Differential Propagation Phase Research Articles

Analysis of a Rainstorm Process in Nanjing Based on Multi-Source Observational Data and Lagrangian Method

Using multi-source observation data including automatic stations, radar, satellite, new detection equipment, and the Fifth Generation European Centre for Medium-Range Weather Forecasts Reanalysis (ERA-5) data, along with the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) platform, an analysis was conducted on a rainstorm process that occurred in Nanjing on 15 June 2020, with the aim of providing reference for future urban flood control planning and heavy rainfall forecasting and early warning. The results showed that this rainstorm process was generated under the background of an eastward-moving northeast cold vortex and a southward retreat of the Western Pacific Subtropical High. Intense precipitation occurred near the region of large top brightness temperature (TBB) gradient values or the center of low TBB values on the northern side of the convective cloud cluster. During the heavy precipitation period, the differential propagation phase shift rate (KDP), differential reflectivity factor (ZDR), and zero-lag correlation coefficient (ρHV) detected by the S-band dual-polarization radar all increased significantly. The vertical structure of the wind field detected by the wind profile radar provided a good indication of changes in precipitation intensity, showing a strong correspondence between the timing of maximum precipitation and the intrusion of upper-level cold air. The abrupt increase in the integrated liquid water content observed by the microwave radiometer can serve as an important indicator of the onset of stronger precipitation. During the Meiyu season in Nanjing, convective precipitation was mainly composed of small to medium raindrops with diameters less than 3 mm, with falling velocities of raindrops mainly clustering between 2 and 6 m·s−1. The rainstorm process featured four water vapor transport channels: the mid-latitude westerly channel, the Indian Ocean channel, the South China Sea channel, and the Pacific Ocean channel. During heavy rainfall, the Pacific Ocean water vapor channel was the main channel at the middle and lower levels, while the South China Sea water vapor channel was the main channel at the upper level, both accounting for a trajectory proportion of 34.2%.

Improving Estimation of Specific Differential Phase and Assessing Differential Backscattering Phase

Abstract Polarimetric variables such as differential phase ΦDP and its range derivative, specific differential phase KDP, contain useful information for improving quantitative precipitation estimation (QPE) and microphysics retrieval. However, the usefulness of the current operationally utilized estimation method of KDP is limited by measurement error and artifacts resulting from the differential backscattering phase δ. The contribution of δ can significantly influence the ΦDP measurements and therefore negatively affect the KDP estimates. Neglecting the presence of δ within non-Rayleigh scattering regimes has also led to the adoption of incorrect terminology regarding signatures seen within current operational KDP estimates implying associated regions of unrealistic liquid water content. A new processing method is proposed and developed to estimate both KDP and δ using classification and linear programming (LP) to reduce bias in KDP estimates caused by the δ component. It is shown that by applying the LP technique specifically to the rain regions of Rayleigh scattering along a radial profile, accurate estimates of differential propagation phase, specific differential phase, and differential backscattering phase can be retrieved within regions of both Rayleigh and non-Rayleigh scattering. This new estimation method is applied to cases of reported hail and tornado debris, and the LP results are compared to the operationally utilized least squares fit (LSF) estimates. The results show the potential use of the differential backscattering phase signature in the detection of hail and tornado debris.

Processing of weather radar raw IQ-data towards the identification and correction of wind turbine interference – Project RIWER: Removing the Influence of Wind Park Echoes in Weather Radar Measurements

Abstract. In recent years, the fast construction, expansion and repowering of wind parks have been a major source of concern for the weather radar community and meteorological services. Among others because wind turbines are extremely tall, reflective, and moving objects, which make them a source of interference that is hard to distinguish from meteorological echoes and therefore difficult to filter and even more difficult to correct. Polarimetric C-Band Doppler weather radar measurements enable us to analyse and understand the impact of wind turbine interference on meteorological weather radar echoes and to build up knowledge. The main idea is to analyse the raw IQ-data in order to quantify the behaviour of wind turbine interference with meteorological scattering. As a first step in this direction, this paper will focus on the derivation and analysis of radar moments such as Reflectivity (Z), Differential Reflectivity (ZDR), Differential Propagation Phase (PHIDP), Mean Doppler Velocity (V), and Correlation Coefficient (RHOHV). We will consider two cases: (i) events with precipitation, and (ii) events without precipitation, in order to understand and model the impact of wind turbine interference (WTI). For this purpose, weather radar measurements from Deutscher Wetterdienst (DWD), recorded under the aegis of the project RIWER (Removing the Influence of Wind Park Echoes in Weather Radar Measurements), are presented, analysed and discussed in detail.

