2021 |
Sillmann, Jana; Shepherd, Theodore G; van den Hurk, Bart; Hazeleger, Wilco; Martius, Olivia; Slingo, Julia; Zscheischler, Jakob Event‐based storylines to address climate risk Journal Article Earth's Future, 9 , pp. 1–6, 2021, ISSN: 2328-4277. @article{Sillmann2021, title = {Event‐based storylines to address climate risk}, author = {Jana Sillmann and Theodore G Shepherd and Bart van den Hurk and Wilco Hazeleger and Olivia Martius and Julia Slingo and Jakob Zscheischler}, url = {https://onlinelibrary.wiley.com/doi/10.1029/2020EF001783}, doi = {10.1029/2020EF001783}, issn = {2328-4277}, year = {2021}, date = {2021-12-01}, journal = {Earth's Future}, volume = {9}, pages = {1--6}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Bevacqua, Emanuele; Michele, Carlo De; Manning, Colin; Couasnon, Anaïs; Ribeiro, Andreia F S; Ramos, Alexandre M; Vignotto, Edoardo; Bastos, Ana; Blesić, Suzana; Durante, Fabrizio; Hillier, John; Oliveira, Sérgio C; Pinto, Joaquim G; Ragno, Elisa; Rivoire, Pauline; Saunders, Kate; van der Wiel, Karin; Wu, Wenyan; Zhang, Tianyi; Zscheischler, Jakob Guidelines for studying diverse types of compound weather and climate events Journal Article Earth's Future, n/a (n/a), pp. e2021EF002340, 2021, (e2021EF002340 2021EF002340). Abstract | Links | BibTeX | Tags: Climate change, compound events, Environmental risk, Guidelines, Multidisciplinary, Typology @article{Bevacqua2021c, title = {Guidelines for studying diverse types of compound weather and climate events}, author = {Emanuele Bevacqua and Carlo De Michele and Colin Manning and Ana\"{i}s Couasnon and Andreia F S Ribeiro and Alexandre M Ramos and Edoardo Vignotto and Ana Bastos and Suzana Blesi\'{c} and Fabrizio Durante and John Hillier and S\'{e}rgio C Oliveira and Joaquim G Pinto and Elisa Ragno and Pauline Rivoire and Kate Saunders and Karin van der Wiel and Wenyan Wu and Tianyi Zhang and Jakob Zscheischler}, url = {https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2021EF002340}, doi = {https://doi.org/10.1029/2021EF002340}, year = {2021}, date = {2021-10-25}, journal = {Earth's Future}, volume = {n/a}, number = {n/a}, pages = {e2021EF002340}, abstract = {Abstract Compound weather and climate events are combinations of climate drivers and/or hazards that contribute to societal or environmental risk. Studying compound events often requires a multidisciplinary approach combining domain knowledge of the underlying processes with, for example, statistical methods and climate model outputs. Recently, to aid the development of research on compound events, four compound event types were introduced, namely (1) preconditioned, (2) multivariate, (3) temporally compounding, and (4) spatially compounding events. However, guidelines on how to study these types of events are still lacking. Here, we consider four case studies, each associated with a specific event type and a research question, to illustrate how the key elements of compound events (e.g., analytical tools and relevant physical effects) can be identified. These case studies show that (1) impacts on crops from hot and dry summers can be exacerbated by preconditioning effects of dry and bright springs. (2) Assessing compound coastal flooding in Perth (Australia) requires considering the dynamics of a non-stationary multivariate process. For instance, future mean sea-level rise will lead to the emergence of concurrent coastal and fluvial extremes, enhancing compound flooding risk. (3) In Portugal, deep-landslides are often caused by temporal clusters of moderate precipitation events. Finally, (4) crop yield failures in France and Germany are strongly correlated, threatening European food security through spatially compounding effects. These analyses allow for identifying general recommendations for studying compound events. Overall, our insights can serve as a blueprint for compound event analysis across disciplines and sectors.}, note = {e2021EF002340 2021EF002340}, keywords = {Climate change, compound events, Environmental risk, Guidelines, Multidisciplinary, Typology}, pubstate = {published}, tppubtype = {article} } Abstract Compound weather and climate events are combinations of climate drivers and/or hazards that contribute to societal or environmental risk. Studying compound events often requires a multidisciplinary approach combining domain knowledge of the underlying processes with, for example, statistical methods and climate model outputs. Recently, to aid the development of research on compound events, four compound event types were introduced, namely (1) preconditioned, (2) multivariate, (3) temporally compounding, and (4) spatially compounding events. However, guidelines on how to study these types of events are still lacking. Here, we consider four case studies, each associated with a specific event type and a research question, to illustrate how the key elements of compound events (e.g., analytical tools and relevant physical effects) can be identified. These case studies show that (1) impacts on crops from hot and dry summers can be exacerbated by preconditioning effects of dry and bright springs. (2) Assessing compound coastal flooding in Perth (Australia) requires considering the dynamics of a non-stationary multivariate process. For instance, future mean sea-level rise will lead to the emergence of concurrent coastal and fluvial extremes, enhancing compound flooding risk. (3) In Portugal, deep-landslides are often caused by temporal clusters of moderate precipitation events. Finally, (4) crop yield failures in France and Germany are strongly correlated, threatening European food security through spatially compounding effects. These analyses allow for identifying general recommendations for studying compound events. Overall, our insights can serve as a blueprint for compound event analysis across disciplines and sectors. |
Owen, Laura E; Catto, Jennifer L; Dunstone, Nick J; Stephenson, David B How well can a seasonal forecast system represent three hourly compound wind and precipitation extremes over Europe? Journal Article Environmental Research Letters, 16 (7), pp. 074019, 2021. Abstract | Links | BibTeX | Tags: @article{Owen2021ERL, title = {How well can a seasonal forecast system represent three hourly compound wind and precipitation extremes over Europe?}, author = {Laura E Owen and Jennifer L Catto and Nick J Dunstone and David B Stephenson}, url = {https://doi.org/10.1088/1748-9326/ac092e}, doi = {10.1088/1748-9326/ac092e}, year = {2021}, date = {2021-06-01}, journal = {Environmental Research Letters}, volume = {16}, number = {7}, pages = {074019}, publisher = {IOP Publishing}, abstract = {Extreme precipitation and winds can have a severe impact on society, particularly when they occur at the same place and time. In this study the Met Office’s Global Seasonal forecast system version 5 (GloSea5) model ensembles are evaluated against the reanalysis dataset ERA5, to find out how well they represent three hourly extreme precipitation, extreme wind and extreme co-occurring events over Europe. Although substantial differences in magnitude are found between precipitation and wind extremes between the datasets, the conditional probability of exceedance above the 99th percentile, which measures the co-occurrence between the two extremes, compares well spatially over Europe. However, significant differences in frequency are found around and over some areas of high topography. Generally GloSea5 underestimates this co-occurrence over sea. The model’s co-occurring events at individual locations investigated occur with very similar synoptic patterns to ERA5, indicating that the compound extremes are produced for the correct reasons.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Extreme precipitation and winds can have a severe impact on society, particularly when they occur at the same place and time. In this study the Met Office’s Global Seasonal forecast system version 5 (GloSea5) model ensembles are evaluated against the reanalysis dataset ERA5, to find out how well they represent three hourly extreme precipitation, extreme wind and extreme co-occurring events over Europe. Although substantial differences in magnitude are found between precipitation and wind extremes between the datasets, the conditional probability of exceedance above the 99th percentile, which measures the co-occurrence between the two extremes, compares well spatially over Europe. However, significant differences in frequency are found around and over some areas of high topography. Generally GloSea5 underestimates this co-occurrence over sea. The model’s co-occurring events at individual locations investigated occur with very similar synoptic patterns to ERA5, indicating that the compound extremes are produced for the correct reasons. |
Vogel, Johannes; Rivoire, Pauline; Deidda, Cristina; Rahimi, Leila; Sauter, Christoph Alexander; Tschumi, Elisabeth; van der Wiel, Karin; Zhang, Tianyi; Zscheischler, Jakob Identifying meteorological drivers of extreme impacts: an application to simulated crop yields Journal Article Earth System Dynamics, 12 (1), pp. 151–172, 2021, ISSN: 2190-4987. Abstract | Links | BibTeX | Tags: Agriculture, Climatology, Collinearity, Crop yield, Environmental science, Growing season, Lasso (statistics), Precipitation, Statistical model, Vapour Pressure Deficit @article{Vogel2021, title = {Identifying meteorological drivers of extreme impacts: an application to simulated crop yields}, author = {Johannes Vogel and Pauline Rivoire and Cristina Deidda and Leila Rahimi and Christoph Alexander Sauter and Elisabeth Tschumi and Karin van der Wiel and Tianyi Zhang and Jakob Zscheischler}, url = {https://esd.copernicus.org/articles/12/151/2021/}, doi = {10.5194/esd-12-151-2021}, issn = {2190-4987}, year = {2021}, date = {2021-02-01}, journal = {Earth System Dynamics}, volume = {12}, number = {1}, pages = {151--172}, abstract = {Compound weather events may lead to extreme impacts that can affect many aspects of society including agriculture. Identifying the underlying mechanisms that cause extreme impacts, such as crop failure, is of crucial importance to improve their understanding and forecasting. In this study, we investigate whether key meteorological drivers of extreme impacts can be identified using the least absolute shrinkage and selection operator (LASSO) in a model environment, a method that allows for automated variable selection and is able to handle collinearity between variables. As an example of an extreme impact, we investigate crop failure using annual wheat yield as simulated by the Agricultural Production Systems sIMulator (APSIM) crop model driven by 1600 years of daily weather data from a global climate model (EC-Earth) under present-day conditions for the Northern Hemisphere. We then apply LASSO logistic regression to determine which weather conditions during the growing season lead to crop failure. We obtain good model performance in central Europe and the eastern half of the United States, while crop failure years in regions in Asia and the western half of the United States are less accurately predicted. Model performance correlates strongly with annual mean and variability of crop yields; that is, model performance is highest in regions with relatively large annual crop yield mean and variability. Overall, for nearly all grid points, the inclusion of temperature, precipitation and vapour pressure deficit is key to predict crop failure. In addition, meteorological predictors during all seasons are required for a good prediction. These results illustrate the omnipresence of compounding effects of both meteorological drivers and different periods of the growing season for creating crop failure events. Especially vapour pressure deficit and climate extreme indicators such as diurnal temperature range and the number of frost days are selected by the statistical model as relevant predictors for crop failure at most grid points, underlining their overarching relevance. We conclude that the LASSO regression model is a useful tool to automatically detect compound drivers of extreme impacts and could be applied to other weather impacts such as wildfires or floods. As the detected relationships are of purely correlative nature, more detailed analyses are required to establish the causal structure between drivers and impacts.}, keywords = {Agriculture, Climatology, Collinearity, Crop yield, Environmental science, Growing season, Lasso (statistics), Precipitation, Statistical model, Vapour Pressure Deficit}, pubstate = {published}, tppubtype = {article} } Compound weather events may lead to extreme impacts that can affect many aspects of society including agriculture. Identifying the underlying mechanisms that cause extreme impacts, such as crop failure, is of crucial importance to improve their understanding and forecasting. In this study, we investigate whether key meteorological drivers of extreme impacts can be identified using the least absolute shrinkage and selection operator (LASSO) in a model environment, a method that allows for automated variable selection and is able to handle collinearity between variables. As an example of an extreme impact, we investigate crop failure using annual wheat yield as simulated by the Agricultural Production Systems sIMulator (APSIM) crop model driven by 1600 years of daily weather data from a global climate model (EC-Earth) under present-day conditions for the Northern Hemisphere. We then apply LASSO logistic regression to determine which weather conditions during the growing season lead to crop failure. We obtain good model performance in central Europe and the eastern half of the United States, while crop failure years in regions in Asia and the western half of the United States are less accurately predicted. Model performance correlates strongly with annual mean and variability of crop yields; that is, model performance is highest in regions with relatively large annual crop yield mean and variability. Overall, for nearly all grid points, the inclusion of temperature, precipitation and vapour pressure deficit is key to predict crop failure. In addition, meteorological predictors during all seasons are required for a good prediction. These results illustrate the omnipresence of compounding effects of both meteorological drivers and different periods of the growing season for creating crop failure events. Especially vapour pressure deficit and climate extreme indicators such as diurnal temperature range and the number of frost days are selected by the statistical model as relevant predictors for crop failure at most grid points, underlining their overarching relevance. We conclude that the LASSO regression model is a useful tool to automatically detect compound drivers of extreme impacts and could be applied to other weather impacts such as wildfires or floods. As the detected relationships are of purely correlative nature, more detailed analyses are required to establish the causal structure between drivers and impacts. |
Pfleiderer, Peter; Jézéquel, Aglaé; Legrand, Juliette; Legrix, Natacha; Markantonis, Iason; Vignotto, Edoardo; Yiou, Pascal Simulating compound weather extremes responsible for critical crop failure with stochastic weather generators Journal Article Earth System Dynamics, 12 (1), pp. 103–120, 2021, ISSN: 2190-4987. Links | BibTeX | Tags: Climate model, Climatology, Crop failure, Crop loss, Environmental science, Importance sampling, Precipitation, Spring season, Weather generator @article{Pfleiderer2021, title = {Simulating compound weather extremes responsible for critical crop failure with stochastic weather generators}, author = {Peter Pfleiderer and Agla\'{e} J\'{e}z\'{e}quel and Juliette Legrand and Natacha Legrix and Iason Markantonis and Edoardo Vignotto and Pascal Yiou}, url = {https://esd.copernicus.org/articles/12/103/2021/}, doi = {10.5194/esd-12-103-2021}, issn = {2190-4987}, year = {2021}, date = {2021-02-01}, journal = {Earth System Dynamics}, volume = {12}, number = {1}, pages = {103--120}, keywords = {Climate model, Climatology, Crop failure, Crop loss, Environmental science, Importance sampling, Precipitation, Spring season, Weather generator}, pubstate = {published}, tppubtype = {article} } |
