Shining light into the dark reveals the unseen, but in some cases, it changes our perception of reality. Through moonlight we learn how the environment tricks our ways of finding nocturnal clouds.
Jonathan H. Jiang
Editor, Earth and Space Science
Posted inEditors' Highlights
Melting Layer Characteristics of Cyclones
Dual‐frequency Precipitation Radar observations reveal the characteristics and microphysical processes of the melting layer in cyclone precipitation over the western North Pacific.
Posted inEditors' Highlights
Polar Vortex Linked to Atmospheric Circulation at Daily Scale
A simplified representation of polar vortex at monthly scale was revised using a new method, and its daily association with air-sea teleconnections was analyzed to study weather impacts.
Posted inEditors' Highlights
Temperature Extremes: Exploring the Global Outbreak
Using cutting-edge observations, reanalyses, and climate models, a new study projects the outbreak of temperature extremes over new global areas by 2100.
Posted inEditors' Highlights
Satellite Estimates for Hydroclimatic Extremes
A new study corrects poor-performing satellite-based rainfall estimates with gauge data and also fills gauge data gaps using well-performing satellite-based rainfall estimates.
Posted inEditors' Highlights
Global Warming Intensifies Turbulence Over Northern Eurasia
A significant increasing trend of turbulence in upper atmosphere over northern Eurasia is attributed to intense anthropogenic activities.
Posted inEditors' Highlights
Using Machine Learning to Detect and Estimate Global Snowfall
Machine learning is used to retrieve global snowfall occurrence and rate from satellite-based passive microwave sounder observations, trained by snowfall data from a high-quality space borne radar.
Posted inEditors' Highlights
Zero-valent Iron in the Oxidizing Atmosphere?
A comparative study of urban, semi-urban, and rural sites reveals that the species of atmospheric iron varies depending on location.
Posted inEditors' Highlights
Ensemble Learning Estimates Terrestrial Water Storage Changes
Ensemble learning models for estimating past changes of terrestrial water storage from climate are presented and tested in the Pearl River basin, China.