X-band Dual-polarization Radar Research Articles

The Macro- and Microphysical Response Characteristics of the Multicell Hailstorm Hail-Suppression Operation: Case Study

Abstract This study analyzed the macro- and microphysical response characteristics of a typical multicell hailstorm after seeding on 27 April 2019 in Weining, China, using X-band dual-polarization radar (YLD1-D) data. An improved X-pol hydrometeor identification algorithm was employed for hydrometeor identification. According to the diffusion of the seeding agents, the seeded hailstorm was graded into three study regions, and the evolution of the seeded hailstorm was divided into four periods. The response characteristics of the seeded hailstorm in each region and period were compared and analyzed. The results show that 1) macroscopically, the decrease in the reflectivity and the height of strong echo mainly occurred in the seeded period, whereas the decrease in the echo top and the height of the storm was mainly in the postseeded period; the echo height variation of the unseeded hailstorm is obviously different from that of the seeded hailstorm; and 2) from the microscopic perspective, the decrease in low-density graupel and supercooled water and the increase in ice crystals and aggregates in the seeded region mainly occurred in the seeded period, which was consistent with the time required for the “benefit competition” after the silver iodide completed nucleation. When compared with the seeded region, the hydrometeors in the unseeded region had an opposite trend (or an in-phase trend with an obviously lower changing rate), which further indicated the impact of the artificial ice nuclei on microphysical processes in the seeded region. For hailstorms with a high content of supercooled droplets and graupel, the key mechanisms of hail suppression are “cloud water glaciation,” “beneficial competition,” and “early rainout.”

Study on the Backscatter Differential Phase Characteristics of X-Band Dual-Polarization Radar and its Processing Methods

The differential propagation phase (ΦDP) of X-band dual-polarization weather radar (including X-band dual-polarization phased-array weather radar, X-PAR) is important for estimating precipitation and classifying hydrometeors. However, the measured differential propagation phase contains the backscatter differential phase (δ), which poses difficulties for the application of the differential propagation phase from X-band radars. This paper presents the following: (1) the simulation and characteristics analysis of the backscatter differential phase based on disdrometer DSD (raindrop size distribution) measurement data; (2) an improved method of the specific differential propagation phase (KDP) estimation based on linear programming and backscatter differential phase elimination; (3) the effect of backscatter differential phase elimination on the specific differential propagation phase estimation of X-PAR. The results show the following: (1) For X-band weather radar, the raindrop equivalent diameters D > 2 mm may cause a backscatter differential phase between 0 and 20°; in particular, the backscatter differential phase varies sharply with raindrop size between 3.2 and 4.5 mm. (2) Using linear programming or smoothing filters to process the differential propagation phase could suppress the backscatter differential phase, but it is hard to completely eliminate the effect of the backscatter differential phase. (3) Backscatter differential phase correction may improve the calculation accuracy of the specific differential propagation phase, and the optimization was verified by the improved self-consistency of polarimetric variables, correlation between specific differential propagation phase estimations from S- and X-band radar and the accuracy of quantitative precipitation estimation. The X-PAR deployed in Shenzhen showed good observation performance and the potential to be used in radar mosaics with S-band weather radar.

Retrieval of microphysical parameters of monsoonal rain using X-band dual-polarization radar: their seasonal dependence and evaluation

Abstract. Multiyear measurements from a Joss–Waldvogel disdrometer (5 years) and X-band dual-polarization radar (2 years) made at Gadanki (13.5∘ N, 79.18∘ E), a low-latitude station, are used to (i) retrieve appropriate raindrop size distribution (DSD) relations for monsoonal rain, (ii) understand their dependency on temperature, the raindrop size shape model and season and (iii) assess polarimetric radar DSD retrievals by various popular techniques (the exponential (Exp), constrained Gamma (CG), normalized Gamma (N-Gamma) and β methods). The coefficients obtained for different DSD relations for monsoonal rain are found to be different from those of existing relations elsewhere. The seasonal variation in DSD is quite large and significant, and as a result, the coefficients also vary considerably between the seasons. The slope of the drop size–shape relation, assumed to be constant in several studies, varies considerably between the seasons, with warmer seasons showing a smaller slope value than the cold season. It is found that the constant (0.062) used in linear drop shape models is valid only for the cold season. The derived coefficients for the CG method for different seasons coupled with those available in the literature reveal that the warm seasons/regions typically have larger curvature and slope values than in the cold seasons/regions. The coefficients of the mass-weighted mean diameter (Dm) and differential reflectivity (ZDR) exhibit a strong dependency on the drop shape model, while those for the derivation intercept parameter exhibit a strong seasonal dependency. Using the retrieved relations and X-band polarimetric radar at Gadanki, four popular DSD methods are evaluated against disdrometer measurements collected over 12 events. All the methods estimated Dm reasonably well with the small root mean square error but failed to estimate the intercept parameter accurately. Only the N-gamma method estimated the normalized intercept parameter reasonably. Problems associated with specific differential-phase (KDP)-based estimates close to the radar location, particularly during overhead convection, are also discussed.

