A monitoring and prediction system for compound dry and hot events

Abstract

Compound dry and hot events (i.e. concurrent or consecutive occurrences of dry and hot events), which may cause larger impacts than those caused by extreme events occurring in isolation, have attracted wide attention in recent decades. Increased occurrences of compound dry and hot events in different regions around the globe highlight the importance of improved understanding and modeling of these events so that they can be tracked and predicted ahead of time. In this study, a monitoring and prediction system of compound dry and hot events at the global scale is introduced. The monitoring component consists of two indicators (standardized compound event indicator and a binary variable) that incorporate both dry and hot conditions for characterizing the severity and occurrence. The two indicators are shown to perform well in depicting compound dry and hot events during June-July-August 2010 in western Russia. The prediction component consists of two statistical models, including a conditional distribution model and a logistic regression model, for predicting compound dry and hot events based on El Niño-Southern Oscillation, which is shown to significantly affect compound events of several regions, including northern South America, southern Africa, southeast Asia, and Australia. These models are shown to perform well in predicting compound events in large regions (e.g. northern South America and southern Africa) during December-January-February 2015-2016. This monitoring and prediction system could be useful for providing early warning information of compound dry and hot events.

Influence of Large‐Scale Circulation Patterns on Compound Dry and Hot Events in China

“…Thus, it is different from the method used above based on discrete occurrences of compound events. The impact of large‐scale circulation anomalies on CDHEs can be assessed through correlation coefficients between climate indices and SCEI (Hao et al., 2019).…”

“…Here, the joint probability p of each pairs of precipitation and temperature (x i , y i ) in observational periods is estimated using the Gringorten plotting position (Hao et al, 2019), as follows:…”

Comment on nhess-2021-46

“…To test the influence of TT and PET on the probability of occurrence of dry events, we employ a joint 150 distribution analysis of compound events (e.g. the co-occurrence of low precipitation and dry events or high temperature and dry events) (Hao et al, 2019). In this study we focus on the SPEI for an accumulation period of 12-months (SPEI12), PET, PP and TT averaged over the three regions: MED, CEU and NEU.…”

Increasing Risk of Wild Swings between Droughts and Floods over Global Land Areas

“…According to the Intergovernmental Panel on Climate Change report, compound events describe multiple climate drivers and/or hazards that occur simultaneously or successively to contribute to societal or environmental risk 41 . In combination, these hazards caused devastating impacts well beyond that which any one of these hazards would have caused in isolation 44 , and for this reason, compound events have received increasing attention in the recent decade 45,46,47,48,49 . By definition, the consecutive occurrence of reversed weather patterns can be considered compound events; however, comparing to the concurrent climate extremes, e.g., droughts and heat waves, heavy precipitation and storm surge, etc., synchronicity of contrasting extreme events has been largely overlooked.…”