CloudNine: Analyzing Meteorological Observation Impact on Weather Prediction Using Explainable Graph Neural Networks

arXiv:2402.14861v1 Announce Type: new
Abstract: The impact of meteorological observations on weather forecasting varies with sensor type, location, time, and other environmental factors. Thus, quantitative analysis of observation impacts is crucial for effective and efficient development of weather forecasting systems. However, the existing impact analysis methods are difficult to be widely applied due to their high dependencies on specific forecasting systems. Also, they cannot provide observation impacts at multiple spatio-temporal scales, only global impacts of observation types. To address these …

abstract analysis arxiv cs.ai cs.lg development environmental forecasting graph graph neural networks impact impacts location networks neural networks observation physics.ao-ph prediction quantitative quantitative analysis sensor systems type weather weather forecasting weather prediction