Geirinhas, João; Russo, Ana; Libonati, Renata; Sousa, Pedro M; Miralles, Diego G; Trigo, Ricardo M Recent increasing frequency of compound summer drought and heatwaves in Southeast Brazil Journal Article Environmental Research Letters, 16 (3), pp. 034036, 2021. Abstract | Links | BibTeX | Tags: Brazil, drought & heat @article{Geirinhas_2021, title = {Recent increasing frequency of compound summer drought and heatwaves in Southeast Brazil}, author = {Jo\~{a}o Geirinhas and Ana Russo and Renata Libonati and Pedro M Sousa and Diego G Miralles and Ricardo M Trigo}, url = {https://doi.org/10.1088/1748-9326/abe0eb}, doi = {10.1088/1748-9326/abe0eb}, year = {2021}, date = {2021-02-01}, journal = {Environmental Research Letters}, volume = {16}, number = {3}, pages = {034036}, publisher = {IOP Publishing}, abstract = {An increase in the frequency of extremely hot and dry events has been experienced over the past few decades in South America, and particularly in Brazil. Regional climate change projections indicate a future aggravation of this trend. However, a comprehensive characterization of drought and heatwave compound events, as well as of the main land\textendashatmosphere mechanisms involved, is still lacking for most of South America. This study aims to fill this gap, assessing for the first time the historical evolution of compound summer drought and heatwave events for the heavily populated region of Southeast Brazil and for the period of 1980\textendash2018. The main goal is to undertake a detailed analysis of the surface and synoptic conditions, as well as of the land\textendashatmosphere coupling processes that led to the occurrence of individual and compound dry and hot extremes. Our results confirm that the S\~{a}o Paulo, Rio de Janeiro and Minas Gerais states have recorded pronounced and statistically significant increases in the number of compound summer drought and heatwave episodes. In particular, the last decade was characterized by two austral summer seasons (2013/14 and 2014/15) with outstanding concurrent drought and heatwave conditions stemmed by severe precipitation deficits and a higher-than-average occurrence of blocking patterns. As result of these land and atmosphere conditions, a high coupling (water-limited) regime was imposed, promoting the re-amplification of hot spells that resulted in mega heatwave episodes. Our findings reveal a substantial contribution of persistent dry conditions to heatwave episodes, highlighting the vulnerability of the region to climate change.}, keywords = {Brazil, drought & heat}, pubstate = {published}, tppubtype = {article} } An increase in the frequency of extremely hot and dry events has been experienced over the past few decades in South America, and particularly in Brazil. Regional climate change projections indicate a future aggravation of this trend. However, a comprehensive characterization of drought and heatwave compound events, as well as of the main land–atmosphere mechanisms involved, is still lacking for most of South America. This study aims to fill this gap, assessing for the first time the historical evolution of compound summer drought and heatwave events for the heavily populated region of Southeast Brazil and for the period of 1980–2018. The main goal is to undertake a detailed analysis of the surface and synoptic conditions, as well as of the land–atmosphere coupling processes that led to the occurrence of individual and compound dry and hot extremes. Our results confirm that the São Paulo, Rio de Janeiro and Minas Gerais states have recorded pronounced and statistically significant increases in the number of compound summer drought and heatwave episodes. In particular, the last decade was characterized by two austral summer seasons (2013/14 and 2014/15) with outstanding concurrent drought and heatwave conditions stemmed by severe precipitation deficits and a higher-than-average occurrence of blocking patterns. As result of these land and atmosphere conditions, a high coupling (water-limited) regime was imposed, promoting the re-amplification of hot spells that resulted in mega heatwave episodes. Our findings reveal a substantial contribution of persistent dry conditions to heatwave episodes, highlighting the vulnerability of the region to climate change. |
Flach, M; Brenning, A; Gans, F; Reichstein, M; Sippel, S; Mahecha, M D Vegetation modulates the impact of climate extremes on gross primary production Journal Article Biogeosciences, 18 (1), pp. 39–53, 2021. Abstract | Links | BibTeX | Tags: drought & heat @article{Flach2021, title = {Vegetation modulates the impact of climate extremes on gross primary production}, author = {M Flach and A Brenning and F Gans and M Reichstein and S Sippel and M D Mahecha}, url = {https://bg.copernicus.org/articles/18/39/2021/}, doi = {10.5194/bg-18-39-2021}, year = {2021}, date = {2021-01-01}, journal = {Biogeosciences}, volume = {18}, number = {1}, pages = {39--53}, abstract = {Drought and heat events affect the uptake and sequestration of carbon in terrestrial ecosystems. Factors such as the duration, timing, and intensity of extreme events influence the magnitude of impacts on ecosystem processes such as gross primary production (GPP), i.e., the ecosystem uptake of CO2. Preceding soil moisture depletion may exacerbate these impacts. However, some vegetation types may be more resilient to climate extremes than others. This effect is insufficiently understood at the global scale and is the focus of this study. Using a global upscaled product of GPP that scales up in situ land CO2 flux observations with global satellite remote sensing, we study the impact of climate extremes at the global scale. We find that GPP in grasslands and agricultural areas is generally reduced during heat and drought events. However, we also find that forests, if considered globally, appear in general to not be particularly sensitive to droughts and heat events that occurred during the analyzed period or even show increased GPP values during these events. On the one hand, normal-to-increased GPP values are in many cases plausible, e.g., when conditions prior to the event have been particularly positive. On the other hand, however, normal-to-increased GPP values in forests may also reflect a lack of sensitivity in current remote-sensing-derived GPP products to the effects of droughts and heatwaves. The overall picture calls for a differentiated consideration of different land cover types in the assessments of risks of climate extremes for ecosystem functioning.}, keywords = {drought & heat}, pubstate = {published}, tppubtype = {article} } Drought and heat events affect the uptake and sequestration of carbon in terrestrial ecosystems. Factors such as the duration, timing, and intensity of extreme events influence the magnitude of impacts on ecosystem processes such as gross primary production (GPP), i.e., the ecosystem uptake of CO2. Preceding soil moisture depletion may exacerbate these impacts. However, some vegetation types may be more resilient to climate extremes than others. This effect is insufficiently understood at the global scale and is the focus of this study. Using a global upscaled product of GPP that scales up in situ land CO2 flux observations with global satellite remote sensing, we study the impact of climate extremes at the global scale. We find that GPP in grasslands and agricultural areas is generally reduced during heat and drought events. However, we also find that forests, if considered globally, appear in general to not be particularly sensitive to droughts and heat events that occurred during the analyzed period or even show increased GPP values during these events. On the one hand, normal-to-increased GPP values are in many cases plausible, e.g., when conditions prior to the event have been particularly positive. On the other hand, however, normal-to-increased GPP values in forests may also reflect a lack of sensitivity in current remote-sensing-derived GPP products to the effects of droughts and heatwaves. The overall picture calls for a differentiated consideration of different land cover types in the assessments of risks of climate extremes for ecosystem functioning. |
Zscheischler, Jakob; Naveau, Philippe; Martius, Olivia; Engelke, Sebastian; Raible, Christoph C Evaluating the dependence structure of compound precipitation and wind speed extremes Journal Article Earth System Dynamics, 12 (1), pp. 1–16, 2021, ISSN: 2190-4987. Links | BibTeX | Tags: Boundary value problem, Climate model, Climatology, Environmental science, Forcing (mathematics), Greenhouse gas, hydrological compound events, multivariate, Orographic lift, Precipitation, Weather Research and Forecasting Model @article{Zscheischler2021, title = {Evaluating the dependence structure of compound precipitation and wind speed extremes}, author = {Jakob Zscheischler and Philippe Naveau and Olivia Martius and Sebastian Engelke and Christoph C Raible}, url = {https://esd.copernicus.org/articles/12/1/2021/}, doi = {10.5194/esd-12-1-2021}, issn = {2190-4987}, year = {2021}, date = {2021-01-01}, journal = {Earth System Dynamics}, volume = {12}, number = {1}, pages = {1--16}, keywords = {Boundary value problem, Climate model, Climatology, Environmental science, Forcing (mathematics), Greenhouse gas, hydrological compound events, multivariate, Orographic lift, Precipitation, Weather Research and Forecasting Model}, pubstate = {published}, tppubtype = {article} } |
Whan, Kirien; Zscheischler, Jakob; Jordan, Alexander I; Ziegel, Johanna F Novel multivariate quantile mapping methods for ensemble post-processing of medium-range forecasts Journal Article Weather and Climate Extremes, pp. 100310, 2021, ISSN: 2212-0947. Abstract | Links | BibTeX | Tags: compound events, ensemble model output statistics, quantile mapping, statistical post-processing @article{Whan2021, title = {Novel multivariate quantile mapping methods for ensemble post-processing of medium-range forecasts}, author = {Kirien Whan and Jakob Zscheischler and Alexander I Jordan and Johanna F Ziegel}, url = {https://www.sciencedirect.com/science/article/pii/S2212094721000086}, doi = {https://doi.org/10.1016/j.wace.2021.100310}, issn = {2212-0947}, year = {2021}, date = {2021-01-01}, journal = {Weather and Climate Extremes}, pages = {100310}, abstract = {Statistical post-processing is an indispensable tool for providing accurate weather forecasts and early warnings for weather extremes. Most statistical post-processing is univariate, with dependencies introduced via use of an empirical copula. Standard empirical methods take a dependence template from either the raw ensemble output (ensemble copula coupling, ECC) or the observations (Schaake Shuffle, SSh). There are drawbacks to both methods. In ECC it is assumed that the raw ensemble simulates the dependence well, which is not always the case (e.g. 2-meter temperature in The Netherlands). The Schaake Shuffle is not able to capture flow dependent changes to the dependence and the choice of observations is key. Here we compare a re-shuffled standard ensemble model output statistics (EMOS) approach with two multivariate bias adjustment approaches that have not been used before in a post-processing context: 1) the multivariate bias correction with N-dimensional probability density function transform (MBCn) and 2) multivariate ranks that are defined with optimal assignment (OA). These methods have the advantage that they are able to explicitly capture the dependence structure that is present in the observations. We apply ECC, the Schaake Shuffle, MBCn and OA to 2-meter and dew point temperature forecasts at seven stations in The Netherlands. Forecasts are verified with both univariate and multivariate methods, and using a heat index derived from both variables, the wet-bulb globe temperature (WBGT). Our results demonstrate that the spatial and inter-variable dependence structure is more realistic in MBCn and OA compared to ECC or the Schaake Shuffle. The variogram score shows that while ECC is most skilful for the first two days, at moderate lead times MBCn is most skilful and at the longest lead times OA is more skilful than both ECC and MBCn. Overall, we highlight the importance of considering the dependence between variables and locations in the statistical post-processing of weather forecasts.}, keywords = {compound events, ensemble model output statistics, quantile mapping, statistical post-processing}, pubstate = {published}, tppubtype = {article} } Statistical post-processing is an indispensable tool for providing accurate weather forecasts and early warnings for weather extremes. Most statistical post-processing is univariate, with dependencies introduced via use of an empirical copula. Standard empirical methods take a dependence template from either the raw ensemble output (ensemble copula coupling, ECC) or the observations (Schaake Shuffle, SSh). There are drawbacks to both methods. In ECC it is assumed that the raw ensemble simulates the dependence well, which is not always the case (e.g. 2-meter temperature in The Netherlands). The Schaake Shuffle is not able to capture flow dependent changes to the dependence and the choice of observations is key. Here we compare a re-shuffled standard ensemble model output statistics (EMOS) approach with two multivariate bias adjustment approaches that have not been used before in a post-processing context: 1) the multivariate bias correction with N-dimensional probability density function transform (MBCn) and 2) multivariate ranks that are defined with optimal assignment (OA). These methods have the advantage that they are able to explicitly capture the dependence structure that is present in the observations. We apply ECC, the Schaake Shuffle, MBCn and OA to 2-meter and dew point temperature forecasts at seven stations in The Netherlands. Forecasts are verified with both univariate and multivariate methods, and using a heat index derived from both variables, the wet-bulb globe temperature (WBGT). Our results demonstrate that the spatial and inter-variable dependence structure is more realistic in MBCn and OA compared to ECC or the Schaake Shuffle. The variogram score shows that while ECC is most skilful for the first two days, at moderate lead times MBCn is most skilful and at the longest lead times OA is more skilful than both ECC and MBCn. Overall, we highlight the importance of considering the dependence between variables and locations in the statistical post-processing of weather forecasts. |
Vogel, Johannes; Paton, Eva; Aich, Valentin; Bronstert, Axel Increasing compound warm spells and droughts in the Mediterranean Basin Journal Article Weather and Climate Extremes, pp. 100312, 2021, ISSN: 2212-0947. Abstract | Links | BibTeX | Tags: Climate change, compound events, Droughts, extreme events, Mediterranean Basin, Warm spells @article{Vogel2021b, title = {Increasing compound warm spells and droughts in the Mediterranean Basin}, author = {Johannes Vogel and Eva Paton and Valentin Aich and Axel Bronstert}, url = {https://www.sciencedirect.com/science/article/pii/S2212094721000104}, doi = {https://doi.org/10.1016/j.wace.2021.100312}, issn = {2212-0947}, year = {2021}, date = {2021-01-01}, journal = {Weather and Climate Extremes}, pages = {100312}, abstract = {The co-occurrence of warm spells and droughts can lead to detrimental socio-economic and ecological impacts, largely surpassing the impacts of either warm spells or droughts alone. We quantify changes in the number of compound warm spells and droughts from 1979 - 2018 in the Mediterranean Basin using the ERA5 data set. We analyse two types of compound events: 1) warm season compound events, which are extreme in absolute terms in the warm season from May to October and 2) year-round deseasonalised compound events, which are extreme in relative terms respective to the time of the year. The number of compound events increases significantly and especially warm spells are increasing strongly \textendash with an annual growth rates of 3.9 (3.5) % for warm season (deseasonalised) compound events and 4.6 (4.4) % for warm spells \textendash, whereas for droughts the change is more ambiguous depending on the applied definition. Therefore, the rise in the number of compound events is primarily driven by temperature changes and not the lack of precipitation. The months July and August show the highest increases in warm season compound events, whereas the highest increases of deseasonalised compound events occur in spring and early summer. This increase in deseasonalised compound events can potentially have a significant impact on the functioning of Mediterranean ecosystems as this is the peak phase of ecosystem productivity and a vital phenophase.}, keywords = {Climate change, compound events, Droughts, extreme events, Mediterranean Basin, Warm spells}, pubstate = {published}, tppubtype = {article} } The co-occurrence of warm spells and droughts can lead to detrimental socio-economic and ecological impacts, largely surpassing the impacts of either warm spells or droughts alone. We quantify changes in the number of compound warm spells and droughts from 1979 - 2018 in the Mediterranean Basin using the ERA5 data set. We analyse two types of compound events: 1) warm season compound events, which are extreme in absolute terms in the warm season from May to October and 2) year-round deseasonalised compound events, which are extreme in relative terms respective to the time of the year. The number of compound events increases significantly and especially warm spells are increasing strongly – with an annual growth rates of 3.9 (3.5) % for warm season (deseasonalised) compound events and 4.6 (4.4) % for warm spells –, whereas for droughts the change is more ambiguous depending on the applied definition. Therefore, the rise in the number of compound events is primarily driven by temperature changes and not the lack of precipitation. The months July and August show the highest increases in warm season compound events, whereas the highest increases of deseasonalised compound events occur in spring and early summer. This increase in deseasonalised compound events can potentially have a significant impact on the functioning of Mediterranean ecosystems as this is the peak phase of ecosystem productivity and a vital phenophase. |
