617–626, https://doi.org/10.5194/esd-8-617-2017, https://doi.org/10.5194/esd-8-617-2017, 2017
Short summary
Short summary
Recent UNFCCC climate meetings have placed much emphasis on constraining global warming to remain below 2 °C. The 2015 Paris meeting went further and gave an aspiration to fulfil a 1.5 °C threshold. We provide a flexible set of algebraic global temperature profiles that stabilise to either target. This will potentially allow the climate research community to estimate local climatic implications for these temperature profiles, along with emissions trajectories to fulfil them.
Guohua Liu, Philippe Ciais, Shengli Tao, Hui Yang, and Ana Bastos
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-330, https://doi.org/10.5194/essd-2025-330, 2025
Preprint under review for ESSD
Short summary
Short summary
We have developed a long-term and high-resolution global map of above-ground biomass changes from 1993 to 2020 using radar data and machine learning approach. This dataset can help understand the effects of disturbances, land-use changes, and extreme events on global carbon cycle, and enhance the representation of these processes in Earth System Models.
Chris Huntingford, Andrew J. Nicoll, Cornelia Klein, and Jawairia A. Ahmad
Earth Syst. Dynam., 16, 475–495, https://doi.org/10.5194/esd-16-475-2025, https://doi.org/10.5194/esd-16-475-2025, 2025
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AI is impacting science, providing key data insights, but most algorithms are statistical requiring cautious "out-of-sample" extrapolation. Yet climate research concerns predicting future climatic states. We consider a new method of AI-led equation discovery. Equations offer process interpretation and more robust predictions. We recommend this method for climate analysis, suggesting illustrative application to atmospheric convection, land–atmosphere CO2 flux, and global ocean circulation models.
Lei Zhu, Philippe Ciais, Yitong Yao, Daniel Goll, Sebastiaan Luyssaert, Isabel Martínez Cano, Arthur Fendrich, Laurent Li, Hui Yang, Sassan Saatchi, and Wei Li
EGUsphere, https://doi.org/10.5194/egusphere-2025-397, https://doi.org/10.5194/egusphere-2025-397, 2025
Short summary
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This study enhances the accuracy of modeling the carbon dynamics of Amazon rainforest by optimizing key model parameters based on satellite data. Using spatially varying parameters for tree mortality and photosynthesis, we improved predictions of biomass, productivity, and tree mortality. Our findings highlight the critical role of wood density and water availability in forest processes, offering insights to refine global carbon cycle models.
Camilla Mathison, Eleanor J. Burke, Gregory Munday, Chris D. Jones, Chris J. Smith, Norman J. Steinert, Andy J. Wiltshire, Chris Huntingford, Eszter Kovacs, Laila K. Gohar, Rebecca M. Varney, and Douglas McNeall
Geosci. Model Dev., 18, 1785–1808, https://doi.org/10.5194/gmd-18-1785-2025, https://doi.org/10.5194/gmd-18-1785-2025, 2025
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We present PRIME (Probabilistic Regional Impacts from Model patterns and Emissions), which is designed to take new emissions scenarios and rapidly provide regional impact information. PRIME allows large ensembles to be run on multi-centennial timescales, including the analysis of many important variables for impact assessments. Our evaluation shows that PRIME reproduces the climate response for known scenarios, providing confidence in using PRIME for novel scenarios.
Paul David Longden Ritchie, Chris Huntingford, and Peter Cox
EGUsphere, https://doi.org/10.5194/egusphere-2024-3023, https://doi.org/10.5194/egusphere-2024-3023, 2024
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Climate Tipping Points are not instantaneous upon crossing critical thresholds in global warming, as is often assumed. Instead, it is possible to temporarily overshoot a threshold without causing tipping, provided the duration of the overshoot is short. In this Idea, we demonstrate that restricting the time over 1.5 °C would considerably reduce tipping point risks.
Mark S. Williamson, Peter M. Cox, Chris Huntingford, and Femke J. M. M. Nijsse
Earth Syst. Dynam., 15, 829–852, https://doi.org/10.5194/esd-15-829-2024, https://doi.org/10.5194/esd-15-829-2024, 2024
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Emergent constraints on equilibrium climate sensitivity (ECS) have generally got statistically weaker in the latest set of state-of-the-art climate models (CMIP6) compared to past sets (CMIP5). We look at why this weakening happened for one particular study (Cox et al, 2018) and attribute it to an assumption made in the theory that when corrected for restores there is a stronger relationship between predictor and ECS.
Emma L. Robinson, Chris Huntingford, Valyaveetil Shamsudheen Semeena, and James M. Bullock
Earth Syst. Sci. Data, 15, 5371–5401, https://doi.org/10.5194/essd-15-5371-2023, https://doi.org/10.5194/essd-15-5371-2023, 2023
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CHESS-SCAPE is a suite of high-resolution climate projections for the UK to 2080, derived from United Kingdom Climate Projections 2018 (UKCP18), designed to support climate impact modelling. It contains four realisations of four scenarios of future greenhouse gas levels (RCP2.6, 4.5, 6.0 and 8.5), with and without bias correction to historical data. The variables are available at 1 km resolution and a daily time step, with monthly, seasonal and annual means and 20-year mean-monthly time slices.
Chris Huntingford, Peter M. Cox, Mark S. Williamson, Joseph J. Clarke, and Paul D. L. Ritchie
Earth Syst. Dynam., 14, 433–442, https://doi.org/10.5194/esd-14-433-2023, https://doi.org/10.5194/esd-14-433-2023, 2023
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Emergent constraints (ECs) reduce the spread of projections between climate models. ECs estimate changes to climate features impacting adaptation policy, and with this high profile, the method is under scrutiny. Asking
What is an EC?, we suggest they are often the discovery of parameters that characterise hidden large-scale equations that climate models solve implicitly. We present this conceptually via two examples. Our analysis implies possible new paths to link ECs and physical processes.
Gang Liu, Shushi Peng, Chris Huntingford, and Yi Xi
Geosci. Model Dev., 16, 1277–1296, https://doi.org/10.5194/gmd-16-1277-2023, https://doi.org/10.5194/gmd-16-1277-2023, 2023
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Due to computational limits, lower-complexity models (LCMs) were developed as a complementary tool for accelerating comprehensive Earth system models (ESMs) but still lack a good precipitation emulator for LCMs. Here, we developed a data-calibrated precipitation emulator (PREMU), a computationally effective way to better estimate historical and simulated precipitation by current ESMs. PREMU has potential applications related to land surface processes and their interactions with climate change.
Louise J. Slater, Chris Huntingford, Richard F. Pywell, John W. Redhead, and Elizabeth J. Kendon
Earth Syst. Dynam., 13, 1377–1396, https://doi.org/10.5194/esd-13-1377-2022, https://doi.org/10.5194/esd-13-1377-2022, 2022
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This work considers how wheat yields are affected by weather conditions during the three main wheat growth stages in the UK. Impacts are strongest in years with compound weather extremes across multiple growth stages. Future climate projections are beneficial for wheat yields, on average, but indicate a high risk of unseen weather conditions which farmers may struggle to adapt to and mitigate against.
