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Motuo and Naqu are two typical regions of the Tibetan Plateau with different geographical locations and climate regimes. These differences may lead to discrepancies in the raindrop size distributions (DSDs) and precipitation microphysical processes between the two regions. This paper investigates discrepancies in the DSDs using disdrometer data obtained during the rainy season in Motuo and Naqu. The DSD characteristics are studied under five different rainfall rate categories and two precipitation types (stratiform and convective). For the total data sets, the number concentrations of drops with diameters D > 0.6 (D < 0.6) mm are higher (lower) in Naqu than in Motuo. The fitted normalized gamma distributions of the averaged DSDs for the five rainfall rate categories show that Naqu has a larger (lower) mass-weighted mean diameter Dm (normalized intercept parameter, log10Nw) than does Motuo. The difference in Dm between Naqu and Motuo increases with the rainfall rate. Convective clusters in Naqu could be identified as continental-like, while convective precipitation in Motuo could be classified as maritime-like. The relationships between the shape factor μ and slope parameter Λ of the gamma distribution model, the radar reflectivity Z and the rainfall rate R are also derived. Furthermore, the possible causative mechanism for the notable DSD variation between the two regions during the rainy season is illustrated using reanalysis data and automated weather station observations. Cold rain processes are mainly responsible for the low concentrations of large drops observed in Naqu, whereas warm rain prevails in Motuo, producing abundant small drops.

Dual-polarization (dual-pol) radar can measure additional parameters that provide more microphysical information of precipitation systems than those provided by conventional Doppler radar. The dual-pol parameters have been successfully utilized to investigate precipitation microphysics and improve radar quantitative precipitation estimation (QPE). The recent progress in dual-pol radar research and applications in China is summarized in four aspects. Firstly, the characteristics of several representative dual-pol radars are reviewed. Various approaches have been developed for radar data quality control, including calibration, attenuation correction, calculation of specific differential phase shift, and identification and removal of non-meteorological echoes. Using dual-pol radar measurements, the microphysical characteristics derived from raindrop size distribution retrieval, hydrometeor classification, and QPE is better understood in China. The limited number of studies in China that have sought to use dual-pol radar data to validate the microphysical parameterization and initialization of numerical models and assimilate dual-pol data into numerical models are summarized. The challenges of applying dual-pol data in numerical models and emerging technologies that may make significant impacts on the field of radar meteorology are discussed.

A modified hydrometeor classification algorithm (HCA) is developed in this study for Chinese polarimetric radars. This algorithm is based on the U.S. operational HCA. Meanwhile, the methodology of statistics-based optimization is proposed including calibration checking, datasets selection, membership functions modification, computation thresholds modification, and effect verification. Zhuhai radar, the first operational polarimetric radar in South China, applies these procedures. The systematic bias of calibration is corrected, the reliability of radar measurements deteriorates when the signal-to-noise ratio is low, and correlation coefficient within the melting layer is usually lower than that of the U.S. WSR-88D radar. Through modification based on statistical analysis of polarimetric variables, the localized HCA especially for Zhuhai is obtained, and it performs well over a one-month test through comparison with sounding and surface observations. The algorithm is then utilized for analysis of a squall line process on 11 May 2014 and is found to provide reasonable details with respect to horizontal and vertical structures, and the HCA results—especially in the mixed rain-hail region—can reflect the life cycle of the squall line. In addition, the kinematic and microphysical processes of cloud evolution and the differences between radar-detected hail and surface observations are also analyzed. The results of this study provide evidence for the improvement of this HCA developed specifically for China.

