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East and Southern Africa Regional Training On the Improved NextGen Seasonal Forecasting Approach (PyCPT 2)
| Content Provider | Consultative Group on International Agricultural Research (CGIAR) |
|---|---|
| Author | Grossi, Amanda Robertson, Andrew Muñoz, Angel Singh, Bohar Dinku, Tufa Demissie, Teferi Dejene Solomon, Dawit |
| Description | From October 3-11, an eight-day training of trainers (ToT) targeting East and Southern Africa (ESA) was implemented in Zanzibar, Tanzania by the International Research Institute for Climate and Society (IRI) of the Columbia Climate School, in close collaboration with the IGAD Climate Prediction and Applications Centre (ICPAC), the International Livestock Research Institute (ILRI), and the Tanzania Meteorological Authority (TMA). The workshop, which was organized as part of the World Bank’s Accelerating the Impact of CGIAR Climate Research for Africa (AICCRA) project, brought together 10 national meteorological services from the ESA region, as well as its regional climate center— IGAD Climate Prediction and Applications Centre (ICPAC)—to improve seasonal forecasting capacities using the “NextGen” approach and its concomitant PyCPT version 2 interface (PyCPT2). In particular, the major objectives of the training were to strengthen the knowledge and understanding of regional and national meteorological services of seasonal forecasting tools and approaches, introduce the new advances and functionalities of the Python (PyCPT2) interface for the NextGen forecasting approach, configure and run PyCPT version 2 to make the best-available forecasts in participants’ home countries, including forecast verification, and provide foundational training on best practices for forecast communication including the Flexible Forecast format. |
| Sponsorship | World Bank |
| Related Links | https://cgspace.cgiar.org/items/342216b0-aa2c-4d6b-aedc-fe94079f21fc |
| File Format | |
| Language | English |
| Publisher | Accelerating Impacts of CGIAR Climate Research for Africa |
| Access Restriction | Open |
| Rights License | CC-BY-NC-4.0 |
| Subject Keyword | Agriculture Next Generation Sequencing Climate-smart Agriculture Climate Change |
| Content Type | Text |
| Resource Type | Report |
| Subject | Agronomy and Crop Science Food Science Plant Science |