Rebecca J. Oliver, Lina M. Mercado, Doug B. Clark, Chris Huntingford, Christopher M. Taylor, Pier Luigi Vidale, Patrick C. McGuire, Markus Todt, Sonja Folwell, Valiyaveetil Shamsudheen Semeena, and Belinda E. Medlyn
Geosci. Model Dev., 15, 5567–5592, https://doi.org/10.5194/gmd-15-5567-2022, https://doi.org/10.5194/gmd-15-5567-2022, 2022
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We introduce new representations of plant physiological processes into a land surface model. Including new biological understanding improves modelled carbon and water fluxes for the present in tropical and northern-latitude forests. Future climate simulations demonstrate the sensitivity of photosynthesis to temperature is important for modelling carbon cycle dynamics in a warming world. Accurate representation of these processes in models is necessary for robust predictions of climate change.
Anna B. Harper, Karina E. Williams, Patrick C. McGuire, Maria Carolina Duran Rojas, Debbie Hemming, Anne Verhoef, Chris Huntingford, Lucy Rowland, Toby Marthews, Cleiton Breder Eller, Camilla Mathison, Rodolfo L. B. Nobrega, Nicola Gedney, Pier Luigi Vidale, Fred Otu-Larbi, Divya Pandey, Sebastien Garrigues, Azin Wright, Darren Slevin, Martin G. De Kauwe, Eleanor Blyth, Jonas Ardö, Andrew Black, Damien Bonal, Nina Buchmann, Benoit Burban, Kathrin Fuchs, Agnès de Grandcourt, Ivan Mammarella, Lutz Merbold, Leonardo Montagnani, Yann Nouvellon, Natalia Restrepo-Coupe, and Georg Wohlfahrt
Geosci. Model Dev., 14, 3269–3294, https://doi.org/10.5194/gmd-14-3269-2021, https://doi.org/10.5194/gmd-14-3269-2021, 2021
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We evaluated 10 representations of soil moisture stress in the JULES land surface model against site observations of GPP and latent heat flux. Increasing the soil depth and plant access to deep soil moisture improved many aspects of the simulations, and we recommend these settings in future work using JULES. In addition, using soil matric potential presents the opportunity to include parameters specific to plant functional type to further improve modeled fluxes.
Garry D. Hayman, Edward Comyn-Platt, Chris Huntingford, Anna B. Harper, Tom Powell, Peter M. Cox, William Collins, Christopher Webber, Jason Lowe, Stephen Sitch, Joanna I. House, Jonathan C. Doelman, Detlef P. van Vuuren, Sarah E. Chadburn, Eleanor Burke, and Nicola Gedney
Earth Syst. Dynam., 12, 513–544, https://doi.org/10.5194/esd-12-513-2021, https://doi.org/10.5194/esd-12-513-2021, 2021
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We model greenhouse gas emission scenarios consistent with limiting global warming to either 1.5 or 2 °C above pre-industrial levels. We quantify the effectiveness of methane emission control and land-based mitigation options regionally. Our results highlight the importance of reducing methane emissions for realistic emission pathways that meet the global warming targets. For land-based mitigation, growing bioenergy crops on existing agricultural land is preferable to replacing forests.
Douglas I. Kelley, Chantelle Burton, Chris Huntingford, Megan A. J. Brown, Rhys Whitley, and Ning Dong
Biogeosciences, 18, 787–804, https://doi.org/10.5194/bg-18-787-2021, https://doi.org/10.5194/bg-18-787-2021, 2021
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Initial evidence suggests human ignitions or landscape changes caused most Amazon fires during August 2019. However, confirmation is needed that meteorological conditions did not have a substantial role. Assessing the influence of historical weather on burning in an uncertainty framework, we find that 2019 meteorological conditions alone should have resulted in much less fire than observed. We conclude socio-economic factors likely had a strong role in the high recorded 2019 fire activity.
Arthur P. K. Argles, Jonathan R. Moore, Chris Huntingford, Andrew J. Wiltshire, Anna B. Harper, Chris D. Jones, and Peter M. Cox
Geosci. Model Dev., 13, 4067–4089, https://doi.org/10.5194/gmd-13-4067-2020, https://doi.org/10.5194/gmd-13-4067-2020, 2020
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The Robust Ecosystem Demography (RED) model simulates cohorts of vegetation through mass classes. RED establishes a framework for representing demographic changes through competition, growth, and mortality across the size distribution of a forest. The steady state of the model can be solved analytically, enabling initialization. When driven by mean growth rates from a land-surface model, RED is able to fit the observed global vegetation map, giving a map of implicit mortality rates.
Jonathan R. Moore, Arthur P. K. Argles, Kai Zhu, Chris Huntingford, and Peter M. Cox
Biogeosciences, 17, 1013–1032, https://doi.org/10.5194/bg-17-1013-2020, https://doi.org/10.5194/bg-17-1013-2020, 2020
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The distribution of tree sizes across Amazonia can be fitted very well (for both trunk diameter and tree mass) by a simple equilibrium model assuming power law growth and size-independent mortality. We find tree growth to mirror some aspects of metabolic scaling theory and that there may be a trade-off between fast-growing, short-lived and longer-lived, slow-growing ones. Our Amazon mortality-to-growth ratio is very similar to US temperate forests, hinting at a universal property for trees.
Karina E. Williams, Anna B. Harper, Chris Huntingford, Lina M. Mercado, Camilla T. Mathison, Pete D. Falloon, Peter M. Cox, and Joon Kim
Geosci. Model Dev., 12, 3207–3240, https://doi.org/10.5194/gmd-12-3207-2019, https://doi.org/10.5194/gmd-12-3207-2019, 2019
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Data from the First ISLSCP Field Experiment, 1987–1989, is used to assess how well the JULES land-surface model simulates water stress in tallgrass prairie vegetation. We find that JULES simulates a decrease in key carbon and water cycle variables during the dry period, as expected, but that it does not capture the shape of the diurnal cycle on these days. These results will be used to inform future model development as part of wider evaluation efforts.
Chris Huntingford, Rebecca J. Oliver, Lina M. Mercado, and Stephen Sitch
Biogeosciences, 15, 5415–5422, https://doi.org/10.5194/bg-15-5415-2018, https://doi.org/10.5194/bg-15-5415-2018, 2018
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Raised ozone levels impact plant stomatal opening and thus photosynthesis. Most models describe this as a suppression of stomata opening. Field evidence suggests more complexity, as ozone damage may make stomatal response
sluggish. In some circumstances, this causes stomata to be more open – a concern during drought conditions – by increasing transpiration. To guide interpretation and modelling of field measurements, we present an equation for sluggish effects, via a single tau parameter.
Przemyslaw Zelazowski, Chris Huntingford, Lina M. Mercado, and Nathalie Schaller
Geosci. Model Dev., 11, 541–560, https://doi.org/10.5194/gmd-11-541-2018, https://doi.org/10.5194/gmd-11-541-2018, 2018
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This paper describes the calibration of the IMOGEN (Integrated Model Of Global Effects of climatic aNomalies) impact modelling system against 22 global climate models (GCMs) in the CMIP3 database.