Woo, Gordon A counterfactual perspective on compound weather risk Journal Article Weather and Climate Extremes, pp. 100314, 2021, ISSN: 2212-0947. Abstract | Links | BibTeX | Tags: Climate change, Compound weather, counterfactual, database, near miss @article{Woo2021, title = {A counterfactual perspective on compound weather risk}, author = {Gordon Woo}, url = {https://www.sciencedirect.com/science/article/pii/S2212094721000128}, doi = {https://doi.org/10.1016/j.wace.2021.100314}, issn = {2212-0947}, year = {2021}, date = {2021-01-01}, journal = {Weather and Climate Extremes}, pages = {100314}, abstract = {ABSTRACT Extreme weather outcomes are a multi-dimensional function of interacting physical processes. Actual compound events correspond to particular specific historical realisations of these coupled processes. But due to their intrinsic stochastic nature, they might have led to different outcomes. Historical meteorological studies tend to focus on explaining what actually happened, rather than on considering the phase space of other possibilities. In contrast with extreme event catalogues, information about near misses and proximity to tipping points is not systematically collated. Consequently, stakeholder awareness of such high risk system states is limited. The exploration of alternative realisations provides a counterfactual perspective on compound weather risk, which broadens understanding of extreme weather events, especially in respect of severe impact consequences. This perspective would be an insightful supplement to statistical studies of extreme compound events.}, keywords = {Climate change, Compound weather, counterfactual, database, near miss}, pubstate = {published}, tppubtype = {article} } ABSTRACT Extreme weather outcomes are a multi-dimensional function of interacting physical processes. Actual compound events correspond to particular specific historical realisations of these coupled processes. But due to their intrinsic stochastic nature, they might have led to different outcomes. Historical meteorological studies tend to focus on explaining what actually happened, rather than on considering the phase space of other possibilities. In contrast with extreme event catalogues, information about near misses and proximity to tipping points is not systematically collated. Consequently, stakeholder awareness of such high risk system states is limited. The exploration of alternative realisations provides a counterfactual perspective on compound weather risk, which broadens understanding of extreme weather events, especially in respect of severe impact consequences. This perspective would be an insightful supplement to statistical studies of extreme compound events. |
Vignotto, Edoardo; Engelke, Sebastian; Zscheischler, Jakob Clustering bivariate dependencies of compound precipitation and wind extremes over Great Britain and Ireland Journal Article Weather and Climate Extremes, pp. 100318, 2021, ISSN: 2212-0947. Abstract | Links | BibTeX | Tags: compound events, extremes, spatial clustering @article{Vignotto2021, title = {Clustering bivariate dependencies of compound precipitation and wind extremes over Great Britain and Ireland}, author = {Edoardo Vignotto and Sebastian Engelke and Jakob Zscheischler}, url = {https://www.sciencedirect.com/science/article/pii/S2212094721000165}, doi = {https://doi.org/10.1016/j.wace.2021.100318}, issn = {2212-0947}, year = {2021}, date = {2021-01-01}, journal = {Weather and Climate Extremes}, pages = {100318}, abstract = {Identifying hidden spatial patterns that define sub-regions characterized by a similar behaviour is a central topic in statistical climatology. This task, often called regionalization, is helpful for recognizing areas in which the variables under consideration have a similar stochastic distribution and thus, potentially, for reducing the dimensionality of the data. Many examples for regionalization are available, spanning from hydrology to weather and climate science. However, the majority of regionalization techniques focuses on the spatial clustering of a single variable of interest and is often not tailored to extremes. Extreme events often have severe impacts, which can be amplified when co-occurring with extremes in other variables. Given the importance of characterizing compound extreme events at the regional scale, here we develop an algorithm that identifies homogeneous spatial sub-regions that are characterized by a common bivariate dependence structure in the tails of a bivariate distribution. In particular, we use a novel non-parametric divergence able to capture the similarities and differences in the tail behaviour of bivariate distributions as the core of our clustering procedure. We apply the approach to identify homogeneous regions that exhibit similar likelihood of compound precipitation and wind extremes in Great Britain and Ireland.}, keywords = {compound events, extremes, spatial clustering}, pubstate = {published}, tppubtype = {article} } Identifying hidden spatial patterns that define sub-regions characterized by a similar behaviour is a central topic in statistical climatology. This task, often called regionalization, is helpful for recognizing areas in which the variables under consideration have a similar stochastic distribution and thus, potentially, for reducing the dimensionality of the data. Many examples for regionalization are available, spanning from hydrology to weather and climate science. However, the majority of regionalization techniques focuses on the spatial clustering of a single variable of interest and is often not tailored to extremes. Extreme events often have severe impacts, which can be amplified when co-occurring with extremes in other variables. Given the importance of characterizing compound extreme events at the regional scale, here we develop an algorithm that identifies homogeneous spatial sub-regions that are characterized by a common bivariate dependence structure in the tails of a bivariate distribution. In particular, we use a novel non-parametric divergence able to capture the similarities and differences in the tail behaviour of bivariate distributions as the core of our clustering procedure. We apply the approach to identify homogeneous regions that exhibit similar likelihood of compound precipitation and wind extremes in Great Britain and Ireland. |
Li, J; Wang, Z; Wu, X; Zscheischler, J; Guo, S; Chen, X A standardized index for assessing sub-monthly compound dry and hot conditions with application in China Journal Article Hydrology and Earth System Sciences, 25 (3), pp. 1587–1601, 2021. @article{Li2021, title = {A standardized index for assessing sub-monthly compound dry and hot conditions with application in China}, author = {J Li and Z Wang and X Wu and J Zscheischler and S Guo and X Chen}, url = {https://hess.copernicus.org/articles/25/1587/2021/}, doi = {10.5194/hess-25-1587-2021}, year = {2021}, date = {2021-01-01}, journal = {Hydrology and Earth System Sciences}, volume = {25}, number = {3}, pages = {1587--1601}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Santos, V M; Casas-Prat, M; Poschlod, B; Ragno, E; van den Hurk, B; Hao, Z; Kalmár, T; Zhu, L; Najafi, H Hydrology and Earth System Sciences, 25 (6), pp. 3595–3615, 2021. @article{Santos2021, title = {Statistical modelling and climate variability of compound surge and precipitation events in a managed water system: a case study in the Netherlands}, author = {V M Santos and M Casas-Prat and B Poschlod and E Ragno and B van den Hurk and Z Hao and T Kalm\'{a}r and L Zhu and H Najafi}, url = {https://hess.copernicus.org/articles/25/3595/2021/}, doi = {10.5194/hess-25-3595-2021}, year = {2021}, date = {2021-01-01}, journal = {Hydrology and Earth System Sciences}, volume = {25}, number = {6}, pages = {3595--3615}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Grix, Le N; Zscheischler, J; Laufkötter, C; Rousseaux, C S; Frölicher, T L Compound high-temperature and low-chlorophyll extremes in the ocean over the satellite period Journal Article Biogeosciences, 18 (6), pp. 2119–2137, 2021. @article{Legrix2021, title = {Compound high-temperature and low-chlorophyll extremes in the ocean over the satellite period}, author = {N Le Grix and J Zscheischler and C Laufk\"{o}tter and C S Rousseaux and T L Fr\"{o}licher}, url = {https://bg.copernicus.org/articles/18/2119/2021/}, doi = {10.5194/bg-18-2119-2021}, year = {2021}, date = {2021-01-01}, journal = {Biogeosciences}, volume = {18}, number = {6}, pages = {2119--2137}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Luan, X; Vico, G Hydrology and Earth System Sciences, 25 (3), pp. 1411–1423, 2021. @article{Luan2021, title = {Canopy temperature and heat stress are increased by compound high air temperature and water stress and reduced by irrigation - a modeling analysis}, author = {X Luan and G Vico}, url = {https://hess.copernicus.org/articles/25/1411/2021/}, doi = {10.5194/hess-25-1411-2021}, year = {2021}, date = {2021-01-01}, journal = {Hydrology and Earth System Sciences}, volume = {25}, number = {3}, pages = {1411--1423}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Villalobos-Herrera, R; Bevacqua, E; Ribeiro, A F S; Auld, G; Crocetti, L; Mircheva, B; Ha, M; Zscheischler, J; Michele, De C Natural Hazards and Earth System Sciences, 21 (6), pp. 1867–1885, 2021. @article{Villalobos-Herrera2021, title = {Towards a compound-event-oriented climate model evaluation: a decomposition of the underlying biases in multivariate fire and heat stress hazards}, author = {R Villalobos-Herrera and E Bevacqua and A F S Ribeiro and G Auld and L Crocetti and B Mircheva and M Ha and J Zscheischler and C De Michele}, url = {https://nhess.copernicus.org/articles/21/1867/2021/}, doi = {10.5194/nhess-21-1867-2021}, year = {2021}, date = {2021-01-01}, journal = {Natural Hazards and Earth System Sciences}, volume = {21}, number = {6}, pages = {1867--1885}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Sanuy, M; Rigo, T; Jiménez, J A; Llasat, M C Classifying compound coastal storm and heavy rainfall events in the north-western Spanish Mediterranean Journal Article Hydrology and Earth System Sciences, 25 (6), pp. 3759–3781, 2021. @article{Sanuy2021, title = {Classifying compound coastal storm and heavy rainfall events in the north-western Spanish Mediterranean}, author = {M Sanuy and T Rigo and J A Jim\'{e}nez and M C Llasat}, url = {https://hess.copernicus.org/articles/25/3759/2021/}, doi = {10.5194/hess-25-3759-2021}, year = {2021}, date = {2021-01-01}, journal = {Hydrology and Earth System Sciences}, volume = {25}, number = {6}, pages = {3759--3781}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Lemus-Canovas, M; Lopez-Bustins, J A Assessing internal changes in the future structure of dry-hot compound events: the case of the Pyrenees Journal Article Natural Hazards and Earth System Sciences, 21 (6), pp. 1721–1738, 2021. @article{Lemus-Canovas2021, title = {Assessing internal changes in the future structure of dry-hot compound events: the case of the Pyrenees}, author = {M Lemus-Canovas and J A Lopez-Bustins}, url = {https://nhess.copernicus.org/articles/21/1721/2021/}, doi = {10.5194/nhess-21-1721-2021}, year = {2021}, date = {2021-01-01}, journal = {Natural Hazards and Earth System Sciences}, volume = {21}, number = {6}, pages = {1721--1738}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Brunner, M I; Gilleland, E; Wood, A W Space-time dependence of compound hot-dry events in the United States: assessment using a multi-site multi-variable weather generator Journal Article Earth System Dynamics, 12 (2), pp. 621–634, 2021. @article{Brunner2021, title = {Space-time dependence of compound hot-dry events in the United States: assessment using a multi-site multi-variable weather generator}, author = {M I Brunner and E Gilleland and A W Wood}, url = {https://esd.copernicus.org/articles/12/621/2021/}, doi = {10.5194/esd-12-621-2021}, year = {2021}, date = {2021-01-01}, journal = {Earth System Dynamics}, volume = {12}, number = {2}, pages = {621--634}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Camus, P; Haigh, I D; Nasr, A A; Wahl, T; Darby, S E; Nicholls, R J Regional analysis of multivariate compound coastal flooding potential around Europe and environs: sensitivity analysis and spatial patterns Journal Article Natural Hazards and Earth System Sciences, 21 (7), pp. 2021–2040, 2021. @article{Camus2021, title = {Regional analysis of multivariate compound coastal flooding potential around Europe and environs: sensitivity analysis and spatial patterns}, author = {P Camus and I D Haigh and A A Nasr and T Wahl and S E Darby and R J Nicholls}, url = {https://nhess.copernicus.org/articles/21/2021/2021/}, doi = {10.5194/nhess-21-2021-2021}, year = {2021}, date = {2021-01-01}, journal = {Natural Hazards and Earth System Sciences}, volume = {21}, number = {7}, pages = {2021--2040}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Messmer, Martina; Simmonds, Ian Global analysis of cyclone-induced compound precipitation and wind extreme events Journal Article Weather and Climate Extremes, 32 , pp. 100324, 2021, ISSN: 2212-0947. Links | BibTeX | Tags: Compound extreme events, Cyclone tracking and detection algorithms, ERA5, Extreme precipitation, Extreme wind, Global weather extremes, Low-pressure systems @article{Messmer2021, title = {Global analysis of cyclone-induced compound precipitation and wind extreme events}, author = {Martina Messmer and Ian Simmonds}, url = {https://www.sciencedirect.com/science/article/pii/S2212094721000220}, doi = {https://doi.org/10.1016/j.wace.2021.100324}, issn = {2212-0947}, year = {2021}, date = {2021-01-01}, journal = {Weather and Climate Extremes}, volume = {32}, pages = {100324}, keywords = {Compound extreme events, Cyclone tracking and detection algorithms, ERA5, Extreme precipitation, Extreme wind, Global weather extremes, Low-pressure systems}, pubstate = {published}, tppubtype = {article} } |
Catto, Jennifer L; Dowdy, Andrew Understanding compound hazards from a weather system perspective Journal Article Weather and Climate Extremes, 32 , pp. 100313, 2021, ISSN: 2212-0947. Links | BibTeX | Tags: Compound hazards, Extreme precipitation, Extreme waves, Extreme winds, Weather systems @article{Catto2021, title = {Understanding compound hazards from a weather system perspective}, author = {Jennifer L Catto and Andrew Dowdy}, url = {https://www.sciencedirect.com/science/article/pii/S2212094721000116}, doi = {https://doi.org/10.1016/j.wace.2021.100313}, issn = {2212-0947}, year = {2021}, date = {2021-01-01}, journal = {Weather and Climate Extremes}, volume = {32}, pages = {100313}, keywords = {Compound hazards, Extreme precipitation, Extreme waves, Extreme winds, Weather systems}, pubstate = {published}, tppubtype = {article} } |
Tuel, Alexandre; Martius, Olivia A global perspective on the sub-seasonal clustering of precipitation extremes Journal Article Weather and Climate Extremes, 33 , pp. 100348, 2021, ISSN: 2212-0947. Abstract | Links | BibTeX | Tags: Precipitation extremes, Temporal clustering, Time series statistics @article{Tuel2021, title = {A global perspective on the sub-seasonal clustering of precipitation extremes}, author = {Alexandre Tuel and Olivia Martius}, url = {https://www.sciencedirect.com/science/article/pii/S2212094721000426}, doi = {https://doi.org/10.1016/j.wace.2021.100348}, issn = {2212-0947}, year = {2021}, date = {2021-01-01}, journal = {Weather and Climate Extremes}, volume = {33}, pages = {100348}, abstract = {The occurrence of several precipitation extremes over sub-seasonal time windows can have major impacts on human societies, leading for instance to floods. Here, we apply a simple statistical framework based on Ripley’s K function, at a global scale and for each season separately, to identify regions where precipitation extremes tend to cluster in time over timescales of a few days to a few weeks. We analyze several observational and reanalysis datasets, as well as output from CMIP6 Global Climate Models (GCMs). Good agreement is found on the spatio-temporal clustering patterns across datasets. Sub-seasonal temporal clustering is largely concentrated over the tropical oceans, where it can be detected year-round. It is also significant over certain tropical lands, like Eastern Africa, and seasonally outside the tropics in several regions, most notably around the eastern subtropical oceans (Iberian Peninsula and Western North America during the DJF and MAM seasons) Southwest Asia (especially during JJA and SON) and Australia (in SON). We also find that CMIP6 models generally correctly reproduce clustering patterns, paving the way for an assessment of trends in sub-seasonal clustering under climate change. Clustering of present-day extremes increases in many areas under climate change. Changes diagnosed by comparing present day and future extreme percentiles are positive and negative and strongest in the tropical areas.}, keywords = {Precipitation extremes, Temporal clustering, Time series statistics}, pubstate = {published}, tppubtype = {article} } The occurrence of several precipitation extremes over sub-seasonal time windows can have major impacts on human societies, leading for instance to floods. Here, we apply a simple statistical framework based on Ripley’s K function, at a global scale and for each season separately, to identify regions where precipitation extremes tend to cluster in time over timescales of a few days to a few weeks. We analyze several observational and reanalysis datasets, as well as output from CMIP6 Global Climate Models (GCMs). Good agreement is found on the spatio-temporal clustering patterns across datasets. Sub-seasonal temporal clustering is largely concentrated over the tropical oceans, where it can be detected year-round. It is also significant over certain tropical lands, like Eastern Africa, and seasonally outside the tropics in several regions, most notably around the eastern subtropical oceans (Iberian Peninsula and Western North America during the DJF and MAM seasons) Southwest Asia (especially during JJA and SON) and Australia (in SON). We also find that CMIP6 models generally correctly reproduce clustering patterns, paving the way for an assessment of trends in sub-seasonal clustering under climate change. Clustering of present-day extremes increases in many areas under climate change. Changes diagnosed by comparing present day and future extreme percentiles are positive and negative and strongest in the tropical areas. |
