Primary Convener:
Haonan Chen, Colorado State University

Convener:
Robert Cifelli, NOAA Physical Sciences Laboratory
V. Chandrasekar, Colorado State University

Early Career Convener:
Sounak Biswas, Colorado State University

Chair:
Haonan Chen, Colorado State University and NOAA Physical Sciences Laboratory
V. Chandrasekar, Colorado State University
Sounak Biswas, Colorado State University

Radar remote sensing of clouds and precipitation is an area of active and vibrant research with numerous advancements resulting in improved hydrometeorological applications. Many processing steps are needed to convert raw radar observations into useful geophysical quantities that require the knowledge of radar technology, atmospheric processes, microphysics, and data sciences. This session focuses on the state-of-the-art radar observations, as well as radar related weather, water, and/or cloud resolving model applications. This session will also feature presentations devoted to machine learning and data sciences in hydrometeorology remote sensing, orographic and extreme precipitation. Topics include but are not limited to: (1) Scanning and vertically pointing radars from S- to W-band; (2) Identification of hydrometeor phases and microphysical features in radar measurements; (3) Network or field campaign observations monitoring clouds and/or precipitation (4) Orographic and winter precipitation; (5) Multi-sensor-based products for weather, water, and/or cloud model applications; (6) AI/ML applications in radar hydrometeorology.

Index Terms
3354 Precipitation
3360 Remote sensing
1840 Hydrometeorology
1847 Modeling

Suggested Itineraries:
Disasters‚ Calamities and Extreme Events
Machine Learning and AI

Cross-Listed:
NH - Natural Hazards
H - Hydrology

Co-Sponsored Sessions:
AMS： American Meteorological Society
EGU： European Geosciences Union
AOGS： Asia Oceania Geosciences Society

Neighborhoods:
3. Earth Covering