A new study demonstrates how researchers can model human–Earth system feedbacks in a single internally consistent, computationally efficient framework.
Ocean biogeochemical modeling software now available as open source to help researchers predict impacts of pollution, sea level rise, and climate change.
Model results show that uncertainties in farmers’ expectations of market and weather conditions amplify agricultural supply and demand variability under a changing climate.
Investigating the soil moisture–precipitation feedbacks that are associated with mesoscale convective system and non-mesoscale convective system rainfall.
Researchers found that increasing restrictions on nonrenewable groundwater use for irrigation shifts agricultural production from western states to the east.
Developing a new approach for defining energy-water-agriculture linkages highlights U.S. regions where focusing on individual sectors may miss cross-sectoral impacts.
Simulations accurately predicted storm cloud shield timing and growth, but not rain intensities, for over 300 tracked storm complexes in a storm-generating hotspot in Argentina.
Four factors, the El Niño-Southern Oscillation, North Atlantic subtropical high, low-level jet, and water vapor transport from Gulf of Mexico, primarily influence hail occurrence in the Northern Great Plains
Leung was honored for pioneering approaches in climate modeling, discovering unexpected impacts of regional climate change, and understanding extreme weather events and their future changes.
Integrating hydrogeology and biogeochemistry are required to model the dynamics of geochemical processes occurring in river corridor zones where groundwater and surface water mix.
New estimates show that coastlines around the world will experience an increase in the frequency of extreme sea level events at a range of global warming levels.
