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 of weather-yield relationships derived from crop models, whether statistical or process-based, is dependent on the quality of the underlying input data used to run these models. In this context, a major challenge in many developing countries is the lack of accessible and reliable meteorological datasets. Gridded weather datasets, derived from combinations of in-situ gauges, remote sensing, and climate models, provide a solution to fill this gap, and have been widely used to evaluate climate impacts on agriculture in data-scarce regions worldwide.
[2]
Technology Partners: MimirTech
Links:
[1] http://admin.indiaenvironmentportal.org.in/reports-documents/weather-dataset-choice-introduces-uncertainty-estimates-crop-yield-responses
[2] http://www.indiaenvironmentportal.org.in/files/file/Weather dataset choice.pdf
[3] http://admin.indiaenvironmentportal.org.in/category/author/ben-parkes
[4] http://admin.indiaenvironmentportal.org.in/category/author/thomas-p-higginbottom
[5] http://admin.indiaenvironmentportal.org.in/category/author/koen-hufkens
[6] http://admin.indiaenvironmentportal.org.in/category/author/et-al
[7] http://admin.indiaenvironmentportal.org.in/category/publisher/international-food-policy-research-institute-ifpri
[8] http://admin.indiaenvironmentportal.org.in/category/thesaurus/extreme-weather-events
[9] http://admin.indiaenvironmentportal.org.in/category/thesaurus/climate-change
[10] http://admin.indiaenvironmentportal.org.in/category/thesaurus/agriculture
[11] http://admin.indiaenvironmentportal.org.in/category/thesaurus/india