IMOGEN uses "pattern scaling" to emulate GCMs, and with such linearity enables projections to be made for alternative future scenarios of atmospheric greenhouse gas concentrations. It is also coupled to the JULES land surface model, to allow impact assessments.
IMOGEN uses "pattern scaling" to emulate GCMs, and with such linearity enables projections to be made for alternative future scenarios of atmospheric greenhouse gas concentrations. It is also coupled to the JULES land surface model, to allow impact assessments.
Chris Huntingford, Hui Yang, Anna Harper, Peter M. Cox, Nicola Gedney, Eleanor J. Burke, Jason A. Lowe, Garry Hayman, William J. Collins, Stephen M. Smith, and Edward Comyn-Platt
Earth Syst. Dynam., 8, 617–626, https://doi.org/10.5194/esd-8-617-2017, https://doi.org/10.5194/esd-8-617-2017, 2017
Short summary
Short summary
Recent UNFCCC climate meetings have placed much emphasis on constraining global warming to remain below 2 °C. The 2015 Paris meeting went further and gave an aspiration to fulfil a 1.5 °C threshold. We provide a flexible set of algebraic global temperature profiles that stabilise to either target. This will potentially allow the climate research community to estimate local climatic implications for these temperature profiles, along with emissions trajectories to fulfil them.
Eleanor J. Burke, Altug Ekici, Ye Huang, Sarah E. Chadburn, Chris Huntingford, Philippe Ciais, Pierre Friedlingstein, Shushi Peng, and Gerhard Krinner
Biogeosciences, 14, 3051–3066, https://doi.org/10.5194/bg-14-3051-2017, https://doi.org/10.5194/bg-14-3051-2017, 2017
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There are large reserves of carbon within the permafrost which might be released to the atmosphere under global warming. Our models suggest this release may cause an additional global temperature increase of 0.005 to 0.2°C by the year 2100 and 0.01 to 0.34°C by the year 2300. Under climate mitigation scenarios this is between 1.5 and 9 % (by 2100) and between 6 and 16 % (by 2300) of the global mean temperature change. There is a large uncertainty associated with these results.
Stefan C. Dekker, Margriet Groenendijk, Ben B. B. Booth, Chris Huntingford, and Peter M. Cox
Earth Syst. Dynam., 7, 525–533, https://doi.org/10.5194/esd-7-525-2016, https://doi.org/10.5194/esd-7-525-2016, 2016
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Our analysis allows us to infer maps of changing plant water-use efficiency (WUE) for 1901–2010, using atmospheric observations of temperature, humidity and CO2. Our estimated increase in global WUE is consistent with the tree-ring and eddy covariance data, but much larger than the historical WUE increases simulated by Earth System Models (ESMs). We therefore conclude that the effects of increasing CO2 on plant WUE are significantly underestimated in the latest climate projections.
S. Sitch, P. Friedlingstein, N. Gruber, S. D. Jones, G. Murray-Tortarolo, A. Ahlström, S. C. Doney, H. Graven, C. Heinze, C. Huntingford, S. Levis, P. E. Levy, M. Lomas, B. Poulter, N. Viovy, S. Zaehle, N. Zeng, A. Arneth, G. Bonan, L. Bopp, J. G. Canadell, F. Chevallier, P. Ciais, R. Ellis, M. Gloor, P. Peylin, S. L. Piao, C. Le Quéré, B. Smith, Z. Zhu, and R. Myneni
Biogeosciences, 12, 653–679, https://doi.org/10.5194/bg-12-653-2015, https://doi.org/10.5194/bg-12-653-2015, 2015
G. D. Hayman, F. M. O'Connor, M. Dalvi, D. B. Clark, N. Gedney, C. Huntingford, C. Prigent, M. Buchwitz, O. Schneising, J. P. Burrows, C. Wilson, N. Richards, and M. Chipperfield
Atmos. Chem. Phys., 14, 13257–13280, https://doi.org/10.5194/acp-14-13257-2014, https://doi.org/10.5194/acp-14-13257-2014, 2014
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Globally, wetlands are a major source of methane, which is the second most important greenhouse gas. We find the JULES wetland methane scheme to perform well in general, although there is a tendency for it to overpredict emissions in the tropics and underpredict them in northern latitudes. Our study highlights novel uses of satellite data as a major tool to constrain land-atmosphere methane flux models in a warming world.
J. B. Fisher, M. Sikka, W. C. Oechel, D. N. Huntzinger, J. R. Melton, C. D. Koven, A. Ahlström, M. A. Arain, I. Baker, J. M. Chen, P. Ciais, C. Davidson, M. Dietze, B. El-Masri, D. Hayes, C. Huntingford, A. K. Jain, P. E. Levy, M. R. Lomas, B. Poulter, D. Price, A. K. Sahoo, K. Schaefer, H. Tian, E. Tomelleri, H. Verbeeck, N. Viovy, R. Wania, N. Zeng, and C. E. Miller
Biogeosciences, 11, 4271–4288, https://doi.org/10.5194/bg-11-4271-2014, https://doi.org/10.5194/bg-11-4271-2014, 2014
C. Le Quéré, R. J. Andres, T. Boden, T. Conway, R. A. Houghton, J. I. House, G. Marland, G. P. Peters, G. R. van der Werf, A. Ahlström, R. M. Andrew, L. Bopp, J. G. Canadell, P. Ciais, S. C. Doney, C. Enright, P. Friedlingstein, C. Huntingford, A. K. Jain, C. Jourdain, E. Kato, R. F. Keeling, K. Klein Goldewijk, S. Levis, P. Levy, M. Lomas, B. Poulter, M. R. Raupach, J. Schwinger, S. Sitch, B. D. Stocker, N. Viovy, S. Zaehle, and N. Zeng
Earth Syst. Sci. Data, 5, 165–185, https://doi.org/10.5194/essd-5-165-2013, https://doi.org/10.5194/essd-5-165-2013, 2013
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A data-driven framework for assessing climatic impact drivers in the context of food security
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Extreme heat and mortality in the State of Rio de Janeiro in the 2023/24 season: attribution to climate change and ENSO
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The anomalously thundery month of June 1925 in southwest Spain: description and synoptic analysis
Spatial identification of regions exposed to multi-hazards at the pan-European level
Classification of North Atlantic and European extratropical cyclones using multiple measures of intensity
Subseasonal forecasts of heat waves in West African cities
Impacts on and damage to European forests from the 2018–2022 heat and drought events
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How well are hazards associated with derechos reproduced in regional climate simulations?
Is considering runs (in)consistency so useless for weather forecasting?
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Insurance loss model vs. meteorological loss index – how comparable are their loss estimates for European windstorms?
