Bias estimation for seven precipitation datasets for the eastern MENA region
Dates
Release Date
2022-12
Publication Date
2022-12-29
Citation
Kagone, S., Velpuri, N.M., Khand, K., and Senay, G.B., 2022, Bias estimation for seven precipitation dataset for the eastern MENA region, U.S. Geological Survey data release, https://doi.org/10.5066/P9HSO45W.
Summary
Information on the spatio-temporal distribution of rainfall is critical for addressing water-related disasters, especially in the Middle East and North Africa's (MENA) arid to semi-arid regions. However, the availability of reliable rainfall datasets for most river basins is limited. In this study, we utilized observations from satellite-based rainfall data, in situ rain gauge observations, and rainfall climatology to determine the most suitable precipitation dataset in the MENA region. First, we evaluated seven different rainfall products (CPC, GPCC, TRMM, PERSIANN, RFE, CHIRPS, MSWEP) using rain gauge observations obtained from Jordan (139 stations), Palestine (9 stations), and Lebanon (16 stations). The validation was conducted [...]
Summary
Information on the spatio-temporal distribution of rainfall is critical for addressing water-related disasters, especially in the Middle East and North Africa's (MENA) arid to semi-arid regions. However, the availability of reliable rainfall datasets for most river basins is limited. In this study, we utilized observations from satellite-based rainfall data, in situ rain gauge observations, and rainfall climatology to determine the most suitable precipitation dataset in the MENA region. First, we evaluated seven different rainfall products (CPC, GPCC, TRMM, PERSIANN, RFE, CHIRPS, MSWEP) using rain gauge observations obtained from Jordan (139 stations), Palestine (9 stations), and Lebanon (16 stations). The validation was conducted at daily, monthly, and annual time scales. Results indicated a weaker correlation between in situ rain gauge observation and satellite rainfall data at the daily time step, mainly due to the lack of range in rainfall distribution. However, the agreement between rainfall estimates and in situ gauge observations improved at monthly and annual time scales, indicating the reliability of satellite observations at monthly and annual time scales. Based on the analysis, the MSWEP rainfall dataset was found to perform best in the region. The observed data and rainfall contours from published literature were combined to create a robust gridded climatology dataset for the region, which was then utilized to estimate bias in the MSWEP dataset. Finally, bias correction of the MSWEP dataset yielded an adjusted regional rainfall product for the region. This study highlights the need for an adjusted regional rainfall product for improved streamflow estimation and other hydrologic applications.
