A parametric multivariate drought index and its application in the attribution and projection of flash drought change in China

Rainfall deficit in the crop growing seasons is usually accompanied by heat waves. Abnormally high temperature increases evapotranspiration and decreases soil moisture rapidly, and ultimately results in a type of drought with a rapid onset, short duration but devastating impact, which is called "Flash drought". With the increase in global temperature, flash drought is expected to occur more frequently. However, there is no consensus on the definition of flash drought so far. Moreover, large uncertainty exists in the estimation of the flash drought and its trend, and the underlying mechanism for its long-term change is not clear. In this presentation, a parametric multivariate drought index that characterizes the joint probability distribution of key variables of flash drought will be developed, and the historical changes in flash drought over China will be analyzed. In addition, a set of land surface model simulations driven by IPCC CMIP5 models with different forcings and future scenarios, will be used for the detection and attribution of flash drought change. This study is targeted at quantifying the influences of natural and anthropogenic climate change on the flash drought change, projecting its future change as well as the corresponding uncertainty, and improving our understanding of the variation of flash drought and its underlying mechanism in a changing climate.