4.6 Article

The record-breaking compound hot and dry 2018 growing season in Germany

Journal

WEATHER AND CLIMATE EXTREMES
Volume 29, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.wace.2020.100270

Keywords

Compound events; Germany; Drought; Heat; Copula; Climate extremes

Funding

  1. European COST Action DAM-OCLES [CA17109]
  2. Swiss National Science Foundation [179876]

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Record-breaking hot temperatures were observed in many places around the world in 2018, causing heat-related deaths, crop failure, wildfires and infrastructural damages. In Germany, extremely hot temperatures were accompanied by extremely low precipitation, compounding the impacts. Here we investigate spring to autumn temperature and precipitation in Germany over the historical period. We show that since measurements started in 1881, Germany has never experienced as hot and dry conditions during March to November as in 2018. We analyse the rarity of the event and illustrate that estimates of return periods for such compound extreme events are extremely high but very uncertain and strongly depend on the way they are estimated. We further investigate output from an ensemble of climate model simulations (CMIP5). Most climate models represent the distributions of temperature and precipitation in Germany and their dependence relatively well. Statistical projections of the bivariate temperature-precipitation distribution suggests that a growing season such as 2018 will become less likely at warmer global mean temperatures due to slight increases in precipitation. In contrast, climate models project an increasing likelihood of a 2018-like event and much larger uncertainties both for temperature and precipitation at different warming levels. Both observation-based scaling and climate model estimates consistently project that the compound hot and dry conditions in peak summer June-August become more likely. Overall, our results highlight the challenges associated with estimating the rarity of very extreme multivariate events and illustrate how consistent future changes in multivariate extremes can be estimated from observations only.

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