Global Vegetation Modeling with Pre-Trained Weather Transformers

arXiv:2403.18438v1 Announce Type: new
Abstract: Accurate vegetation models can produce further insights into the complex interaction between vegetation activity and ecosystem processes. Previous research has established that long-term trends and short-term variability of temperature and precipitation affect vegetation activity. Motivated by the recent success of Transformer-based Deep Learning models for medium-range weather forecasting, we adapt the publicly available pre-trained FourCastNet to model vegetation activity while accounting for the short-term dynamics of climate variability. We investigate how the learned global representation …

abstract arxiv cs.lg deep learning ecosystem forecasting global insights long-term medium modeling precipitation processes research success transformer transformers trends type weather weather forecasting