Comparison and Analysis of X-Band Dual Linear Polarization Radar Observations

Comparison and Analysis of X-Band Dual Linear Polarization Radar Observations

Raindrop Size Distribution Retrieval Model for X-Band Dual-Polarization Radar in China Incorporating Various Climatic and Geographical Elements

The X-band dual-polarization radar can provide raindrop size distribution (DSD) data at a continuous spatiotemporal scale; however, the traditional empirical-formula-based DSD retrieval methods for X-band radar are limited by high uncertainty and poor generality such as differences due to rainfall type, seasons, and geographical environment. This study identified strong correlations between polarimetric radar variables and various climatic and geographical elements. Two random-forest-based DSD retrieval models, one using only X-band radar parameters as the model input (RF-DSD) and the other containing multielement inputs as well (RF-M-DSD), were established using datasets from 18 sites in China. This study also evaluated the proposed models using different error indices over three test sites. Compared with the traditional DSD retrieval model for X-band dual-polarization radar, RF-DSD and RF-M-DSD showed improved predictive ability for all DSD parameters. The root-mean-square error (RMSE) values for <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$D_{0}$ </tex-math></inline-formula> (median volume diameter parameter), <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${\text {log}}_{10}N_{w}$ </tex-math></inline-formula> (normalized intercept parameter), and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu $ </tex-math></inline-formula> (shape parameter) were 27%, 55%, and 39% lower, respectively, for RF-DSD, and 48%, 68%, and 43% lower, respectively, for RF-M-DSD. Finally, the DSD retrieval models were applied on one CLA-12A X-band radar in the Jiangsu Province. The DSD retrieval results suggest that the proposed models perform well on radar observation data with low uncertainty especially for <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$D_{0}$ </tex-math></inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${\text {log}}_{10}N_{w}$ </tex-math></inline-formula> . Summary reveals that the RF-M-DSD performs superior and has stable DSD retrieval capabilities across different geographical areas, which can provide reliable radar-DSD retrieval data for areas with scarce disdrometer data.

Analyzing the Application of X-Band Radar for Improving Rainfall Observation and Flood Forecasting in Yeongdong, South Korea

The mountainous Yeongdong region of South Korea contains mountains over 1 km. Owing to this topographic blockage, the region has a low-density rain-gauge network, and there is a low-altitude (~1.5 km) observation gap with the nearest large S-band radar. The Korean government installed an X-band dual-polarization radar in 2019 to improve rainfall observations and to prevent hydrological disasters in the Yeongdong region. The present study analyzed rainfall estimates using the newly installed X-band radar to evaluate its hydrological applicability. The rainfall was estimated using a distributed specific differential phase-based technique for a high-resolution 75 m grid. Comparison of the rainfall estimates of the X-band radar and the existing rainfall information showed that the X-band radar was less likely to underestimate rainfall compared to the S-band radar. The accuracy was particularly high within a 10 km observation radius. To evaluate the hydrological applicability of X-band radar rainfall estimates, this study developed a rain-based flood forecasting method—the flow nomograph—for the Samcheok-osib stream, which is vulnerable to heavy rain and resultant floods. This graph represents the flood risk level determined by hydrological–hydraulic modeling with various rainfall scenarios. Rainfall information (X-band radar, S-band radar, ground rain gauge) was applied as input to the flow nomograph to predict the flood level of the stream. Only the X-band radar could accurately predict the actual high-risk increase in the water level for all studied rainfall events.

