Gridded daily 2-m air temperature dataset for Ethiopia derived by debiasing and downscaling ERA5-Land for the period 1981-2010.

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State: Public
Version: Final published version
License: CC BY 4.0
Serval ID
serval:BIB_300CD647F325
Type
Article: article from journal or magazin.
Publication sub-type
Review (review): journal as complete as possible of one specific subject, written based on exhaustive analyses from published work.
Collection
Publications
Institution
Title
Gridded daily 2-m air temperature dataset for Ethiopia derived by debiasing and downscaling ERA5-Land for the period 1981-2010.
Journal
Data in brief
Author(s)
Wakjira M.T., Peleg N., Burlando P., Molnar P.
ISSN
2352-3409 (Electronic)
ISSN-L
2352-3409
Publication state
Published
Issued date
02/2023
Peer-reviewed
Oui
Volume
46
Pages
108844
Language
english
Notes
Publication types: Journal Article
Publication Status: epublish
Abstract
A gridded maximum and minimum (Tx and Tn) daily temperature dataset derived by spatial downscaling and bias correction of the ERA5-Land (ERA5L) for the period 1981-2010 is presented. Observed daily Tx and Tn at 154 stations in Ethiopia covering record lengths of 5-30 years were used as a reference. The statistics that define the Gaussian distribution (mean and standard deviation) of Tx and Tn from the station observations were interpolated in space to create a monthly climatology and interannual statistics at 0.05° × 0.05° resolution using a hybrid interpolation approach that combines linear regression with topographic and location attributes, and non-Euclidean inverse distance weighting interpolation. The interpolated monthly and interannual statistics were then used to debias the ERA5L Tx and Tn using a quantile mapping approach. Leave-one-out cross-validation showed that the mean absolute errors in the corrected and downscaled daily temperatures are about 0.7 °C for Tx and 1.1 °C for Tn, reducing the statistical biases in the ERA5L Tx and Tn by 68% and 25% respectively. For monthly climatology, 40-64% of the biases were removed for Tx while for Tn the reductions range from 19% to 32%. The correction also improved commonly used indices for extremes like the probability of warm days, cold days, and warm nights, but overestimated the probability of cold nights. The presented open-access Tx and Tn dataset is a substantial improvement over existing gridded temperature datasets for Ethiopia, such as ERA5L and the Climate Hazards Infrared Temperature with Station (CHIRTS), and we suggest it is suitable for a wide range of environmental applications, e.g. in the fields of hydrology, agriculture, and ecology.
Keywords
Climate data, Linear regression, Inverse distance weighting, Spatial interpolation, Bias correction, Quantile mapping, Bias correction, Climate data, Inverse distance weighting, Linear regression, Quantile mapping, Spatial interpolation
Pubmed
Web of science
Open Access
Yes
Create date
22/12/2022 14:51
Last modification date
18/02/2023 7:09
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