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Intense rains in Israel associated with the train effect
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Convection-permitting climate model representation of severe convective wind gusts and future changes in southeastern Australia
Impact-based temporal clustering of multiple meteorological hazard types in southwestern Germany
On the potential of using smartphone sensors for wildfire hazard estimation through citizen science
Global estimates of 100-year return values of daily precipitation from ensemble weather prediction data
Exploring the sensitivity of extreme event attribution of two recent extreme weather events in Sweden using long-running meteorological observations
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Andreas Trojand, Henning W. Rust, and Uwe Ulbrich
Nat. Hazards Earth Syst. Sci., 25, 2331–2350, https://doi.org/10.5194/nhess-25-2331-2025, https://doi.org/10.5194/nhess-25-2331-2025, 2025
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The study investigates how the intensity of previous windstorm events and the time between two events affect the vulnerability of residential buildings in Germany. By analyzing 23 years of data, it was found that higher intensity of previous events generally reduces vulnerability in subsequent storms, while shorter intervals between events increase vulnerability. The results emphasize the approach of considering vulnerability in risk assessments as temporally dynamic.
Shao-Yi Lee, Sicheng He, and Tetsuya Takemi
Nat. Hazards Earth Syst. Sci., 25, 2225–2253, https://doi.org/10.5194/nhess-25-2225-2025, https://doi.org/10.5194/nhess-25-2225-2025, 2025
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The authors performed verification on the relationships between extreme monsoon rainfall over Japan and Pacific sea surface temperature variability in the “database for Policy Decision-making for Future climate changes” (d4PDF). Observations showed widespread weak relationships between hourly extremes and the warming mode but reversed relationships between daily extremes and the decadal variability mode. Biases in d4PDF could be explained by the monsoon's slower movement over Japan in the model.
Rike Lorenz, Nico Becker, Barry Gardiner, Uwe Ulbrich, Marc Hanewinkel, and Benjamin Schmitz
Nat. Hazards Earth Syst. Sci., 25, 2179–2196, https://doi.org/10.5194/nhess-25-2179-2025, https://doi.org/10.5194/nhess-25-2179-2025, 2025
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Tree fall events have an impact on forests and transport systems. Our study explored tree fall in relation to wind and other weather conditions. We used tree fall data along railway lines and ERA5 and radar meteorological data to build a logistic regression model. We found that high and prolonged wind speeds, wet conditions, and high air density increase tree fall risk. These factors might change in the changing climate, which in return will change risks for trees, forests and transport.
Natalia Korhonen, Otto Hyvärinen, Virpi Kollanus, Timo Lanki, Juha Jokisalo, Risto Kosonen, David S. Richardson, and Kirsti Jylhä
Nat. Hazards Earth Syst. Sci., 25, 1865–1879, https://doi.org/10.5194/nhess-25-1865-2025, https://doi.org/10.5194/nhess-25-1865-2025, 2025
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The skill of hindcasts from the European Centre for Medium-Range Weather Forecasts in forecasting heat wave days, defined as periods with the 5 d moving average temperature exceeding its local summer 90th percentile over Europe 1 to 4 weeks ahead, is examined. Forecasts of heat wave days show potential for warning of heat risk 1 to 2 weeks in advance and enhanced accuracy in forecasting prolonged heat waves up to 3 weeks ahead, when the heat wave had already begun before forecast issuance.
Cees de Valk and Henk van den Brink
Nat. Hazards Earth Syst. Sci., 25, 1769–1788, https://doi.org/10.5194/nhess-25-1769-2025, https://doi.org/10.5194/nhess-25-1769-2025, 2025
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Estimates of the risk posed by rare and catastrophic weather events are often derived from relatively short measurement records, which renders them highly uncertain. We investigate if (and by how much) this uncertainty can be reduced by making use of large datasets of simulated weather. More specifically, we focus on coastal flood hazard in the Netherlands and on the challenge of estimating the once in 10 million years coastal water level and wind stress as accurately as possible.
Felix Erdmann and Dieter Roel Poelman
Nat. Hazards Earth Syst. Sci., 25, 1751–1768, https://doi.org/10.5194/nhess-25-1751-2025, https://doi.org/10.5194/nhess-25-1751-2025, 2025
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This study provides detailed insight into the thunderstorm characteristics associated with abrupt changes in the lightning activity of a thunderstorm – lightning jumps (LJs) and lightning dives (LDs) – using geostationary satellite observations. Thunderstorms exhibiting one or multiple LJs or LDs feature characteristics similar to severe thunderstorms. Storms with multiple LJs contain strong convective updrafts and are prone to produce high rain rates, large hail, or tornadoes.
Jinfang Yin, Feng Li, Mingxin Li, Rudi Xia, Xinghua Bao, Jisong Sun, and Xudong Liang
Nat. Hazards Earth Syst. Sci., 25, 1719–1735, https://doi.org/10.5194/nhess-25-1719-2025, https://doi.org/10.5194/nhess-25-1719-2025, 2025
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A persistent severe rainfall event occurred over North China in July 2023, which was regarded as one of the most extreme episodes globally during that year. The extreme rainfall was significantly underestimated by forecasters at that time. Flooding from this event affected 1.3 million people, causing severe human casualties and economic losses. We examined the convective initiation and subsequent persistent heavy rainfall based on simulations with the Weather Research and Forecasting model.
Ilona Láng-Ritter, Terhi Kristiina Laurila, Antti Mäkelä, Hilppa Gregow, and Victoria Anne Sinclair
Nat. Hazards Earth Syst. Sci., 25, 1697–1717, https://doi.org/10.5194/nhess-25-1697-2025, https://doi.org/10.5194/nhess-25-1697-2025, 2025
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We present a classification method for extratropical cyclones and windstorms and show their impacts on Finland's electricity grid by analysing the 92 most damaging windstorms (2005–2018). The south-west- and north-west-arriving windstorms cause the most damage to the power grid. The most relevant parameters for damage are the wind gust speed and extent of wind gusts. Windstorms are more frequent and damaging in autumn and winter, but weaker wind speeds in summer also cause significant damage.
Joseph W. Gallear, Marcelo Valadares Galdos, Marcelo Zeri, and Andrew Hartley
Nat. Hazards Earth Syst. Sci., 25, 1521–1541, https://doi.org/10.5194/nhess-25-1521-2025, https://doi.org/10.5194/nhess-25-1521-2025, 2025
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In Brazil, drought is of national concern and can have major consequences for agriculture. Here, we determine how to develop forecasts for drought stress on vegetation health using machine learning. Results aim to inform future developments in operational drought monitoring at the National Centre for Monitoring and Early Warning of Natural Disasters (CEMADEN) in Brazil. This information is essential for disaster preparedness and planning of future actions to support areas affected by drought.
Thomas Schwitalla, Lisa Jach, Volker Wulfmeyer, and Kirsten Warrach-Sagi
Nat. Hazards Earth Syst. Sci., 25, 1405–1424, https://doi.org/10.5194/nhess-25-1405-2025, https://doi.org/10.5194/nhess-25-1405-2025, 2025
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During recent decades, Europe has experienced increasing periods of severe drought and heatwave. To provide an overview of how land-surface conditions shape land–atmosphere (LA) coupling, the interannual LA coupling strength variability for the summer seasons of 1991–2022 is investigated by means of ERA5 data. The results clearly reflect ongoing climate change by a shift in the coupling relationships towards reinforced heating and drying by the land surface.