Hydrometeor Classification of Winter Precipitation in Northern China Based on Multi-Platform Radar Observation System

Hydrometeor classification remains a challenge in winter precipitation cloud systems. To address this issue, 42 snowfall events were investigated based on a multi-platform radar observation system (i.e., X-band dual-polarization radar, Ka-band millimeter wave cloud radar, microwave radiometer, airborne equipment, etc.) in the mountainous region of northern China from 2016 to 2020. A fuzzy logic classification method is proposed to identify the particle phases, and the retrieval result was further verified with ground-based radar observation. Moreover, the hydrometeor characteristics were compared with the numerical simulations to clarify the reliability of the proposed hydrometeor classification approach. The results demonstrate that the X-/Ka- band radars are capable of identifying hydrometeor phases in winter precipitation in accordance with both ground observations and numerical simulations. Three particle categories, including snow, graupel and the mixture of snow and graupel are also detected in the winter precipitation cloud system, and there are three vertical layers identified from top to bottom, including the ice crystal layer, snow-graupel mixed layer and snowflake layer. Overall, this study has the potential for improving the understanding of microphysical processes such as freezing, deposition and aggregation of ice crystal particles in the winter precipitation cloud system.

Multivariate Analysis and Warning of a Tornado Embedded in Tropical Cyclone in Southern China

An EF1 tornado associated with tropical cyclone (TC) Ewiniar hit Dali Town, Foshan, Guangdong Province at 06:03 UTC on June 8, 2018, and the first special tornado warning was issued to five towns at 05:05 UTC. This paper utilizes minute- scale observations from an X-band dual-polarization radar and measurements from an S-band Doppler radar to resolve the polarization characteristics associated with this tornado. In addition, second-scale atmospheric pressure data obtained from micropressure gauge and NCEP FNL (Final) Operational Global Analysis data are used to investigate the synoptic conditions and features of gravity waves (GWs). The conspicuous features of the descending reflectivity core, Doppler velocity couplet, ZDR arc, KDP foot, and the separation of the ZDR arc and KDP foot are detailed to quantify the tornadic evolution. The amplitude fluctuation of the GWs suddenly increased to 77.3 Pa two hours before the tornado occurred. Two focus regions with KDP values greater than 6/km are discussed by combining the Doppler velocity couplet and ZDR arc. The separation distance of the ZDR arc and KDP foot was approximately 2.1 km. The appearance of these features may be indicative of fundamental processes intrinsic to tornado storms.

An improved hydrometeor identification method for X-band dual-polarization radar and its application for one summer Hailstorm over Northern China

Currently, high-resolution severe storm observations obtained by vehicle-mounted mobile X-band dual-polarization radar (X-pol) are widely used in severe storm structure and dynamics studies; however, the identification of hailstones based on X-pol is still rare, leading to the limited application of X-pol in identifying hydrometeors in the microphysical processes of severe storms. Based on previous works, this study constructs an improved X-pol hydrometeor identification (HID) method for hailstorms; the hydrometeor categories include a rain-hail mixtures (RH) category indicating hailstones are melting or experiencing wet growth, and the correlation coefficient between horizontally and vertically polarized echoes (ρHV) is used to locate the local mixed phase region in storms to avoid misclassifications of hydrometeors resulted by environmental temperature in this local mixed phase region. The improved HID method can see liquid water information above the melting layer; it provides a possibility to observe the microphysical process of hailstones wet growth above the melting layer. Furthermore, this improved HID method was utilized to study the high spatiotemporal resolution data collected by the Institute of Atmospheric Physics of Chinese Academy of Sciences (IAP) X-pol for one summer hailstorm over northern China. The results indicate that the identified RH is consistent with the surface hail record of National weather observatory of China Meteorological Administration (CMA), the specific differential phase (KDP) column is more sensitive than the differential reflectivity (ZDR) column for indicating the updraft zone movement, and we considered that the relative position between the key area of hail (KAH, where above the ZDR column, ZDR ~ −2 to 0 dB, ZH ~ ≥ 50 dBZ) and the updraft zone (indicated by the ZDR, KDP column) will determine the evolution of hail. Furthermore, high-density graupels (HDGs) in the upper layer of the KAH may be the source of RH embryos, and these HDGs collect liquid droplets from the liquid water-rich (LWR) area located behind the KAH to form a large number of RH in the lower layer of the KAH. These characteristics are important for hailstone forecasting and warnings.

