资源环境科技发展态势分析平台

Compound precipitation and temperature events have received much attention in recent decades owing to their amplified impacts on agriculture, economy and public health. Due to the relationship between precipitation and temperature, both of which are affected by El Niño–Southern Oscillation (ENSO) in large regions across the globe, joint modeling of their variability under influences of ENSO is desirable for understanding compound events. In this study, a statistical approach is proposed for the evaluation and prediction of compound precipitation and temperature events (with a focus on compound dry and hot events) under influences of ENSO by constructing the joint distribution of precipitation, temperature, and the ENSO indicator. The joint probability of precipitation and temperature is compared with the conditional probability given different states of ENSO for June–July-August (JJA) and December–January-February (DJF) over global land areas. Results show that ENSO affects the risk of compound dry and hot events in regions including southern Canada, northern South America, southeast Asia, south Africa, and part of Australia. The conditional distribution of precipitation and temperature given ENSO enables the probabilistic prediction of compound events. The strong El Niño event during DJF 2015–2016 significantly affects risks of the compound dry and hot event and provides useful early warning information for large regions including northern South America and south Africa. This study provides useful insights for improved understanding and early warning of compound dry and hot events to reduce their negative impacts.