8A.6 Assimilation of dual-polarimetric radar observations and its impact on a summertime local convective storm

Tuesday, 6 November 2012: 4:45 PM
Symphony I (Loews Vanderbilt Hotel)
Xuanli Li, University of Alabama, Huntsville, AL; and J. Mecikalski

Handout (1.3 MB)

Dual-polarimetric (or “dual-pol”) radars transmit and receive both horizontally and vertically polarized signals. Owing to this feature, it is demonstrated that dual-pol Doppler variables provide more accurate measurements of liquid and solid cloud and precipitation particles than traditional weather radars. The utilization of dual-pol radar observations can be a potential way to improve radar data assimilation performance. However, assimilation of dual-pol radar observations (e.g., horizontal and differential reflectivity, the correlation between the reflected horizontal and vertical power returns, specific differential phase as the returned phase difference between horizontal and vertical pulses) is a challenging problem due to several issues including the uncertainties in forward operators for dual-pol variables (especially the ice particles), and the effectiveness and noise of using radar information for model variables. To date, there have been only limited studies in dual-polarimetric radar data assimilation research, mostly because of limitation of data availability, and because of the uncertainty in characterizing hydrometeor types using these data within cloud-resolving models. With the ongoing upgrade of the current U.S. NEXRAD radar network to include dual-pol capabilities, it is important to explore how to take advantage of the polarimetric variables to improve model initial condition for severe storm and convective weather forecasting.

Our main goals in this study are to develop the methodology to assimilate polarimetric radar variables; to seek improvement in storm initialization and short-term quantitative precipitation forecast with the assimilation of dual-pol radar variables; and to understand how the dual-pol variables can be used more efficiently in numerical weather prediction.

High-resolution (≤1 km) WRF model and its 3DVAR data assimilation system are used to conduct this research. We will present our recent work on assimilating the dual-polarimetric radar data for a case study – a summertime convective storm. Details of the methodology of radar data assimilation and the results of numerical simulations will be presented in the conference. We will also compare and discuss the influences of different data assimilation procedures, constrain parameters, an information content analysis, and influences of microphysical characteristics on storm initialization and short-term precipitation prediction.

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