Abstract
Abstract. Estimating the likelihood of compound climate extremes such as concurrent drought and heatwaves or compound precipitation and wind speed extremes is important for assessing climate risks. Typically, simulations from climate models are used to assess future risks, but it is largely unknown how well the current generation of models represents compound extremes. Here, we introduce a new metric that measures whether the tails of bivariate distributions show a similar dependence structure across different datasets. We analyse compound precipitation and wind extremes in reanalysis data and different high-resolution simulations for central Europe. A state-of-the-art reanalysis dataset (ERA5) is compared to simulations with a weather model (Weather Research and Forecasting – WRF) either driven by observation-based boundary conditions or a global circulation model (Community Earth System Model – CESM) under present-day and future conditions with strong greenhouse gas forcing (Representative Concentration Pathway 8.5 – RCP8.5). Over the historical period, the high-resolution WRF simulations capture precipitation and wind extremes as well as their response to orographic effects more realistically than ERA5. Thus, WRF simulations driven by observation-based boundary conditions are used as a benchmark for evaluating the dependence structure of wind and precipitation extremes. Overall, boundary conditions in WRF appear to be the key factor in explaining differences in the dependence behaviour between strong wind and heavy precipitation between simulations. In comparison, external forcings (RCP8.5) are of second order. Our approach offers new methodological tools to evaluate climate model simulations with respect to compound extremes.
Highlights
Compound climate extremes such as co-occurring drought and heat or compound precipitation and wind extremes can have a substantial impact on the natural environment and human systems that often exceeds the impact caused by a single extreme (Zscheischler et al, 2014; Raveh-Rubin and Wernli, 2015; Martius et al, 2016; Sippel et al, 2018)
ERAI-Weather Research and Forecasting (WRF) shows slightly higher tail dependence compared to the WRF simulations driven by Community Earth System Model (CESM)
We have introduced a new metric for comparing tail dependence structures between wind and precipitation extremes in reanalysis data and weather model simulations
Summary
Compound climate extremes such as co-occurring drought and heat or compound precipitation and wind extremes can have a substantial impact on the natural environment and human systems that often exceeds the impact caused by a single extreme (Zscheischler et al, 2014; Raveh-Rubin and Wernli, 2015; Martius et al, 2016; Sippel et al, 2018). Other studies have investigated the cooccurrence of hot days and hot nights (Wang et al, 2020) or the co-occurrence rate of heavy precipitation and snowmelt to estimate the risk of rain-on-snow events (Musselman et al, 2018; Poschlod et al, 2020). Such a quantification of the occurrence rate of compound extremes is important for assessing the risk of associated impacts today and in the future. Due to the rarity of compound extremes, a large number of samples is required to obtain robust estimates, making it difficult to rely solely on observational data (Ridder et al, 2020)
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