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.

The Retrieval of Drop Size Distribution Parameters Using a Dual-Polarimetric Radar

The raindrop size distribution (DSD) is vital for applications such as quantitative precipitation estimation, understanding microphysical processes, and validation/improvement of two-moment bulk microphysical schemes. We trace the history of the DSD representation and its linkage to polarimetric radar observables from functional forms (exponential, gamma, and generalized gamma models) and its normalization (un-normalized, single/double-moment scaling normalized). The four-parameter generalized gamma model is a good candidate for the optimal representation of the DSD variability. A radar-based disdrometer was found to describe the five archetypical shapes (from Montreal, Canada) consisting of drizzle, the larger precipitation drops and the ‘S’-shaped curvature that occurs frequently in between the drizzle and the larger-sized precipitation. Similar ‘S’-shaped DSDs were reproduced by combining the disdrometric measurements of small-sized drops from an optical array probe and large-sized drops from 2DVD. A unified theory based on the double-moment scaling normalization is described. The theory assumes the multiple power law among moments and DSDs are scaling normalized by the two characteristic parameters which are expressed as a combination of any two moments. The normalized DSDs are remarkably stable. Thus, the mean underlying shape is fitted to the generalized gamma model from which the ‘optimized’ two shape parameters are obtained. The other moments of the distribution are obtained as the product of power laws of the reference moments M3 and M6 along with the two shape parameters. These reference moments can be from dual-polarimetric measurements: M6 from the attenuation-corrected reflectivity and M3 from attenuation-corrected differential reflectivity and the specific differential propagation phase. Thus, all the moments of the distribution can be calculated, and the microphysical evolution of the DSD can be inferred. This is one of the major findings of this article.

Clear-Air Turbulence (CAT) Identification with X-Band Dual Polarimetric Radar Based on Bayesian Approach

The echo of weather radar is seriously disturbed by clear-air turbulence echo (CAT) which needs identifying and eliminating to improve the data quality of weather radar. Using the data observed with the five X-band dual polarimetric radars in Changping, Fangshan, Miyun, Shunyi, and Tongzhou, Beijing in 2018, the probability density distribution (PDD) of the horizontal texture of four radar moments reflectively factor (ZH), differential reflectivity (ZDR), correlation coefficient (ρHV), differential propagation phase shift (ΦDP), and then the CAT is identified and removed using Bayesian method. The results show that the radar data can be effectively improved after the CAT has been eliminated, which include: (1) the removal rate of CAT is more than 98.2% in the analyzed cases. (2) In the area with high-frequency distribution of CAT, the CAT can be effectively suppressed; in the area with low-frequency distribution, some weather echo in the edge with SNR < 15 dB may be mistakenly identified as CAT, but the proportion of meteorological echoes to the total echoes is more than 85%, which indicate that the error rate is very low and does not affect the radar operation.

Interpretation of the Precipitation Structure Contained in Polarimetric Radio Occultation Profiles Using Passive Microwave Satellite Observations

