The Compatibility between the Pangu Weather Forecasting Model and Meteorological Operational Data

Abstract: Recently, multiple data-driven models based on machine learning for weather forecasting have emerged. These models are highly competitive in terms of accuracy compared to traditional numerical weather prediction (NWP) systems. In particular, the Pangu-Weather model, which is open source for non-commercial use, has been validated for its forecasting performance by the European Centre for Medium-Range Weather Forecasts (ECMWF) and has recently been published in the journal "Nature". In this paper, we evaluate the compatibility of the Pangu-Weather model with several commonly used NWP operational analyses through case studies. The results indicate that the Pangu-Weather model is compatible with different operational analyses from various NWP systems as the model initial conditions, and it exhibits a relatively stable forecasting capability. The forecast results of these models, according to their claims in the papers, have reached or exceeded the performance of the products from the European Centre for Medium-Range Weather Forecasts (ECMWF), leading to widespread attention in the meteorological community.