The characteristics of raindrop size distribution (DSD) over the Tibetan Plateau and southern China are studied in this paper, using the DSD data from April to August 2014 collected by HSC-PS32 disdrometers in Nagqu and Yangjiang, comprising a total of 9430 and 6366 1-min raindrop spectra, respectively. The raindrop spectra, characteristics of parameter variations with rainfall rate, and the relationships between reflectivity factor (Z) and rainfall rate (R) are analyzed, as well as their DSD changes with precipitation type and rainfall rate. The results show that the average raindrop spectra appear to be one-peak curves, the number concentration for larger drops increase significantly with rainfall rate, and its value over southern China is much higher, especially in convective rain. Standardized Gamma distributions better describe DSD for larger drops, especially for convective rain in southern China. All three Gamma parameters for stratiform precipitation over the Tibetan Plateau are much higher, while its shape parameter (μ) and mass-weighted mean diameter (D m), for convective precipitation, are less. In terms of parameter variation with rainfall rate, the normalized intercept parameter (N w) over the Tibetan Plateau for stratiform rain increases with rainfall rate, which is opposite to the situation in convective rain. The μ over the Tibetan Plateau for stratiform and convective precipitation types decreases with an increase in rainfall rate, which is opposite to the case for D m variation. In Z–R relationships, like “Z = AR b ”, the coefficient A over the Tibetan Plateau is smaller, while its b is higher, when the rain type transfers from stratiform to convective ones. Furthermore, with an increase in rainfall rate, parameters A and b over southern China increase gradually, while A over the Tibetan Plateau decreases substantially, which differs from the findings of previous studies. In terms of geographic location and climate over the Tibetan Plateau and southern China, the precipitation in the pre-flood seasons is dominated by strong convective rain, while weak convective rain occurs frequently in northern Tibet with lower humidity and higher altitude.

This study concerns a Ka-band solid-state transmitter cloud radar, made in China, which can operate in three different work modes, with different pulse widths, and coherent and incoherent integration numbers, to meet the requirements for cloud remote sensing over the Tibetan Plateau. Specifically, the design of the three operational modes of the radar (i.e., boundary mode M1, cirrus mode M2, and precipitation mode M3) is introduced. Also, a cloud radar data merging algorithm for the three modes is proposed. Using one month’s continuous measurements during summertime at Naqu on the Tibetan Plateau, we analyzed the consistency between the cloud radar measurements of the three modes. The number of occurrences of radar detections of hydrometeors and the percentage contributions of the different modes’ data to the merged data were estimated. The performance of the merging algorithm was evaluated. The results indicated that the minimum detectable reflectivity for each mode was consistent with theoretical results. Merged data provided measurements with a minimum reflectivity of −35 dBZ at the height of 5 km, and obtained information above the height of 0.2 km. Measurements of radial velocity by the three operational modes agreed very well, and systematic errors in measurements of reflectivity were less than 2 dB. However, large discrepancies existed in the measurements of the linear depolarization ratio taken from the different operational modes. The percentage of radar detections of hydrometeors in mid- and high-level clouds increased by 60% through application of pulse compression techniques. In conclusion, the merged data are appropriate for cloud and precipitation studies over the Tibetan Plateau.

An X-band phased-array meteorological radar (XPAR) was developed in China and will be installed in an airplane to observe precipitation systems for research purposes. In order to examine the observational capability of the XPAR and to test the operating mode and calibration before installation in the airplane, a mobile X-band Doppler radar (XDR) and XPAR were installed at the same site to observe convective precipitation events. Nearby S-band operational radar (SA) data were also collected to examine the reflectivity bias of XPAR. An algorithm for quantitative analysis of reflectivity and velocity differences and radar sensitivity of XPAR is presented. The reflectivity and velocity biases of XPAR are examined with SA and XDR. Reflectivity sensitivities, the horizontal and vertical structures of reflectivity by the three radars are compared and analyzed. The results indicated that while the XPRA with different operating modes can capture the main characteristic of 3D structures of precipitation, and the averaged reflectivity differences between XPAR and XDR, and XDR and SA, were 0.4 dB and 6.6 dB on 13 July and −4.5 dB and 5.1 dB on 2 August 2012, respectively. The minimum observed reflectivities at a range of 50 km for XPAR, XDR and SA were about 15.4 dBZ, 13.5 dBZ and −3.5 dBZ, respectively. The bias of velocity between XPAR and XDR was negligible. This study provides a possible method for the quantitative comparison of the XPAR data, as well as the sensitivity of reflectivity, calibration, gain and bias introduced by pulse compression.

