Weather dataset choice introduces uncertainty to estimates of crop yield responses to climate variability and change
Extreme weather events, such as heatwaves, droughts, and excess rainfall, are a major cause of crop yield losses and food insecurity worldwide. Statistical or process-based crop models can be used to quantify how yields will respond to extreme weather and future climate change. However, the accuracy...
| Autores principales: | , , , , , |
|---|---|
| Formato: | Artículo preliminar |
| Lenguaje: | Inglés |
| Publicado: |
International Food Policy Research Institute
2019
|
| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/146078 |
Ejemplares similares: Weather dataset choice introduces uncertainty to estimates of crop yield responses to climate variability and change
- Weather dataset choice introduces uncertainty to estimates of crop yield responses to climate variability and change
- Overcoming basis risk in agricultural index insurance using crop simulation modeling and satellite crop phenology
- Improving the performance of index insurance using crop models and phenological monitoring
- Convening CGIAR Researchers to Build a Community of Practice on Weather-related Agricultural Insurance
- Demand for a simple weather insurance product in India: Theory and evidence
- A new approach to weather insurance: Simple weather securities