AbstractObservationally, a major source of uncertainty in evaluation of climate models arises from the difficulty in obtaining globally distributed, fine scale profiles of temperature, pressure and water vapor, that probe through convective precipitating clouds, from the boundary layer to the upper levels of the free troposphere. In this manuscript, a two-year analysis of data from the Radio Occultations through Heavy Precipitation (ROHP) polarimetric RO demonstration mission onboard the Spanish PAZ spacecraft is presented. ROHP measures the difference in the differential propagation phase delay (Δ𝜙) between two orthogonal polarization receive states that is induced from the presence of non-spherically shaped hydrometeors along the Global Navigation Satellite System (GNSS) propagation path, complementing the standard RO thermodynamic profile. Since Δφ is a net path-accumulated depolarization and does not resolve the precipitation structure along the propagation path, orbital coincidences between ROHP and the Global Precipitation Measurement (GPM) constellation passive MW radiometers are identified to provides three-dimensional precipitation context to the RO thermodynamic profile. Passive MW-derived precipitation profiles are used to simulate the Δφalong the ROHP propagation paths. Comparison between the simulated and observed Δφare indicative of the ability of ROHP to detect threshold levels of ray path-averaged condensed water content, as well as to suggest possible inferences on the average ice phase hydrometeor non-sphericity. The use of the polarimetric RO vertical structure is demonstrated as a means to condition the lower tropospheric humidity by the top-most height of the associated convective cloud structure.

Evaluation of KDP Estimation Algorithm Performance in Rain Using a Known-Truth Framework

AbstractAccurate estimation of specific differential phase (KDP) is necessary for rain rate estimation, attenuation correction, and hydrometeor classification algorithms. There are numerous published methods to process polarimetric radar observations of propagation differential phase shift (ΦDP) and estimate KDP, but the corresponding KDP estimate uncertainty is unquantified. This study provides guidance on how commonly used KDP estimation algorithms perform in various environments. We create numerous synthetic (“true”) KDP profiles, integrate over them to obtain “smoothed” ΦDP, and then add noise typical of S-band operational weather radar measurements. Each algorithm is applied to our noisy ΦDP profiles and compared to the true KDP profile such that the errors and uncertainty are quantified. The synthetic KDP profiles are Gaussian in shape, which allows systematic variations in their magnitude and width to determine how each algorithm performs in smooth, slowly changing KDP profiles, as well as steep profiles. Results demonstrate that algorithm performance is dependent on the ΦDP field received. These results are further supported by an error analysis of each algorithm for two more complicated synthetic KDP profiles. Some KDP algorithms allow users to change various tuning parameters; a subset of these tuning parameters is tested to provide guidance on how changing these parameters impacts algorithm performance. We then provide evidence that our known-truth framework provides insight into algorithm performance in observed data through two case studies.

Combining Radar Attenuation and Partial Beam Blockage Corrections for Improved Quantitative Application

AbstractPartial beam blockage (PBB) correction is an indispensable step in weather radar data quality control and subsequent quantitative applications, such as precipitation estimation, especially in urban and/or complex terrain environments. This paper developed a novel PBB correction procedure based on the improved ZPHI method for attenuation correction and regional specific differential propagation phase (KDP)–reflectivity (ZH) relationship derived from in situ raindrop size distribution (DSD) measurements. The practical performance of this PBB correction technique was evaluated through comparing the spatial continuity of reflectivity measurements, the consistency between radar-measured and DSD-derived KDP and ZH relationships, as well as rainfall estimates based on R(ZH) and R(KDP). The results showed that through incorporating attenuation and PBB corrections (i) the spatial continuity of ZH measurements can effectively be enhanced; (ii) the distribution of radar-measured KDP versus ZH is more consistent with the DSD-derived KDP versus ZH; (iii) the measured ZH from a C-band radar in the PBB-affected area becomes more consistent with collocated S-band measurements, particularly in the rainstorm center area where ZH is larger than 30 dBZ; and (iv) rainfall estimates based on R(ZH) in the PBB-affected area are incrementally improved with better spatial continuity and the performance tends to be more comparable with R(KDP).

An Inverse Mapping Table Method for Raindrop Size Distribution Parameters Retrieval Using X-band Dual-Polarization Radar Observations

