Depiction of drought over sub-Saharan Africa using reanalyses precipitation data sets
Depiction of drought over sub-Saharan Africa using reanalyses precipitation data sets
Reanalysis precipitation is routinely used as a surrogate for observations due to its high spatial and temporal resolution and global coverage, and it has been widely used in hydrologic and agricultural applications. The resultant product and analysis are largely dependent on the accuracy of the reanalysis precipitation data set. In this study, we analyze the impact of reanalysis precipitation uncertainties on drought depiction. Five reanalyses precipitation data sets (Climate Forecast System Reanalysis, R1: National Centers for Environmental Prediction (NCEP)/National Center for Atmospheric Research reanalysis, R2: NCEP/Department of Energy reanalysis II, 20CR: The Twentieth Century Reanalysis version 2 and Modern-Era Retrospective Analysis for Research and Applications) are evaluated from 1979 to 2012 over sub-Saharan Africa against an observational-based reference: The Princeton Global Meteorological Forcing data set. Results show that all the reanalyses precipitation data sets provide a relatively good representation of the long-term statistics of spatiotemporal drought characteristics in sub-Saharan Africa. However, deficiencies are found in the estimation of drought severity, the spatial pattern, and temporal persistency of droughts. Drought depiction over central Africa appears more problematic due to a lack of observational data. A comparison of drought depiction based on the Standardized Precipitation Index reveals higher monthly to seasonal precipitation variability that further increases after ~1999 due to changes in the observations included in the reanalyses assimilation systems.
10,555-10,574
Zhan, Wang
cfbebb9a-95c6-4e7d-a3b6-360c3d222db8
Guan, Kaiyu
79efc8b7-8ae3-43c7-a39c-9831af3ae12f
Sheffield, Justin
dd66575b-a4dc-4190-ad95-df2d6aaaaa6b
Wood, Eric F.
ee59ebb9-367e-48ce-beab-22666be5095d
2016
Zhan, Wang
cfbebb9a-95c6-4e7d-a3b6-360c3d222db8
Guan, Kaiyu
79efc8b7-8ae3-43c7-a39c-9831af3ae12f
Sheffield, Justin
dd66575b-a4dc-4190-ad95-df2d6aaaaa6b
Wood, Eric F.
ee59ebb9-367e-48ce-beab-22666be5095d
Zhan, Wang, Guan, Kaiyu, Sheffield, Justin and Wood, Eric F.
(2016)
Depiction of drought over sub-Saharan Africa using reanalyses precipitation data sets.
Journal of Geophysical Research, 121 (18), .
(doi:10.1002/2016JD024858).
Abstract
Reanalysis precipitation is routinely used as a surrogate for observations due to its high spatial and temporal resolution and global coverage, and it has been widely used in hydrologic and agricultural applications. The resultant product and analysis are largely dependent on the accuracy of the reanalysis precipitation data set. In this study, we analyze the impact of reanalysis precipitation uncertainties on drought depiction. Five reanalyses precipitation data sets (Climate Forecast System Reanalysis, R1: National Centers for Environmental Prediction (NCEP)/National Center for Atmospheric Research reanalysis, R2: NCEP/Department of Energy reanalysis II, 20CR: The Twentieth Century Reanalysis version 2 and Modern-Era Retrospective Analysis for Research and Applications) are evaluated from 1979 to 2012 over sub-Saharan Africa against an observational-based reference: The Princeton Global Meteorological Forcing data set. Results show that all the reanalyses precipitation data sets provide a relatively good representation of the long-term statistics of spatiotemporal drought characteristics in sub-Saharan Africa. However, deficiencies are found in the estimation of drought severity, the spatial pattern, and temporal persistency of droughts. Drought depiction over central Africa appears more problematic due to a lack of observational data. A comparison of drought depiction based on the Standardized Precipitation Index reveals higher monthly to seasonal precipitation variability that further increases after ~1999 due to changes in the observations included in the reanalyses assimilation systems.
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Published date: 2016
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Local EPrints ID: 480468
URI: http://eprints.soton.ac.uk/id/eprint/480468
ISSN: 0148-0227
PURE UUID: 20fe7b2e-dba4-4a12-8da1-a06ae33d0a4c
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Date deposited: 02 Aug 2023 17:11
Last modified: 18 Mar 2024 03:33
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Author:
Wang Zhan
Author:
Kaiyu Guan
Author:
Eric F. Wood
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