Using numerical simulation data of the forward differential propagation shift (ϕDP) of polarimetric radar, the principle and performing steps of noise reduction by wavelet analysis are introduced in detail. Profiting from the multiscale analysis, various types of noises can be identified according to their characteristics in different scales, and suppressed in different resolutions by a penalty threshold strategy through which a fixed threshold value is applied, a default threshold strategy through which the threshold value is determined by the noise intensity, or a ϕDP penalty threshold strategy through which a special value is designed for ϕDP de-noising. Then, a hard-or soft-threshold function, depending on the de-noising purpose, is selected to reconstruct the signal. Combining the three noise suppression strategies and the two signal reconstruction functions, and without loss of generality, two schemes are presented to verify the de-noising effect by dbN wavelets: (1) the penalty threshold strategy with the soft threshold function scheme (PSS); (2) the ϕDP penalty threshold strategy with the soft threshold function scheme (PPSS). Furthermore, the wavelet de-noising is compared with the mean, median, Kalman, and finite impulse response (FIR) methods with simulation data and two actual cases. The results suggest that both of the two schemes perform well, especially when ϕDP data are simultaneously polluted by various scales and types of noises. A slight difference is that the PSS method can retain more detail, and the PPSS can smooth the signal more successfully.

A variety of faulty radar echoes may cause serious problems with radar data applications, especially radar data assimilation and quantitative precipitation estimates. In this study, “test pattern” caused by test signal or radar hardware failures in CINRAD (China New Generation Weather Radar) SA and SB radar operational observations are investigated. In order to distinguish the test pattern from other types of radar echoes, such as precipitation, clear air and other non-meteorological echoes, five feature parameters including the effective reflectivity data percentage (R Z), velocity RF (range folding) data percentage (R RF), missing velocity data percentage (R M), averaged along-azimuth reflectivity fluctuation $$\left( {R_{N_{r,Z} } } \right)$$ and averaged along-beam reflectivity fluctuation $$\left( {R_{N_{a,Z} } } \right)$$ are proposed. Based on the fuzzy logic method, a test pattern identification algorithm is developed, and the statistical results from all the different kinds of radar echoes indicate the performance of the algorithm. Analysis of two typical cases with heavy precipitation echoes located inside the test pattern are performed. The statistical results show that the test pattern identification algorithm performs well, since the test pattern is recognized in most cases. Besides, the algorithm can effectively remove the test pattern signal and retain strong precipitation echoes in heavy rainfall events.

Cloud properties were investigated based on aircraft and cloud radar co-observation conducted at Yitong, Jilin, Northeast China. The aircraft provided in situ measurements of cloud droplet size distribution, while the millimeter-wavelength cloud radar vertically scanned the same cloud that the aircraft penetrated. The reflectivity factor calculated from aircraft measurements was compared in detail with simultaneous radar observations. The results showed that the two reflectivities were comparable in warm clouds, but in ice cloud there were more differences, which were probably associated with the occurrence of liquid water. The acceptable agreement between reflectivities obtained in water cloud confirmed that it is feasible to derive cloud properties by using aircraft data, and hence for cloud radar to remotely sense cloud properties. Based on the dataset collected in warm clouds, the threshold of reflectivity to diagnose drizzle and cloud particles was studied by analyses of the probability distribution function of reflectivity from cloud particles and drizzle drops. The relationship between reflectivity factor (Z) and cloud liquid water content (LWC) was also derived from data on both cloud particles and drizzle. In comparison with cloud droplets, the relationship for drizzle was blurred by many scatter points and thus was less evident. However, these scatters could be partly removed by filtering out the drop size distribution with a large ratio of reflectivity and large extinction coefficient but small effective radius. Empirical relationships of Z-LWC for both cloud particles and drizzle could then be derived.

