Identifying meteorological drivers of extreme impacts: an application to simulated crop yields
Authors:Vogel, JohannesRivoire, PaulineDeidda, CristinaRahimi, LeilaSauter, Christoph A.Tschumi, Elisabethvan der Wiel, KarinZhang, TianyiZscheischler, Jakob
Source:EARTH SYSTEM DYNAMICS
Volume:12
Published:2021
Document Type:Article
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.
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Reprint Address:Vogel, J (corresponding author), Univ Potsdam, Inst Environm Sci & Geog, Potsdam, Germany.; Vogel, J (corresponding author), Tech Univ Berlin, Inst Ecol, Berlin, Germany.; Rivoire, P (corresponding author), Univ Bern, Oeschger Ctr Climate Change Res, Bern, Switzerland.; Rivoire, P (corresponding author), Univ Bern, Inst Geog, Bern, Switzerland.; Zhang, TY (corresponding author), Chinese Acad Sci, Inst Atmospher Phys, Beijing, Peoples R China.
Addresses:[Vogel, Johannes] Univ Potsdam, Inst Environm Sci & Geog, Potsdam, Germany. [Vogel, Johannes] Tech Univ Berlin, Inst Ecol, Berlin, Germany. [Rivoire, Pauline; Tschumi, Elisabeth; Zscheischler, Jakob] Univ Bern, Oeschger Ctr Climate Change Res, Bern, Switzerland. [Rivoire, Pauline] Univ Bern, Inst Geog, Bern, Switzerland. [Deidda, Cristina; Rahimi, Leila] Politecn Milan, Dept Civil & Environm Engn, Milan, Italy. [Rahimi, Leila] Univ Tabriz, Dept Water Engn, Tabriz, Iran. [Sauter, Christoph A.] Univ Strathclyde, Dept Civil & Environm Engn, Glasgow, Lanark, Scotland. [Tschumi, Elisabeth; Zscheischler, Jakob] Univ Bern, Climate & Environm Phys, Bern, Switzerland. [van der Wiel, Karin] Royal Netherlands Meteorol Inst KNMI, De Bilt, Netherlands. [Zhang, Tianyi] Chinese Acad Sci, Inst Atmospher Phys, Beijing, Peoples R China. [Zscheischler, Jakob] UFZ Helmholtz Ctr Environm Res, Dept Computat Hydrosyst, Leipzig, Germany.
E-mail Addresses:joschavogel@uni-potsdam.de; pauline.rivoire@giub.unibe.ch; wiel@knmi.nl; zhangty@post.iap.ac.cn