Global and regional quantitative precipitation estimates (QPEs) are critical for understanding climate variability and hydrometeorological cycles, detecting natural disasters, improving flash flood and weather forecasts, and effectively managing the use of Earth's freshwater resources. However, obtaining accurate QPEs is a challenging task in many areas of the world due to sparse gauge networks, complex terrain, and global water cycle acceleration. The science of precipitation remote sensing, including instrumentation and algorithms, is progressing rapidly, with the aims of providing accurate high-resolution precipitation estimates, improving forecasting at a variety of temporal scales, and understanding the causes and underlying processes of these natural hazards. This session invites high quality, original research contributions from radar and satellite meteorology and associated precipitation data sciences, including improved radar and satellite QPE retrievals and novel methods to produce multi-sensor QPEs by merging multiple satellite/radar products and/or in-situ observations. Assessments of remotely sensed QPE product performance, as well as demonstrations of the applicability of remotely sensed QPEs for improved weather and hazards forecasting or hydrometeorological process understanding are also encouraged.
Submitters: Janice L. Bytheway, Physical Sciences Laboratory, NOAA, Boulder, CO; Haonan Chen, Colorado State University and NOAA Physical Sciences Laboratory, Boulder, CO and Ryan Gonzalez, Department of Atmospheric Science, Colorado State University, Fort Collins, CO
- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner