Rain-rate estimation algorithm using signal attenuation of Ka-band cloud radar

Abstract

A millimetre-wave cloud radar has limitations for observing heavy rainfall because the short wavelength leads to strong attenuation from raindrops. However, recent studies have attempted to estimate the rain rate using attenuation, which becomes greater as the rain intensity increases. The rain-rate-retrieval algorithm is developed in the present paper using the Ka-band cloud radar (KaCR) installed at the Boseong Global Standard Observatory (BGSO) in the Republic of Korea. First, rain profiles were identified using the threshold of reflectivity (Z) and Doppler velocity (DV) averaged for the analysis of layer that minimized the effects of the receiver saturation and classified as low or high rain-rate cases using the averaged DV. The reflectivity and rain-rate (Z-R) relationship was then derived for low rain-rate cases that showed insignificant effects for signal attenuation. On the other hand, the attenuation and rain-rate (A-R) relationship was derived using high rain-rate cases that showed the dominant effects of attenuation. The attenuation was calculated using a reflectivity gradient between the upper and lower boundaries of the attenuated layer. Finally, the rain-rate-retrieval algorithm was designed using the derived Z-R and A-R relationship and then applied back to the KaCR. The estimated rain rate in the KaCR was a similar trend to the observed rain rate in the optical rain gauge (ORG), but slightly underestimated.