Abstract
The historical datasets of five regional climate models (RCMs) available in the Coordinated Regional Downscaling Experiment (CORDEX)–Africa database are evaluated against ground-based observed rainfall in the Central Rift Valley Lakes Basin of Ethiopia. The evaluation is aimed at determining how well the RCMs reproduce monthly, seasonal, and annual cycles of rainfall and quantify the uncertainty between the RCMs in downscaling the same global climate model outputs. Root mean square, bias, and correlation coefficient are used to evaluate the ability of the RCM output. The multicriteria decision method of compromise programming was used to choose the best climate models for the climate condition of the Central Rift Valley Lakes subbasin. The Rossby Center Regional Atmospheric Model (RCA4) has downscaled ten global climate models (GCMs) and reproduces the monthly rainfall with a complex spatial distribution of bias and root mean square errors. The monthly bias varies in the range of − 35.8 to 189%. The summer (wet), spring, winter (dry), and annual rainfall varied within the range of 1.44 to 23.66%, − 7.08 to 20.04%, − 7.35 to 57%, and − 3.11 to 16.5%, respectively. To find the source of uncertainty, the same GCMs but downscaled by different RCMs were analyzed. The test results showed that each RCM differently downscaled the same GCM, and there was no single RCM model that consistently simulated the climate conditions over the stations in the study regions. However, the evaluation finds reasonable model skill in representing the temporal cycles of rainfall and suggests the use of RCMs where climate data is scarce after bias correction.
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Data availability
All datasets, raw or preprocessed, are available upon request from the corresponding author. However, permission is required for observed data collected from the National Meteorological Agency of Ethiopia.
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Acknowledgements
The authors acknowledge the National Meteorological Agency of Ethiopia for the provision of climate data. The climate data used for this study were sourced from the CORDEX-Africa database (https://esgf-node.llnl.gov/search/esgf-llnl/). The authors would like to thank Mr. Jacob Agyekum from Kwame Nkrumah University of Science and Technology (KNUST), Kumasi, Ghana, for providing Zoom training on Climate Data Operator (CDO).
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This work was supported by the Water Security and Sustainable Development Hub funded by the UK Research and Innovation’s Global Challenges Research Fund (GCRF) (grant number: ES/S008179/1).
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All authors significantly contributed to the development of this manuscript. Sisay Kebede Balcha oversaw the conceptualization, data collection, software, data analysis, investigation, and preparation of the original draft. The manuscript was reviewed, edited, and improved by Taye Alemayehu Hulluka and Gebiaw T. Ayele. The overall research work for this study was overseen by Adane Abebe Awass and Amare Bantider. All authors have read and agreed to the published version of the manuscript.
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Balcha, S.K., Hulluka, T.A., Awass, A.A. et al. Performance evaluation of multiple regional climate models to simulate rainfall in the Central Rift Valley Lakes Basin of Ethiopia and their selection criteria for the best climate model. Environ Monit Assess 195, 888 (2023). https://doi.org/10.1007/s10661-023-11437-w
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DOI: https://doi.org/10.1007/s10661-023-11437-w