Special issue | Understanding compound weather and climate events and related impacts (BG/ESD/HESS/NHESS inter-journal SI)(BG/ESD/HESS/NHESS inter-journal SI)
Editor(s): Jakob Zscheischler, Bart van den Hurk, and Gabriele Messori Special issue jointly organized between Biogeosciences, Earth System Dynamics, Hydrology and Earth System Sciences, and Natural Hazards and Earth System Sciences More information
Compound weather and climate events refer to combinations of multiple weather and climate drivers and/or hazards that lead to potentially large impacts. Compound events encompass a highly diverse set of events including concurrent climate extremes but also an array of nonstandard high-impact events. Consequently, research on compound events requires expertise from a variety of disciplines such as climate science, hydrology, impact modelling, engineering, and statistics, among others. The European COST Action DAMOCLES (http://damocles.compoundevents.org) provides a platform for compound event research and for generating synergies between the different research domains. This inter-journal special issue will serve as an outlet for the work within DAMOCLES and aims to advance our understanding of different aspects of compound events, including present-day and future risk assessments of such events, modelling of individual compound events, bottom-up approaches to identify new types of compound events, and novel model evaluation techniques. It is open for all submissions within its scope.
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Assessing internal changes in the future structure of Dry-Hot compound events. The case of the Pyrenees
Marc Lemus-Canovas and Joan Albert Lopez-Bustins
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2021-5,https://doi.org/10.5194/nhess-2021-5, 2021
Preprint under review for NHESS (discussion: open, 0 comments)
We present a research that attempts to address recent and future changes of hot and dry compound events in the Pyrenees, which can induce severe environmental hazards in this area. The results show that during last decades, this kind of compound events only increased due to the temperature increase. However, for the future, it is expected that the risk associated with these compound events will raise both by the thermal increase and the longer duration of drought periods.
Machine learning methods to assess the effects of a non-linear damage spectrum taking into account soil moisture on winter wheat yields in Germany
Michael Peichl, Stephan Thober, Luis Samaniego, Bernd Hansjürgens, and Andreas Marx
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-9,https://doi.org/10.5194/hess-2021-9, 2021
Preprint under review for HESS (discussion: open, 0 comments)
A statistical model that can account for complex systems is used to identify the main factors affecting wheat yield in Germany. In many parts of Germany, the main adverse effect is caused by too much soil water in spring. Yield losses in northeastern Germany are related to soil moisture drought. Meteorological effects such as heat do not seem to play a prominent role. Furthermore, the model is able to explain both exceptionally high yields (2014) and yields in very high loss years (2003, 2018).
Evaluating the dependence structure of compound precipitation and wind speed extremes
Jakob Zscheischler, Philippe Naveau, Olivia Martius, Sebastian Engelke, and Christoph C. Raible
Earth Syst. Dynam., 12, 1–16, https://doi.org/10.5194/esd-12-1-2021,https://doi.org/10.5194/esd-12-1-2021, 2021
Compound extremes such as heavy precipitation and extreme winds can lead to large damage. To date it is unclear how well climate models represent such compound extremes. Here we present a new measure to assess differences in the dependence structure of bivariate extremes. This measure is applied to assess differences in the dependence of compound precipitation and wind extremes between three model simulations and one reanalysis dataset in a domain in central Europe.
Vegetation modulates the impact of climate extremes on gross primary production
Milan Flach, Alexander Brenning, Fabian Gans, Markus Reichstein, Sebastian Sippel, and Miguel D. Mahecha
Biogeosciences, 18, 39–53, https://doi.org/10.5194/bg-18-39-2021,https://doi.org/10.5194/bg-18-39-2021, 2021
Drought and heat events affect the uptake and sequestration of carbon in terrestrial ecosystems. We study the impact of droughts and heatwaves on the uptake of CO2 of different vegetation types at the global scale. We find that agricultural areas are generally strongly affected. Forests instead are not particularly sensitive to the events under scrutiny. This implies different water management strategies of forests but also a lack of sensitivity to remote-sensing-derived vegetation activity.
