Takuya Kawabata, Meteorological Research Institute / Japan meteorological agency
Development of assimilation methods for polarimetric radars at storm scales
CoauthorsThomas Schwitalla, Hans-Stefan Bauer, Ahoro Adachi, Volker Wulfmeyer
Abstract: Assimilation methods for dual polarimetric radars are developed. Before the implementation of these methods, five forward operators for polarimetric radars that focus on warm rain are compared with each other and actual radar observations in terms of their performance. These operators mutually consider 1) radar beam broadening with Gaussian weights in three-dimensional directions, 2) climatological beam bending, and 3) attenu-ation effects. Two of the operators derive polarimetric parameters assuming the exponential raindrop size distribution obtained by the models. The first operator uses the T-matrix method and the second one is based on fitting functions against scattering amplitudes. Comparisons with the observations show that ac-curacy of these converters are totally fair, but the second one has the smallest bias. When the shape parameter in the first converter is considered, the first one is a bit superior to the second.
The remaining three converters estimates the mixing ratio of rainwater (Qr) from the measured polarimetric parameters. The third converter uses both ZH and ZDR, the fourth uses the specific differential phase (KDP), and the fifth uses both KDP and ZDR. Comparisons with actual measurements showed that the accuracies of the fourth converters are superior to the other two. Another evaluation showed that both the first and second converters have slightly higher equitable threat scores and fraction skill scores than the other three. Considering the attenua-tion effect, the fitting function and the operator with KDP are the most suita-ble for data assimilation.
After the evaluation of accuracy of the five operators, two operators with the fitting function and KDP are implemented into a strom scale variational DA system. A preliminary result show that the assimilation of polarimetric parameters improves a rainfall distribution in a numerical model.