Zambia Report on the Africa Wide Training on the Improved NextGen Approach (PyCPT2.5) for Seasonal and Subseasonal Forecasting - Sinachikupo, Kenneth (Accelerating Impacts of CGIAR Climate Research for Africa, 2023)
This training focused on generation of high-resolution sub-seasonal rainfall forecast. The objective of the training was to strengthen knowledge of seasonal and sub-seasonal forecasting tools: Global Climate Models (GCMs) and observed data and statistical methods; introduce PyCPT 2.5: structure, inputs, outputs, workflow, examples, and automation; configure and run PyCPT 2.5 to make the best seasonal and subseasonal forecasts of precipitation and related quantities in participants’ home countries, including forecast verification; and capitalize on GCM forecast products from WMO Global Producing Centres and U.S. research centers, accessible through the IRI Data Library (NMME, C3S, S2S, and SubX databases), as well as online global precipitation datasets and offline prediction data files.