van der Wiel, Karin; Lenderink, Geert; de Vries, Hylke Physical storylines of future European drought events like 2018 based on ensemble climate modelling Journal Article Weather and Climate Extremes, 33 , pp. 100350, 2021, ISSN: 2212-0947. Abstract | Links | BibTeX | Tags: Climate change, Drought 2018, Extreme weather, Future weather, Large ensembles, storylines @article{Wiel2021, title = {Physical storylines of future European drought events like 2018 based on ensemble climate modelling}, author = {Karin van der Wiel and Geert Lenderink and Hylke de Vries}, url = {https://www.sciencedirect.com/science/article/pii/S2212094721000438}, doi = {https://doi.org/10.1016/j.wace.2021.100350}, issn = {2212-0947}, year = {2021}, date = {2021-01-01}, journal = {Weather and Climate Extremes}, volume = {33}, pages = {100350}, abstract = {In the aftermath of observed extreme weather events, questions arise on the role of climate change in such events and what future events might look like. We present a method for the development of physical storylines of future events comparable to a chosen observed event, to answer some of these questions. A storyline approach, focusing on physical processes and plausibility rather than probability, improves risk awareness through its relation with our memory of the observed event and contributes to decision making processes through their user focus. The method is showcased by means of a proof-of-concept for the 2018 drought in western Europe. We create analogues of the observed event based on large ensemble climate model simulations representing 2 °C and 3 °C global warming scenarios, and discuss how event severity, event drivers and physical processes are influenced by climate change. We show that future Rhine basin meteorological summer droughts like 2018 will be more severe. Decreased precipitation and increased potential evapotranspiration, caused by higher temperatures and increased incoming solar radiation, lead to higher precipitation deficits and lower plant available soil moisture. Possibly, changes in atmospheric circulation contribute to increased spring drought, amplifying the most severe summer drought events. The spatial extent of the most severe drought impacts increases substantially. The noted changes can partly be explained by changes in mean climate, but for many variables, changes in the relative event severity on top of these mean changes contribute as well.}, keywords = {Climate change, Drought 2018, Extreme weather, Future weather, Large ensembles, storylines}, pubstate = {published}, tppubtype = {article} } In the aftermath of observed extreme weather events, questions arise on the role of climate change in such events and what future events might look like. We present a method for the development of physical storylines of future events comparable to a chosen observed event, to answer some of these questions. A storyline approach, focusing on physical processes and plausibility rather than probability, improves risk awareness through its relation with our memory of the observed event and contributes to decision making processes through their user focus. The method is showcased by means of a proof-of-concept for the 2018 drought in western Europe. We create analogues of the observed event based on large ensemble climate model simulations representing 2 °C and 3 °C global warming scenarios, and discuss how event severity, event drivers and physical processes are influenced by climate change. We show that future Rhine basin meteorological summer droughts like 2018 will be more severe. Decreased precipitation and increased potential evapotranspiration, caused by higher temperatures and increased incoming solar radiation, lead to higher precipitation deficits and lower plant available soil moisture. Possibly, changes in atmospheric circulation contribute to increased spring drought, amplifying the most severe summer drought events. The spatial extent of the most severe drought impacts increases substantially. The noted changes can partly be explained by changes in mean climate, but for many variables, changes in the relative event severity on top of these mean changes contribute as well. |
Owen, Laura E; Catto, Jennifer L; Stephenson, David B; Dunstone, Nick J Compound precipitation and wind extremes over Europe and their relationship to extratropical cyclones Journal Article Weather and Climate Extremes, pp. 100342, 2021, ISSN: 2212-0947. Abstract | Links | BibTeX | Tags: Compound extremes, Extratropical cyclones, Precipitation, Winds @article{Owen2021, title = {Compound precipitation and wind extremes over Europe and their relationship to extratropical cyclones}, author = {Laura E Owen and Jennifer L Catto and David B Stephenson and Nick J Dunstone}, url = {https://www.sciencedirect.com/science/article/pii/S2212094721000384}, doi = {https://doi.org/10.1016/j.wace.2021.100342}, issn = {2212-0947}, year = {2021}, date = {2021-01-01}, journal = {Weather and Climate Extremes}, pages = {100342}, abstract = {Extratropical cyclones and their associated extreme precipitation and winds can have a severe impact on society and the co-occurrence between the two extremes is important when assessing risk. In this study the extremal dependency measure, χ, is used to quantify the co-occurrence of extreme precipitation and wind gusts, and is investigated at individual grid points and spatially over Europe. Results using three observational datasets and a higher spatial and temporal resolution version of ERA5 than previously used confirm previous studies. Over Europe high co-occurrence is found over western coasts and low co-occurrence is found over eastern coasts. All datasets have qualitatively similar spatial patterns over most regions of Europe excluding some regions of high topography where ERA5 χ values are much larger. ERA5 represents the timings of daily extreme co-occurring events well, compared to observations. The differences in precipitation accumulation timescales are also accounted for by considering hourly, 6, 24 and 48 hourly co-occurrence. In a few regions co-occurrence changes with longer accumulations, indicating the different speeds and sizes of weather systems affecting these regions. χ in most regions has little increase by allowing a 24 h lag and lead between the precipitation and wind, with a few exceptions where χ is increased by up to 24%. Regions with the larger of these increases are on or around elevated topography. Using an objective feature tracking method, insight into the spatial pattern of extreme precipitation and wind within cyclones over Europe is given. As well as suggesting how many hours apart the extremes occur from one another in a particular location. Extreme co-occurring events are associated with cyclones far more of the time than non extreme events. Given an extreme co-occurring event the chance of a cyclone being within 1110 km is more than 70% for much of Europe. Regions with low co-occurrence have extremes caused by different weather systems and regions with large co-occurrence have both extremes caused by the same weather system. Cyclones linked to extreme events, particularly co-occurring and extreme wind, have larger intensity than those not and for most of Europe these cyclones also have faster mean speed.}, keywords = {Compound extremes, Extratropical cyclones, Precipitation, Winds}, pubstate = {published}, tppubtype = {article} } Extratropical cyclones and their associated extreme precipitation and winds can have a severe impact on society and the co-occurrence between the two extremes is important when assessing risk. In this study the extremal dependency measure, χ, is used to quantify the co-occurrence of extreme precipitation and wind gusts, and is investigated at individual grid points and spatially over Europe. Results using three observational datasets and a higher spatial and temporal resolution version of ERA5 than previously used confirm previous studies. Over Europe high co-occurrence is found over western coasts and low co-occurrence is found over eastern coasts. All datasets have qualitatively similar spatial patterns over most regions of Europe excluding some regions of high topography where ERA5 χ values are much larger. ERA5 represents the timings of daily extreme co-occurring events well, compared to observations. The differences in precipitation accumulation timescales are also accounted for by considering hourly, 6, 24 and 48 hourly co-occurrence. In a few regions co-occurrence changes with longer accumulations, indicating the different speeds and sizes of weather systems affecting these regions. χ in most regions has little increase by allowing a 24 h lag and lead between the precipitation and wind, with a few exceptions where χ is increased by up to 24%. Regions with the larger of these increases are on or around elevated topography. Using an objective feature tracking method, insight into the spatial pattern of extreme precipitation and wind within cyclones over Europe is given. As well as suggesting how many hours apart the extremes occur from one another in a particular location. Extreme co-occurring events are associated with cyclones far more of the time than non extreme events. Given an extreme co-occurring event the chance of a cyclone being within 1110 km is more than 70% for much of Europe. Regions with low co-occurrence have extremes caused by different weather systems and regions with large co-occurrence have both extremes caused by the same weather system. Cyclones linked to extreme events, particularly co-occurring and extreme wind, have larger intensity than those not and for most of Europe these cyclones also have faster mean speed. |
Bevacqua, Emanuele; Shepherd, Theodore G; Watson, Peter A G; Sparrow, Sarah; Wallom, David; Mitchell, Dann Larger Spatial Footprint of Wintertime Total Precipitation Extremes in a Warmer Climate Journal Article Geophysical Research Letters, 48 (8), pp. e2020GL091990, 2021, (e2020GL091990 2020GL091990). Abstract | Links | BibTeX | Tags: anthropogenic climate change, compound events, flooding hazard, future projections, Precipitation extremes, spatial statistics @article{Bevacqua2021, title = {Larger Spatial Footprint of Wintertime Total Precipitation Extremes in a Warmer Climate}, author = {Emanuele Bevacqua and Theodore G Shepherd and Peter A G Watson and Sarah Sparrow and David Wallom and Dann Mitchell}, url = {https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2020GL091990}, doi = {https://doi.org/10.1029/2020GL091990}, year = {2021}, date = {2021-01-01}, journal = {Geophysical Research Letters}, volume = {48}, number = {8}, pages = {e2020GL091990}, abstract = {Abstract The simultaneous occurrence of extremely wet winters at multiple locations in the same region can contribute to widespread flooding and associated socio-economic losses. However, the spatial extent of precipitation extremes (i.e., the area in which nearby locations experience precipitation extremes simultaneously) and its future changes are largely overlooked in climate assessments. Employing new multi-thousand-year climate model simulations, we show that under both 2.0 °C and 1.5 °C warming scenarios, wintertime total precipitation extreme extents would increase over about 80%\textendash90% of the Northern Hemisphere extratropics (i.e., of the latitude band 28°\textendash78°N). Stabilizing at 1.5 °C rather than 2.0 °C would reduce the average magnitude of the increase by 1.7\textendash2 times. According to the climate model, the increased extents are caused by increases in precipitation intensity rather than changes in the spatial organization of the events. Relatively small percentage increases in precipitation intensities (e.g., by 4%) can drive disproportionately larger, by 1\textendash2 orders of magnitude, growth in the spatial extents (by 93%).}, note = {e2020GL091990 2020GL091990}, keywords = {anthropogenic climate change, compound events, flooding hazard, future projections, Precipitation extremes, spatial statistics}, pubstate = {published}, tppubtype = {article} } Abstract The simultaneous occurrence of extremely wet winters at multiple locations in the same region can contribute to widespread flooding and associated socio-economic losses. However, the spatial extent of precipitation extremes (i.e., the area in which nearby locations experience precipitation extremes simultaneously) and its future changes are largely overlooked in climate assessments. Employing new multi-thousand-year climate model simulations, we show that under both 2.0 °C and 1.5 °C warming scenarios, wintertime total precipitation extreme extents would increase over about 80%–90% of the Northern Hemisphere extratropics (i.e., of the latitude band 28°–78°N). Stabilizing at 1.5 °C rather than 2.0 °C would reduce the average magnitude of the increase by 1.7–2 times. According to the climate model, the increased extents are caused by increases in precipitation intensity rather than changes in the spatial organization of the events. Relatively small percentage increases in precipitation intensities (e.g., by 4%) can drive disproportionately larger, by 1–2 orders of magnitude, growth in the spatial extents (by 93%). |
Messori, Gabriele; Bevacqua, Emanuele; Caballero, Rodrigo; Coumou, Dim; Luca, Paolo De; Faranda, Davide; Kornhuber, Kai; Martius, Olivia; Pons, Flavio; Raymond, Colin; Ye, Kunhui Ye; Yiou, Pascal Yiou; Zscheischler, Jakob Compound Climate Events and Extremes in the Midlatitudes: Dynamics, Simulation, and Statistical Characterization Journal Article Bulletin of the American Meteorological Society, 102 (4), pp. E774–E781, 2021. @article{Messori2021, title = {Compound Climate Events and Extremes in the Midlatitudes: Dynamics, Simulation, and Statistical Characterization}, author = {Gabriele Messori and Emanuele Bevacqua and Rodrigo Caballero and Dim Coumou and Paolo De Luca and Davide Faranda and Kai Kornhuber and Olivia Martius and Flavio Pons and Colin Raymond and Kunhui Ye Ye and Pascal Yiou Yiou and Jakob Zscheischler}, url = {https://journals.ametsoc.org/view/journals/bams/102/4/BAMS-D-20-0289.1.xml}, doi = {https://doi.org/10.1175/BAMS-D-20-0289.1}, year = {2021}, date = {2021-01-01}, journal = {Bulletin of the American Meteorological Society}, volume = {102}, number = {4}, pages = {E774--E781}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Potopová, Vera; Tűrkott, Luboš; Musiolková, Marie; Možny, Martin; Lhotka, Ondřej The compound nature of soil temperature anomalies at various depths in the Czech Republic Journal Article Theoretical and Applied Climatology, pp. 1–19, 2021. BibTeX | Tags: @article{Potopova2021compound, title = {The compound nature of soil temperature anomalies at various depths in the Czech Republic}, author = {Vera Potopov\'{a} and Lubo\v{s} T\H{u}rkott and Marie Musiolkov\'{a} and Martin Mo\v{z}ny and Ond\v{r}ej Lhotka}, year = {2021}, date = {2021-01-01}, journal = {Theoretical and Applied Climatology}, pages = {1--19}, publisher = {Springer}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Zscheischler, Jakob; Lehner, Flavio Attributing compound events to anthropogenic climate change Journal Article Bulletin of the American Meteorological Society, pp. 1 - 45, 2021. @article{ZscheischlerLehner2021c, title = {Attributing compound events to anthropogenic climate change}, author = {Jakob Zscheischler and Flavio Lehner}, url = {https://journals.ametsoc.org/view/journals/bams/aop/BAMS-D-21-0116.1/BAMS-D-21-0116.1.xml}, doi = {10.1175/BAMS-D-21-0116.1}, year = {2021}, date = {2021-01-01}, journal = {Bulletin of the American Meteorological Society}, pages = {1 - 45}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Markiewicz, Iwona Depth-Duration-Frequency Relationship Model of Extreme Precipitation in Flood Risk Assessment in the Upper Vistula Basin Journal Article Water, 13 (23), 2021, ISSN: 2073-4441. Abstract | Links | BibTeX | Tags: @article{Markiewicz, title = {Depth-Duration-Frequency Relationship Model of Extreme Precipitation in Flood Risk Assessment in the Upper Vistula Basin}, author = {Iwona Markiewicz}, url = {https://www.mdpi.com/2073-4441/13/23/3439}, doi = {10.3390/w13233439}, issn = {2073-4441}, year = {2021}, date = {2021-01-01}, journal = {Water}, volume = {13}, number = {23}, abstract = {The Upper Vistula Basin is a flood-prone region in the summer season (May–October) due to intensive rainfall. From the point of view of water management, it is particularly important to assess the variability in this main factor of flood risk, as well as to establish the depth-duration-frequency (DDF) relationship for maximum precipitation, this having not yet been derived for the region. The analysis of a 68-year (1951-2018) data series of summer maximum precipitation collected by 11 meteorological stations showed the series’ stationarity, which supports the conclusion that there is no increase in the risk of rainfall floods due to the intensification of extreme precipitation. A new approach is proposed for the determination of the DDF relationship, where the best-fitted distribution for each station is selected from among the set of candidate distributions, instead of adopting one fixed distribution for all stations. This approach increases the accuracy of the DDF relationships for individual stations as compared to the commonly used approach. In particular, the traditionally used Gumbel distribution turns out to be not well fitted to the investigated data series, and the advantage of the recently popular GEV distribution is not significant.}, keywords = {}, pubstate = {published}, tppubtype = {article} } The Upper Vistula Basin is a flood-prone region in the summer season (May–October) due to intensive rainfall. From the point of view of water management, it is particularly important to assess the variability in this main factor of flood risk, as well as to establish the depth-duration-frequency (DDF) relationship for maximum precipitation, this having not yet been derived for the region. The analysis of a 68-year (1951-2018) data series of summer maximum precipitation collected by 11 meteorological stations showed the series’ stationarity, which supports the conclusion that there is no increase in the risk of rainfall floods due to the intensification of extreme precipitation. A new approach is proposed for the determination of the DDF relationship, where the best-fitted distribution for each station is selected from among the set of candidate distributions, instead of adopting one fixed distribution for all stations. This approach increases the accuracy of the DDF relationships for individual stations as compared to the commonly used approach. In particular, the traditionally used Gumbel distribution turns out to be not well fitted to the investigated data series, and the advantage of the recently popular GEV distribution is not significant. |
