Research Highlights

The hydrologic cycle is strongly influenced by the balance of sunlight and thermal radiation on the ground or snow surface. We quantify the combined impacts of clouds and snow cover on the surface radiative energy balance in a high-elevation region of the upper Colorado River basin. Since snow is bright and reflects sunlight, our results demonstrate that the surface energy balance will become increasingly sensitive to cloud cover as snow cover declines. 

We combined laboratory experiments, modeling, and field data to demonstrate that organic aerosols may significantly contribute to the formation of ice clouds in certain atmospheric regions.

Marine stratocumulus clouds often organize into mesoscale cellular convection (MCC), forming large-scale open or closed cell patterns. However, Earth system models struggle to simulate these regimes due to limited observations and understanding of physical processes. In this study, researchers at Pacific Northwest National Laboratory applied an artificial intelligence/machine learning (AI/ML) approach to analyze long-term vertically pointing cloud radar data from the Atmospheric Radiation Measurement (ARM) user facility’s Eastern North Atlantic (ENA) site. The method enables continuous time series of MCC classification, performs well, and reveals clear cloud and meteorological differences between the two MCC types. It also holds great potential for application to other ARM locations.