Marcos Roberto Benso, Roberto Fray Silva, Gabriela Chiquito Gesualdo, Antonio Mauro Saraiva, Alexandre Cláudio Botazzo Delbem, Patricia Angélica Alves Marques, José Antonio Marengo, and Eduardo Mario Mendiondo
Nat. Hazards Earth Syst. Sci., 25, 1387–1404, https://doi.org/10.5194/nhess-25-1387-2025, https://doi.org/10.5194/nhess-25-1387-2025, 2025
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This study applies climate extreme indices to assess climate risks to food security. Using an explainable machine learning analysis, key climate indices affecting maize and soybean yields in Brazil were identified. Results reveal the temporal sensitivity of these indices and critical yield loss thresholds, informing policy and adaptation strategies.
Juan F. Dueñas, Edda Kunze, Huiying Li, and Matthias C. Rillig
Nat. Hazards Earth Syst. Sci., 25, 1377–1386, https://doi.org/10.5194/nhess-25-1377-2025, https://doi.org/10.5194/nhess-25-1377-2025, 2025
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We investigated the potential of adding mixtures composed of minimum dosages of several popular amendment types to soil. Our goal was to increase the resistance of agricultural soil to drought stress. We found that adding mixtures of three to five amendment types increased the capacity of soil to retain water, reduced soil erosion, and increased fungal abundance while buffering soil from drastic changes in pH. More research is encouraged to validate this approach.
Killian P. Brennan, Iris Thurnherr, Michael Sprenger, and Heini Wernli
EGUsphere, https://doi.org/10.5194/egusphere-2025-918, https://doi.org/10.5194/egusphere-2025-918, 2025
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Hailstorms can cause severe damage to homes, crops, and infrastructure. Using high-resolution climate simulations, we tracked thousands of hailstorms across Europe to study future changes. Large hail will become more frequent, hail-covered areas will expand, and extreme hail combined with heavy rain will double. These shifts could increase risks for communities and businesses, highlighting the need for better preparedness and adaptation.
Soledad Collazo, David Barriopedro, Ricardo García-Herrera, and Santiago Beguería
EGUsphere, https://doi.org/10.5194/egusphere-2025-792, https://doi.org/10.5194/egusphere-2025-792, 2025
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In the 2023/24 season, Rio de Janeiro experienced record-breaking heatwaves linked to climate change and El Niño. Our study shows global warming made these extreme temperatures at least 2°C hotter than in pre-industrial times. Heat-related deaths surged, with climate change contributing to 1 in 3 fatalities during the peak event. Without adaptation, future heatwaves will claim even more lives. This underscores the urgent need for policies to mitigate climate impacts from escalating heat threats.
François Collet, Margot Bador, Julien Boé, Laurent Dubus, and Bénédicte Jourdier
Nat. Hazards Earth Syst. Sci., 25, 843–856, https://doi.org/10.5194/nhess-25-843-2025, https://doi.org/10.5194/nhess-25-843-2025, 2025
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Our aim is to characterize the observed evolution of compound winter low-wind and cold events impacting the French electricity system. The frequency of compound events exhibits a decrease over the 1950–2022 period, which is likely due to a decrease in cold days. Large-scale atmospheric circulation is an important driver of compound event occurrence and has likely contributed to the decrease in cold days, while we cannot draw conclusions on its influence on the decrease in compound events.
Fabio Dioguardi, Giovanni Chiodini, and Antonio Costa
Nat. Hazards Earth Syst. Sci., 25, 657–674, https://doi.org/10.5194/nhess-25-657-2025, https://doi.org/10.5194/nhess-25-657-2025, 2025
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We present results of non-volcanic-gas (CO2) hazard assessment at the Mefite d’Ansanto area (Italy) where a cold-gas stream, which has already been lethal to humans and animals, forms in the valleys surrounding the emission zone. We took the uncertainty related to the gas emission and meteorological conditions into account. Results include maps of CO2 concentrations at defined probability levels and the probability of overcoming specified CO2 concentrations over specified time intervals.
Sonja Szymczak, Frederick Bott, Vigile Marie Fabella, and Katharina Fricke
Nat. Hazards Earth Syst. Sci., 25, 683–707, https://doi.org/10.5194/nhess-25-683-2025, https://doi.org/10.5194/nhess-25-683-2025, 2025
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We investigate the correlation between heavy-rainfall events and three associated natural hazards along the German rail network using GIS analyses and random-effects logistic models. The results show that 23 % of floods, 14 % of gravitational mass movements, and 2 % of tree fall events between 2017 and 2020 occurred after a heavy-rainfall event, and the probability of occurrence of flood and tree fall events significantly increased. This study contributes to more resilient rail transport.
Daniel G. Kingston, Liam Cooper, David A. Lavers, and David M. Hannah
Nat. Hazards Earth Syst. Sci., 25, 675–682, https://doi.org/10.5194/nhess-25-675-2025, https://doi.org/10.5194/nhess-25-675-2025, 2025
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Extreme rainfall comprises a major hydrohazard for New Zealand and is commonly associated with atmospheric rivers – narrow plumes of very high atmospheric moisture transport. Here, we focus on improved forecasting of these events by testing a forecasting tool previously applied to similar situations in western Europe. However, our results for New Zealand suggest the performance of this forecasting tool may vary depending on geographical setting.
Tiago M. Ferreira, Ricardo M. Trigo, Tomás H. Gaspar, Joaquim G. Pinto, and Alexandre M. Ramos
Nat. Hazards Earth Syst. Sci., 25, 609–623, https://doi.org/10.5194/nhess-25-609-2025, https://doi.org/10.5194/nhess-25-609-2025, 2025
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We investigate the synoptic evolution associated with the occurrence of an atmospheric river that led to a 24 h record-breaking extreme precipitation event (120.3 mm) in Lisbon, Portugal, on 13 December 2022. The synoptic background allowed the formation, on 10 December, of an atmospheric river associated with a deep extratropical cyclone and with a high moisture content and an inflow of moisture, due to the warm conveyor belt, throughout its life cycle. The system made landfall on 12 December.
Elena Xoplaki, Florian Ellsäßer, Jens Grieger, Katrin M. Nissen, Joaquim G. Pinto, Markus Augenstein, Ting-Chen Chen, Hendrik Feldmann, Petra Friederichs, Daniel Gliksman, Laura Goulier, Karsten Haustein, Jens Heinke, Lisa Jach, Florian Knutzen, Stefan Kollet, Jürg Luterbacher, Niklas Luther, Susanna Mohr, Christoph Mudersbach, Christoph Müller, Efi Rousi, Felix Simon, Laura Suarez-Gutierrez, Svenja Szemkus, Sara M. Vallejo-Bernal, Odysseas Vlachopoulos, and Frederik Wolf
Nat. Hazards Earth Syst. Sci., 25, 541–564, https://doi.org/10.5194/nhess-25-541-2025, https://doi.org/10.5194/nhess-25-541-2025, 2025
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Europe frequently experiences compound events, with major impacts. We investigate these events’ interactions, characteristics, and changes over time, focusing on socio-economic impacts in Germany and central Europe. Highlighting 2018’s extreme events, this study reveals impacts on water, agriculture, and forests and stresses the need for impact-focused definitions and better future risk quantification to support adaptation planning.
