climate extremes; copulas; multivariate extremes; carbon cycle; climate risk; climate model; compound events
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 (2020), A typology of compound weather and climate events, in
Nature Reviews Earth & Environment, -.
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 (2020), Understanding and managing connected extreme events, in
Nature Climate Change, -.
Poschlod Benjamin, Zscheischler Jakob, Sillmann Jana, Wood Raul R., Ludwig Ralf (2020), Climate change effects on hydrometeorological compound events over southern Norway, in
Weather and Climate Extremes, 100253-100253.
Tschumi Elisabeth, Zscheischler Jakob (2020), Countrywide climate features during recorded climate-related disasters, in
Climatic Change, 158(3-4), 593-609.
Paschalis Athanasios, Fatichi Simone, Zscheischler Jakob, Ciais Philippe, Bahn Michael, Boysen Lena, Chang Jinfeng, De Kauwe Martin, Estiarte Marc, Goll Daniel, Hanson Paul J., Harper Anna B., Hou Enqing, Kigel Jaime, Knapp Alan K., Larsen Klaus Steenberg, Li Wei, Lienert Sebastian, Luo Yiqi, Meir Patrick, Nabel Julia E.M.S., Ogaya Romà, Parolari Anthony J, Peng Changhui, et al. (2020), Rainfall‐manipulation experiments as simulated by terrestrial biosphere models: where do we stand?, in
Global Change Biology, gcb.15024-gcb.15024.
Runge Jakob, Bathiany Sebastian, Bollt Erik, Camps-Valls Gustau, Coumou Dim, Deyle Ethan, Glymour Clark, Kretschmer Marlene, Mahecha Miguel D., Muñoz-Marí Jordi, van Nes Egbert H., Peters Jonas, Quax Rick, Reichstein Markus, Scheffer Marten, Schölkopf Bernhard, Spirtes Peter, Sugihara George, Sun Jie, Zhang Kun, Zscheischler Jakob (2019), Inferring causation from time series in Earth system sciences, in
Nature Communications, 10(1), 2553-2553.
VogelMartha, ZscheischlerJakob, WartenburgerRichard, DeeDick, SeneviratneSonia (2019), Concurrent 2018 Hot Extremes Across Northern Hemisphere Due to Human‐Induced Climate Change, in
Earth's Future, 7, 693-703.
Yang Hui, Piao Shilong, Huntingford Chris, Peng Shushi, Ciais Philippe, Chen Anping, Zhou Guiyun, Wang Xuhui, Gao Mengdi, Zscheischler Jakob (2019), Strong but Intermittent Spatial Covariations in Tropical Land Temperature, in
Geophysical Research Letters, 46(1), 356-364.
Zscheischler Jakob, Fischer Erich M., Lange Stefan (2019), The effect of univariate bias adjustment on multivariate hazard estimates, in
Earth System Dynamics, 10(1), 31-43.
Climate-related hazards such as heat waves, droughts, and floods can lead to devastating impacts on human societies and ecosystems. The impacts are often particularly severe when several hazards occur at the same time. Many hazards result from a combination of physical processes that interact on multiple spatial and temporal scales. Climate change will alter many of these processes and their interactions, making projections of future hazards based on single driver analyses difficult. Impact studies that consider only one climatic driver usually fail to assess the full extent of the impacts associated with multiple dependent drivers. Furthermore, it is not clear whether current climate models can capture major changes in risk associated with climate-related hazards. Existing modelling approaches used to assess risk may therefore lead to serious mal-adaptation. This project will (i) develop new metrics to evaluate climate models with respect to multivariate relationships, extremes, and compound hazards, (ii) constrain model ensembles with observations to improve projections of hazards and compound hazards, and (iii) relate hazard probabilities with impacts to quantify the importance of climate in comparison to vulnerability and exposure for high-impact climate events. The project will focus on the compound hazards a) drought and heat, b) wind and precipitation extremes, as well as on the hazards c) human heat stress and d) fire risk, which both can be expressed in terms of temperature and relative humidity. As a data basis for the development of new metrics, the project will largely rely on pre-industrial control simulations of climate models. These long simulations do not contain trends and other non-stationarities associated with human-induced climate change and thus provide an excellent environment to develop new robust statistical approaches. Subsequently, the new metrics will be used to constrain hazards in present-day and future simulations from climate model ensembles with observation-based gridded climate and reanalysis datasets. Furthermore, estimated hazard probabilities will be confronted with modeled and observed impacts such as extremely anomalous carbon fluxes, extremely low crop yields, human mortality, damaged infrastructure, and large wildfires. We will further conduct experiments with a dynamical vegetation model to study the influence of different drought-heat signatures on carbon dynamics such as interannual variability of carbon fluxes and cumulative carbon uptake. The newly developed metrics will serve a wide community of Earth system modelers for better evaluating process-based models against multivariate dependencies that are critical for large impacts. These metrics will complement and extend established model evaluation systems. Improved projections of hazards, in particular compound hazards, are highly relevant for assessing future risks associated with climate extremes. Comparing hazard probabilities with actual impacts will put the contribution of climate drivers into perspective and reveal in which regions and for which hazards other non-climatic factors related to vulnerability and exposure play an important role. These insights are critical for a broad community including risk managers, decision-makers and private businesses such as the insurance sector.