Details zur Publikation

Kategorie Textpublikation
Referenztyp Zeitschriften
DOI 10.1038/s41597-022-01279-5
Lizenz creative commons licence
Titel (primär) Development and application of high resolution SPEI drought dataset for Central Asia
Autor Pyarali, K.; Peng, J. ORCID logo ; Disse, M.; Tuo, Y.
Quelle Scientific Data
Erscheinungsjahr 2022
Department RS
Band/Volume 9
Seite von art. 172
Sprache englisch
Topic T5 Future Landscapes
Supplements https://static-content.springer.com/esm/art%3A10.1038%2Fs41597-022-01279-5/MediaObjects/41597_2022_1279_MOESM1_ESM.pdf
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.
dauerhafte UFZ-Verlinkung https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=26084
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