Lixin Song, Feifei Shen, Zhixin He, Dongmei Xu, Aiqing Shu, and Jiajun Chen
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-203, https://doi.org/10.5194/nhess-2024-203, 2025
Revised manuscript accepted for NHESS
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When retrieving hydrometeors from reflectivity, there are two methods to allocate hydrometeor types: temperature-based and background hydrometer-dependent schemes. The temperature-based method divides hydrometeor proportions based on the background temperature, while the other scheme calculates average weights of each hydrometeor in various reflectivity intervals from background fields. The blending scheme adaptively combines these methods and is found to improve precipitation forecast accuracy.
Alan Demortier, Marc Mandement, Vivien Pourret, and Olivier Caumont
Nat. Hazards Earth Syst. Sci., 25, 429–449, https://doi.org/10.5194/nhess-25-429-2025, https://doi.org/10.5194/nhess-25-429-2025, 2025
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The use of numerical weather prediction models enables the forecasting of hazardous weather situations. The incorporation of new temperature and relative humidity observations from personal weather stations into the French limited-area model is evaluated in this study. This leads to the improvement of the associated near-surface variables of the model during the first hours of the forecast. Examples are provided for a sea breeze case during a heatwave and a fog episode.
Francisco Javier Acero, Manuel Antón, Alejandro Jesús Pérez Aparicio, Nieves Bravo-Paredes, Víctor Manuel Sánchez Carrasco, María Cruz Gallego, José Agustín García, Marcelino Núñez, Irene Tovar, Javier Vaquero-Martínez, and José Manuel Vaquero
Nat. Hazards Earth Syst. Sci., 25, 305–320, https://doi.org/10.5194/nhess-25-305-2025, https://doi.org/10.5194/nhess-25-305-2025, 2025
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The month of June 1925 was found to be exceptional in the southwest interior of the Iberian Peninsula due to the large number of thunderstorms and their significant impacts, with serious losses of human lives and material resources. We analyzed this event from different, complementary perspectives: reconstruction of the history of the events from newspapers, study of monthly meteorological variables of the longest series available, and the analysis of the meteorological synoptic situation.
Tiberiu-Eugen Antofie, Stefano Luoni, Aloïs Tilloy, Andrea Sibilia, Sandro Salari, Gustav Eklund, Davide Rodomonti, Christos Bountzouklis, and Christina Corbane
Nat. Hazards Earth Syst. Sci., 25, 287–304, https://doi.org/10.5194/nhess-25-287-2025, https://doi.org/10.5194/nhess-25-287-2025, 2025
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This is the first study that uses spatial patterns (clusters/hotspots) and meta-analysis in order to identify the regions at a European level at risk of multi-hazards. The findings point out the socioeconomic dimension as a determining factor in the potential risk of multi-hazards. The outcome provides valuable input for the disaster risk management policy support and will assist national authorities on the implementation of a multi-hazard approach in national risk assessment preparation.
Joona Cornér, Clément Bouvier, Benjamin Doiteau, Florian Pantillon, and Victoria A. Sinclair
Nat. Hazards Earth Syst. Sci., 25, 207–229, https://doi.org/10.5194/nhess-25-207-2025, https://doi.org/10.5194/nhess-25-207-2025, 2025
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Classification reduces the considerable variability between extratropical cyclones (ETCs) and thus simplifies studying their representation in climate models and changes in the future climate. In this paper we present an objective classification of ETCs using measures of ETC intensity. This is motivated by the aim of finding a set of ETC intensity measures which together comprehensively describe both the dynamical and impact-relevant nature of ETC intensity.
Cedric G. Ngoungue Langue, Christophe Lavaysse, and Cyrille Flamant
Nat. Hazards Earth Syst. Sci., 25, 147–168, https://doi.org/10.5194/nhess-25-147-2025, https://doi.org/10.5194/nhess-25-147-2025, 2025
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The present study addresses the predictability of heat waves at subseasonal timescales in West African cities over the period 2001–2020. Two models, the European Centre for Medium-Range Weather Forecasts (ECMWF) and the UK Met Office models, were evaluated using two reanalyses: ERA5 and MERRA. The results suggest that at subseasonal timescales, the forecast models provide a better forecast than climatology, but the hit rate and false alarm rate are sub-optimal.
Florian Knutzen, Paul Averbeck, Caterina Barrasso, Laurens M. Bouwer, Barry Gardiner, José M. Grünzweig, Sabine Hänel, Karsten Haustein, Marius Rohde Johannessen, Stefan Kollet, Mortimer M. Müller, Joni-Pekka Pietikäinen, Karolina Pietras-Couffignal, Joaquim G. Pinto, Diana Rechid, Efi Rousi, Ana Russo, Laura Suarez-Gutierrez, Sarah Veit, Julian Wendler, Elena Xoplaki, and Daniel Gliksman
Nat. Hazards Earth Syst. Sci., 25, 77–117, https://doi.org/10.5194/nhess-25-77-2025, https://doi.org/10.5194/nhess-25-77-2025, 2025
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Our research, involving 22 European scientists, investigated drought and heat impacts on forests in 2018–2022. Findings reveal that climate extremes are intensifying, with central Europe being most severely impacted. The southern region showed resilience due to historical drought exposure, while northern and Alpine areas experienced emerging or minimal impacts. The study highlights the need for region-specific strategies, improved data collection, and sustainable practices to safeguard forests.
Georgy Ayzel and Maik Heistermann
Nat. Hazards Earth Syst. Sci., 25, 41–47, https://doi.org/10.5194/nhess-25-41-2025, https://doi.org/10.5194/nhess-25-41-2025, 2025
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Forecasting rainfall over the next hour is an essential feature of early warning systems. Deep learning (DL) has emerged as a powerful alternative to conventional nowcasting technologies, but it still struggles to adequately predict impact-relevant heavy rainfall. We think that DL could do much better if the training tasks were defined more specifically and that such specification presents an opportunity to better align the output of nowcasting models with actual user requirements.
Monica Ionita, Petru Vaideanu, Bogdan Antonescu, Catalin Roibu, Qiyun Ma, and Viorica Nagavciuc
Nat. Hazards Earth Syst. Sci., 24, 4683–4706, https://doi.org/10.5194/nhess-24-4683-2024, https://doi.org/10.5194/nhess-24-4683-2024, 2024
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Eastern Europe's heat wave history is explored from 1885 to 2023, with a focus on pre-1960 events. The study reveals two periods with more frequent and intense heat waves (HWs): 1920s–1960s and 1980s–present. The research highlights the importance of a long-term perspective, revealing that extreme heat events have occurred throughout the entire study period, and it emphasizes the combined influence of climate change and natural variations on increasing HW severity.