A new radar echo tracking algorithm known as multi-scale tracking radar echoes by cross-correlation (MTREC) was developed in this study to analyze movements of radar echoes at different spatial scales. Movement of radar echoes, particularly associated with convective storms, exhibits different characteristics at various spatial scales as a result of complex interactions among meteorological systems leading to the formation of convective storms. For the null echo region, the usual correlation technique produces zero or a very small magnitude of motion vectors. To mitigate these constraints, MTREC uses the tracking radar echoes by correlation (TREC) technique with a large “box” to determine the systematic movement driven by steering wind, and MTREC applies the TREC technique with a small “box” to estimate small-scale internal motion vectors. Eventually, the MTREC vectors are obtained by synthesizing the systematic motion and the small-scale internal motion. Performance of the MTREC technique was compared with TREC technique using case studies: the Khanun typhoon on 11 September 2005 observed by Wenzhou radar and a squall-line system on 23 June 2011 detected by Beijing radar. The results demonstrate that more spatially smoothed and continuous vector fields can be generated by the MTREC technique, which leads to improvements in tracking the entire radar reflectivity pattern. The new multi-scale tracking scheme was applied to study its impact on the performance of quantitative precipitation nowcasting. The location and intensity of heavy precipitation at a 1-h lead time was more consistent with quantitative precipitation estimates using radar and rain gauges.

A prototype space-based cloud radar has been developed and was installed on an airplane to observe a precipitation system over Tianjin, China in July 2010. Ground-based S-band and Ka-band radars were used to examine the observational capability of the prototype. A cross-comparison algorithm between different wavelengths, spatial resolutions and platform radars is presented. The reflectivity biases, correlation coefficients and standard deviations between the radars are analyzed. The equivalent reflectivity bias between the S- and Ka-band radars were simulated with a given raindrop size distribution. The results indicated that reflectivity bias between the S- and Ka-band radars due to scattering properties was less than 5 dB, and for weak precipitation the bias was negligible. The prototype space-based cloud radar was able to measure a reasonable vertical profile of reflectivity, but the reflectivity below an altitude of 1.5 km above ground level was obscured by ground clutter. The measured reflectivity by the prototype space-based cloud radar was approximately 10.9 dB stronger than that by the S-band Doppler radar (SA radar), and 13.7 dB stronger than that by the ground-based cloud radar. The reflectivity measured by the SA radar was 0.4 dB stronger than that by the ground-based cloud radar. This study could provide a method for the quantitative examination of the observation ability for space-based radars.

Radar parameters including radar reflectivity, Doppler velocity, and Doppler spectrum width were obtained from Doppler spectrum moments. The Doppler spectrum moment is the convolution of both the particle spectrum and the mean air vertical motion. Unlike strong precipitation, the motion of particles in cirrus clouds is quite close to the air motion around them. In this study, a method of Doppler moments was developed and used to retrieve cirrus cloud microphysical properties such as the mean air vertical velocity, mass-weighted diameter, effective particle size, and ice content. Ice content values were retrieved using both the Doppler spectrum method and classic Z-IWC (radar reflectivity-ice water content) relationships; however, the former is a more reasonable method.

The errors in radar quantitative precipitation estimations consist not only of systematic biases caused by random noises but also spatially nonuniform biases in radar rainfall at individual rain-gauge stations. In this study, a real-time adjustment to the radar reflectivity-rainfall rates (Z-R) relationship scheme and the gauge-corrected, radar-based, estimation scheme with inverse distance weighting interpolation was developed. Based on the characteristics of the two schemes, the two-step correction technique of radar quantitative precipitation estimation is proposed. To minimize the errors between radar quantitative precipitation estimations and rain gauge observations, a real-time adjustment to the Z-R relationship scheme is used to remove systematic bias on the time-domain. The gauge-corrected, radar-based, estimation scheme is then used to eliminate non-uniform errors in space. Based on radar data and rain gauge observations near the Huaihe River, the two-step correction technique was evaluated using two heavy-precipitation events. The results show that the proposed scheme improved not only in the underestimation of rainfall but also reduced the root-mean-square error and the mean relative error of radar-rain gauge pairs.

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).

