Publication Details

Category Text Publication
Reference Category Journals
DOI 10.1038/s41597-022-01279-5
Licence creative commons licence
Title (Primary) Development and application of high resolution SPEI drought dataset for Central Asia
Author Pyarali, K.; Peng, J. ORCID logo ; Disse, M.; Tuo, Y.
Source Titel Scientific Data
Year 2022
Department RS
Volume 9
Page From art. 172
Language englisch
Topic T5 Future Landscapes
Abstract Central Asia is a data scarce region, which makes it difficult to monitor and minimize the impacts of a drought. To address this challenge, in this study, a high-resolution (5 km) Standardized Precipitation Evaporation Index (SPEI-HR) drought dataset was developed for Central Asia with different time scales from 1981–2018, using Climate Hazards group InfraRed Precipitation with Station’s (CHIRPS) precipitation and Global Land Evaporation Amsterdam Model’s (GLEAM) potential evaporation (Ep) datasets. As indicated by the results, in general, over time and space, the SPEI-HR correlated well with SPEI values estimated from coarse-resolution Climate Research Unit (CRU) gridded time series dataset. The 6-month timescale SPEI-HR dataset displayed a good correlation of 0.66 with GLEAM root zone soil moisture (RSM) and a positive correlation of 0.26 with normalized difference vegetation index (NDVI) from Global Inventory Monitoring and Modelling System (GIMMS). After observing a clear agreement between SPEI-HR and drought indicators for the 2001 and 2008 drought events, an emerging hotspot analysis was conducted to identify drought prone districts and sub-basins.
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Pyarali, K., Peng, J., Disse, M., Tuo, Y. (2022):
Development and application of high resolution SPEI drought dataset for Central Asia
Sci. Data 9 , art. 172 10.1038/s41597-022-01279-5