An inverse mapping table (IMT) method is proposed in this article to retrieve the raindrop size distribution (RSD) parameters from X-band polarimetric weather radar data. In the IMT method, a forward mapping database from three parameters of a gamma-type RSD to polarimetric radar variables is first built based on the scattering simulations under ideal atmospheric conditions, and then an inverse mapping database is derived. In particular, given a fixed shape parameter ( $\mu $ ) of RSD, the intersection of horizontal reflectivity ( $Z_{\text {H}}$ ) and differential reflectivity ( $Z_{\text {DR}}$ ) contour lines is first obtained in the domain of total number concentration ( $N_{\text {T}}$ ) and median volume diameter (MVD) $D_{0}$ ; and the inverse mapping relationship between $Z_{H}$ and $Z_{\text {DR}}$ to $N_{T}$ and $D_{0}$ at a fixed $\mu $ value is derived to form a single layer of IMT. Then, the monotonic relationship between $\mu $ and the specific differential propagation phase shift ( $K_{\text {DP}}$ ) or backscatter differential phase ( $\delta _{\text {CO}}$ ) can aid in determining $\mu $ and a single layer of IMT. Thus, the inverse mapping database from polarimetric observations to the three gamma-type RSD parameters $\mu $ , $N_{\text {T}}$ , and $D_{0}$ can be established. Demonstration studies during a convective rainfall event and a large-scale rainfall event which occurred in northeastern China are carried out to examine the performance of this IMT method compared to a constrained-gamma (C-G) method that uses empirical relations between RSD parameters. The results show that the IMT method has a better performance in the convective case and similar performance in the large-scale continuous rainfall case.

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.

An improved self-consistent approach to attenuation correction for C-band polarimetric radar measurements and its impact on quantitative precipitation estimation

Attenuation correction of measured reflectivity (ZH) and differential reflectivity (ZDR) is critical in short-wavelength radar applications, especially during extreme precipitation events such as heavy rain. This paper develops an improved self-consistent approach (improved ZPHI method) for attenuation correction in practical environment. In particular, a non-negative constraint is imposed on the specific attenuation, which is inferred from the monotonic increasing characteristic of differential propagation phase (ΦDP). The copolar correlation coefficient (ρHV) is used to partition the ΦDP profiles into independent range segments, which are featured by different hydrometeor phases such as liquid rain or mixed-phase precipitation. Additional minimization constraint is imposed on the cost function of the difference between preprocessed ΦDP and reconstructed ΦDPto ensure its appropriate convergence. In addition, an exponential ZDR − ZH relation derived from local raindrop size distribution (DSD) data is applied in the procedure of ZDR correction. Polarimetric measurements from a C-band radar (CPOL) in Hangzhou of China during two extreme precipitation events are used to demonstrate the improved attenuation correction method. DSD observations from disdrometers and radar data from a nearby system operating at non-attenuated frequency (i.e., S-band) at Huangshan Mountain are used to evaluate the attenuation correction performance. This paper also studies the impact of attenuation correction on the radar-derived quantitative precipitation estimation (QPE) product, through cross-comparison with rain gauge observations. Results show that the polarimetric observations from CPOL radar are effectively enhanced and more consistent with collocated S-band measurements and the simulated radar moments based on DSD data. Hourly rainfall products derived from R(ZH) and R(ZH,ZDR) are significantly improved, which are comparable to R(KDP) after attenuation correction.

Improved Estimation of the Specific Attenuation and Backscatter Differential Phase over Short Rain Paths

AbstractIn radar polarimetry, the differential phase consists of the propagation differential phase and the backscatter differential phase . While is commonly used for attenuation correction (i.e., estimation of the specific attenuation A and specific differential phase ), recent studies have demonstrated that can provide information concerning the dominant size of raindrops. However, the estimation of and is not straightforward given their coupled nature and the noisy behavior of , especially over short paths. In this work, the impacts of estimating on the estimation of A over short paths, using the extended version of the ZPHI method, are examined. Special attention is given to the optimization of the parameter α that connects and A. In addition, an improved technique is proposed to compute from and in rain. For these purposes, diverse storm events observed by a polarimetric X-band radar in the Netherlands are used. Statistical analysis based on the minimum errors associated with the optimization of α and the consistency between and A showed that more accurate and stable α and A are obtained if is estimated at range resolution, which is not possible by conventional range filtering techniques. Accurate estimates were able to depict the spatial variability of dominant raindrop size in the observed storms. By following the presented study, the ZPHI method and its variations can be employed without the need for considering long paths, leading to localized and accurate estimation of A and .

