Blending high-resolution satellite rainfall estimates over urban catchment

Authors: Wegayehu Asfaw, Tom Rientjes, Alemseged Tamiru Haile

This study evaluates dynamic Bayesian Model Averaging (BMA) approach to improve rainfall estimation over the catchment by blending four high-resolution satellite rainfall estimate (SRE) products. Using daily data (2003–2019) observed at thirteen stations as a reference, seven statistical metrics served to assess the point and spatial scale accuracy of the rainfall estimates.

Highlights

• Blending high-resolution satellite products using the Bayesian Model Averaging (BMA) approach improved rainfall estimation.
• The blended rainfall product outperformed the individual satellite products by reducing the error of rainfall estimation.
• The blended and individual rainfall estimate products performed better in the highlands than the lowlands of the catchment.
• The rainfall during the main-rainy season was reasonably detected by the blended product than the individual SRE products.