At a critical moment in the effort to end one of the world’s worst oil spills, one scientist holed up in his office and pulled an all-nighter to calculate the well’s aquifer support.
Modeling
Posted inResearch Spotlights
Evaluating Cloud Cover Predictions in Climate Models
A new analysis highlights progress in predictions of cloud cover from models that are part of the Coupled Model Intercomparison Project.
Posted inNews
Rastreando Los Misteriosos Manantiales Del Gran Cañón
Mejorar los modelos ayudará a proteger una fuente crucial de agua potable para ambos bordes del Parque Nacional del Gran Cañón.
Posted inResearch Spotlights
Pushing the Computational Limits of Climate Simulation
Researchers apply a superparameterization technique to boost the accuracy and efficiency of climate predictions generated by the Energy Exascale Earth System Model.
Posted inNews
Nuclear War Would Spawn a “Nuclear” El Niño
A jolt to the climate system provided by nuclear war could spur an El Niño like we’ve never seen before.
Posted inEditors' Highlights
Novel Simulations of Upper Atmosphere Gravity Wave Dynamics
Gravity waves play a key role in driving upper atmosphere circulations but are poorly understood. New high-resolution simulations are resolving complex wave behaviors with unprecedented detail.
Posted inNews
Tracking the Grand Canyon’s Mysterious Springs
Improved modeling will help protect a crucial drinking water source for both rims of Grand Canyon National Park.
Posted inEditors' Highlights
Modeling Transport and Charge Effects in Heterogeneous Media
Simulation of charged species reactive transport in complex physically and electrostatically heterogeneous porous media is possible with a multiple continua approach coupled to a geochemical code.
Posted inNews
River Ice Is Disappearing
Over the past 3 decades, the persistence of river ice has decreased by almost a week. The decrease in ice has important implications for ecology, climate, and the economy.
Posted inNews
New Study Hints at Bespoke Future of Lightning Forecasting
Researchers used machine learning to develop a model that can predict lightning strikes to within 30 minutes of their occurrence and within 30 kilometers of a weather station by using just four simple atmospheric measurements.