Training on seasonal forecasting using the IRI Climate Predictability Tool and Data Library
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Siebert A, Kagabo DM, Vuguziga F. 2017. Training on seasonal forecasting using the IRI Climate Predictability Tool and Data Library. CCAFS Workshop Report. Wageningen, Netherlands: CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS).
Permanent link to cite or share this item: http://hdl.handle.net/10568/89105
This report summarizes the interactions, discussions, and analyses of Asher Siebert, Post-Doctoral Research Scientist at the International Research Institute for Climate and Society (IRI), during his three-week visit to Rwanda in late August to mid- September 2017 as part of the Rwanda Climate Services for Agriculture project. The project aims to provide climate services widely throughout Rwanda and help farmers better adapt to climate variability and climate change impacts. In doing so, the project seeks to help improve agriculture outcomes and ensure food security. During the visit, trainings were held to discuss seasonal climate forecasting and downscaling methods. A particular national forecast for Rwanda along with downscaled results in probability of exceedance format for ten Rwandan districts (those in the first two phases of the project) was developed using the IRI Climate Predictability Tool (CPT). A critical component of the project’s mission is capacity building and to that end, a number of staff from the Rwanda Meteorology Agency (Météo Rwanda) were trained in CPT, the IRI Data Library, and the Météo Rwanda maprooms. Further discussions addressed longer-term collaborative work on both climatology and further seasonal prediction work, particularly with regard to El Niño - Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD). Discussions with experts at International Center for Tropical Agriculture (CIAT) and the Rwanda Agriculture Board (RAB) also focused on the newly developed water balance maprooms and the possibilities of updating these maprooms in the future.