Machine Learning and Hybrid Approaches in Weather and Climate

Abstract

Climate change is one of the most significant global challenges that need to be managed Understanding of the natural environment is increasingly important to respond to the climate change negative impacts and anthropogenic pressures on finite natural resources, and their impacts on water, energy and food security, infrastructure, human health, natural hazards. The paper reviewed ML application in weather and acclimate, its further development and activities and achievements of ECMWF in creating and app]lying of ML/AI methods. This is also a major interdisciplinary challenge involving almost all scientific fields Artificial intelligence and machine learning (AI/ML) applications have recently widely expanded in all fields. ML can enhance our computations by adding components or replacing some parts of the process. This is what is called the ‘hybrid’ approach. Instead, ML can also fully replace the whole model, at a much lower computing cost. In addition, AI/ML opens some avenues in other activities we are involved in, such as flood forecasts, fire danger forecasts, monitoring of observations, managing the supercomputer, or enhancing user experience.