Kowalewska-Kalkowska, Halina Storm-Surge Induced Water Level Changes in the Odra River Mouth Area (Southern Baltic Coast) Journal Article Atmosphere, 12 (12), pp. 1559, 2021. Abstract | Links | BibTeX | Tags: @article{Kowalewska2021, title = {Storm-Surge Induced Water Level Changes in the Odra River Mouth Area (Southern Baltic Coast)}, author = {Halina Kowalewska-Kalkowska}, url = {https://doi.org/10.3390/atmos12121559}, doi = {10.3390/atmos12121559}, year = {2021}, date = {2021-01-01}, journal = {Atmosphere}, volume = {12}, number = {12}, pages = {1559}, publisher = {Multidisciplinary Digital Publishing Institute}, abstract = {The Odra River mouth area is a region of the Southern Baltic coastal zone especially prone to the influence of storm surges. In the present study, the height and extent of the Baltic storm surges, and temporal offsets of the respective maximum water level occurrences in the Odra River mouth area were explored using cross-correlation, cluster analysis and principal component analysis. The analyses were based on hourly water level readings retrieved from water gauging stations located along the lower Odra reaches and at the coasts of the Szczecin Lagoon and the Pomeranian Bay during storm surge years 2008/2009\textendash2019/2020. The analysis of mutual relationships between water levels during storm surges indicated that the extent of marine influence on the lower Odra River and within the Szczecin Lagoon was variable during the studied surge events, and dependent on meteorological conditions (the strongest during the sustained occurrence of wind blowing from the northern sector), discharge from the Odra River catchment (the strongest at low discharge), ice conditions on the lower Odra (suppressing the storm surge propagation upstream), and general sea level in the Pomeranian Bay (stronger at high sea levels). The strongest correlation between sea levels at \'{S}winouj\'{s}cie and water levels in the Szczecin Lagoon and the lower Odra was found at a 6\textendash7 h offset. The extent of storm surges usually reached 100 km up the lower Odra channels, less frequently reaching 130 km away from the sea.}, keywords = {}, pubstate = {published}, tppubtype = {article} } The Odra River mouth area is a region of the Southern Baltic coastal zone especially prone to the influence of storm surges. In the present study, the height and extent of the Baltic storm surges, and temporal offsets of the respective maximum water level occurrences in the Odra River mouth area were explored using cross-correlation, cluster analysis and principal component analysis. The analyses were based on hourly water level readings retrieved from water gauging stations located along the lower Odra reaches and at the coasts of the Szczecin Lagoon and the Pomeranian Bay during storm surge years 2008/2009–2019/2020. The analysis of mutual relationships between water levels during storm surges indicated that the extent of marine influence on the lower Odra River and within the Szczecin Lagoon was variable during the studied surge events, and dependent on meteorological conditions (the strongest during the sustained occurrence of wind blowing from the northern sector), discharge from the Odra River catchment (the strongest at low discharge), ice conditions on the lower Odra (suppressing the storm surge propagation upstream), and general sea level in the Pomeranian Bay (stronger at high sea levels). The strongest correlation between sea levels at Świnoujście and water levels in the Szczecin Lagoon and the lower Odra was found at a 6–7 h offset. The extent of storm surges usually reached 100 km up the lower Odra channels, less frequently reaching 130 km away from the sea. |
2020 |
Bevacqua, Emanuele; Zappa, Giuseppe; Shepherd, Theodore G Shorter cyclone clusters modulate changes in European wintertime precipitation extremes Journal Article Environmental Research Letters, 15 (12), pp. 124005, 2020, ISSN: 1748-9326. Abstract | Links | BibTeX | Tags: anthropogenic climate change, compound events, cyclone clustering, extremes, flooding, Precipitation, storylines @article{Bevacqua2020b, title = {Shorter cyclone clusters modulate changes in European wintertime precipitation extremes}, author = {Emanuele Bevacqua and Giuseppe Zappa and Theodore G Shepherd}, url = {https://iopscience.iop.org/article/10.1088/1748-9326/abbde7}, doi = {10.1088/1748-9326/abbde7}, issn = {1748-9326}, year = {2020}, date = {2020-11-01}, journal = {Environmental Research Letters}, volume = {15}, number = {12}, pages = {124005}, abstract = {Wintertime extreme precipitation from cyclone clusters, i.e. consecutive cyclones moving across the same region, can lead to flooding and devastating socio-economic impacts in Europe. Previous studies have suggested that the future direction of the changes in these events are uncertain across climate models. By employing an impact-based metric of accumulated precipitation extremes, we show that projections of cyclone clusters are instead broadly robust, i.e. consistent in sign, across models. A novel physical diagnostic shows that accumulated precipitation extremes are projected to grow by only +1.0%/K on average across Europe, although the mean precipitation per cyclone increases by +4.7%/K. This results from a decreased number of clustered cyclones, associated with decreased wintertime storminess, the extent of which varies from northern to southern Europe and depends on the future storyline of atmospheric circulation change. Neglecting the changes in the number of clustered cyclones, i.e. assuming that accumulated precipitation extremes would change as the mean precipitation per cyclone, would lead to overestimating the population affected by increased accumulated wintertime precipitation extremes by 130-490 million across Europe.}, keywords = {anthropogenic climate change, compound events, cyclone clustering, extremes, flooding, Precipitation, storylines}, pubstate = {published}, tppubtype = {article} } Wintertime extreme precipitation from cyclone clusters, i.e. consecutive cyclones moving across the same region, can lead to flooding and devastating socio-economic impacts in Europe. Previous studies have suggested that the future direction of the changes in these events are uncertain across climate models. By employing an impact-based metric of accumulated precipitation extremes, we show that projections of cyclone clusters are instead broadly robust, i.e. consistent in sign, across models. A novel physical diagnostic shows that accumulated precipitation extremes are projected to grow by only +1.0%/K on average across Europe, although the mean precipitation per cyclone increases by +4.7%/K. This results from a decreased number of clustered cyclones, associated with decreased wintertime storminess, the extent of which varies from northern to southern Europe and depends on the future storyline of atmospheric circulation change. Neglecting the changes in the number of clustered cyclones, i.e. assuming that accumulated precipitation extremes would change as the mean precipitation per cyclone, would lead to overestimating the population affected by increased accumulated wintertime precipitation extremes by 130-490 million across Europe. |
Lhotka, Ondřej; Trnka, Mirek; Kysely, Jan; Markonis, Yannis; Balek, Jan; Možny, Martin Atmospheric circulation as a factor contributing to increasing drought severity in Central Europe Journal Article Journal of Geophysical Research: Atmospheres, pp. e2019JD032269, 2020. Abstract | Links | BibTeX | Tags: drought, spatiotemporal @article{Lhotka2020b, title = {Atmospheric circulation as a factor contributing to increasing drought severity in Central Europe}, author = {Ond\v{r}ej Lhotka and Mirek Trnka and Jan Kysely and Yannis Markonis and Jan Balek and Martin Mo\v{z}ny}, url = {https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2019JD032269}, doi = {10.1029/2019JD032269}, year = {2020}, date = {2020-09-20}, journal = {Journal of Geophysical Research: Atmospheres}, pages = {e2019JD032269}, publisher = {Wiley Online Library}, abstract = {Long‐lasting and severe droughts seriously threaten agriculture, ecosystems, and society. Summer 2018 in central Europe was characterized by unusually persistent heat and drought, causing substantial economic losses, and became a part of a several years long dry period observed across this region. This study assesses the magnitude of the recent drought within a long‐term context and links the increased drought severity to changes in atmospheric circulation. Temporal variability of drought conditions since the late 19th century was analyzed at seven long‐term stations distributed across the Czech Republic using the Palmer Drought Severity Index and the Standardized Precipitation Evaporation Index. The Palmer Z Index and a variation of the Standardized Precipitation Evaporation Index were used to study rapidly emerging short‐term droughts and to link these episodes to atmospheric circulation. Changes in circulation were analyzed through circulation types calculated from flow strength, direction and vorticity in mean sea level pressure data from the National Centers for Environmental Prediction (NCEP)/National Center for Atmospheric Research (NCAR) reanalysis for 1948\textendash2018. Increasing drought severity across the Czech Republic with record‐low values of the drought indices during 2015\textendash2018 was found. The trend was distinctive in both vegetation (April\textendashSeptember) and cold (October\textendashMarch) periods. The tendency toward more severe droughts in recent decades was linked to changes in frequency of dry and wet circulation types, highlighting the important role of atmospheric circulation in regional climate. It remains an open question whether the significantly increasing frequency of dry circulation types in the vegetation period is related to climate change, or rather represents multidecadal climate variability.}, keywords = {drought, spatiotemporal}, pubstate = {published}, tppubtype = {article} } Long‐lasting and severe droughts seriously threaten agriculture, ecosystems, and society. Summer 2018 in central Europe was characterized by unusually persistent heat and drought, causing substantial economic losses, and became a part of a several years long dry period observed across this region. This study assesses the magnitude of the recent drought within a long‐term context and links the increased drought severity to changes in atmospheric circulation. Temporal variability of drought conditions since the late 19th century was analyzed at seven long‐term stations distributed across the Czech Republic using the Palmer Drought Severity Index and the Standardized Precipitation Evaporation Index. The Palmer Z Index and a variation of the Standardized Precipitation Evaporation Index were used to study rapidly emerging short‐term droughts and to link these episodes to atmospheric circulation. Changes in circulation were analyzed through circulation types calculated from flow strength, direction and vorticity in mean sea level pressure data from the National Centers for Environmental Prediction (NCEP)/National Center for Atmospheric Research (NCAR) reanalysis for 1948–2018. Increasing drought severity across the Czech Republic with record‐low values of the drought indices during 2015–2018 was found. The trend was distinctive in both vegetation (April–September) and cold (October–March) periods. The tendency toward more severe droughts in recent decades was linked to changes in frequency of dry and wet circulation types, highlighting the important role of atmospheric circulation in regional climate. It remains an open question whether the significantly increasing frequency of dry circulation types in the vegetation period is related to climate change, or rather represents multidecadal climate variability. |
Eilander, Dirk; Couasnon, Anaïs; Ikeuchi, Hiroaki; Muis, Sanne; Yamazaki, Dai; Winsemius, Hessel C; Ward, Philip J The effect of surge on riverine flood hazard and impact in deltas globally Journal Article Environmental Research Letters, 15 (10), pp. 104007, 2020. Abstract | Links | BibTeX | Tags: flooding, hydrological compound events, Storm surge @article{Eilander2020, title = {The effect of surge on riverine flood hazard and impact in deltas globally}, author = {Dirk Eilander and Ana\"{i}s Couasnon and Hiroaki Ikeuchi and Sanne Muis and Dai Yamazaki and Hessel C Winsemius and Philip J Ward}, url = {https://doi.org/10.1088/1748-9326/ab8ca6}, doi = {10.1088/1748-9326/ab8ca6}, year = {2020}, date = {2020-09-01}, journal = {Environmental Research Letters}, volume = {15}, number = {10}, pages = {104007}, publisher = {IOP Publishing}, abstract = {Current global riverine flood risk studies assume a constant mean sea level boundary. In reality high sea levels can propagate up a river, impede high river discharge, thus leading to elevated water levels. Riverine flood risk in deltas may therefore be underestimated. This paper presents the first global scale assessment of the joint influence of riverine and coastal drivers of flooding in deltas. We show that if storm surge is ignored, flood depths are significantly underestimated for 9.3% of the expected annual population exposed to riverine flooding. The assessment is based on extreme water levels at 3433 river mouth locations as modeled by a state-of-the-art global river routing model, forced with a multi-model runoff ensemble and bounded by dynamic sea level conditions derived from a global tide and surge reanalysis. We first classified the drivers of riverine flooding at each location into four classes: surge-dominant, discharge-dominant, compound-dominant or insignificant. We then developed a model experiment to quantify the effect of surge on flood hazard and impacts. Drivers of riverine flooding are compound-dominant at 19.7% of the locations analyzed, discharge-dominant at 69.2%, and surge-dominant at 7.8%. Compared to locations with either surge- or discharge-dominant flood drivers, locations with compound-dominant flood drivers generally have larger surge extremes and are located in basins with faster discharge response and/or flat topography. Globally, surge exacerbates 1-in-10 years flood levels at 64.0% of the locations analyzed, with a mean increase of 11 cm. While this increase is generally larger at locations with compound- or surge-dominant flood drivers, flood levels also increase at locations with discharge-dominant flood drivers. This study underlines the importance of including dynamic downstream sea level boundaries in (global) riverine flood risk studies.}, keywords = {flooding, hydrological compound events, Storm surge}, pubstate = {published}, tppubtype = {article} } Current global riverine flood risk studies assume a constant mean sea level boundary. In reality high sea levels can propagate up a river, impede high river discharge, thus leading to elevated water levels. Riverine flood risk in deltas may therefore be underestimated. This paper presents the first global scale assessment of the joint influence of riverine and coastal drivers of flooding in deltas. We show that if storm surge is ignored, flood depths are significantly underestimated for 9.3% of the expected annual population exposed to riverine flooding. The assessment is based on extreme water levels at 3433 river mouth locations as modeled by a state-of-the-art global river routing model, forced with a multi-model runoff ensemble and bounded by dynamic sea level conditions derived from a global tide and surge reanalysis. We first classified the drivers of riverine flooding at each location into four classes: surge-dominant, discharge-dominant, compound-dominant or insignificant. We then developed a model experiment to quantify the effect of surge on flood hazard and impacts. Drivers of riverine flooding are compound-dominant at 19.7% of the locations analyzed, discharge-dominant at 69.2%, and surge-dominant at 7.8%. Compared to locations with either surge- or discharge-dominant flood drivers, locations with compound-dominant flood drivers generally have larger surge extremes and are located in basins with faster discharge response and/or flat topography. Globally, surge exacerbates 1-in-10 years flood levels at 64.0% of the locations analyzed, with a mean increase of 11 cm. While this increase is generally larger at locations with compound- or surge-dominant flood drivers, flood levels also increase at locations with discharge-dominant flood drivers. This study underlines the importance of including dynamic downstream sea level boundaries in (global) riverine flood risk studies. |