Operation Techniques and Hydrological Applications of X-band Dual-polarization Radar for Monitoring Flash Flood in Metropolitan Area

Radar is useful for monitoring flash flood in urban areas because it provides rainfall data with high spatial and temporal resolution for a wide area. In 2014, the Korea Institute of Civil Engineering and Building Technology introduced the first X-band dual-polarization radar in Korea and has subsequently been researching on flash floods in the metropolitan area using the rainfall data. Considering the various advantages of X-band dual-polarization radar, the Water Hazard Information Platform in Korea introduced two X-band dual-polarization radars (KRU and YSU radars) into the metropolitan area, in 2017. This study described the characteristics of KRU and YSU radars, their observation strategies, and quality control techniques. Moreover, we also assessed the hydrological applications of the X-band dual-polarization radars in the metropolitan area by analyzing three years of rainfall data from 2017 to 2019.

The Quality Control and Rain Rate Estimation for the X-Band Dual-Polarization Radar: A Study of Propagation of Uncertainty

In this study, the specific differential phase ( K d p ) is applied to attenuation correction for radar reflectivity Z H and differential reflectivity Z D R , and then the corrected Z H , Z D R , and K d p are studied in the rain rate (R) estimation at the X-band. The statistical uncertainties of Z H , Z D R , and R are propagated from the uncertainty of K d p , leading to variability in their error characteristics. For the attenuation correction, a differential phase shift ( Φ d p )-based method is adopted, while the statistical uncertainties σ ( Z H ) and σ ( Z D R ) are related to σ ( K d p ) via the relations of K d p -specific attenuation ( A H ) and K d p -specific differential attenuation ( A D P ), respectively. For the rain rate estimation, the rain rates are retrieved by the power-law relations of R ( K d p ) , R ( Z h ) , R ( Z h , Z d r ) , and R ( Z h , Z d r , K d p ) . The statistical uncertainty σ ( R ) is propagated from Z H , Z D R , and K d p via the Taylor series expansion of the power-law relations. A composite method is then proposed to reduce the σ ( R ) effect. When compared to the existing algorithms, the composite method yields the best performance in terms of root mean square error and Pearson correlation coefficient, but shows slightly worse normalized bias than R ( K d p ) and R ( Z h , Z d r , K d p ) . The attenuation correction and rain rate estimation are evaluated by analyzing a squall line event and a prolonged rain event. It is clear that Z H , Z D R , and K d p show the storm structure consistent with the theoretical model, while the statistical uncertainties σ ( Z H ) , σ ( Z D R ) and σ ( K d p ) are increased in the transition region. The scatterplots of Z H , Z D R , and K d p agree with the self-consistency relations at X-band, indicating a fairly good performance. The rain rate estimation algorithms are also evaluated by the time-series of the prolonged rain event, yielding strong correlations between the composite method and rain gauge data. In addition, the statistical uncertainty σ ( R ) is propagated from Z H , Z D R , and K d p , showing higher uncertainty when the large gradient presents.

Integrated Correction Algorithm for X Band Dual-Polarization Radar Reflectivity Based on CINRAD/SA Radar

The values of ratio a of the linear relationship between specific attenuation and specific differential phase vary significantly in convective storms as a result of resonance scattering. The best-linear-fit ratio a at X band is determined using the modified attenuation correction algorithm based on differential phase and attenuation, as well as the premise that reflectivity is unattenuated in S band radar detection. Meanwhile, the systemic reflectivity bias between the X band radar and S band radar and water layer attenuation (ZW) on the wet antenna cover of the X band radar are also considered. The good performance of the modified correction algorithm is demonstrated in a moderate rainfall event. The data were collected by four X band dual-polarization (X-POL) radar sites, namely, BJXCP, BJXFS, BJXSY, and BJXTZ, and a China’s New Generation Weather Radar (CINRAD/SA radar) site, BJSDX, in Beijing on 20 July 2016. Ratio a is calculated for each volume scan of the X band radar, with a mean value of 0.26 dB deg−1 varying from 0.20 to 0.31 dB deg−1. The average values of systemic reflectivity bias between the X band radar (at BJXCP, BJXFS, BJXSY, and BJXTZ) and S band radar (at BJSDX) are 0, −3, 2, and 0 dB, respectively. The experimentally determined ZW is in substantial agreement with the theoretically calculated ones, and their values are an order of magnitude smaller than rain attenuation. The comparison of the modified attenuation correction algorithm and the empirical-fixed-ratio correction algorithm is further evaluated at the X-POL radar. It is shown that the modified attenuation correction algorithm in the present paper provides higher correction accuracy for rain attenuation than the empirical-fixed-ratio correction algorithm.

