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The objective of this research was to acquire a raindrop size distribution (DSDs) retrieved from C-band polarimetric radar observations scheme for the first time in south China. An observation period of the precipitation process was selected, and the shape-slope (μ-Λ) relationship of this region was statistically analyzed using the raindrop sample observations from the two-dimensional video disdrometer (2DVD) at Xinfeng Station, Guangdong Province. Simulated data of the C-band polarimetric radar reflectivity ZHH and differential reflectivity ZDR were obtained through scattering simulation. The simulation data were combined with DSD fitting to determine the ZDR-Λ and log10(ZHH/N0)-Λ relationships. Using Xinfeng C-band polarimetric radar observations ZDR and ZHH, the raindrop Gamma size distribution parameters μ, Λ, and N0 were retrieved. A scheme for using C-band polarimetric radar to retrieve the DSDs was developed. This research revealed that during precipitation process, the DSDs obtained using the C-band polarimetric radar retrieval scheme are similar to the 2DVD observations, the precipitation characteristics of rainfall intensity (R), mass-weighted mean diameter (Dm) and intercept parameter (Nw) with time obtained by radar retrieval are basically consistent with the observational results of the 2DVD. This scheme establishes the relationship between the observations of the C-band polarimetric radar and the physical quantities of the numerical model. This method not only can test the prediction of the model data assimilation system on the convective scale and determine error sources, but also can improve the microphysical precipitation processes analysis and radar quantitative precipitation estimation. The present research will facilitate radar data assimilation in the future. [ABSTRACT FROM AUTHOR]

The measurement error of differential reflectivity (ZDR), especially systematic ZDR bias, is a fundamental issue for the application of polarimetric radar data. Several calibration methods have been proposed and applied to correct ZDR bias. However, recent studies have shown that ZDR bias is time-dependent and can be significantly different on two adjacent days. This means that the frequent monitoring of ZDR bias is necessary, which is difficult to achieve with existing methods. As radar sensitivity has gradually been enhanced, large amounts of online solar echoes have begun to be observed in volume-scan data. Online solar echoes have a high frequency, and a known theoretical value of ZDR (0 dB) could thus allow the continuous monitoring of ZDR bias. However, online solar echoes are also affected by low signal-to-noise ratio and precipitation attenuation for short-wavelength radar. In order to understand the variation of ZDR bias in a C-band polarimetric radar at the Nanjing University of Information Science and Technology (NUIST-CDP), we analyzed the characteristics of online solar echoes from this radar, including the daily frequency of occurrence, the distribution along the radial direction, precipitation attenuation, and fluctuation caused by noise. Then, an automatic method based on online solar echoes was proposed to monitor the daily ZDR bias of the NUIST-CDP. In the proposed method, a one-way differential attenuation correction for solar echoes and a maximum likelihood estimation using a Gaussian model were designed to estimate the optimal daily ZDR bias. The analysis of three months of data from the NUIST-CDP showed the following: (1) Online solar echoes occurred very frequently regardless of precipitation. Under the volume-scan mode, the average number of occurrences was 15 per day and the minimum number was seven. This high frequency could meet the requirements of continuous monitoring of the daily ZDR bias under precipitation and no-rain conditions. (2) The result from the proposed online solar method was significantly linearly correlated with that from the vertical pointing method (observation at an elevation angle of 90°), with a correlation coefficient of 0.61, suggesting that the proposed method is feasible. (3) The day-to-day variation in the ZDR bias was relatively large, and 32% of such variations exceeded 0.2 dB, meaning that a one-time calibration was not representative in time. Accordingly, continuous calibration will be necessary. (4) The ZDR bias was found to be largely influenced by the ambient temperature, with a large negative correlation between the ZDR bias and the temperature.

A mobile C-band dual polarimetric weather radar J type (PCDJ), which adopts simultaneous transmission and simultaneous reception (STSR) of horizontally and vertically polarized signals, was first developed in China in 2008. It was deployed in the radar observation plan in the South China Heavy Rainfall Experiment (SCHeREX) in the summer of 2008 and 2009, as well as in Tropical Western Pacific Ocean Observation Experiments and Research on the Predictability of High Impact Weather Events from 2008 to 2010 in China (TWPOR). Using the observation data collected in these experiments, the radar systematic error and its sources were analyzed in depth. Meanwhile an algorithm that can smooth differential propagation phase ( Φ) for estimating the high-resolution specific differential phase ( K) was developed. After attenuation correction of reflectivity in horizontal polarization ( Z) and differential reflectivity ( Z) of PCDJ radar by means of K, the data quality was improved significantly. Using quality-controlled radar data, quantitative rainfall estimation was performed, and the resutls were compared with rain-gauge measurements. A synthetic Z / K-based method was analyzed. The results suggest that the synthetic method has the advantage over the traditional Z-based method when the rain rate is >5 mm h. The more intensive the rain rates, the higher accuracy of the estimation. [ABSTRACT FROM AUTHOR]

The measurement error of differential reflectivity (ZDR), especially systematic ZDR bias, is a fundamental issue for the application of polarimetric radar data. Several calibration methods have been proposed and applied to correct ZDR bias. However, recent studies have shown that ZDR bias is time-dependent and can be significantly different on two adjacent days. This means that the frequent monitoring of ZDR bias is necessary, which is difficult to achieve with existing methods. As radar sensitivity has gradually been enhanced, large amounts of online solar echoes have begun to be observed in volume-scan data. Online solar echoes have a high frequency, and a known theoretical value of ZDR (0 dB) could thus allow the continuous monitoring of ZDR bias. However, online solar echoes are also affected by low signal-to-noise ratio and precipitation attenuation for short-wavelength radar. In order to understand the variation of ZDR bias in a C-band polarimetric radar at the Nanjing University of Information Science and Technology (NUIST-CDP), we analyzed the characteristics of online solar echoes from this radar, including the daily frequency of occurrence, the distribution along the radial direction, precipitation attenuation, and fluctuation caused by noise. Then, an automatic method based on online solar echoes was proposed to monitor the daily ZDR bias of the NUIST-CDP. In the proposed method, a one-way differential attenuation correction for solar echoes and a maximum likelihood estimation using a Gaussian model were designed to estimate the optimal daily ZDR bias. The analysis of three months of data from the NUIST-CDP showed the following: (1) Online solar echoes occurred very frequently regardless of precipitation. Under the volume-scan mode, the average number of occurrences was 15 per day and the minimum number was seven. This high frequency could meet the requirements of continuous monitoring of the daily ZDR bias under precipitation and no-rain conditions. (2) The result from the proposed online solar method was significantly linearly correlated with that from the vertical pointing method (observation at an elevation angle of 90°), with a correlation coefficient of 0.61, suggesting that the proposed method is feasible. (3) The day-to-day variation in the ZDR bias was relatively large, and 32% of such variations exceeded 0.2 dB, meaning that a one-time calibration was not representative in time. Accordingly, continuous calibration will be necessary. (4) The ZDR bias was found to be largely influenced by the ambient temperature, with a large negative correlation between the ZDR bias and the temperature. [ABSTRACT FROM AUTHOR]