Primary Convener:
Paul Kucera, University Corporation for Atmospheric Research

Convener:
Ali Behrangi, University of Arizona

Early Career Convener:
Andrew Newman, NSF National Center for Atmospheric Research

Chair:
Andrew Newman, NSF National Center for Atmospheric Research
Ali Behrangi, University of Arizona
Paul Kucera, NCAR

This session seeks contributions from the research, operational, and user communities that utilize precipitation datasets in applications that address scientific and societal needs from flood forecasts to climate impact studies. Uncertainties in precipitation data have a significant impact on the usefulness of these applications. This session also seeks contributions that present advances in error characterization and uncertainty quantification in diverse precipitation datasets and to enhance our understanding on how the uncertainties propagate to hydrological processes and thus affecting the modeling and data-assimilation in these applications. The session can host broad topics including evaluation efforts. Presentations that present precipitation applications and various error components in precipitation datasets are welcome.

Index Terms
3354 Precipitation
1840 Hydrometeorology
1854 Precipitation
4315 Monitoring, forecasting, prediction

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

Cross-Listed:
NH - Natural Hazards
SY - Science and Society
A - Atmospheric Sciences
GC - Global Environmental Change

Co-Organized Sessions:
Atmospheric Sciences
Natural Hazards

Neighborhoods:
3. Earth Covering
1. Science Nexus