Assigning tropical rainfall rates for multisensor QPE using environmental moisture fields and vertical profiles of reflectivity

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Wednesday, 20 January 2010: 10:45 AM
B304 (GWCC)
Heather Moser, CIMMS/Univ. of Oklahoma, Norman, OK; and K. Howard, J. Zhang, and S. Vasiloff

Presentation PDF (2.5 MB)

The National Mosaic and Multisensor QPE Project (NMQ) is a testbed for both real-time, high-resolution precipitation estimation and short-term QPF. The NMQ QPE (Q2) product has a 1-km spatial resolution over the continental United States and is updated every five minutes. It is a fully automated multisensor rainfall estimate that incorporates data from radar, rain gauges, satellites, lightning detection networks, and numerical weather prediction (NWP) model analyses. The various inputs are used to segregate different types of precipitation (stratiform and convective rain, hail, tropical rain, and snow) and assign different Z-R relationships at each grid point.

Identification of tropical (warm rain) precipitation for Q2 is currently based on vertical profiles of reflectivity (VPR) calculated at each radar location. If a VPR is identified as tropical, the tropical Z-R function is then applied to all locations within a distance from the radar where reflectivity exceeds a threshold (generally the value at which tropical rainfall rates begin to differ significantly from convective or stratiform rates). However, a maritime airmass at the radar site may not always be representative of the radar's entire domain, leading to tropical rainfall rates being applied erroneously where a different airmass is present.

Research has shown that environmental properties such as precipitable water and precipitation efficiency can be effective for discriminating between tropical and continental convection. An algorithm has been developed for Q2 that uses environmental analyses from NWP models to more precisely delineate areas of tropical rainfall based on these airmass properties. Hourly accumulations derived from both the new algorithm and the current tropical rainfall identification method were compared to rain gauge data for two rainfall events to determine whether the use of environmental fields led to an improvement in the spatial distribution of Q2 rainfall rates.