Occurrence of drought events at the land–atmosphere interface in Central Asia assessed via advanced microwave scanning radiometer data

Abstract

AbstractThe timely and effective early warning of sudden drought events is of great importance for reducing disaster losses and drought risk. Satellite microwave remote sensing with the advanced microwave scanning radiometer (AMSR) has enabled the global monitoring of multiple components of water, such as soil moisture (SM), vapour pressure deficit (VPD), and open water fraction (OWF), on a daily scale since 2002. In this study, the applicability of the AMSR surface wetness index (ASWI) and drought features in Central Asia were studied from 2002 to 2017 based on AMSR data. This study concluded that (1) the spatial and temporal differences in the various water components and coefficient of variation of the Central Asia land–atmosphere interface were large, which led to large spatial and temporal differences under both dry and wet conditions in Central Asia; (2) although the ASWI was not significantly correlated with other drought indices (i.e., gravity recovery and climate experiment (GRACE) combined climatological deviation index (CCDI) and GRACE drought severity index (DSI)) over Central Asia, the maximum Pearson correlation coefficient (CC) between the ASWI and Palmer drought severity index (PDSI) in the Irtysh River Basin was 0.824 (p < 0.05), corresponding to a moving average window of 11 months. The CCs of ASWI and Standardized Precipitation Evapotranspiration Index on a 6‐month scale (SPEI‐6) in Central Asia were generally more than 0.8 (p < 0.05), indicating that the ASWI was effective for retrieving drought conditions in Central Asia. In addition, these four drought indices (ASWI, PDSI, GRACE‐DSI, and GRACE‐CCDI) revealed that drought occurred continuously after 2003 in Central Asia; (3) the spatial and temporal distribution of dry and wet conditions in Central Asia is closely related to the teleconnection indices (i.e., MEI, SOI, and PDO). Thus, AMSR data are critical for understanding drought events and their evolution in regions influenced by climate change.