Scattering Calculations at C-Band for Asymmetric Raindrops Reconstructed from 2D Video Disdrometer Measurements

AbstractThe distribution of raindrop shapes is well known to be important in deriving retrieval algorithms for drop size distribution parameters (such as the mass-weighted mean diameter) and rain rate, as well as for attenuation correction using the differential propagation phase constraint. While past work has shown that in the vast majority of rain events the most “probable” shapes conform to those arising primarily from the axisymmetric (2,0) oscillation mode, a more recent event analysis has shown that drop collisions can give rise to mixed-mode oscillations and that for high collision rate scenarios, a significant percentage of drops can become “asymmetric” at any given instant.As a follow-up to such studies, this study involved performing scattering calculations for 3D-reconstructed shapes of asymmetric drops using the shape measurements from a 2D video disdrometer (2DVD) during the above-mentioned rain event. A recently developed technique is applied to facilitate the 3D reconstruction from the 2DVD camera data for these asymmetric drops. The reconstruction requires a specific technique to correct for the drop image distortions due to horizontal velocities. Scattering calculations for the reconstructed asymmetric drops have been performed using a higher-order method of moments solution to the electric and magnetic field surface integral equations. Results show that the C-band scattering amplitudes of asymmetric drops are markedly different from those of oblate spheroids. The intention for future studies is to automate the entire procedure so that more realistic simulations can be performed using the 2DVD-based data, particularly for cases where collision-induced drop oscillations give rise to considerable numbers of asymmetric drops.

Insights into the Evolving Microphysical and Kinematic Structure of Northeastern U.S. Winter Storms from Dual-Polarization Doppler Radar

The recent Weather Surveillance Radar-1988 Doppler (WSR-88D) network upgrade to dual-polarization capabilities allows for bulk characterization of microphysical processes in northeastern U.S. winter storms for the first time. In this study, the quasi-vertical profile (QVP) technique (wherein data from a given elevation angle scan are azimuthally averaged and the range coordinate is converted to height) is extended and applied to polarimetric WSR-88D observations of six Northeast winter storms to survey their evolving, bulk vertical microphysical and kinematic structures. These analyses are supplemented using hourly analyses from the Rapid Refresh (RAP) model. Regions of ascent inferred from QVPs were consistently associated with notable polarimetric signatures, implying planar crystal growth when near −15°C, and riming and secondary ice production at higher temperatures. The heaviest snowfall occurred most often when ascent and enhanced propagation differential phase shift ([Formula: see text]) occurred near −15°C. When available, limited surface observations confirmed heavy snowfall rates and revealed large snow-to-liquid ratios at these times. Other cases revealed sudden, large melting-layer excursions associated with precipitation-type transitions near the surface. RAP analyses failed to capture such complex evolution, demonstrating the added value of dual-polarization radar observations in these scenarios and the potential use of radar data for assessing model performance in real time. These insights are a preliminary step toward better understanding the complex processes in northeastern U.S. winter storms.

An Examination of Precipitation Using CSU–CHILL Dual-Wavelength, Dual-Polarization Radar Observations

AbstractThe CSU–CHILL radar is a dual-wavelength, dual-polarization weather radar system operating at S and X bands with coaxial beams. One of the capabilities of this radar system is the possibility of developing and/or validating algorithms across dual wavelengths and dual polarizations. This paper presents one such instance, showing how the rainfall field can be estimated either from the S- and X-band reflectivities or from the differential propagation phase at X band. To do so, the paper first presents a dual-wavelength attenuation correction method that uses the reflectivity measured at S band, as the constraint for the correction of the reflectivity measured at X band, and it describes how Mie scattering regions at X band may be detected from the retrieved path-integrated attenuation field. Then, the paper describes how the resulting specific attenuation field relates to rainfall and specific phase at X band, which can be obtained from dual-polarization data at a single wavelength as well, and shows examples. Finally, the paper looks at the relation between attenuation and the differential phase as a function of elevation angle for a few cases, which may be related to the drop size distribution and mean diameter, as well as temperature.

