Journal
JOURNAL OF METEOROLOGICAL RESEARCH
Volume 35, Issue 4, Pages 673-689Publisher
SPRINGER HEIDELBERG
DOI: 10.1007/s13351-021-0199-7
Keywords
climatic datasets; evaluation; rainfall; temperature; Tekeze River basin
Categories
Funding
- National Natural Science Foundation of China [41790424, 41730645, 41877164]
- Strategic Priority Research Program of the Chinese Academy of Sciences [XDA20060402]
- International Partnership Program of the Chinese Academy of Sciences [131A11KYSB20170113]
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The study evaluated the reliability of nine gridded precipitation and temperature datasets against ground-based observations in the upper Tekeze River basin of Ethiopia. Results showed that the EWEMBI and CHIRPS datasets provided the best estimates of precipitation at both daily and monthly timescales, while ERA5 and CHIRTS datasets were closest to the observations for temperature estimates.
The availability of satellite and reanalysis climate datasets and their applicability have been greatly promoted in hydro-climatic studies. However, such climatic products are still subject to considerable uncertainties and an evaluation of the products is necessary for applications in specific regions. This study aims to evaluate the reliability of nine gridded precipitation and temperature datasets against ground-based observations in the upper Tekeze River basin (UTB) of Ethiopia from 1982 to 2016. Precipitation, maximum temperature (T-max), minimum temperature (T-min), and mean temperature (T-mean) were evaluated at daily and monthly timescales. The results show that the best estimates of precipitation are from the EartH2Observe, WFDEI, and ERA-Interim reanalysis data Merged and Bias-corrected for the Inter-Sectoral Impact Model Intercomparison Project (EWEMBI), and the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) datasets. The percentage biases and correlation coefficients (CCs) are within +/- 15% and > 0.5, respectively, for both EWEMBI and CHIRPS at the two timescales. All products underestimate the drought conditions indicated by the standardized precipitation index (SPI), while the EWEMBI and CHIRPS datasets show higher agreement with the observations than other datasets. The T-mean estimates produced by the ECMWF Re-Analysis version 5 (ERA5) and the Climate Hazards Group InfraRed Temperature with Station data (CHIRTS) are the closest to the observations, with CCs of 0.65 and 0.55, respectively, at the daily timescale. The CHIRTS and EWEMBI datasets show better representations of T-max (T-min), with CCs of 0.69 (0.72) and 0.62 (0.68), respectively, at the monthly timescale. The temperature extremes are better captured by the ERA5 (T-mean), CHIRTS (T-max), and EWEMBI (T-min) datasets. The findings of this study provide useful information to select the most appropriate dataset for hydrometeorological studies in the UTB and could help to improve the regional representation of global datasets.
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