Cloud Cover

Cloud cover research focuses on accurately modeling and predicting cloud distribution and its impact on various Earth systems, primarily for improving weather forecasting and climate modeling. Current research employs machine learning techniques, including neural networks and Monte Carlo Tree Search, to analyze high-resolution data and develop more sophisticated parameterizations within climate models, often focusing on improving the representation of cloud-radiation interactions and the impact of cloud cover on solar irradiance. These advancements aim to enhance the accuracy of weather predictions, optimize satellite resource allocation, and refine climate projections by better capturing the complex dynamics of cloud formation and evolution.