Quantitative precipitation estimation improved by multiple sensor approach

A new, real-time multi-sensor algorithm to estimate rainfall and snowfall is being developed by the Western and Intermountain Storms Hydrometeorology group at NSSL. The multiple-sensor approach will address problems that radars have with operational quantitative precipitation estimation in areas situated in complex terrain. In addition, the algorithm has been designed to detect mixed phase precipitation, and thus handle rain at low elevations, and snow at high elevations.

Case study examples showed that including infrared satellite data in a Quantitative Precipitation Estimation (QPE) product improved precipitation estimates. Satellite-derived cloud top temperatures provided the spatial pattern of precipitation. In addition, identifying bright band heights helped segregate rain from snow. Finally, after the initial QPE product was generated, estimates were calibrated by rain gauge reports.

The multi-sensor approach is evolving into a real-time automated algorithm called QPE SUMS (Quantitative Precipitation Estimation and Segregation Using Multiple Sensors) with the initial proof-of-concept taking place in Arizona.

For more informationon the Web, go to: http://www.nssl.noaa.gov/teams/western/qpe