Training on the Improved NextGen Approach (PyCPT2.8) for Seasonal and Subseasonal Forecasting with the Ethiopian Meteorological Institute

New AICCRA-supported state-of-the-art forecasting systems are enabling regional and national meteorological agencies to generate timely and decision-relevant climate information for their agricultural sectors. Being able to generate and have access to reliable, location-specific forecasts enables th...

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Detalles Bibliográficos
Autores principales: Grossi, Amanda, Mason, Simon J.
Formato: Informe técnico
Lenguaje:Inglés
Publicado: Accelerating Impacts of CGIAR Climate Research for Africa 2024
Materias:
Acceso en línea:https://hdl.handle.net/10568/163366
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author Grossi, Amanda
Mason, Simon J.
author_browse Grossi, Amanda
Mason, Simon J.
author_facet Grossi, Amanda
Mason, Simon J.
author_sort Grossi, Amanda
collection Repository of Agricultural Research Outputs (CGSpace)
description New AICCRA-supported state-of-the-art forecasting systems are enabling regional and national meteorological agencies to generate timely and decision-relevant climate information for their agricultural sectors. Being able to generate and have access to reliable, location-specific forecasts enables the kinds of tailored advisories that farmers as well as staff from humanitarian and development agencies need for planning and supporting agricultural growth and resilience. It also enables anticipatory action in advance of emergencies. Towards the AICCRA project’s vision of actualizing a climate-smart African future driven by science and innovation in agriculture, the technical training on PyCPT immediately followed a workshop organized by the World Food Programme (WFP) in partnership with the IRI and EMI on anticipatory action trigger design, financing arrangements, and evidence generation in Ethiopia. This complementary workshop and initiative through WFP aimed to strengthen national capacities and systems for climate risk management, based on the generation, use and integration of tailored climate forecasts (such as those generated with PyCPT) and triggers into an Anticipatory Action Plan (AAP) including forecast-based finance (FbF) against drought. As such, the AICCRA-supported workshop in tandem with the AAP efforts through the WFP represent an important joint effort towards moving beyond access of climate information to advancing its use in decision-making, aligned with the goals of AICCRA Additional Finance (AF).
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publishDate 2024
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publisher Accelerating Impacts of CGIAR Climate Research for Africa
publisherStr Accelerating Impacts of CGIAR Climate Research for Africa
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spelling CGSpace1633662025-11-11T16:25:43Z Training on the Improved NextGen Approach (PyCPT2.8) for Seasonal and Subseasonal Forecasting with the Ethiopian Meteorological Institute Grossi, Amanda Mason, Simon J. forecasting climate change adaptation technology transfer capacity building New AICCRA-supported state-of-the-art forecasting systems are enabling regional and national meteorological agencies to generate timely and decision-relevant climate information for their agricultural sectors. Being able to generate and have access to reliable, location-specific forecasts enables the kinds of tailored advisories that farmers as well as staff from humanitarian and development agencies need for planning and supporting agricultural growth and resilience. It also enables anticipatory action in advance of emergencies. Towards the AICCRA project’s vision of actualizing a climate-smart African future driven by science and innovation in agriculture, the technical training on PyCPT immediately followed a workshop organized by the World Food Programme (WFP) in partnership with the IRI and EMI on anticipatory action trigger design, financing arrangements, and evidence generation in Ethiopia. This complementary workshop and initiative through WFP aimed to strengthen national capacities and systems for climate risk management, based on the generation, use and integration of tailored climate forecasts (such as those generated with PyCPT) and triggers into an Anticipatory Action Plan (AAP) including forecast-based finance (FbF) against drought. As such, the AICCRA-supported workshop in tandem with the AAP efforts through the WFP represent an important joint effort towards moving beyond access of climate information to advancing its use in decision-making, aligned with the goals of AICCRA Additional Finance (AF). 2024-07-01 2024-12-11T16:15:25Z 2024-12-11T16:15:25Z Report https://hdl.handle.net/10568/163366 en Open Access application/pdf Accelerating Impacts of CGIAR Climate Research for Africa Mason, S.J. Grossi, A. 2024. Training on the Improved NextGen Approach (PyCPT2.8) for Seasonal and Subseasonal Forecasting with the Ethiopian Meteorological Institute. AICCRA Report. Accelerating Impacts of CGIAR Climate Research for Africa (AICCRA).
spellingShingle forecasting
climate change adaptation
technology transfer
capacity building
Grossi, Amanda
Mason, Simon J.
Training on the Improved NextGen Approach (PyCPT2.8) for Seasonal and Subseasonal Forecasting with the Ethiopian Meteorological Institute
title Training on the Improved NextGen Approach (PyCPT2.8) for Seasonal and Subseasonal Forecasting with the Ethiopian Meteorological Institute
title_full Training on the Improved NextGen Approach (PyCPT2.8) for Seasonal and Subseasonal Forecasting with the Ethiopian Meteorological Institute
title_fullStr Training on the Improved NextGen Approach (PyCPT2.8) for Seasonal and Subseasonal Forecasting with the Ethiopian Meteorological Institute
title_full_unstemmed Training on the Improved NextGen Approach (PyCPT2.8) for Seasonal and Subseasonal Forecasting with the Ethiopian Meteorological Institute
title_short Training on the Improved NextGen Approach (PyCPT2.8) for Seasonal and Subseasonal Forecasting with the Ethiopian Meteorological Institute
title_sort training on the improved nextgen approach pycpt2 8 for seasonal and subseasonal forecasting with the ethiopian meteorological institute
topic forecasting
climate change adaptation
technology transfer
capacity building
url https://hdl.handle.net/10568/163366
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AT masonsimonj trainingontheimprovednextgenapproachpycpt28forseasonalandsubseasonalforecastingwiththeethiopianmeteorologicalinstitute