Site-specific Deterministic Temperature and Humidity Forecasts with Explainable and Reliable Machine Learning

arXiv:2404.03310v1 Announce Type: cross
Abstract: Site-specific weather forecasts are essential to accurate prediction of power demand and are consequently of great interest to energy operators. However, weather forecasts from current numerical weather prediction (NWP) models lack the fine-scale detail to capture all important characteristics of localised real-world sites. Instead they provide weather information representing a rectangular gridbox (usually kilometres in size). Even after post-processing and bias correction, area-averaged information is usually not optimal for specific sites. Prior work on site …

abstract arxiv cs.lg current demand energy however machine machine learning numerical numerical weather prediction nwp operators physics.ao-ph power prediction scale type weather weather prediction world