Examining the vast scientific literature about the urban impact on weather and climate enabled researchers to synthesize current understanding and to inform future work.

State-of-the-art numerical models can better simulate the convective clouds that produce most of the Amazon’s wet season rainfall.

Researchers used ground-based and remote-sensed datasets to comprehensively validate a tool for simulating land surface processes.

A new hexagonal framework helps more accurately model watersheds at a range of scales.

Study reveals importance of accounting for micrometer scale distribution of substrates to predict carbon emissions from soil.

Developing a model for global soil erosion and sediment flux to advance understanding of land, river, and ocean geomorphology and biogeochemistry.

Researchers are developing an understanding of how either wet or dry soil patches change the sizes of atmospheric eddies and cloud clusters.

The overlooked impact of regional hydroclimate changes on lake evaporation implies more robust regional lake volume changes around the globe.

Changes in the downward flow of infrared energy in clear skies are a key factor influencing recent rapid wintertime Arctic warming.

Ensembles of 20–25 members, notably smaller than traditional large ensembles, can accurately represent changes in extremes of temperature and precipitation.

Researchers developed a new model to understand the initiation of summer-time mesoscale convective systems over the central United States.

Implementing and evaluating a new radiative transfer scheme that accounts for various topographic effects on solar radiation in an Earth system model.

A multi-institutional team has developed a deep learning framework to identify novel molecules as drug candidates.

Better representing cloud microphysics can Reduce model bias in simulating mesoscale convective system precipitation.

New analysis demonstrates that the Madden-Julian Oscillation can influence tropical cyclones in the Pacific through both the atmosphere and the ocean.

Researchers developed a new tool that combines artificial intelligence and microscopy data to rapidly test new materials for fusion reactor use.

Contributions from researchers across Pacific Northwest National Laboratory (PNNL) were recently recognized in the preliminary findings of a Secretary of Energy Advisory Board (SEAB) report.