Tristan Shepherd, Frederick Letson, Rebecca J. Barthelmie, and Sara C. Pryor
Nat. Hazards Earth Syst. Sci., 24, 4473–4505, https://doi.org/10.5194/nhess-24-4473-2024, https://doi.org/10.5194/nhess-24-4473-2024, 2024
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A historic derecho in the USA is presented. The 29 June 2012 derecho caused more than 20 deaths and millions of US dollars of damage. We use a regional climate model to understand how model fidelity changes under different initial conditions. We find changes drive different convective conditions, resulting in large variation in the simulated hazards. The variation using different reanalysis data shows that framing these results in the context of contemporary and future climate is a challenge.
Hugo Marchal, François Bouttier, and Olivier Nuissier
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-208, https://doi.org/10.5194/nhess-2024-208, 2024
Revised manuscript accepted for NHESS
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This paper investigates the relationship between changes in weather forecasts and predictability, which has so far been considered weak. By focusing on the persistence of weather scenarios over successive forecasts, we found that it significantly affects the reliability of forecasts.
Lena Wilhelm, Cornelia Schwierz, Katharina Schröer, Mateusz Taszarek, and Olivia Martius
Nat. Hazards Earth Syst. Sci., 24, 3869–3894, https://doi.org/10.5194/nhess-24-3869-2024, https://doi.org/10.5194/nhess-24-3869-2024, 2024
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In our study we used statistical models to reconstruct past hail days in Switzerland from 1959–2022. This new time series reveals a significant increase in hail day occurrences over the last 7 decades. We link this trend to increases in moisture and instability variables in the models. This time series can now be used to unravel the complexities of Swiss hail occurrence and to understand what drives its year-to-year variability.
Marc Lemus-Canovas, Sergi Gonzalez-Herrero, Laura Trapero, Anna Albalat, Damian Insua-Costa, Martin Senande-Rivera, and Gonzalo Miguez-Macho
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-192, https://doi.org/10.5194/nhess-2024-192, 2024
Revised manuscript accepted for NHESS
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This study explores the 2022 heatwaves in the Pyrenees, examining the factors that contributed to their intensity and distribution. The June event was driven by strong winds that created uneven temperature patterns, while the July heatwave featured calmer conditions and more uniform temperatures. Human-driven climate change has made these heatwaves more severe compared to the past. This research helps us better understand how climate change affects extreme weather in mountainous regions.
Diego Saúl Carrió, Vincenzo Mazzarella, and Rossella Ferretti
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-177, https://doi.org/10.5194/nhess-2024-177, 2024
Revised manuscript accepted for NHESS
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Populated coastal regions in the Mediterranean are known to be severely affected by extreme weather events that are initiated over maritime regions. These weather events are known to pose a serious problem in terms of numerical predictability. Different Data Assimilation techniques are used in this study with the main aim of enhancing short-range forecasts of two challenging severe weather events.
Thomas Loridan and Nicolas Bruneau
EGUsphere, https://doi.org/10.5194/egusphere-2024-3253, https://doi.org/10.5194/egusphere-2024-3253, 2024
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Tropical Cyclone (TC) risk models have been used by the insurance industry to quantify occurrence and severity risk since the 90s. To date these models are mostly built from backward looking statistics and portray risk under a static view of the climate. We here introduce a novel approach, based on machine learning, that allows sampling of climate variability when assessing TC risk globally. This is of particular importance when computing forward looking views of TC risk.
Herijaona Hani-Roge Hundilida Randriatsara, Eva Holtanova, Karim Rizwan, Hassen Babaousmail, Mirindra Finaritra Tanteliniaina Rabezanahary, Kokou Romaric Posset, Donnata Alupot, and Brian Odhiambo Ayugi
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-191, https://doi.org/10.5194/nhess-2024-191, 2024
Revised manuscript accepted for NHESS
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This study aims to analyze the spatiotemporal characteristics of drought (duration, frequency, severity, intensity) over Madagascar during 1981–2022 by using Standardized Precipitation Index (SPI-3, -6 and -12). Additionally, the impact of drought on vegetation over the studied area was assessed based on the relationship evaluation between SPI and the Normalized Difference Vegetation Index (NDVI) during 2000–2022.
Xiaowei Zhao, Tianzeng Yang, Hongbo Zhang, Tian Lan, Chaowei Xue, Tongfang Li, Zhaoxia Ye, Zhifang Yang, and Yurou Zhang
Nat. Hazards Earth Syst. Sci., 24, 3479–3495, https://doi.org/10.5194/nhess-24-3479-2024, https://doi.org/10.5194/nhess-24-3479-2024, 2024
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To effectively track and identify droughts, we developed a novel integrated drought index that combines the effects of precipitation, temperature, and soil moisture on drought. After comparison and verification, the integrated drought index shows superior performance compared to a single meteorological drought index or agricultural drought index in terms of drought identification.
Julia Moemken, Inovasita Alifdini, Alexandre M. Ramos, Alexandros Georgiadis, Aidan Brocklehurst, Lukas Braun, and Joaquim G. Pinto
Nat. Hazards Earth Syst. Sci., 24, 3445–3460, https://doi.org/10.5194/nhess-24-3445-2024, https://doi.org/10.5194/nhess-24-3445-2024, 2024
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European windstorms regularly cause damage to natural and human-made environments, leading to high socio-economic losses. For the first time, we compare estimates of these losses using a meteorological loss index (LI) and the insurance loss (catastrophe) model of Aon Impact Forecasting. We find that LI underestimates high-impact windstorms compared to the insurance model. Nonetheless, due to its simplicity, LI is an effective index, suitable for estimating impacts and ranking storm events.
Jannick Fischer, Pieter Groenemeijer, Alois Holzer, Monika Feldmann, Katharina Schröer, Francesco Battaglioli, Lisa Schielicke, Tomáš Púčik, Christoph Gatzen, Bogdan Antonescu, and the TIM Partners
EGUsphere, https://doi.org/10.5194/egusphere-2024-2798, https://doi.org/10.5194/egusphere-2024-2798, 2024
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Strong thunderstorms have been studied mainly over flat terrain and in computer simulations in the past. However, they are particularly frequent near mountain ranges, which emphasizes the need to study storms near mountains. This article gives an overview about our existing knowledge on this topic and presents plans for a large European field campaign with the goals to fill these knowledge gaps, validate tools for thunderstorm warnings, and improve numerical weather prediction near mountains.
Baruch Ziv, Uri Dayan, Lidiya Shendrik, and Elyakom Vadislavsky
Nat. Hazards Earth Syst. Sci., 24, 3267–3277, https://doi.org/10.5194/nhess-24-3267-2024, https://doi.org/10.5194/nhess-24-3267-2024, 2024
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The train effect is related to convective cells that pass over the same place. Trains produce heavy rainfall and sometimes floods and are reported in North America during spring and summer. In Israel, 17 trains associated with Cyprus lows were identified by radar images and were found within the cold sector south of the low center and in the left flank of a maximum wind belt; they cross the Israeli coast, with a mean length of 45 km; last 1–3 h; and yield 35 mm of rainfall up to 60 mm.
