This rainbow-like atmospheric phenomenon depends on a very specific set of circumstances. It is common on Earth and incredibly rare beyond it.
clouds
Posted inEditors' Highlights
Tuning Improves High-Resolution Climate Simulations
Tuning parameterizations of turbulent mixing and of the fall velocity of precipitation and cloud ice alleviates long-standing biases in climate simulations.
Posted inNews
Low-Level Clouds Disappear During a Solar Eclipse
Cumulus clouds rapidly dissipate as the land surface cools, a finding that has implications for Sun-obscuring geoengineering efforts.
Posted inEditors' Highlights
Machine Learning Accelerates the Simulation of Dynamical Fields
Fourier neural operator solvers accurately emulate particle-resolved direct numerical simulations and significantly reduce the computational time by two orders of magnitude.
Posted inEditors' Highlights
Using Satellite Observations for Attribution of Radiation Changes
Analysis of infrared satellite measurements identifies the climate response to an increase in greenhouse gases in the atmosphere.
Posted inEditors' Vox
Challenges in Measuring Aerosol Cloud-Mediated Radiative Forcing
Satellites are required for the global measurement of aerosol cloud-mediated radiative forcing, but satellite retrievals of aerosols and cloud properties still have challenges to overcome.
Posted inEditors' Vox
Accounting for Small-Scale Processes in Large-Scale Models
A new book explores how fast processes can be better represented in atmospheric models to improve weather and climate prediction.
Posted inScience Updates
Decoding the Dialogue Between Clouds and Land
New research is challenging established assumptions about how clouds form and interact with Earth’s surface. One result may be better weather forecasts.
Posted inNews
Cold Fog Is Capricious, but Not for Long
New observations of cold fog formation could eventually improve forecasting.
Posted inEditors' Highlights
Using Machine Learning to Reconstruct Cloud-Obscured Dust Plumes
Satellite-observed dust plumes from North Africa are frequently obscured by clouds, but a new study uses machine learning to reconstruct dust patterns, demonstrating a new way to validate dust forecasts.