This study proposes an automatic method to parameterize atmospheric optical depths in the Radiative Transfer for TIROS Operational Vertical Sounder (RTTOV) version 13 model. The approach combines statistical inference and Least Absolute Shrinkage and Selection Operator (LASSO) regression to reduce parameters and select relevant gases. Tests with Visible Infrared Imaging Radiometer Suite (VIIRS) channels show reduced computation while preserving accuracy.

This study evaluates the performance of the varying-resolution mesh model, E3SMv2-MPAS, in simulating key Arctic processes—from sea ice distribution and surface properties to the complex, three-dimensional structures of the Atlantic Water layer. We also pinpoint specific areas where the model still struggles, providing valuable directions for future model development. This progress means scientists can now use this tool more confidently to understand how Arctic ocean layers work and change.

We evaluated a new ensemble data assimilation system that uses satellite observations in all weather conditions for global weather forecasts. The results show that including cloud- and precipitation-affected satellite data improves forecasts of moisture, wind, and clouds, especially in the tropics. This work highlights the potential of this new ensemble data assimilation system to enhance global weather forecasts.

CIBUSmod is a biophysical agri-food system model designed to evaluate resource use and environmental impacts on national and sub-national level under future scenarios involving changes in demand and agricultural production systems. It provides a flexible framework that can integrate regionalised data at the spatial resolution and aggregation level available. By enhancing transparency and usability in food systems modelling, CIBUSmod is a valuable tool for exploring agri-food systems transitions.