Identification of Range Overlaid Echoes Using Polarimetric Radar Measurements Based on a Fuzzy Logic Approach

AbstractThe Ministry of Land, Infrastructure and Transport (MOLIT) of South Korea operates two S-band dual-polarimetric radars, as of 2013, to manage water resources through quantitative rainfall estimations at the surface level. However, the radar measurements suffer from range ambiguity. In this study, an algorithm based on fuzzy logic is developed to identify range overlaid echoes using seven inputs: standard deviations of differential reflectivity SD(ZDR), differential propagation phase SD(ϕDP), correlation coefficient SD(ρHV) and spectrum width SD(συ), mean of ρHV and συ, and difference of ϕDP from the system offset ΔϕDP. An examination of the algorithm’s performance shows that these echoes can be well identified and that echoes strongly affected by second trip are highlighted by high probabilities, over 0.6; echoes weakly affected have probabilities from 0.4 to 0.6; and those with low probabilities, below 0.4, are assigned as echoes without range ambiguity. A quantitative analysis of a limited number of cases using the usual skill scores shows that when the probability of 0.4 is considered as a threshold for identifying the range overlaid echoes, they can be identified with a probability of detection of 90%, a false alarm rate of 6%, and a critical success index of 84%.

X-Band Polarimetric and Ka-Band Doppler Spectral Radar Observations of a Graupel-Producing Arctic Mixed-Phase Cloud

AbstractCharacteristics of graupel in an Arctic deep mixed-phase cloud on 7 December 2013 were identified with observations from an X-band scanning polarimetric radar and a Ka-band zenith-pointing radar in conjunction with scattering calculations. The cloud system produced generating cells and strongly sheared precipitation fall streaks. The X-band radar hemispheric RHI observables revealed spatial sorting of polarimetric signatures: decreasing (with increasing range) differential propagation phase shift φDP, negative specific differential phase KDP collocated with negative differential reflectivity ZDR in the upper half of the fall streak, and increasing or near-constant φDP with positive ZDR at the bottom edge of the fall streak. The negative KDP and ZDR, indicating prolate particles with vertically oriented maximum dimensions, were consistent with small, slow-falling conical graupel coexisting with low concentrations of more isometric graupel. The observed negative KDP values were best matched by scattering calculations for small, dense conical graupel with 30°–40° cone angles. The positive KDP and ZDR and the Doppler spectra indicate that large isometric graupel coexisted with a second population of slower-falling rimed platelike particles in the lower half of the fall streak. Through the core of the fall streak, φDP decreased in range while ZDR was slightly positive, indicating that the prolate conical graupel dominated φDP while the isometric larger graupel dominated reflectivity (and thus ZDR). These results demonstrate the capability of polarimetric observables and Doppler spectra to distinguish different growth stages of rimed particles, allowing for the improvement of hydrometeor classification methods.

Polarimetric rainfall retrieval from a C-Band weather radar in a tropical environment (The Philippines)

We evaluated the potential of polarimetric rainfall retrieval methods for the Tagaytay C-Band weather radar in the Philippines. For this purpose, we combined a method for fuzzy echo classification, an approach to extract and reconstruct the differential propagation phase, Φ DP , and a polarimetric self-consistency approach to calibrate horizontal and differential reflectivity. The reconstructed Φ DP was used to estimate path-integrated attenuation and to retrieve the specific differential phase, K DP . All related algorithms were transparently implemented in the Open Source radar processing software wradlib. Rainfall was then estimated from different variables: from re-calibrated reflectivity, from re-calibrated reflectivity that has been corrected for path-integrated attenuation, from the specific differential phase, and from a combination of reflectivity and specific differential phase. As an additional benchmark, rainfall was estimated by interpolating the rainfall observed by rain gauges. We evaluated the rainfall products for daily and hourly accumulations. For this purpose, we used observations of 16 rain gauges from a five-month period in the 2012 wet season. It turned out that the retrieval of rainfall from K DP substantially improved the rainfall estimation at both daily and hourly time scales. The measurement of reflectivity apparently was impaired by severe miscalibration while K DP was immune to such effects. Daily accumulations of rainfall retrieved from K DP showed a very low estimation bias and small random errors. Random scatter was, though, strongly present in hourly accumulations.

Applications of wavelet analysis in differential propagation phase shift data de-noising

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.