Circulation types and AI for crop yield anomaly detection and prediction

Funder	Natural Environment Research Council
Recipient Organization	Cranfield University
Country	United Kingdom
Start Date	Sep 30, 2021
End Date	Mar 30, 2025
Duration	1,277 days
Number of Grantees	1
Roles	Student
Data Source	UKRI Gateway to Research
Grant ID	`2753490`

Grant Description

The main hypothesis of this PhD project is that weather types can be used to explain spatial and temporal climate-related crop variability and can provide longer crop yield prediction lead times than for example using specific indicators such as precipitation or temperature.

The study will be applied to Europe and North America given the availability of the crop yield data, with a focus on the UK.