Generative weather for improved crop model simulations

arXiv:2404.00528v1 Announce Type: new
Abstract: Accurate and precise crop yield prediction is invaluable for decision making at both farm levels and regional levels. To make yield prediction, crop models are widely used for their capability to simulate hypothetical scenarios. While accuracy and precision of yield prediction critically depend on weather inputs to simulations, surprisingly little attention has been paid to preparing weather inputs. We propose a new method to construct generative models for long-term weather forecasts and ultimately improve crop …

abstract accuracy arxiv capability cs.lg decision decision making generative inputs making precision prediction regional simulations type weather