Impact of bias nonstationarity on the performance of uni- and multivariate bias-adjusting methods
Jorn Van de Velde, Matthias Demuzere, Bernard De Baets, and Niko E. C. Verhoest
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2020-639,https://doi.org/10.5194/hess-2020-639, 2020
Preprint under review for HESS (discussion: open, 1 comment)
An important step in projecting future climate is the bias adjustment of the climatological and hydrological variables. In this paper, we illustrate how bias adjustment can be impaired by bias nonstationarity. Two univariate and three multivariate methods are compared, and for both types the bias nonstationarity can be linked with less robust adjustment. However, the multivariate methods show greater variability and thus univariate methods may currently be preferred.
Classifying compound coastal storm and heavy rainfall events in the north-western Spanish Mediterranean
Marc Sanuy, Tomeu Rigo, José A. Jiménez, and M. Carmen Llasat
Towards a compound event-oriented climate model evaluation: A decomposition of the underlying biases in multivariate fire and heat stress hazards
Roberto Villalobos-Herrera, Emanuele Bevacqua, Andreia F. S. Ribeiro, Graeme Auld, Laura Crocetti, Bilyana Mircheva, Minh Ha, Jakob Zscheischler, and Carlo De Michele
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2020-383,https://doi.org/10.5194/nhess-2020-383, 2020
Preprint under review for NHESS (discussion: open, 1 comment)
Climate hazards may be caused by events which have multiple drivers. Here we present a method to break down climate model biases in hazard indicators down to the bias caused by each driving variable. Using simplified fire and heat stress indicators driven by temperature and relative humidity, we show how multivariate indicators may have complex biases and that the relationship between driving variables is a source of bias that must be considered in climate model bias corrections.
Compound high temperature and low chlorophyll extremes in the ocean over the satellite period
Natacha Le Grix, Jakob Zscheischler, Charlotte Laufkötter, Cécile S. Rousseaux, and Thomas L. Frölicher
Biogeosciences Discuss., https://doi.org/10.5194/bg-2020-412,https://doi.org/10.5194/bg-2020-412, 2020
Revised manuscript under review for BG (discussion: final response, 4 comments)
Marine ecosystems could suffer severe damage from the co-occurrence of a marine heatwave with extremely low chlorophyll concentration. Here, we provide a first assessment of compound marine heatwave and low chlorophyll events in the global ocean from 1998 to 2018. We reveal hotspots of these compound events in the equatorial Pacific and in the Arabian Sea, show that they mostly occur in summer at high latitudes, and that their frequency is modulated by large-scale modes of climate variability.
Canopy temperature and heat stress are increased by compound high air temperature and water stress, and reduced by irrigation – A modeling analysis
Xiangyu Luan and Giulia Vico
Preprint under review for HESS (discussion: final response, 4 comments)
Crop yield is reduced by heat and water stress, in particular when they co-occur. We quantify the joint effects of the (unpredictable) air temperature and water availability on crop heat stress via a mechanistic model. Larger but more infrequent rainfalls increased crop canopy temperatures. Keeping crops well watered via irrigation could reduce canopy temperature, but not enough to exclude heat damage. Thus, irrigation is only a partial solution to adapt to warmer and drier climates.
Multivariate statistical modelling of extreme coastal water levels and the effect of climate variability: a case study in the Netherlands
Victor M. Santos, Mercè Casas-Prat, Benjamin Poschlod, Elisa Ragno, Bart van den Hurk, Zengchao Hao, Tímea Kalmár, Lianhua Zhu, and Husain Najafi
Risk of crop failure due to compound dry and hot extremes estimated with nested copulas
Andreia Filipa Silva Ribeiro, Ana Russo, Célia Marina Gouveia, Patrícia Páscoa, and Jakob Zscheischler
Biogeosciences, 17, 4815–4830, https://doi.org/10.5194/bg-17-4815-2020,https://doi.org/10.5194/bg-17-4815-2020, 2020
This study investigates the impacts of compound dry and hot extremes on crop yields, namely wheat and barley, over two regions in Spain dominated by rainfed agriculture. We provide estimates of the conditional probability of crop loss under compound dry and hot conditions, which could be an important tool for responsible authorities to mitigate the impacts magnified by the interactions between the different hazards.
Estimating the Probability of Compound Floods in Estuarine Regions
Wenyan Wu, Seth Westra, and Michael Leonard
Revised manuscript under review for HESS (discussion: final response, 4 comments)
Flood probability estimation is important for applications such as land use planning, reservoir operation, infrastructure design and safety assessments. However, it is a challenging task, especially in estuarine areas where floods are caused by both intense rainfall and storm surge. This study provides a review of approaches to flood probability estimation in these areas. Based analysis of a real-world river system, guidance on method selection is provided.
