School of Meteorology (Defense)

Assimilation of Attenuated Reflectivity Data from X-band Network Radars Using Ensemble Kalman Filter

Jing Cheng

School of Meteorology

31 July 2013, 1:00 PM

National Weather Center, Room 4140
120 David L. Boren Blvd.
University of Oklahoma
Norman, OK

To use reflectivity data from X-band radars for quantitative precipitation estimation and storm-scale data assimilation, the effect of attenuation must be properly accounted for. Traditional approaches try to make correction to the attenuated reflectivity first before using the data. An alternative, theoretically more attractive approach build the attenuation effect into the observation operator of reflectivity within a data assimilation system, such as an ensemble Kalman filter (EnKF); such a system directly assimilates the attenuated reflectivity and takes advantage of the power of EnKF in microphysical state estimation for potentially more accurate solution.

This study first test the approach for the CASA (Center for Collaborative Adaptive Sensing of the Atmosphere) X-band radar network configuration through observing system simulation experiments (OSSE) for a quasi-linear convective system that has more significant attenuation than isolated storms. To avoid the problem of potentially giving too much trust to fully attenuated reflectivity, an analytical echo-intensity-dependent model for the observation error (AEM) is developed and is found to improve the performance of the filter. Sensitivity experiments are designed to examine the effectiveness of AEM by introducing multiple sources of observation errors into the simulated observations. The performance of such an approach in the presence of resolution-induced model error is also evaluated and good results are obtained. This system with build-in attenuation correction is then applied, for the first time, to a real case, using data from the X-band radars from the CASA Oklahoma testbed. For the 24 May 2011 Chickasha, Oklahoma, tornado case, the attenuation correction procedure is found to be very effective – the analyses obtained using attenuated data are better than those obtained using pre-corrected data when all the values of reflectivity observations are assimilated. The effectiveness of the procedure is further examined by comparing deterministic and ensemble forecasts.

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