Evaluation of the applicability of multiple drought indices in the core zone of “westerlies-dominated climatic regime”

Drought indices are frequently used to measure the intensity,start and end of droughts.However,the performances of these indices depend on regions and the type of droughts.Therefore,it is necessary to evaluate whether these indices are applicable for a given region.This study evaluated the ability of the self-calibrating Palmer Drought Severity Index(sc PDSI),the Standardized Precipitation Evapotranspiration Index(SPEI),and the Standardized Moisture Anomaly Index(SZI) to describe the dry-wet conditions and drought events in the core zone of the “westerlies-dominated climatic regime”.The results showed that the 12-month SZI(SZI12) and SPEI(SPEI12) have good correlations with precipitation and PET respectively,while the sc PDSI can capture the changes in precipitation and soil moisture.In Xinjiang region of China,the SZI12 and sc PDSI showed that this region gradually became wetter during 1961–2014,which was consistent with increased precipitation,decreased PET,and improved vegetation.However,the SPEI12 showed significant drying due to the strong influence of the PET,suggesting that this index exaggerated the drought conditions in this region.Precipitation in Kazakhstan and the southern Central Asian regions has increased slightly over the past 50 years,but the PET has greatly increased,altogether,all three indices suggested a drying trend in Central Asia.The evaluation of the ability of these drought indices to identify typical drought events in Xinjiang region of China suggested that the sc PDSI can better detect the typical drought events compared with the SZI12.In conclusion,the sc PDSI is the most suitable index for characterizing the long-term trend of hydroclimate conditions and drought events in the core zone of the “westerlies-dominated climatic regime”.This study provides a theoretical basis for the rational utilization and improvement of the drought index,which is critical for monitoring,attributing,and predicting of drought events in arid areas.