Reliability of X-band Dual-polarization Phased Array Radars Through Comparison with an S-band Dual-polarization Doppler Radar

Based on the observations of a squall line on 11 May 2020 and stratiform precipitation on 6 June 2020 from two X-band dual-polarization phased array weather radars(DP-PAWRs)and an S-band dual-polarization Doppler weather radar(CINRAD/SA-D),the data reliability of DP-PAWR and its ability to detect the fine structures of mesoscale weather systems were assessed.After location matching,the observations of DP-PAWR and CINRAD/SA-D were compared in terms of reflectivity(Z_(H)),radial velocity(V),differential reflectivity(Z_(DR)),and specific differential phase(K_(DP)).The results showed that:(1)DP-PAWR has better ability to detect mesoscale weather systems than CINRAD/SAD;the multi-elevation-angles scanning of the RHI mode enables DP-PAWR to obtain a wider detection range in the vertical direction.(2)DP-PAWR’s Z_(H)and V structures are acceptable,while its sensitivity is worse than that of CINRAD/SA-D.The Z H suffers from attenuation and the Z_(H)area distribution is distorted around strong rainfall regions.(3)DP-PAWR’s Z_(DR)is close to a normal distribution but slightly smaller than that of CINRAD/SA-D.The K_(DP)products of DP-PAWR have much higher sensitivity,showing a better indication of precipitation.(4)DP-PAWR is capable of revealing a detailed and complete structure of the evolution of the whole storm and the characteristics of particle phase variations during the process of triggering and enhancement of a small cell in the front of a squall line,as well as the merging of the cell with the squall line,which cannot be observed by CINRAD/SA-D.With its fast volume scan feature and dual-polarization detection capability,DP-PAWR shows great potential in further understanding the development and evolution mechanisms of meso-γ-scale and microscale weather systems.

Suppression of Log-Normal Distributed Weather Clutter Observed by an S-Band Radar

We have observed weather clutter containing targets (ships) using an S-band radar with a frequency 3.05 GHz, a beam width 1.8°, and a pulsewidth 0.5 μs. To investigate the weather clutter amplitude statistics, we introduce the Akaike Information Criterion (AIC). We have found that the weather clutter amplitudes obey the log-normal, Weibull, and log-Weibull distributions with the shape parameters of 0.308 to 0.470, 4.42 to 4.51, and 15.91 to 16.44, respectively, for small data within the beam width of an antenna. We have proposed the log-normal/CFAR circuit modified a Cell-Averaging (CA) LOG/CFAR circuit. It is found that weather clutter is suppressed with improvement of 51.58 dB by log-normal/CFAR. As a result, we have showed that weather clutter observed by S-band radar does not obey the Rayleigh distribution and our log-normal/CFAR circuit has an effect on suppression of clutter and detection of target, while conventional LOG/CFAR circuit does not. In addition, if our circuit can be realized, we will have an advantage economically.

Utilization of Specific Attenuation for Rainfall Estimation in Southern China

This study uses rain gauge observations to assess the performance of different radar estimators R(ZH),R(KDP)and R(A)in estimating precipitation based on the observations of an S-band polarimetric radar over southern China during a typical convective storm and an extremely severe typhoon,i.e.,Typhoon Manghkut.These radar estimators were derived from observations of a local autonomous particle size and velocity(Parsivel)unit(APU)disdrometer.A key parameter,alpha(α),which is the ratio of specific attenuation A to specific differential phase KDP with three fixed values(α=0.015 dB deg^(-1),α=0.0185 dB deg^(-1)andα=0.03 dB deg^(-1))was examined to test the sensitivity of the R(A)rain retrievals.The results show that:(1)All radar estimators can capture the spatio-temporal patterns of two precipitation events,R(A)withα=0.0185 dB deg^(-1)is well correlated with gauge measurement via higher Pearson’s correlation coefficient(CC)of 0.87,lower relative bias(RB)of 16%,and lower root mean square error(RMSE)of 17.09 mm in the convective storm while it underestimates the typhoon event with RB of 35%;(2)R(A)withα=0.03 dB deg^(-1)shows the best statistical scores with the highest CC(0.92),lowest RB(7%)and RMSE(25.74 mm)corresponding to Typhoon Manghkut;(3)R(A)estimates are more efficient in mitigating the impact of partial beam blockage.The results indicate thatαis remarkably influenced by the variation of drop size distribution.Thus,more work is needed to establish an automated and optimizedαfor the R(A)relation during different rainfall events over different regions.