Statistically Downscaled Climate Dataset for East Africa

Gebrechorkos, Solomon H., Hülsmann, Stephan and Bernhofer, Christian, (2019). Statistically Downscaled Climate Dataset for East Africa. Scientific Data, 1-8

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  • Sub-type Journal article
    Author Gebrechorkos, Solomon H.
    Hülsmann, Stephan
    Bernhofer, Christian
    Title Statistically Downscaled Climate Dataset for East Africa
    Appearing in Scientific Data
    Publication Date 2019-04-15
    Place of Publication Online
    Publisher Springer Nature
    Start page 1
    End page 8
    Language eng
    Abstract For many regions of the world, current climate change projections are only available at coarser spatial resolution from Global Climate Models (GCMs) that cannot directly be used in impact assessment and adaptation studies at regional and local scale. Impact assessment studies require high-resolution climate data to drive impact assessment models. To overcome this data challenge, we produced a station based climate projection (precipitation and maximum and minimum temperature) for Ethiopia, Kenya, and Tanzania using observed daily data from 211 stations obtained from the National Meteorological Agency of Ethiopia and international databases. Moreover, 26 large-scale climate variables derived from the National Centers for Environmental Prediction reanalysis data (1961–2005) and second generation Canadian Earth System Model (CanESM2, 1961–2100) are used. Statistical Down-Scaling Model (SDSM) is used to produce the required high-resolution climate projection by developing a statistical relationship between the large- and local-scale climate variables. The predictors are analysed more than 16458 times and we provided 20 ensembles for the current (1961–2005) and future (2006–2100, under RCP2.6, RCP4.5, and RCP8.5) climate.
    Copyright Holder The Authors
    Copyright Year 2019
    Copyright type Creative commons
    DOI 10.1038/s41597-019-0038-1
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    Created: Tue, 16 Apr 2019, 18:45:48 JST by Claudia Matthias on behalf of UNU FLORES