Retrieval of Vertical Structure of Raindrop Size Distribution from Equatorial Atmosphere Radar and Boundary Layer Radar

Abstract

This work develops an algorithm to retrieve the vertical structure of the raindrop size distribution (DSD) of rain from simultaneous observations of 47 MHz Equatorial Atmosphere Radar (EAR) and 1.3 GHz Boundary Layer Radar (BLR) at Koto Tabang, West Sumatra, Indonesia (0.20°S, 100.32°E, 865 m above sea level). EAR is sensitive to the detection of turbulence, and BLR is susceptible to identifying precipitation echo. The EAR Doppler spectrum broadening effects due to turbulence and finite radar beam width were reduced using the convolution process. The Gaussian function was used to model the turbulence Doppler spectrum. A non-linear least-squares fitting method was applied to retrieve DSD parameters. Subsequently, the equations to estimate DSD using this dual-frequency algorithm assume the gamma DSD model to retrieve the distribution from the Doppler spectrum of precipitation echo. The precipitation events on April 23, 2004 on the Coupling Processes in the Equatorial Atmosphere (CPEA-I) project have been analyzed. Results show that the precipitation spectrum obtained using the dual-frequency method is higher, more precise, and well-fitted than the single-frequency method, meaning the dual-frequency method has great potential to be used in observing the microphysical process and remote sensing application analysis of DSD in Indonesia, particularly at Koto Tabang. The analyses show various microphysical processes that occur in the rain, such as coalescence, evaporation, break-up, and condensation. Furthermore, for the purpose of easier remote sensing application analysis of profile DSD characteristics, we use a DSD ΔΖMP parameter. ΔΖMP is a rain rate insensitive DSD parameter representing mean drop size. The trend of ΔZMP is not totally uniform with regards to rain rate and reflectivity factors, with ΔZMP higher in the first half of the event and becoming lower toward the end. This suggests that we have to use different Z-R relations within the event. Doi: 10.28991/ESJ-2022-06-03-02 Full Text: PDF