Validation and Intercomparison of Rain Rate Retrievals using the S-Pol Radar during PRECIP

Modern weather radars provide high-resolution temporal and spatial estimates of rainfall and are crucial in expanding quantitative precipitation estimations beyond sparsely connected surface observations. Dual-polarization capabilities allow for more advanced “hybrid” rain rate retrieval algorithms than traditional Z-R-based relationships, although they also rely on climatologically-tuned coefficients. In this study, the Lidar Radar Open Software Environment (LROSE) is utilized to apply a Z-R relationship as well as the NCAR hybrid rain rate retrieval algorithm to the S-band, dual-polarization radar, S-Pol, during its deployment in the 2022 Prediction of Rainfall Extremes Campaign In the Pacific (PRECIP) in Taiwan. The goals of this campaign were to understand the ingredients necessary in producing extreme rainfall, requiring accurate rainfall estimates from S-Pol to connect the microphysical characteristics of rainfall and the precipitation at the surface. The radar was deployed for a 2.5-month period near the mountainous terrain of Taiwan, proving a challenge for most rain rate retrieval algorithms due to terrain blockage effects. This challenge prompted a new implementation of a specific attenuation-based rain rate retrieval algorithm into LROSE that can mitigate the effects of partial beam blockage.

Validation and assessment of each algorithm is done using instrumentation provided by the Central Weather Bureau of Taiwan during PRECIP, including 1000+ rain gauges and the existing operational radar network. Modification of coefficients for the three rain rate algorithms is performed using Parsivel disdrometers. While validation encompasses the entirety of the field campaign, this presentation focuses on a comparison of these rain rate algorithms using PRECIP IOP 1 (0000 UTC 26 May - 0000 UTC 28 May 2022). A major rain producer during this case was a quasi-stationary Mei-yu front, contributing to 300 mm of rainfall in 2-days in the S-Pol domain. Rainfall during this case included stratiform precipitation spanning from the ocean to the complex terrain with multiple embedded convective cells producing a wide array of rainfall intensities to assess in the S-Pol domain. This research serves to test the new specific attenuation-based rain rate retrieval algorithm implemented into LROSE as well as compare the skill of multiple rain rate retrieval algorithms in representing extreme, subtropical rainfall in complex terrain.