NDLI: West Africa Regional Training On the Improved NextGen Seasonal Forecasting Approach (PyCPT 2)

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West 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 Trzaska, Sylwia Dinku, Tufa Zougmoré, Robert B. Minoungou, Bernard Mohamed, Hamatan
Description	From October 10-19, a nine-day training targeting West Africa (WA) was implemented in Lomé, Togo by the International Research Institute for Climate and Society (IRI) of the Columbia Climate School, in close collaboration with the AICCRA-West Africa team, the Regional Center for Training and Application in Agrometeorology and Operational Hydrology (AGRHYMET) and Meteo Togo. 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 7 national meteorological services from the WA region, as well as its regional climate center (AGRHYMET) 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 national meteorological services of seasonal forecasting tools, 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/3fc81b2b-089c-4bd7-8f19-8754ab25155b
File Format	PDF
Language	English
Publisher	Accelerating Impacts of CGIAR Climate Research for Africa
Access Restriction	Open
Rights License	CC-BY-NC-4.0
Subject Keyword	Agriculture Climate-smart Agriculture Climate Change Forecasting Capacity Development Climate Variability
Content Type	Text
Resource Type	Report
Subject	Agronomy and Crop Science Food Science Plant Science

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