Zscheischler, Jakob; Martius, Olivia; Westra, Seth; Bevacqua, Emanuele; Raymond, Colin; Horton, Radley M; van den Hurk, Bart; AghaKouchak, Amir; Jézéquel, Aglaé; Mahecha, Miguel D; Maraun, Douglas; Ramos, Alexandre M; Ridder, Nina N; Thiery, Wim; Vignotto, Edoardo A typology of compound weather and climate events Journal Article Nature Reviews Earth & Environment, 2020, ISSN: 2662-138X. Abstract | Links | BibTeX | Tags: @article{Zscheischler2020, title = {A typology of compound weather and climate events}, author = {Jakob Zscheischler and Olivia Martius and Seth Westra and Emanuele Bevacqua and Colin Raymond and Radley M Horton and Bart van den Hurk and Amir AghaKouchak and Agla\'{e} J\'{e}z\'{e}quel and Miguel D Mahecha and Douglas Maraun and Alexandre M Ramos and Nina N Ridder and Wim Thiery and Edoardo Vignotto}, url = {http://www.nature.com/articles/s43017-020-0060-z}, doi = {10.1038/s43017-020-0060-z}, issn = {2662-138X}, year = {2020}, date = {2020-06-01}, journal = {Nature Reviews Earth & Environment}, abstract = {Compound weather and climate events describe combinations of multiple climate drivers and/or hazards that contribute to societal or environmental risk. Although many climate-related disasters are caused by compound events, the understanding, analysis, quantification and prediction of such events is still in its infancy. In this Review, we propose a typology of compound events and suggest analytical and modelling approaches to aid in their investigation. We organize the highly diverse compound event types according to four themes: preconditioned, where a weather- driven or climate- driven precondition aggravates the impacts of a hazard; multivariate, where multiple drivers and/or hazards lead to an impact; temporally compounding, where a succession of hazards leads to an impact; and spatially compounding, where hazards in multiple connected locations cause an aggregated impact. Through structuring compound events and their respective analysis tools, the typology offers an opportunity for deeper insight into their mechanisms and impacts, benefiting the development of effective adaptation strategies. However, the complex nature of compound events results in some cases inevitably fitting into more than one class, necessitating soft boundaries within the typology. Future work must homogenize the available analytical approaches into a robust toolset for compound-event analysis under present and future climate conditions. }, keywords = {}, pubstate = {published}, tppubtype = {article} } Compound weather and climate events describe combinations of multiple climate drivers and/or hazards that contribute to societal or environmental risk. Although many climate-related disasters are caused by compound events, the understanding, analysis, quantification and prediction of such events is still in its infancy. In this Review, we propose a typology of compound events and suggest analytical and modelling approaches to aid in their investigation. We organize the highly diverse compound event types according to four themes: preconditioned, where a weather- driven or climate- driven precondition aggravates the impacts of a hazard; multivariate, where multiple drivers and/or hazards lead to an impact; temporally compounding, where a succession of hazards leads to an impact; and spatially compounding, where hazards in multiple connected locations cause an aggregated impact. Through structuring compound events and their respective analysis tools, the typology offers an opportunity for deeper insight into their mechanisms and impacts, benefiting the development of effective adaptation strategies. However, the complex nature of compound events results in some cases inevitably fitting into more than one class, necessitating soft boundaries within the typology. Future work must homogenize the available analytical approaches into a robust toolset for compound-event analysis under present and future climate conditions. |
Raymond, Colin; Horton, Radley M; Zscheischler, Jakob; Martius, Olivia; AghaKouchak, Amir; Balch, Jennifer; Bowen, Steven G; Camargo, Suzana J; Hess, Jeremy; Kornhuber, Kai; Oppenheimer, Michael; Ruane, Alex C; Wahl, Thomas; White, Kathleen Understanding and managing connected extreme events Journal Article Nature Climate Change, 2020, ISSN: 1758-678X. Abstract | Links | BibTeX | Tags: @article{Raymond2020, title = {Understanding and managing connected extreme events}, author = {Colin Raymond and Radley M Horton and Jakob Zscheischler and Olivia Martius and Amir AghaKouchak and Jennifer Balch and Steven G Bowen and Suzana J Camargo and Jeremy Hess and Kai Kornhuber and Michael Oppenheimer and Alex C Ruane and Thomas Wahl and Kathleen White}, url = {http://www.nature.com/articles/s41558-020-0790-4}, doi = {10.1038/s41558-020-0790-4}, issn = {1758-678X}, year = {2020}, date = {2020-06-01}, journal = {Nature Climate Change}, abstract = {Extreme weather and climate events and their impacts can occur in complex combinations, an interaction shaped by physical drivers and societal forces. In these situations, governance, markets and other decision-making structures\textemdashtogether with population exposure and vulnerability\textemdashcreate nonphysical interconnections among events by linking their impacts, to positive or negative effect. Various anthropogenic actions can also directly affect the severity of events, further complicating these feedback loops. Such relationships are rarely characterized or considered in physical-sciences-based research contexts. Here, we present a multidisciplinary argument for the concept of connected extreme events, and we suggest vantage points and approaches for producing climate information useful in guiding decisions about them.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Extreme weather and climate events and their impacts can occur in complex combinations, an interaction shaped by physical drivers and societal forces. In these situations, governance, markets and other decision-making structures—together with population exposure and vulnerability—create nonphysical interconnections among events by linking their impacts, to positive or negative effect. Various anthropogenic actions can also directly affect the severity of events, further complicating these feedback loops. Such relationships are rarely characterized or considered in physical-sciences-based research contexts. Here, we present a multidisciplinary argument for the concept of connected extreme events, and we suggest vantage points and approaches for producing climate information useful in guiding decisions about them. |
Potopová, Vera; Trnka, Miroslav; Hamouz, Pavel; Soukup, Josef; Castraveț, Tudor Agricultural Water Management, 236 , pp. 106168, 2020, ISSN: 0378-3774. Abstract | Links | BibTeX | Tags: crops, drought @article{POTOPOVA2020, title = {Statistical modelling of drought-related yield losses using soil moisture-vegetation remote sensing and multiscalar indices in the south-eastern Europe}, author = {Vera Potopov\'{a} and Miroslav Trnka and Pavel Hamouz and Josef Soukup and Tudor Castraveț}, url = {http://www.sciencedirect.com/science/article/pii/S0378377420303656}, doi = {https://doi.org/10.1016/j.agwat.2020.106168}, issn = {0378-3774}, year = {2020}, date = {2020-04-02}, journal = {Agricultural Water Management}, volume = {236}, pages = {106168}, abstract = {Meteorological and agricultural information coupled with remote sensing observations has been used to assess the effectiveness of satellite-derived indices in yield estimations. The estimate yield models generated by both the regression (MLR) and Bayesian network (BBN) algorithms and their levels of predictive skill were assessed. The enhanced vegetation index (EVI2), soil water index (SWI), standardized precipitation evaporation index (SPEI) have been considered predictors for three rainfed crops (maize, sunflower and grapevine) grown in 37 districts in the Republic of Moldova (RM). We used the weekly EVI2, which was collected by MODIS instruments aboard the Terra satellite with a 250m × 250m spatial resolution and aggregated for each district during the 2000\textendash2018 period. We also used the weekly SWI, which was collected from the ASCAT instruments with a 12 km x 12 km spatial resolution and aggregated for each district at the topsoil (0\textendash40 cm; SWI-12) and the root-zone layer (0\textendash100 cm; SWI-14) during 2000\textendash2018. The multiscalar SPEI during 1951\textendash2018 farming years proved to be a significant addition to the remote sensing indices and led to the development of a model that improved the yield assessment. The study also summarized (i) the optimal time window of satellite-derived SWIi and EVI2i for yield estimation, and (ii) the capability of remotely sensed indices for representing the spatio\textendashtemporal variations of agricultural droughts. We developed statistical soil-vegetation-atmosphere models to explore drought-related yield losses. The skill scores of the sunflower MLR and BBN models were higher than those for the maize and grape models and were able to estimate yields with reasonable accuracy and predictive power. The accurate estimation of maize, sunflower and grapevine yields was observed two months before the harvest (RMSE of ∼1.2 tha-1). Despite the fact that summer crops (maize, sunflower) are able to develop a root system that uses the entire root zone depth, however, the SWI-12 had the stronger correlation with crop yield, then SWI-14. This explains much better the fit between yields of the crops and SWI-12, which represents soil moisture anomaly in the key rooting layer of soil. In any case, all summer crops showed negative correlations with each of the remote sensing soil moisture indices in the early and middle of the growing season, with SWI-12 performing better than SWI-14. Based on the crop-specific soil moisture model, we found that topsoil moisture declines in the most drought-susceptible crop growth stages, which indicates that RM is a good candidate for studying drought persists as main driver of rainfed yield losses in the south-eastern Europe.}, keywords = {crops, drought}, pubstate = {published}, tppubtype = {article} } Meteorological and agricultural information coupled with remote sensing observations has been used to assess the effectiveness of satellite-derived indices in yield estimations. The estimate yield models generated by both the regression (MLR) and Bayesian network (BBN) algorithms and their levels of predictive skill were assessed. The enhanced vegetation index (EVI2), soil water index (SWI), standardized precipitation evaporation index (SPEI) have been considered predictors for three rainfed crops (maize, sunflower and grapevine) grown in 37 districts in the Republic of Moldova (RM). We used the weekly EVI2, which was collected by MODIS instruments aboard the Terra satellite with a 250m × 250m spatial resolution and aggregated for each district during the 2000–2018 period. We also used the weekly SWI, which was collected from the ASCAT instruments with a 12 km x 12 km spatial resolution and aggregated for each district at the topsoil (0–40 cm; SWI-12) and the root-zone layer (0–100 cm; SWI-14) during 2000–2018. The multiscalar SPEI during 1951–2018 farming years proved to be a significant addition to the remote sensing indices and led to the development of a model that improved the yield assessment. The study also summarized (i) the optimal time window of satellite-derived SWIi and EVI2i for yield estimation, and (ii) the capability of remotely sensed indices for representing the spatio–temporal variations of agricultural droughts. We developed statistical soil-vegetation-atmosphere models to explore drought-related yield losses. The skill scores of the sunflower MLR and BBN models were higher than those for the maize and grape models and were able to estimate yields with reasonable accuracy and predictive power. The accurate estimation of maize, sunflower and grapevine yields was observed two months before the harvest (RMSE of ∼1.2 tha-1). Despite the fact that summer crops (maize, sunflower) are able to develop a root system that uses the entire root zone depth, however, the SWI-12 had the stronger correlation with crop yield, then SWI-14. This explains much better the fit between yields of the crops and SWI-12, which represents soil moisture anomaly in the key rooting layer of soil. In any case, all summer crops showed negative correlations with each of the remote sensing soil moisture indices in the early and middle of the growing season, with SWI-12 performing better than SWI-14. Based on the crop-specific soil moisture model, we found that topsoil moisture declines in the most drought-susceptible crop growth stages, which indicates that RM is a good candidate for studying drought persists as main driver of rainfed yield losses in the south-eastern Europe. |
Poschlod, Benjamin; Zscheischler, Jakob; Sillmann, Jana; Wood, Raul R; Ludwig, Ralf Climate change effects on hydrometeorological compound events over southern Norway Journal Article Weather and Climate Extremes, 28 , pp. 100253, 2020, ISSN: 2212-0947. Abstract | Links | BibTeX | Tags: hydrological compound events, Large ensemble, Norway, Rain-on-snow @article{POSCHLOD2020, title = {Climate change effects on hydrometeorological compound events over southern Norway}, author = {Benjamin Poschlod and Jakob Zscheischler and Jana Sillmann and Raul R Wood and Ralf Ludwig}, url = {http://www.sciencedirect.com/science/article/pii/S2212094719301574}, doi = {https://doi.org/10.1016/j.wace.2020.100253}, issn = {2212-0947}, year = {2020}, date = {2020-03-19}, journal = {Weather and Climate Extremes}, volume = {28}, pages = {100253}, abstract = {Hydrometeorological compound events cause severe economical, societal and environmental damage, but their investigation is difficult as they occur rarely and are multivariate. Here we use 50 high-resolution climate simulations from the single model initial condition large ensemble CRCM5-LE to examine two such compound event types in southern Norway: (1) Heavy rainfall on saturated soil during the summer months (June, July, August, September; SES) and (2) Concurrent heavy rainfall and snowmelt (rain-on-snow; ROS). We compare present-day conditions (1980\textendash2009) with future conditions under a high-emission scenario (2070\textendash2099) and investigate the impact of climate change on the frequency and spatial distribution of SES and ROS events. We find that the probability of occurrence of SES events during the summer increases by 38% until 2070\textendash2099 over the whole study area. The areas with the highest occurrence probability extend from the west coast into the interior. In contrast, the frequency of ROS is projected to decrease by 48% on average, largely driven by decreases in snowfall. Moreover, the spatial pattern of ROS are projected to change, with the most frequently affected areas shifting from the west coast towards the inner country. Our study highlights the benefits of single model large ensemble simulations for the analysis of compound events.}, keywords = {hydrological compound events, Large ensemble, Norway, Rain-on-snow}, pubstate = {published}, tppubtype = {article} } Hydrometeorological compound events cause severe economical, societal and environmental damage, but their investigation is difficult as they occur rarely and are multivariate. Here we use 50 high-resolution climate simulations from the single model initial condition large ensemble CRCM5-LE to examine two such compound event types in southern Norway: (1) Heavy rainfall on saturated soil during the summer months (June, July, August, September; SES) and (2) Concurrent heavy rainfall and snowmelt (rain-on-snow; ROS). We compare present-day conditions (1980–2009) with future conditions under a high-emission scenario (2070–2099) and investigate the impact of climate change on the frequency and spatial distribution of SES and ROS events. We find that the probability of occurrence of SES events during the summer increases by 38% until 2070–2099 over the whole study area. The areas with the highest occurrence probability extend from the west coast into the interior. In contrast, the frequency of ROS is projected to decrease by 48% on average, largely driven by decreases in snowfall. Moreover, the spatial pattern of ROS are projected to change, with the most frequently affected areas shifting from the west coast towards the inner country. Our study highlights the benefits of single model large ensemble simulations for the analysis of compound events. |
