Storage Targets and Release Function Inference Tool uses data to infer the operating policies of large reservoirs on a national scale.

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

A multisectoral analysis that combines land use data with hydrological simulations reveals wide disparities in potential source water contamination.

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

Using unique laboratory single-particle measurements to understand some of the most uncertain processes affecting secondary organic aerosol formation.

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.

Moving toward a deeper understanding of the influence of large marine biogenic particles on cloud ice formation by combining modeling and observational data.

COVID-19 had multiple impacts on the electric sector and the nature of those impacts varied on the scale analyzed.

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

Researchers characterize protein signatures that indicate Acute Kidney Injury in COVID-19 patients.

The rapid growth of urban nanoparticles via the condensation of organic vapors substantially alters shallow cloud formation and suppresses precipitation.

Simulations reveal advantages of using new model vs. allometric scaling for risk assessment.

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.

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.

Despite an increase in future electricity demands, virtual water trading in the U.S. electricity sector is expected to decline as renewable energy expands.

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

Using a novel settlement-related dataset produced more accurate population downscaling than using other, more traditional datasets.