Abstract

A variety of global spatial interpolation models for rainfall estimates (e.g. TRMM: Tropical Rainfall Measurement Mission; GPM: Global Precipitation Measurement; CHIRPS: Climate Hazards Infrared Precipitation with Station) are freely available at the global level. For Ethiopia, however, rainfall patterns are strongly influenced by topography and the monsoon regime. Strong deviations from the precipitation estimates are therefore quite common. In preparation of the map, the geostatistical interpolation model (CoKriging) was used to validate the gridded models for best fit regarding annual average rainfall estimates for Ethiopia. A cross-validation based on 107 long-term monthly NMAE station data (National Meteorological Agency of Ethiopia), terrain data (altitude, aspect, slope), NDVI and temperature data resulted in a best RMSE fit (error of differences between values predicted and observed) by using CHIRPS geospatial modelling framework. The model combines 0.05 degree resolution satellite imagery with in-situ station data to create gridded rainfall time series for trend analysis and the seasonal drought monitoring. For improved reading, the map contains various geographic feature classes derived from a wide range of individual data sources: Open Street Map data from https://osmaxx.hsr.ch, terrain features (e.g. mountain peaks, contour lines, hillshade) derived from https://www.eorc.jaxa.jp/ALOS/en/aw3d30/index.htm. Please ignore the slivers along the model boundaries and use the scale bar for measurements on the map when resized to scales other than the original A0 pdf-format! The detailed 1:1,000,000 or 1:500,000 Thematic Overview Map Series best suits the needs of regional/national project management and policy advice.

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