The mobile incoherent Doppler lidar (MIDL), which was jointly developed by State Key Laboratory of Severe Weather (LaSW) of the Chinese Academy of Meteorological Sciences (CAMS) and Ocean University of China, provided meteorological services during the Olympic sailing events in Qingdao in 2008. In this study, two experiments were performed based on these measurements. First, the capabilities of MIDL detection of sea-surface winds were investigated by comparing its radial velocities with those from a sea buoy. MIDL radial velocity was almost consistent with sea-buoy data; both reflected the changes in wind with time. However, the MIDL data was 0.5 m s−1 lower on average than the sea-buoy data due to differences in detection principle, sample volume, sample interval, spatial and temporal resolution. Second, the wind fields during the Olympic sailing events were calculated using a four-dimensional variation data assimilation (4DVAR) algorithm and were evaluated by comparing them with data from a sea buoy. The results show that the calculations made with the 4DVAR wind retrieval method are able to simulate the fine retrieval of sea-surface wind data—the retrieved wind fields were consistent with those of sea-buoy data. Overall, the correlation coefficient of wind direction was 0.93, and the correlation coefficient of wind speed was 0.70. The distribution of retrieval wind fields was consistent with that of MIDL radial velocity; the root-mean-square error between them had an average of only 1.52 m s−1.

A long-lived and loosely organized squall line moved rapidly across Urumqi, the capital city of Xinjiang Uygur Autonomous Region of China on 26 June 2005, generating hail and strong winds. The squall line was observed by a dual Doppler radar system in a field experiment conducted in 2004 and 2005 by the Chinese Academy of Meteorological Sciences and the local meteorological bureau in northwestern China. The 3D wind fields within the squall line were retrieved through dual Doppler analyses and a variational Doppler radar analysis system (VDRAS). The formation and structure of the squall line as well as the genesis and evolution of embedded convective cells were investigated. During its life period, the squall line consisted of six storm cells extending about 100 km in length, and produced hail of about 25 mm in diameter and strong surface winds up to 11 m s−1. Radar observations revealed a broad region of stratiform rain in a meso-β cyclone, with the squall line located to the west of this. Two meso-γ scale vortices were found within the squall line. Compared to typical squall lines in moist regions, such as Guangdong Province and Shanghai, which tend to be around 300–400 km in length, have echo tops of 17–19 km, and produce maximum surface winds of about 25 m s−1 and temperature variations of about 8°C this squall line system had weaker maximum reflectivity (55 dBZ), a lower echo top (13 km) and smaller extension (about 100 km), relatively little stratiform rainfall preceding the convective line, and a similar moving speed and temperature variation at the surface.

In mountain areas, radar observations are often contaminated (1) by echoes from high-speed moving vehicles and (2) by point-wise ground clutter under either normal propagation (NP) or anomalous propagation (AP) conditions. Level II data are collected from KMTX (Salt Lake City, Utah) radar to analyze these two types of contamination in the mountain area around the Great Salt Lake. Human experts provide the “ground truth” for possible contamination of either type on each individual pixel. Common features are then extracted for contaminated pixels of each type. For example, pixels contaminated by echoes from high-speed moving vehicles are characterized by large radial velocity and spectrum width. Echoes from a moving train tend to have larger velocity and reflectivity but smaller spectrum width than those from moving vehicles on highways. These contaminated pixels are only seen in areas of large terrain gradient (in the radial direction along the radar beam). The same is true for the second type of contamination-point-wise ground clutters. Six quality control (QC) parameters are selected to quantify the extracted features. Histograms are computed for each QC parameter and grouped for contaminated pixels of each type and also for non-contaminated pixels. Based on the computed histograms, a fuzzy logical algorithm is developed for automated detection of contaminated pixels. The algorithm is tested with KMTX radar data under different (clear and rainy) weather conditions.

The detailed kinematic structure of a heavy rain event that occurred in the middle reaches of the Yangtze River was investigated using dual-Doppler radar observation. A variational analysis method was developed to obtain the three-dimensional wind fields. Before the analysis, a data preprocessing procedure was carried out, in which the temporal variation with the scanning time interval and the effect of the earth curvature on the data position were taken into account. The analysis shows that a shear line in the lower and middle levels played an important role in the rainfall event. The precipitation fell mainly on the south end of the shear line where southerly flow prevailed and convergence and updraft were obvious. With the movement and decay of the shear line, the precipitation moved and decayed correspondingly.