Couasnon, Anaïs; Eilander, Dirk; Muis, Sanne; Veldkamp, Ted I E; Haigh, Ivan D; Wahl, Thomas; Winsemius, Hessel C; Ward, Philip J Measuring compound flood potential from river discharge and storm surge extremes at the global scale Journal Article Natural Hazards and Earth System Sciences, 20 (2), pp. 489–504, 2020, ISSN: 1684-9981. Abstract | Links | BibTeX | Tags: @article{Couasnon2020, title = {Measuring compound flood potential from river discharge and storm surge extremes at the global scale}, author = {Ana\"{i}s Couasnon and Dirk Eilander and Sanne Muis and Ted I E Veldkamp and Ivan D Haigh and Thomas Wahl and Hessel C Winsemius and Philip J Ward}, url = {https://www.nat-hazards-earth-syst-sci.net/20/489/2020/}, doi = {10.5194/nhess-20-489-2020}, issn = {1684-9981}, year = {2020}, date = {2020-02-01}, journal = {Natural Hazards and Earth System Sciences}, volume = {20}, number = {2}, pages = {489--504}, abstract = {The interaction between physical drivers from oceanographic, hydrological, and meteorological processes in coastal areas can result in compound flooding. Compound flood events, like Cyclone Idai and Hurricane Harvey, have revealed the devastating consequences of the co-occurrence of coastal and river floods. A number of studies have recently investigated the likelihood of compound flooding at the continental scale based on simulated variables of flood drivers, such as storm surge, precipitation, and river discharges. At the global scale, this has only been performed based on observations, thereby excluding a large extent of the global coastline. The purpose of this study is to fill this gap and identify regions with a high compound flooding po- tential from river discharge and storm surge extremes in river mouths globally. To do so, we use daily time series of river discharge and storm surge from state-of-the-art global mod- els driven with consistent meteorological forcing from reanalysis datasets. We measure the compound flood potential by analysing both variables with respect to their timing, joint statistical dependence, and joint return period. Our analysis indicates many regions that deviate from statistical indepen- dence and could not be identified in previous global studies based on observations alone, such as Madagascar, northern Morocco, Vietnam, and Taiwan. We report possible causal mechanisms for the observed spatial patterns based on existing literature. Finally, we provide preliminary insights on the implications of the bivariate dependence behaviour on the flood hazard characterisation using Madagascar as a case study. Our global and local analyses show that the depen- dence structure between flood drivers can be complex and can significantly impact the joint probability of discharge and storm surge extremes. These emphasise the need to refine global flood risk assessments and emergency planning to account for these potential interactions.}, keywords = {}, pubstate = {published}, tppubtype = {article} } The interaction between physical drivers from oceanographic, hydrological, and meteorological processes in coastal areas can result in compound flooding. Compound flood events, like Cyclone Idai and Hurricane Harvey, have revealed the devastating consequences of the co-occurrence of coastal and river floods. A number of studies have recently investigated the likelihood of compound flooding at the continental scale based on simulated variables of flood drivers, such as storm surge, precipitation, and river discharges. At the global scale, this has only been performed based on observations, thereby excluding a large extent of the global coastline. The purpose of this study is to fill this gap and identify regions with a high compound flooding po- tential from river discharge and storm surge extremes in river mouths globally. To do so, we use daily time series of river discharge and storm surge from state-of-the-art global mod- els driven with consistent meteorological forcing from reanalysis datasets. We measure the compound flood potential by analysing both variables with respect to their timing, joint statistical dependence, and joint return period. Our analysis indicates many regions that deviate from statistical indepen- dence and could not be identified in previous global studies based on observations alone, such as Madagascar, northern Morocco, Vietnam, and Taiwan. We report possible causal mechanisms for the observed spatial patterns based on existing literature. Finally, we provide preliminary insights on the implications of the bivariate dependence behaviour on the flood hazard characterisation using Madagascar as a case study. Our global and local analyses show that the depen- dence structure between flood drivers can be complex and can significantly impact the joint probability of discharge and storm surge extremes. These emphasise the need to refine global flood risk assessments and emergency planning to account for these potential interactions. |
Bastos, A; Ciais, P; Friedlingstein, P; Sitch, S; Pongratz, J; Fan, L; Wigneron, J P; Weber, U; Reichstein, M; Fu, Z; Anthoni, P; Arneth, A; Haverd, V; Jain, A K; Joetzjer, E; Knauer, J; Lienert, S; Loughran, T; McGuire, P C; Tian, H; Viovy, N; Zaehle, S Direct and seasonal legacy effects of the 2018 heat wave and drought on European ecosystem productivity Journal Article Science Advances, 6 (24), pp. eaba2724, 2020, ISSN: 23752548. Abstract | Links | BibTeX | Tags: @article{Bastos2020, title = {Direct and seasonal legacy effects of the 2018 heat wave and drought on European ecosystem productivity}, author = {A Bastos and P Ciais and P Friedlingstein and S Sitch and J Pongratz and L Fan and J P Wigneron and U Weber and M Reichstein and Z Fu and P Anthoni and A Arneth and V Haverd and A K Jain and E Joetzjer and J Knauer and S Lienert and T Loughran and P C McGuire and H Tian and N Viovy and S Zaehle}, doi = {10.1126/sciadv.aba2724}, issn = {23752548}, year = {2020}, date = {2020-01-01}, journal = {Science Advances}, volume = {6}, number = {24}, pages = {eaba2724}, abstract = {In summer 2018, central and northern Europe were stricken by extreme drought and heat (DH2018). The DH2018 differed from previous events in being preceded by extreme spring warming and brightening, but moderate rainfall deficits, yet registering the fastest transition between wet winter conditions and extreme summer drought. Using 11 vegetation models, we show that spring conditions promoted increased vegetation growth, which, in turn, contributed to fast soil moisture depletion, amplifying the summer drought. We find regional asymmetries in summer ecosystem carbon fluxes: increased (reduced) sink in the northern (southern) areas affected by drought. These asymmetries can be explained by distinct legacy effects of spring growth and of water-use efficiency dynamics mediated by vegetation composition, rather than by distinct ecosystem responses to summer heat/drought. The asymmetries in carbon and water exchanges during spring and summer 2018 suggest that future land-management strategies could influence patterns of summer heat waves and droughts under long-term warming.}, keywords = {}, pubstate = {published}, tppubtype = {article} } In summer 2018, central and northern Europe were stricken by extreme drought and heat (DH2018). The DH2018 differed from previous events in being preceded by extreme spring warming and brightening, but moderate rainfall deficits, yet registering the fastest transition between wet winter conditions and extreme summer drought. Using 11 vegetation models, we show that spring conditions promoted increased vegetation growth, which, in turn, contributed to fast soil moisture depletion, amplifying the summer drought. We find regional asymmetries in summer ecosystem carbon fluxes: increased (reduced) sink in the northern (southern) areas affected by drought. These asymmetries can be explained by distinct legacy effects of spring growth and of water-use efficiency dynamics mediated by vegetation composition, rather than by distinct ecosystem responses to summer heat/drought. The asymmetries in carbon and water exchanges during spring and summer 2018 suggest that future land-management strategies could influence patterns of summer heat waves and droughts under long-term warming. |
Sezen, Cenk; Šraj, Mojca; Medved, Anže; Bezak, Nejc Investigation of Rain-On-Snow Floods under Climate Change Journal Article Applied Sciences, 10 (4), 2020, ISSN: 2076-3417. Abstract | Links | BibTeX | Tags: @article{Sezen2020, title = {Investigation of Rain-On-Snow Floods under Climate Change}, author = {Cenk Sezen and Mojca \v{S}raj and An\v{z}e Medved and Nejc Bezak}, url = {https://www.mdpi.com/2076-3417/10/4/1242}, doi = {10.3390/app10041242}, issn = {2076-3417}, year = {2020}, date = {2020-01-01}, journal = {Applied Sciences}, volume = {10}, number = {4}, abstract = {Rain-on-snow (ROS) floods can cause economic damage and endanger human lives due to the compound effect of rainfall and snowmelt, especially under climate change. In this study, possible future changes of seasonality, magnitude and frequency characteristics of ROS floods were investigated for the selected catchments in Slovenia, Europe. For this purpose, five global/regional climate models (GCM/RCM) combinations were applied using the RCP4.5 climate scenario for the period 1981\textendash2100. To determine ROS floods’ characteristics in the future, a lumped conceptual hydrological model G\'{e}nie Rural \`{a} 6 param\`{e}tres Journalier (GR6J) with snow module CemaNeige was applied. The results indicate that the number of ROS floods could increase in the future. Moreover, also the magnitudes of extreme ROS floods could increase, while a slight decrease in the median values of ROS flood magnitudes was observed. The strength of seasonality for a high-altitude catchment could decrease in the future. A slight shift in the average ROS floods’ timing could be expected. Furthermore, a catchment located in a temperate continental climate could have a different response to the climate change impact in comparison to a catchment located in a mountain climate with alpine characteristics. Additionally, differences among investigated climate models show a large variability.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Rain-on-snow (ROS) floods can cause economic damage and endanger human lives due to the compound effect of rainfall and snowmelt, especially under climate change. In this study, possible future changes of seasonality, magnitude and frequency characteristics of ROS floods were investigated for the selected catchments in Slovenia, Europe. For this purpose, five global/regional climate models (GCM/RCM) combinations were applied using the RCP4.5 climate scenario for the period 1981–2100. To determine ROS floods’ characteristics in the future, a lumped conceptual hydrological model Génie Rural à 6 paramètres Journalier (GR6J) with snow module CemaNeige was applied. The results indicate that the number of ROS floods could increase in the future. Moreover, also the magnitudes of extreme ROS floods could increase, while a slight decrease in the median values of ROS flood magnitudes was observed. The strength of seasonality for a high-altitude catchment could decrease in the future. A slight shift in the average ROS floods’ timing could be expected. Furthermore, a catchment located in a temperate continental climate could have a different response to the climate change impact in comparison to a catchment located in a mountain climate with alpine characteristics. Additionally, differences among investigated climate models show a large variability. |
Bevacqua, Emanuele; Vousdoukas, Michalis; Shepherd, Theodore; Vrac, Mathieu Brief communication: The role of using precipitation or river discharge data when assessing global coastal compound flooding Journal Article Natural Hazards and Earth System Sciences, (4), pp. 1–20, 2020, ISSN: 1561-8633. Abstract | Links | BibTeX | Tags: Climatology, Discharge, Drainage basin, Estuary, Flooding (psychology), Geology, Hydrology, Precipitation, Spatial ecology, Storm surge @article{Bevacqua2020, title = {Brief communication: The role of using precipitation or river discharge data when assessing global coastal compound flooding}, author = {Emanuele Bevacqua and Michalis Vousdoukas and Theodore Shepherd and Mathieu Vrac}, doi = {10.5194/nhess-2019-415}, issn = {1561-8633}, year = {2020}, date = {2020-01-01}, journal = {Natural Hazards and Earth System Sciences}, number = {4}, pages = {1--20}, abstract = {Interacting storm surges and high water runoff can cause compound flooding (CF) in low-lying coasts and river estuaries. The large-scale CF hazard has been typically studied using proxies such as the concurrence of storm surge extremes either with precipitation or with river discharge ex- tremes. Here the impact of the choice of such proxies is addressed employing state-of-the-art global datasets. Although they are proxies of diverse physical mechanisms, we find that the two approaches show similar CF spatial patterns. On average, deviations are smaller in regions where assessing the actual CF is more relevant, i.e. where the CF potential is high. Differences between the two assessments increase with the catchment size, and our findings indicate that CF in long rivers (catchment >5\textendash10,000 km2) should be analysed using river discharge data. The precipitation-based assessment allows for considering local-rainfall-driven CF and CF in small rivers not resolved by large-scale datasets.}, keywords = {Climatology, Discharge, Drainage basin, Estuary, Flooding (psychology), Geology, Hydrology, Precipitation, Spatial ecology, Storm surge}, pubstate = {published}, tppubtype = {article} } Interacting storm surges and high water runoff can cause compound flooding (CF) in low-lying coasts and river estuaries. The large-scale CF hazard has been typically studied using proxies such as the concurrence of storm surge extremes either with precipitation or with river discharge ex- tremes. Here the impact of the choice of such proxies is addressed employing state-of-the-art global datasets. Although they are proxies of diverse physical mechanisms, we find that the two approaches show similar CF spatial patterns. On average, deviations are smaller in regions where assessing the actual CF is more relevant, i.e. where the CF potential is high. Differences between the two assessments increase with the catchment size, and our findings indicate that CF in long rivers (catchment >5–10,000 km2) should be analysed using river discharge data. The precipitation-based assessment allows for considering local-rainfall-driven CF and CF in small rivers not resolved by large-scale datasets. |
Lhotka, Ondřej; Brönnimann, Stefan Possible Increase of Vegetation Exposure to Spring Frost under Climate Change in Switzerland Journal Article Atmosphere, 11 (4), pp. 391, 2020. Abstract | Links | BibTeX | Tags: @article{lhotka2020, title = {Possible Increase of Vegetation Exposure to Spring Frost under Climate Change in Switzerland}, author = {Ond\v{r}ej Lhotka and Stefan Br\"{o}nnimann}, url = {https://www.mdpi.com/2073-4433/11/4/391}, doi = {10.3390/atmos11040391}, year = {2020}, date = {2020-01-01}, journal = {Atmosphere}, volume = {11}, number = {4}, pages = {391}, publisher = {Multidisciplinary Digital Publishing Institute}, abstract = {We assessed future changes in spring frost risk for the Aare river catchment that comprises the Swiss Plateau, the most important agricultural region of Switzerland. An ensemble of 15 bias-corrected regional climate model (RCM) simulations from the EXAR data set forced by the RCP 4.5 and RCP 8.5 concentration pathways were analysed for two future periods. Correlating actual meteorological observations and Swiss phenological spring index, we proposed and tested an RCM-compatible methodology (based on temperature data only) for estimating a start of spring and severity of frost events. In the historical climate, a significant advancement in start of spring was observed and frost events were more frequent in those years in which spring started sooner. In 2021\textendash2050, spring is projected to start eight (twelve) days earlier, considering the RCP 4.5 (8.5) scenario. Substantial changes were simulated for the 2070\textendash2099 period under RCP 8.5, when the total severity of frost events was projected to be increased by a factor of 2.1 compared to the historical climate. The study revealed the possible future increase of vegetation exposure to spring frost in Switzerland and that this phenomenon is noticeable even in the near future under the ‘low concentration’ RCP 4.5 scenario.}, keywords = {}, pubstate = {published}, tppubtype = {article} } We assessed future changes in spring frost risk for the Aare river catchment that comprises the Swiss Plateau, the most important agricultural region of Switzerland. An ensemble of 15 bias-corrected regional climate model (RCM) simulations from the EXAR data set forced by the RCP 4.5 and RCP 8.5 concentration pathways were analysed for two future periods. Correlating actual meteorological observations and Swiss phenological spring index, we proposed and tested an RCM-compatible methodology (based on temperature data only) for estimating a start of spring and severity of frost events. In the historical climate, a significant advancement in start of spring was observed and frost events were more frequent in those years in which spring started sooner. In 2021–2050, spring is projected to start eight (twelve) days earlier, considering the RCP 4.5 (8.5) scenario. Substantial changes were simulated for the 2070–2099 period under RCP 8.5, when the total severity of frost events was projected to be increased by a factor of 2.1 compared to the historical climate. The study revealed the possible future increase of vegetation exposure to spring frost in Switzerland and that this phenomenon is noticeable even in the near future under the ‘low concentration’ RCP 4.5 scenario. |