Lou Brett, Christopher J. White, Daniela I.V. Domeisen, Bart van den Hurk, Philip Ward, and Jakob Zscheischler
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-182, https://doi.org/10.5194/nhess-2024-182, 2024
Revised manuscript accepted for NHESS
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Compound events, where multiple weather or climate hazards occur together, pose significant risks to both society and the environment. These events, like simultaneous wind and rain, can have more severe impacts than single hazards. Our review of compound event research from 2012–2022 reveals a rise in studies, especially on events that occur concurrently, hot and dry events and compounding flooding. The review also highlights opportunities for research in the coming years.
Andrew Brown, Andrew Dowdy, and Todd P. Lane
Nat. Hazards Earth Syst. Sci., 24, 3225–3243, https://doi.org/10.5194/nhess-24-3225-2024, https://doi.org/10.5194/nhess-24-3225-2024, 2024
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A computer model that simulates the climate of southeastern Australia is shown here to represent extreme wind events associated with convective storms. This is useful as it allows us to investigate possible future changes in the occurrences of these events, and we find in the year 2050 that our model simulates a decrease in the number of occurrences. However, the model also simulates too many events in the historical climate compared with observations, so these future changes are uncertain.
Katharina Küpfer, Alexandre Tuel, and Michael Kunz
EGUsphere, https://doi.org/10.5194/egusphere-2024-2803, https://doi.org/10.5194/egusphere-2024-2803, 2024
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Using loss data, we assess when and how single and multiple types of meteorological extremes (river floods and heavy rainfall events, windstorms and convective gusts, and hail). We find that the combination of several types of hazards clusters robustly on a seasonal scale, whereas only some single hazard types occur in clusters. This can be associated with higher losses compared to isolated events. We argue for the relevance of jointly considering multiple types of hazards.
Hofit Shachaf, Colin Price, Dorita Rostkier-Edelstein, and Cliff Mass
Nat. Hazards Earth Syst. Sci., 24, 3035–3047, https://doi.org/10.5194/nhess-24-3035-2024, https://doi.org/10.5194/nhess-24-3035-2024, 2024
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We have used the temperature and relative humidity sensors in smartphones to estimate the vapor pressure deficit (VPD), an important atmospheric parameter closely linked to fuel moisture and wildfire risk. Our analysis for two severe wildfire case studies in Israel and Portugal shows the potential for using smartphone data to compliment the regular weather station network while also providing high spatial resolution of the VPD index.
Florian Ruff and Stephan Pfahl
Nat. Hazards Earth Syst. Sci., 24, 2939–2952, https://doi.org/10.5194/nhess-24-2939-2024, https://doi.org/10.5194/nhess-24-2939-2024, 2024
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High-impact river floods are often caused by extreme precipitation. Flood protection relies on reliable estimates of the return values. Observational time series are too short for a precise calculation. Here, 100-year return values of daily precipitation are estimated on a global grid based on a large set of model-generated precipitation events from ensemble weather prediction. The statistical uncertainties in the return values can be substantially reduced compared to observational estimates.
Erik Holmgren and Erik Kjellström
Nat. Hazards Earth Syst. Sci., 24, 2875–2893, https://doi.org/10.5194/nhess-24-2875-2024, https://doi.org/10.5194/nhess-24-2875-2024, 2024
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Associating extreme weather events with changes in the climate remains difficult. We have explored two ways these relationships can be investigated: one using a more common method and one relying solely on long-running records of meteorological observations.
Our results show that while both methods lead to similar conclusions for two recent weather events in Sweden, the commonly used method risks underestimating the strength of the connection between the event and changes to the climate.
François Bouttier and Hugo Marchal
Nat. Hazards Earth Syst. Sci., 24, 2793–2816, https://doi.org/10.5194/nhess-24-2793-2024, https://doi.org/10.5194/nhess-24-2793-2024, 2024
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Weather prediction uncertainties can be described as sets of possible scenarios – a technique called ensemble prediction. Our machine learning technique translates them into more easily interpretable scenarios for various users, balancing the detection of high precipitation with false alarms. Key parameters are precipitation intensity and space and time scales of interest. We show that the approach can be used to facilitate warnings of extreme precipitation.
Xiaoxiang Guan, Dung Viet Nguyen, Paul Voit, Bruno Merz, Maik Heistermann, and Sergiy Vorogushyn
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-143, https://doi.org/10.5194/nhess-2024-143, 2024
Revised manuscript accepted for NHESS
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We evaluated a multi-site stochastic regional weather generator (nsRWG) for its ability to capture the cross-scale extremity of high precipitation events (HPEs) in Germany. We generated 100 realizations of 72 years of daily synthetic precipitation data. The performance was assessed using WEI and xWEI indices, which measure event extremity across spatio-temporal scales. Results show nsRWG simulates well the extremity patterns of HPEs, though it overestimates short-duration, small-extent events.
Joy Ommer, Jessica Neumann, Milan Kalas, Sophie Blackburn, and Hannah L. Cloke
Nat. Hazards Earth Syst. Sci., 24, 2633–2646, https://doi.org/10.5194/nhess-24-2633-2024, https://doi.org/10.5194/nhess-24-2633-2024, 2024
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What’s the worst that could happen? Recent floods are often claimed to be beyond our imagination. Imagination is the picturing of a situation in our mind and the emotions that we connect with this situation. But why is this important for disasters? This survey found that when we cannot imagine a devastating flood, we are not preparing in advance. Severe-weather forecasts and warnings need to advance in order to trigger our imagination of what might happen and enable us to start preparing.
Raphael Portmann, Timo Schmid, Leonie Villiger, David N. Bresch, and Pierluigi Calanca
Nat. Hazards Earth Syst. Sci., 24, 2541–2558, https://doi.org/10.5194/nhess-24-2541-2024, https://doi.org/10.5194/nhess-24-2541-2024, 2024
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The study presents an open-source model to determine the occurrence of hail damage to field crops and grapevines after hailstorms in Switzerland based on radar, agricultural land use data, and insurance damage reports. The model performs best at 8 km resolution for field crops and 1 km for grapevine and in the main production areas. Highlighting performance trade-offs and the relevance of user needs, the study is a first step towards the assessment of risk and damage for crops in Switzerland.
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Short summary
Major drought in East Africa at the end of 2016 caused severe famine and loss of life. We pose the following question: are increasing levels of atmospheric greenhouse gas concentrations, due to human activity, making droughts such as this more likely? Computer models of the climate system are powerful tools to answer this. Scanning across a full set of these, we find that how future climate change will impact on East Africa ASO drought risk remains uncertain, in any particular year.
Major drought in East Africa at the end of 2016 caused severe famine and loss of life. We pose...
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