Tuesday, 17 September 2013: 11:45 AM
Colorado Ballroom (Peak 5, 3rd Floor) (Beaver Run Resort and Conference Center)
Dual-polarimetric radar measurements (DPM) are routinely used for studying microphysical processes of a precipitation system and also more accurate for quantitative precipitation estimation (QPE). Understanding the error characteristics of DPM can help us avoid using low quality DPM for microphysical retrieval and QPE. Moreover, assimilation of DPMs for improving convective scale prediction using NWP models is a long-standing goal. The process of assimilation of DPMs depends on the error covariances of background term (B) and the observations (R). The DPM is affected by several factors, such as; beam broadening, partial beam blockage, miss-match between horizontal and vertical channels; thermal noise of radar system; and Mie-scattering. In this paper, statistical diagnostic method is presented, A statistical diagnostic method (Desroziers et al. 2005) estimates the case dependent measurement error covariance matrix (R) in observation space.. The diagnostic approach combines observation, analysis, and background information for tuning observation and background errors adaptively using innovation vectors of background (dobs.ana.=yobs.-Hxana.) and analysis (dobs.bg.=yobs.-Hxbg.) from observation. The algorithm is examined by using Observing System Simulation Experiments (OSSE) studies at S and X-band radar wave-lengths and scenario of the observations. The results indicate that the algorithm can obtained the variance (σ2) of observation error with sufficient accuracy. The results show that variance (σ2) of observation error can be obtained, even when an underestimated initial variance (σ2) is specified.. The algorithm is further applied to NCAR S-Pol and Taiwan X-band TEAM-R radar measurements. The known biased ZDR measurements by the nearby ground targets with high correlation coefficient (ρhv > 0.99) were investigated. The algorithm identified biased ZDR measurements whereas, convectional approach failed to detect the same.
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