Melting Layer Detection and Characterization based on Range Height Indicator–Quasi Vertical Profiles

The melting layer (ML) is an important region used to describe the transition of hydrometeors from the solid to the liquid phase. It is a typical feature used to characterize the vertical structure of the stratiform precipitation. The present study implements a new automatic melting-layer detection algorithm based on the range-height-indicator–quasi-vertical profile (R-QVP) in the X-band dual-polarization radars. The algorithm uses the gradients of the polarimetric radar variables reflectivity factor at horizontal polarization (Zh), differential reflectivity (Zdr), and copolar correlation coefficient (ρhv), and their combinations to describe the ML characteristics. The melting layer heights derived from the radar were compared and validated with the heights of the 0 °C wet-bulb temperature derived from the Modern-Era retrospective analysis for research and applications (MERRA) reanalysis datasets and obtained high correlation coefficient 0.96. The R-QVP combined with this algorithm led to spatial and temporal variabilities of the melting layer thickness. The thickness of the melting layer was independent of the seasonal, spatial, and temporal variabilities of the precipitations. Intriguing polarimetric signatures have been observed inside, above, and below the ML, based on the phase of the precipitation particles. The statistics of the polarimetric variables were evaluated for ML, rain, and snow. Further, the linkage between enhanced specific differential phase shift (Kdp) and Zdr in the dendritic growth layer (DGL) and surface precipitation was also described.

A Gaussian mixture method for specific differential phase retrieval at X-band frequency

Abstract. The specific differential phase Kdp is one of the most important polarimetric radar variables, but the variance σ2(Kdp), regarding the errors in the calculation of the range derivative of the differential phase shift Φdp, is not well characterized due to the lack of a data generation model. This paper presents a probabilistic method based on the Gaussian mixture model for Kdp estimation at X-band frequency. The Gaussian mixture method can not only estimate the expected values of Kdp by differentiating the expected values of Φdp, but also obtain σ2(Kdp) from the product of the square of the first derivative of Kdp and the variance of Φdp. Additionally, the ambiguous phase and backscattering differential phase shift are corrected via the mixture model. The method is qualitatively evaluated with a convective event of a bow echo observed by the X-band dual-polarization radar in the University of Missouri. It is concluded that Kdp estimates are highly consistent with the gradients of Φdp in the leading edge of the bow echo, and large σ2(Kdp) occurs with high variation of Kdp. Furthermore, the performance is quantitatively assessed by 2-year radar–gauge data, and the results are compared to linear regression model. It is clear that Kdp-based rain amounts have good agreement with the rain gauge data, while the Gaussian mixture method gives improvements over the linear regression model, particularly for far ranges.

X-Band Dual-Polarization Radar Observations of Snow Growth Processes of a Severe Winter Storm: Case of 12 December 2013 in South Korea

AbstractThe characteristics of microphysical processes of a severe winter storm that occurred on the Korean Peninsula on 12 December 2013 was studied in this work for the first time via X-band dual-polarization weather radar observations. A new range–height indicator (RHI) scan-based quasi-vertical profile methodology, in which polarimetric radar variables were averaged at each height of the RHI scan, was introduced to investigate the snow microphysics, and the obtained polarimetric radar signatures served as fingerprints of the dendritic growth, aggregation, and riming processes. Enhanced differential reflectivity (Zdr) and specific differential phase shift (Kdp) bands were detected near the −15°C isotherm, which signified the growth of dendrites or platelike crystals. The observed correlation between the increases in the reflectivity factor at horizontal polarization Zh and copolar correlation coefficient ρhv and the decreases in Zdr and Kdp magnitudes at lower heights suggested the occurrence of the aggregation process. The combination of high Zh and low Zdr values with turbulent atmospheric conditions observed at the ground level indicated the occurrence of the riming process. In addition, the negative Kdp and Zdr values combined with high Zh and ρhv magnitudes (observed near the end of the snow event) indicated the formation of graupel particles. The polarimetric radar signatures obtained for the snow growth processes were evident from ground observations and agreed well with the results of the Weather Research and Forecasting Model and Modern-Era Retrospective Analysis for Research and Applications data. Furthermore, the spatial variability of Zh methodology was implemented to describe both aggregates and rimed ice particles.

