Attenuation Correction in Weather Radars for Snow.

Weather radars play a prominent role in remote sensing of the atmosphere. Various fields, such as meteorology and hydrology, rely on accurate weather radar data as input for their models. Different hydrometeors present during a weather event influence the amount of attenuation encountered by the radar signal. Attenuation correction for dual-polarization weather radar data is necessary to improve the radar products and get accurate measurements. Most of the existing attenuation correction research is associated with rain hydrometeors. Currently, research that addresses the attenuation correction of snow in weather radars is limited. Although it is known that attenuation of radar signals when it encounters rain is much greater than that for snow, attenuation for all hydrometeors needs to be addressed for accurate radar estimates. In this research work, the attenuation of different hydrometeors is studied using signal simulations. Various factors which influence attenuation, such as the elevation angle and particle size distribution, are considered, and the results are presented. An attenuation correction algorithm that uses the hydrometeor classification and specific differential phase products from the DROPS2.0 algorithm is introduced. Signal simulations are employed to obtain the relationship between specific attenuation and specific differential phases for different hydrometeors used in the proposed algorithm. The attenuation correction method is applied to X-band and Ku-band radar data. Path-integrated attenuation of about 8 dB was observed in the snow case discussed from Ku-band radar data. The method proposed for attenuation shows promising results at both frequency bands.