Reliability of NASA NEX-GDDP Dataset in Reproducing Climatological Mean Temperature and Precipitation over the Gibe III Watershed, Omo-Gibe Basin, Ethiopia
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Background: The challenge of climate variability is a major problem for developing and using
water resources. Scarcity of climate data compounds the problem and undermines the efforts to
acquire updated information for predicting climate change and reduce its risks.
Objective: The objective of the study was to evaluate and select the best climate models having
NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) dataset for Gibe
III watershed. Material and Methods: NEX-GDDP data of precipitation and temperature with
spatial resolution of 0.25º x 0.25º of ten CMIP5 models was, evaluated against observed data of
eight stations distributed in the Watershed.
Results: The models showed a consistent and reasonable pattern for mean monthly total
precipitation and mean temperature (max and min). The mean monthly precipitation of all models
against observation also resulted to R2 of 0.71 to 0.99 and the Nash–Sutcliffe efficiency (NSE)
value of 0.66 to 0.99. Mean annual precipitation of model ensemble mean over the watershed
against observation spatially varied between –100 and 100 mm underestimating at the northern
and southern tips of watershed while overestimating at central and northeastern parts. The mean
maximum and minimum temperature varied from –1.6 ºC to +2.9 ºC and 0.4 ºC to 3.8 ºC,
respectively.
Conclusion: The result indicates that, selecting climate models’ ensemble mean could provide
higher confidence in climate change projection than choosing a specific model for an entire
watershed. Based on evaluation metrics and long-term mean annual rainfall, NEX-GDDP dataset
of CSIRO-MK3-6-0, MIROC5, MPI-ESM-MR, NorESM1-M, MIROC5 and GFDL-ESM2M
models reasonably simulated the mean annual rainfall at Shebe, Sodo, Jimma, Hosaina, Sokoru
and Woliso stations respectively for uses of climate change projection in the Watershed. The
reliability of NEX-GDDP dataset for the climate models need seasonal basis study in the future
at the Watershed since this study did not conduct seasonal data analysis.
Keywords: Bias corrected; Climatological mean; Model ensemble mean; Statistically downscaled
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