Monitoring wildfire using high-resolution compact X-band dual-polarization radar: A case study in southern China

Weather radar has demonstrated the ability to monitor wildfires and associated smoke plumes. However, the long-range, S-band operational radar network has severe limitations in providing high-resolution observations in the lower atmosphere due to the earth curvature. This paper presents an innovative technique of using shorter-range, low-power, fast scanning X-band radar for monitoring wildfires. Sample observations from wildfire events in southern China show that the polarimetric radar correlation coefficient of wildfire echoes varies from 0.55 to 0.75, with an average value of 0.61; the differential reflectivity varies from 2.28 to 5.08 dB with an average value of 3.99 dB; the differential propagation phase varies from 40.27° to 69.27°, with an average value of 56.66°; and all observables exhibit subtle changes at different scanning elevation angles. In addition, changes in echo intensity observed by higher elevation scans lag behind those observed by lower elevation scans, and the change of wildfire area lags behind the variation of echo intensity. Given the emerging interest in deploying such compact, cheaper X-band systems for urban hydrometeorological applications, it is expected that these radars, customized with flexible scan strategy, will provide new opportunities and advantages in wildfire detection and mitigation.

A Multi-Platform Hydrometeorological Analysis of the Flash Flood Event of 15 November 2017 in Attica, Greece

Urban areas often experience high precipitation rates and heights associated with flash flood events. Atmospheric and hydrological models in combination with remote-sensing and surface observations are used to analyze these phenomena. This study aims to conduct a hydrometeorological analysis of a flash flood event that took place in the sub-urban area of Mandra, western Attica, Greece, using remote-sensing observations and the Chemical Hydrological Atmospheric Ocean Wave System (CHAOS) modeling system that includes the Advanced Weather Research Forecasting (WRF-ARW) model and the hydrological model (WRF-Hydro). The flash flood was caused by a severe storm during the morning of 15 November 2017 around Mandra area resulting in extensive damages and 24 fatalities. The X-band dual-polarization (XPOL) weather radar of the National Observatory of Athens (NOA) observed precipitation rates reaching 140 mm/h in the core of the storm. CHAOS simulation unveils the persistent orographic convergence of humid southeasterly airflow over Pateras mountain as the dominant parameter for the evolution of the storm. WRF-Hydro simulated the flood using three different precipitation estimations as forcing data, obtained from the CHAOS simulation (CHAOS-hydro), the XPOL weather radar (XPOL-hydro) and the Global Precipitation Measurement (GMP)/Integrated Multi-satellitE Retrievals for GPM (IMERG) satellite dataset (GPM/IMERG-hydro). The findings indicate that GPM/IMERG-hydro underestimated the flood magnitude. On the other hand, XPOL-hydro simulation resulted to discharge about 115 m3/s and water level exceeding 3 m in Soures and Agia Aikaterini streams, which finally inundated. CHAOS-hydro estimated approximately the half water level and even lower discharge compared to XPOL-hydro simulation. Comparing site-detailed post-surveys of flood extent, XPOL-hydro is characterized by overestimation while CHAOS-hydro and GPM/IMERG-hydro present underestimation. However, CHAOS-hydro shows enough skill to simulate the flooded areas despite the forecast inaccuracies of numerical weather prediction. Overall, the simulation results demonstrate the potential benefit of using high-resolution observations from a X-band dual-polarization radar as an additional forcing component in model precipitation simulations.

