Assimilation of the dual-polarization Doppler radar data for a convective storm with a warm-rain radar forward operator

• Published in: Journal of Geophysical Research: Atmospheres Vol. 115; no. D16
• Main Authors: Li, Xuanli, Mecikalski, John R.
• Format: Journal Article
• Language: English
• Published: Washington, DC Blackwell Publishing Ltd 27.08.2010; American Geophysical Union
• Subjects: Atmospheric sciences; Data assimilation; Data collection; Doppler radar; dual polarization; Earth sciences; Earth, ocean, space; Exact sciences and technology; Geophysics; Horizontal; Mathematical models; Mesoclimatology; Operational research; Operators; Polarization; Radar; Rain; Reflectivity; Storms; Water content; Southern Europe; Italy; Marches Italy; Alabama; United States; Europe; Short term; Operator; Three-dimensional calculations; case studies; networks; North America; currents; water content; Variational calculus; polarization; Radial velocity; models; rainfall; Initial condition; atmospheric precipitation; Mesoscale convective system; Regional scope; lead; Short range forecast; Radar observation; Numerical forecast; Doppler radar; radar methods; storms; Data assimilation; Reflectance
• ISSN: 0148-0227; 2169-897X; 2156-2202; 2169-8996
• DOI: 10.1029/2009JD013666

In this paper, a data assimilation scheme is built to utilize the dual‐polarization Doppler radar observations collected by the C band Advanced Radar for Meteorological and Operational Research and is tested with a case study for a mesoscale convective system (MCS) over northern Alabama in the afternoon of 15 March 2008. Three variables, horizontal reflectivity, differential reflectivity, and radial velocity are assimilated into the advanced research version of the Weather Research and Forecasting model. A warm rain radar operator is constructed to assimilate the horizontal reflectivity and differential reflectivity data with the three‐dimensional variational data assimilation (3DVAR) system. The main goals of this paper are to, first, demonstrate the improvements in short‐term forecasts of the moist convection when fields unique to the dual‐polarization radar are assimilated into a regional model and, second, to understand how these fields may best be integrated in a data assimilation system like 3DVAR to improve short‐term storm forecast. The results show that the horizontal reflectivity, differential reflectivity, and radial velocity data can be successfully assimilated using our data assimilation scheme. The assimilation of the horizontal reflectivity and radial velocity data has a significant positive impact on the reflectivity distribution of the MCS. An additional improvement (10%–20%) in the initial condition is found when the differential reflectivity data are further assimilated. Moreover, the improved initial condition leads to apparent improvement in short‐term forecast of the MCS. The best forecast is produced when both horizontal and differential reflectivity and radial velocity data are assimilated. This improvement can be attributed to the improved estimate of liquid water content by using the radar operator with combined information of both horizontal reflectivity and differential reflectivity. This study demonstrates the benefit of utilizing the observations from single dual‐polarization radar. With the forthcoming upgrade of the current U. S. “NEXRAD” radar system (set to begin in ∼2010), a dual‐polarization radar network will be available. Assimilating observations from the dual‐polarization Doppler radar network could be a potential technique to further improve the short‐term numerical forecasts of convective storms.