A dynamical and thermodynamic mechanism to explain heavy snowfalls in current and future climate over Italy during cold spells
Miriam D'Errico, Pascal Yiou, Cesare Nardini, Frank Lunkeit, and Davide Faranda
Earth Syst. Dynam. Discuss., https://doi.org/10.5194/esd-2020-61,https://doi.org/10.5194/esd-2020-61, 2020
Preprint under review for ESD (discussion: final response, 2 comments)
Climate change is already affecting weather extreme. In a warming climate, we will expect the intensity of cold spells to decrease in frequency and intensity. However, our analysis shows that the intensity of snowy cold spells events over Italy is not decreasing and that most of the extreme snowfalls occur in the very recent past. Using climate simulations, we show a key mechanism in modulating snowfall in a warming climate: the convective feedback of the Mediterranean Sea.
Compound warm–dry and cold–wet events over the Mediterranean
Paolo De Luca, Gabriele Messori, Davide Faranda, Philip J. Ward, and Dim Coumou
Earth Syst. Dynam., 11, 793–805, https://doi.org/10.5194/esd-11-793-2020,https://doi.org/10.5194/esd-11-793-2020, 2020
In this paper we quantify Mediterranean compound temperature and precipitation dynamical extremes (CDEs) over the 1979–2018 period. The strength of the temperature–precipitation coupling during summer increased and is driven by surface warming. We also link the CDEs to compound hot–dry and cold–wet events during summer and winter respectively.
Compound flood potential from storm surge and heavy precipitation in coastal China
Jiayi Fang, Thomas Wahl, Jian Fang, Xun Sun, Feng Kong, and Min Liu
A standardized index for assessing sub-monthly compound dry and hot conditions
Jun Li, Zhaoli Wang, Xushu Wu, Jakob Zscheischler, Shenglian Guo, and Xiaohong Chen
We introduce a daily-scale index, termed as the standardized compound drought and heat index (SCDHI), to measure the intensity of compound dry and hot conditions. SCDHI can not only monitor the long-term compound dry and hot events, but also capture such events at sub-monthly scale and reflect the related vegetation activity impacts. The index can provide a new tool to quantify sub-monthly characteristics of compound dry and hot events, which are vital to release early and timely warnings.
Identifying meteorological drivers of extreme impacts: an application to simulated crop yields
Johannes Vogel, Pauline Rivoire, Cristina Deidda, Leila Rahimi, Christoph Alexander Sauter, Elisabeth Tschumi, Karin van der Wiel, Tianyi Zhang, and Jakob Zscheischler
Revised manuscript accepted for ESD (discussion: closed, 6 comments)
We present a statistical approach for automatically identifying multiple drivers of extreme impacts based on Lasso regression. We apply the approach to simulated crop failure in the Northern Hemisphere and identify which meteorological variables including climate extreme indices and which seasons are relevant to predict crop failure. The presented approach can help unravel compounding drivers in high-impact events and could be applied to other impacts such as wildfires or flooding.
Quantifying the Impacts of Compound Extremes on Agriculture and Irrigation Water Demand
Iman Haqiqi, Danielle S. Grogan, Thomas W. Hertel, and Wolfram Schlenker
Revised manuscript accepted for HESS (discussion: closed, 4 comments)
We combine a high-resolution weather product with fine-scale outputs of a hydrological model to construct functional indicators of compound hydroclimatic extremes for agriculture. We confirm that "wet heat" is more damaging than "dry heat" for crops. We show the average damage from heat stress has been up to four times more severe when combined with water stress. The results are important for research on climate change, irrigation water demand, and subsurface drainage.
Simulating compound weather extremes responsible for critical crop failure with stochastic weather generators
Peter Pfleiderer, Aglaé Jézéquel, Juliette Legrand, Natacha Legrix, Iason Markantonis, Edoardo Vignotto, and Pascal Yiou
In 2016, northern France experienced an unprecedented wheat crop loss. This crop loss was likely due to an extremely warm December 2015 and abnormally high precipitation during the following spring season. Using stochastic weather generators we investigate how severe the metrological conditions leading to the crop loss could be in current climate conditions. We find that December temperatures were close to the plausible maximum but that considerably wetter springs would be possible.