Abstract
Data availability and accessibility often present challenges to resolving regional water management issues. One primary input essential to models and other tools used to inform policy decisions is daily precipitation. Since observed datasets are not always present or accessible, data from the Climate Forecast System Reanalysis (CFSR) have become a potential alternative. A comparison of CFSR precipitation data to available observed data from stations in the East African countries Kenya, Uganda, and Tanzania showed notable differences between the two datasets, particularly with respect to precipitation totals and number of days receiving rainfall. A sliding window bias correction approach evaluated using 3 methods with 8 different window length and timestep variations showed that empirical quantile mapping with a 30-day sliding window length and 1-day timestep achieved the best performance. A comparison of bias corrected CFSR precipitation data against observed data showed marked improvement in the similarity of the number of wet days and maximum daily rainfall between the two datasets. For precipitation totals, bias correction reduced underprediction errors by 32% and overprediction errors by 81%. Results indicate that bias-corrected CFSR precipitation data provides an improved basis for water resources applications in the study region. Methodologies and approaches are extendable to other data-scarce regions or areas where complete and consistent data are not easily accessible.
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Data Availability
Datasets developed through this work will be made available through the Purdue University Research Repository (PURR).
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Not applicable.
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This work was funded in part by USDA National Institute of Food and Agriculture, Hatch Project IND00000752.
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All authors contributed to the conceptualization of the study. V. M. Garibay and M. W. Gitau designed the framework for the analyses. V. M. Garibay conducted the analysis. V. M. Garibay and M. W. Gitau wrote the manuscript in consultation with N. Kiggundu, D. Moriasi, and F. Mishili. All authors reviewed the results and contributed to the final version of the manuscript.
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Garibay, V.M., Gitau, M.W., Kiggundu, N. et al. Evaluation of Reanalysis Precipitation Data and Potential Bias Correction Methods for Use in Data-Scarce Areas. Water Resour Manage 35, 1587–1602 (2021). https://doi.org/10.1007/s11269-021-02804-8
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DOI: https://doi.org/10.1007/s11269-021-02804-8