Modelling approaches for climate risk and adaptation in the context of sustainable intensification
From September 11th to 17th 2022, was held at the Centre d’étude régional pour l’amélioration de l’adaptation à la sécheresse (CERAAS), Thiès Escale, Senegal, an international summer school (summer school CMRA 2022) organized by the Leibniz Centre for Agricultural Landscape Research (ZALF) in coll...
| Autores principales: | , , , , , , |
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| Formato: | Informe técnico |
| Lenguaje: | Inglés |
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Accelerating Impacts of CGIAR Climate Research for Africa
2022
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| Acceso en línea: | https://hdl.handle.net/10568/126578 |
| _version_ | 1855520138477961216 |
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| author | Diancoumba, Madina Akinseye, Folorunso M. Faye, Awa Emanuel, Joseph Jacob Webber, Heidi Faye, Aliou Worou, Nadine |
| author_browse | Akinseye, Folorunso M. Diancoumba, Madina Emanuel, Joseph Jacob Faye, Aliou Faye, Awa Webber, Heidi Worou, Nadine |
| author_facet | Diancoumba, Madina Akinseye, Folorunso M. Faye, Awa Emanuel, Joseph Jacob Webber, Heidi Faye, Aliou Worou, Nadine |
| author_sort | Diancoumba, Madina |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | From September 11th to 17th 2022, was held at the Centre d’étude régional pour l’amélioration de l’adaptation
à la sécheresse (CERAAS), Thiès Escale, Senegal, an international summer school (summer school CMRA 2022) organized by the Leibniz Centre for Agricultural Landscape Research (ZALF) in collaboration with the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) and the International Livestock research Institute (ILRI).
With the financial and technical supports of Volkswagen Foundation and AICCRA project, this summer school equiped the West Africa’s next-generation agricultural researchers and policymakers to use modeling tools to accelerate decision-making in addressing climate risks and sustainable intensification. A total of 32 participants from across European, Asian and African institutions that have different background were convened. The summer school was designed to provide Master, doctoral and postdoc scholars with a broad overview of the system’s analysis, best practices in model application climate change impact assessments, as well as emerging applications and challenges for crop modeling to support sustainable intensification of smallholder farming systems. The participants were equipped with the knowledge and skills to use crop models in the design and
evaluation of resilient and productive cropping systems. |
| format | Informe técnico |
| id | CGSpace126578 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2022 |
| publishDateRange | 2022 |
| publishDateSort | 2022 |
| publisher | Accelerating Impacts of CGIAR Climate Research for Africa |
| publisherStr | Accelerating Impacts of CGIAR Climate Research for Africa |
| record_format | dspace |
| spelling | CGSpace1265782025-12-08T09:54:28Z Modelling approaches for climate risk and adaptation in the context of sustainable intensification Diancoumba, Madina Akinseye, Folorunso M. Faye, Awa Emanuel, Joseph Jacob Webber, Heidi Faye, Aliou Worou, Nadine agriculture climate-smart agriculture climate change modelling sustainability From September 11th to 17th 2022, was held at the Centre d’étude régional pour l’amélioration de l’adaptation à la sécheresse (CERAAS), Thiès Escale, Senegal, an international summer school (summer school CMRA 2022) organized by the Leibniz Centre for Agricultural Landscape Research (ZALF) in collaboration with the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) and the International Livestock research Institute (ILRI). With the financial and technical supports of Volkswagen Foundation and AICCRA project, this summer school equiped the West Africa’s next-generation agricultural researchers and policymakers to use modeling tools to accelerate decision-making in addressing climate risks and sustainable intensification. A total of 32 participants from across European, Asian and African institutions that have different background were convened. The summer school was designed to provide Master, doctoral and postdoc scholars with a broad overview of the system’s analysis, best practices in model application climate change impact assessments, as well as emerging applications and challenges for crop modeling to support sustainable intensification of smallholder farming systems. The participants were equipped with the knowledge and skills to use crop models in the design and evaluation of resilient and productive cropping systems. 2022-12 2023-01-04T21:16:08Z 2023-01-04T21:16:08Z Report https://hdl.handle.net/10568/126578 en Open Access application/pdf Accelerating Impacts of CGIAR Climate Research for Africa Diancoumba M, Akinseye F, Faye A, Emanuel JJ, Webber H, Faye A, Worou N. 2022. Modelling approaches for climate risk and adaptation in the context of sustainable intensification. AICCRA Report. Accelerating Impacts of CGIAR Climate Research for Africa (AICCRA). |
| spellingShingle | agriculture climate-smart agriculture climate change modelling sustainability Diancoumba, Madina Akinseye, Folorunso M. Faye, Awa Emanuel, Joseph Jacob Webber, Heidi Faye, Aliou Worou, Nadine Modelling approaches for climate risk and adaptation in the context of sustainable intensification |
| title | Modelling approaches for climate risk and adaptation in the context of sustainable intensification |
| title_full | Modelling approaches for climate risk and adaptation in the context of sustainable intensification |
| title_fullStr | Modelling approaches for climate risk and adaptation in the context of sustainable intensification |
| title_full_unstemmed | Modelling approaches for climate risk and adaptation in the context of sustainable intensification |
| title_short | Modelling approaches for climate risk and adaptation in the context of sustainable intensification |
| title_sort | modelling approaches for climate risk and adaptation in the context of sustainable intensification |
| topic | agriculture climate-smart agriculture climate change modelling sustainability |
| url | https://hdl.handle.net/10568/126578 |
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