Polarimetric Radar Signatures of a Rare Tornado Event over South Korea

AbstractThe Korea Institute of Civil Engineering and Building Technology (KICT) made one of the first radar observations of a rare tornadic storm that occurred on 10 June 2014 in the Seoul metropolitan region, South Korea, using X-band dual-polarization radar. The tornado lasted for about 18 min, during which it destroyed about 20 greenhouses and injured several people. This tornado was rated at F0 on the Fujita scale. The KICT X-band dual-polarization radar was installed in the area northwest of Seoul to monitor storm development, measure rainfall, improve hazard mitigation, and disaster management. This paper presents the high-resolution (both spatial and temporal) polarimetric radar observations of the tornado, along with the radar parameters of reflectivity, differential reflectivity, Doppler velocity, and copolar correlation coefficient. The characteristic signatures of polarimetric variables, including the descending reflectivity core, weak echo hole, Doppler velocity couplet, and hook echo, are used to describe the tornado vortex and its development. In addition, the close range (about 5-km distance) observations of the hook echo show the high-resolution radar signatures of a weak echo region surrounded by high-reflectivity annular rings inside the tornado vortex. From development to dissipation, various finescale features are observed, including lofted tornadic debris and potential hail signatures. The high-resolution (close range) observations were also compared against low-resolution (long range) radar observations. The comparison shows that high-spatiotemporal, low-altitude, and close-range observations can be significantly advantageous for tornado detection and early warning.

Characteristic Analysis of the Downburst in Greely, Colorado on 30 July 2017 Using WPEA Method and X-Band Radar Observations

As a manifestation of low-altitude wind shear, a downburst is a localized, strong downdraft that can lead to disastrous wind on the ground surface. For effective pre-warning and forecasting of downbursts, it is particularly critical to understand relevant weather features that occur before and during a downburst process. It is important to identify the macroscopic features associated with the downburst weather process before considering fine-scale observations because this would greatly increase the accuracy and timeliness of forecasts. Therefore, we applied the wind-vector potential-temperature energy analysis (WPEA) method and CSU-CHILL X-band dual-polarization radar to explore the features of the downburst process. Here it was found that prior to the occurrence of the downburst of interest, the specific areas that should be monitored in future events could be determined by studying the atmospherically unstable areas using the WPEA method. Combining the WPEA method with dual-polarization radar observations, we can better distinguish the phase distribution of the hydrometeor in the process and greatly enhance the judgment of the possibility of the downburst. From exploration of the microphysical features of the downburst, we further found that ‘Zdr (differential reflectivity) column’ can be regarded as an important early warning indicator of the location of the downburst. Finally, a schematic of the formation process of the downburst according to the analyses was produced.

Advancing Precipitation Estimation and Streamflow Simulations in Complex Terrain with X-Band Dual-Polarization Radar Observations

In mountain basins, the use of long-range operational weather radars is often associated with poor quantitative precipitation estimation due to a number of challenges posed by the complexity of terrain. As a result, the applicability of radar-based precipitation estimates for hydrological studies is often limited over areas that are in close proximity to the radar. This study evaluates the advantages of using X-band polarimetric (XPOL) radar as a means to fill the coverage gaps and improve complex terrain precipitation estimation and associated hydrological applications based on a field experiment conducted in an area of Northeast Italian Alps characterized by large elevation differences. The corresponding rainfall estimates from two operational C-band weather radar observations are compared to the XPOL rainfall estimates for a near-range (10–35 km) mountainous basin (64 km2). In situ rainfall observations from a dense rain gauge network and two disdrometers (a 2D-video and a Parsivel) are used for ground validation of the radar-rainfall estimates. Ten storm events over a period of two years are used to explore the differences between the locally deployed XPOL vs. longer-range operational radar-rainfall error statistics. Hourly aggregate rainfall estimates by XPOL, corrected for rain-path attenuation and vertical reflectivity profile, exhibited correlations between 0.70 and 0.99 against reference rainfall data and 21% mean relative error for rainfall rates above 0.2 mm h−1. The corresponding metrics from the operational radar-network rainfall products gave a strong underestimation (50–70%) and lower correlations (0.48–0.81). For the two highest flow-peak events, a hydrological model (Kinematic Local Excess Model) was forced with the different radar-rainfall estimations and in situ rain gauge precipitation data at hourly resolution, exhibiting close agreement between the XPOL and gauge-based driven runoff simulations, while the simulations obtained by the operational radar rainfall products resulted in a greatly underestimated runoff response.