Potopová, Vera; Lhotka, Ondrej; Možny, Martin; Musiolková, Marie Vulnerability of hop-yields due to compound drought and heat events over European key-hop regions Journal Article International Journal of Climatology, 2020. Abstract | Links | BibTeX | Tags: compound events, crops, drought & heat @article{Potopova2020b, title = {Vulnerability of hop-yields due to compound drought and heat events over European key-hop regions}, author = {Vera Potopov\'{a} and Ondrej Lhotka and Martin Mo\v{z}ny and Marie Musiolkov\'{a}}, url = {https://rmets.onlinelibrary.wiley.com/doi/10.1002/joc.6836}, doi = {10.1002/joc.6836}, year = {2020}, date = {2020-01-01}, journal = {International Journal of Climatology}, publisher = {Wiley Online Library}, abstract = {Compound climate events in which only one variable is extreme (e.g., either hot but no drought or extreme drought but not hot) and events in which both variables are extreme (e.g., drought and heat waves) may have different impacts on hop yields and alpha‐bitter acid contents. Increasing occurrences of compound drought and heat events have led to increased income variability for beer production, and also affecting the major hop growers across Europe (EU). Our study includes the key hop‐growing regions across the EU such as Hallertau (Germany); \'{U}\v{s}tv{e}cko, \v{Z}atecko and Tr\v{s}ick\'{a} (Czech Republic); Kent (Great Britain); Alsace (France); Lublin (Poland); Koro\v{s}ka (Slovenia) and Le\'{o}n and Galicia (Spain). For these regions, we used the concurrent bivariate return period to model the joint probability distributions of daily precipitation and maximum temperature extremes and to provide risk assessments for concurrent drought‐heat waves during the hop‐growing season. We estimated the risk of lower yields from hop cones based on concurrent dry‐cool, dry‐hot, wet‐cool and wet‐hot modes over the target areas. The results show that longer and more severe drought and heat wave concurrences have increased more frequently than shorter concurrences. The degree of risk was estimated as being higher over the extensive hop‐growing areas in the Czech Republic and Germany. A total of 22.4, 12.5 and 7.2% of EU areas with conditions suitable for commercial hop production fell into the moderate, high and very high yield loss risk categories, respectively. Integrating the damage between April and August indicated that more than 62.7% of total yield losses were due to high temperatures under dry conditions and that 21.5% of the yield losses were due to dry‐cool conditions in the top hop‐farming regions. The hotter European droughts caused decreases in noble aromatic hops by 29\textendash68%. This indicates that hop yields are very vulnerable to these events due to a slower rate of adaptation of hops compared to field crops.}, keywords = {compound events, crops, drought & heat}, pubstate = {published}, tppubtype = {article} } Compound climate events in which only one variable is extreme (e.g., either hot but no drought or extreme drought but not hot) and events in which both variables are extreme (e.g., drought and heat waves) may have different impacts on hop yields and alpha‐bitter acid contents. Increasing occurrences of compound drought and heat events have led to increased income variability for beer production, and also affecting the major hop growers across Europe (EU). Our study includes the key hop‐growing regions across the EU such as Hallertau (Germany); Úštěcko, Žatecko and Tršická (Czech Republic); Kent (Great Britain); Alsace (France); Lublin (Poland); Koroška (Slovenia) and León and Galicia (Spain). For these regions, we used the concurrent bivariate return period to model the joint probability distributions of daily precipitation and maximum temperature extremes and to provide risk assessments for concurrent drought‐heat waves during the hop‐growing season. We estimated the risk of lower yields from hop cones based on concurrent dry‐cool, dry‐hot, wet‐cool and wet‐hot modes over the target areas. The results show that longer and more severe drought and heat wave concurrences have increased more frequently than shorter concurrences. The degree of risk was estimated as being higher over the extensive hop‐growing areas in the Czech Republic and Germany. A total of 22.4, 12.5 and 7.2% of EU areas with conditions suitable for commercial hop production fell into the moderate, high and very high yield loss risk categories, respectively. Integrating the damage between April and August indicated that more than 62.7% of total yield losses were due to high temperatures under dry conditions and that 21.5% of the yield losses were due to dry‐cool conditions in the top hop‐farming regions. The hotter European droughts caused decreases in noble aromatic hops by 29–68%. This indicates that hop yields are very vulnerable to these events due to a slower rate of adaptation of hops compared to field crops. |
Luca, De P; Messori, G; Faranda, D; Ward, P J; Coumou, D Compound warm-dry and cold-wet events over the Mediterranean Journal Article Earth System Dynamics, 11 (3), pp. 793–805, 2020. Abstract | Links | BibTeX | Tags: compound events, drought & heat @article{DeLuca2020, title = {Compound warm-dry and cold-wet events over the Mediterranean}, author = {P De Luca and G Messori and D Faranda and P J Ward and D Coumou}, editor = {Jakob Zscheischler}, url = {https://esd.copernicus.org/articles/11/793/2020/}, doi = {10.5194/esd-11-793-2020}, year = {2020}, date = {2020-01-01}, journal = {Earth System Dynamics}, volume = {11}, number = {3}, pages = {793--805}, abstract = {The Mediterranean (MED) Basin is a climate change hotspot that has seen drying and a pronounced increase in heatwaves over the last century. At the same time, it is experiencing increased heavy precipitation during wintertime cold spells. Understanding and quantifying the risks from compound events over the MED is paramount for present and future disaster risk reduction measures. Here, we apply a novel method to study compound events based on dynamical systems theory and analyse compound temperature and precipitation events over the MED from 1979 to 2018. The dynamical systems analysis quantifies the strength of the coupling between different atmospheric variables over the MED. Further, we consider compound warm\textendashdry anomalies in summer and cold\textendashwet anomalies in winter. Our results show that these warm\textendashdry and cold\textendashwet compound days are associated with large values of the temperature\textendashprecipitation coupling parameter of the dynamical systems analysis. This indicates that there is a strong interaction between temperature and precipitation during compound events. In winter, we find no significant trend in the coupling between temperature and precipitation. However in summer, we find a significant upward trend which is likely driven by a stronger coupling during warm and dry days. Thermodynamic processes associated with long-term MED warming can best explain the trend, which intensifies compound warm\textendashdry events.}, keywords = {compound events, drought & heat}, pubstate = {published}, tppubtype = {article} } The Mediterranean (MED) Basin is a climate change hotspot that has seen drying and a pronounced increase in heatwaves over the last century. At the same time, it is experiencing increased heavy precipitation during wintertime cold spells. Understanding and quantifying the risks from compound events over the MED is paramount for present and future disaster risk reduction measures. Here, we apply a novel method to study compound events based on dynamical systems theory and analyse compound temperature and precipitation events over the MED from 1979 to 2018. The dynamical systems analysis quantifies the strength of the coupling between different atmospheric variables over the MED. Further, we consider compound warm–dry anomalies in summer and cold–wet anomalies in winter. Our results show that these warm–dry and cold–wet compound days are associated with large values of the temperature–precipitation coupling parameter of the dynamical systems analysis. This indicates that there is a strong interaction between temperature and precipitation during compound events. In winter, we find no significant trend in the coupling between temperature and precipitation. However in summer, we find a significant upward trend which is likely driven by a stronger coupling during warm and dry days. Thermodynamic processes associated with long-term MED warming can best explain the trend, which intensifies compound warm–dry events. |
Vogel, Martha M; Hauser, Mathias; Seneviratne, Sonia Isabelle Projected changes in hot, dry and wet extreme events' clusters in CMIP6 multi-model ensemble Journal Article Environmental Research Letters, 15 , pp. 094021, 2020. Abstract | Links | BibTeX | Tags: climate extremes, compound events @article{Vogel2020, title = {Projected changes in hot, dry and wet extreme events' clusters in CMIP6 multi-model ensemble}, author = {Martha M Vogel and Mathias Hauser and Sonia Isabelle Seneviratne}, url = {https://doi.org/10.1088/1748-9326/ab90a7}, doi = {10.1088/1748-9326/ab90a7}, year = {2020}, date = {2020-01-01}, journal = {Environmental Research Letters}, volume = {15}, pages = {094021}, publisher = {IOP Publishing}, abstract = {Concurrent extreme events, i.e. multi-variate extremes, can be associated with strong impacts. Hence, an understanding of how such events are changing in a warming climate is helpful to avoid some associated climate change impacts and better prepare for them. In this article, we analyse the projected occurrence of hot, dry, and wet extreme events' clusters in the multi-model ensemble of the 6th phase of the Coupled Model Intercomparison Project (CMIP6). Changes in 'extreme extremes', i.e. events with only 1% probability of occurrence in the current climate are analysed, first as univariate extremes, and then when co-occurring with other types of extremes (i.e. events clusters) within the same week, month or year. The projections are analysed for present-day climate (+1 °C) and different levels of additional global warming (+1.5 °C, +2 °C, +3 °C). The results reveal substantial risk of occurrence of extreme events' clusters of different types across the globe at higher global warming levels. Hotspot regions for hot and dry clusters are mainly found in Brazil, i.e. in the Northeast and the Amazon rain forest, the Mediterranean region, and Southern Africa. Hotspot regions for wet and hot clusters are found in tropical Africa but also in the Sahel region, Indonesia, and in mountainous regions such as the Andes and the Himalaya.}, keywords = {climate extremes, compound events}, pubstate = {published}, tppubtype = {article} } Concurrent extreme events, i.e. multi-variate extremes, can be associated with strong impacts. Hence, an understanding of how such events are changing in a warming climate is helpful to avoid some associated climate change impacts and better prepare for them. In this article, we analyse the projected occurrence of hot, dry, and wet extreme events' clusters in the multi-model ensemble of the 6th phase of the Coupled Model Intercomparison Project (CMIP6). Changes in 'extreme extremes', i.e. events with only 1% probability of occurrence in the current climate are analysed, first as univariate extremes, and then when co-occurring with other types of extremes (i.e. events clusters) within the same week, month or year. The projections are analysed for present-day climate (+1 °C) and different levels of additional global warming (+1.5 °C, +2 °C, +3 °C). The results reveal substantial risk of occurrence of extreme events' clusters of different types across the globe at higher global warming levels. Hotspot regions for hot and dry clusters are mainly found in Brazil, i.e. in the Northeast and the Amazon rain forest, the Mediterranean region, and Southern Africa. Hotspot regions for wet and hot clusters are found in tropical Africa but also in the Sahel region, Indonesia, and in mountainous regions such as the Andes and the Himalaya. |
Ridder, Nina N; Pitman, Andy J; Westra, Seth; Ukkola, Anna; Hong, Do X; Bador, Margot; Hirsch, Annette L; Evans, Jason P; Luca, Alejandro Di; Zscheischler, Jakob Global hotspots for the occurrence of compound events Journal Article Nature Communications, 11 , pp. 5956, 2020. Abstract | Links | BibTeX | Tags: climate extremes, compound events @article{Ridder2020, title = {Global hotspots for the occurrence of compound events}, author = {Nina N Ridder and Andy J Pitman and Seth Westra and Anna Ukkola and X Do Hong and Margot Bador and Annette L Hirsch and Jason P Evans and Alejandro Di Luca and Jakob Zscheischler}, url = {https://doi.org/10.1038/s41467-020-19639-3}, doi = {10.1038/s41467-020-19639-3}, year = {2020}, date = {2020-01-01}, journal = {Nature Communications}, volume = {11}, pages = {5956}, publisher = {Nature Publishing Group}, abstract = {Compound events (CEs) are weather and climate events that result from multiple hazards or drivers with the potential to cause severe socio-economic impacts. Compared with isolated hazards, the multiple hazards/drivers associated with CEs can lead to higher economic losses and death tolls. Here, we provide the first analysis of multiple multivariate CEs potentially causing high-impact floods, droughts, and fires. Using observations and reanalysis data during 1980\textendash2014, we analyse 27 hazard pairs and provide the first spatial estimates of their occurrences on the global scale. We identify hotspots of multivariate CEs including many socio-economically important regions such as North America, Russia and western Europe. We analyse the relative importance of different multivariate CEs in six continental regions to highlight CEs posing the highest risk. Our results provide initial guidance to assess the regional risk of CE events and an observationally-based dataset to aid evaluation of climate models for simulating multivariate CEs.}, keywords = {climate extremes, compound events}, pubstate = {published}, tppubtype = {article} } Compound events (CEs) are weather and climate events that result from multiple hazards or drivers with the potential to cause severe socio-economic impacts. Compared with isolated hazards, the multiple hazards/drivers associated with CEs can lead to higher economic losses and death tolls. Here, we provide the first analysis of multiple multivariate CEs potentially causing high-impact floods, droughts, and fires. Using observations and reanalysis data during 1980–2014, we analyse 27 hazard pairs and provide the first spatial estimates of their occurrences on the global scale. We identify hotspots of multivariate CEs including many socio-economically important regions such as North America, Russia and western Europe. We analyse the relative importance of different multivariate CEs in six continental regions to highlight CEs posing the highest risk. Our results provide initial guidance to assess the regional risk of CE events and an observationally-based dataset to aid evaluation of climate models for simulating multivariate CEs. |
Bevacqua, Emanuele; Vousdoukas, Michalis I; Zappa, Giuseppe; Hodges, Kevin; Shepherd, Theodore G; Maraun, Douglas; Mentaschi, Lorenzo; Feyen, Luc More meteorological events that drive compound coastal flooding are projected under climate change Journal Article Communications Earth & Environment, 1 , pp. 47, 2020. Abstract | Links | BibTeX | Tags: compound flooding, hydrological compound events @article{Bevacqua2020bb, title = {More meteorological events that drive compound coastal flooding are projected under climate change}, author = {Emanuele Bevacqua and Michalis I Vousdoukas and Giuseppe Zappa and Kevin Hodges and Theodore G Shepherd and Douglas Maraun and Lorenzo Mentaschi and Luc Feyen}, url = {https://www.nature.com/articles/s43247-020-00044-z}, doi = {10.1038/s43247-020-00044-z}, year = {2020}, date = {2020-01-01}, journal = {Communications Earth & Environment}, volume = {1}, pages = {47}, publisher = {Nature Publishing Group}, abstract = {Compound flooding arises from storms causing concurrent extreme meteorological tides (that is the superposition of storm surge and waves) and precipitation. This flooding can severely affect densely populated low-lying coastal areas. Here, combining output from climate and ocean models, we analyse the concurrence probability of the meteorological conditions driving compound flooding. We show that, under a high emissions scenario, the concurrence probability would increase globally by more than 25% by 2100 compared to present. In latitudes above 40o north, compound flooding could become more than 2.5 times as frequent, in contrast to parts of the subtropics where it would weaken. Changes in extreme precipitation and meteorological tides account for most (77% and 20%, respectively) of the projected change in concurrence probability. The evolution of the dependence between precipitation and meteorological tide dominates the uncertainty in the projections. Our results indicate that not accounting for these effects in adaptation planning could leave coastal communities insufficiently protected against flooding.}, keywords = {compound flooding, hydrological compound events}, pubstate = {published}, tppubtype = {article} } Compound flooding arises from storms causing concurrent extreme meteorological tides (that is the superposition of storm surge and waves) and precipitation. This flooding can severely affect densely populated low-lying coastal areas. Here, combining output from climate and ocean models, we analyse the concurrence probability of the meteorological conditions driving compound flooding. We show that, under a high emissions scenario, the concurrence probability would increase globally by more than 25% by 2100 compared to present. In latitudes above 40o north, compound flooding could become more than 2.5 times as frequent, in contrast to parts of the subtropics where it would weaken. Changes in extreme precipitation and meteorological tides account for most (77% and 20%, respectively) of the projected change in concurrence probability. The evolution of the dependence between precipitation and meteorological tide dominates the uncertainty in the projections. Our results indicate that not accounting for these effects in adaptation planning could leave coastal communities insufficiently protected against flooding. |
Hillier, John K; Matthews, Tom; Wilby, Robert L; Murphy, Conor Multi-hazard dependencies can increase or decrease risk Journal Article Nature Climate Change, 10 (7), pp. 595–598, 2020. Abstract | Links | BibTeX | Tags: @article{hillier2020a, title = {Multi-hazard dependencies can increase or decrease risk}, author = {John K Hillier and Tom Matthews and Robert L Wilby and Conor Murphy}, url = {https://www.nature.com/articles/s41558-020-0832-y}, doi = {10.1038/s41558-020-0832-y}, year = {2020}, date = {2020-01-01}, journal = {Nature Climate Change}, volume = {10}, number = {7}, pages = {595--598}, publisher = {Nature Publishing Group}, abstract = {In risk analysis, it is recognized that hazards can often combine to worsen their joint impact, but impact data for a rail network show that hazards can also tend to be mutually exclusive at seasonal timescales. Ignoring this overestimates worst-case risk, so we therefore champion a broader view of risk from compound hazards.}, keywords = {}, pubstate = {published}, tppubtype = {article} } In risk analysis, it is recognized that hazards can often combine to worsen their joint impact, but impact data for a rail network show that hazards can also tend to be mutually exclusive at seasonal timescales. Ignoring this overestimates worst-case risk, so we therefore champion a broader view of risk from compound hazards. |