Prompt Federated Learning for Weather Forecasting: Toward Foundation Models on Meteorological Data

Understand

To tackle the global climate challenge, it urgently needs to develop a collaborative platform for comprehensive weather forecasting on large-scale meteorological data.

• Despite urgency, heterogeneous meteorological sensors across countries and regions, inevitably causing multivariate heterogeneity and data exposure, become the main barrier.
• This paper develops a foundation model across regions capable of understanding complex meteorological data and providing weather forecasting.
• To relieve the data exposure concern across regions, a novel federated learning approach has been proposed to collaboratively learn a brand-new spatio-temporal Transformer-based foundation model across participants with heterogeneous meteorological data.