Dual-polarization Doppler Radar Research Articles

P-Type Processes and Predictability: The Winter Precipitation Type Research Multiscale Experiment (WINTRE-MIX)

Abstract During near-0°C surface conditions, diverse precipitation types (p-types) are possible, including rain, drizzle, freezing rain, freezing drizzle, ice pellets, wet snow, snow, and snow pellets. Near-0°C precipitation affects wide swaths of the United States and Canada, impacting aviation, road transportation, power generation and distribution, winter recreation, ecology, and hydrology. Fundamental challenges remain in observing, diagnosing, simulating, and forecasting near-0°C p-types, particularly during transitions and within complex terrain. Motivated by these challenges, the field phase of the Winter Precipitation Type Research Multiscale Experiment (WINTRE-MIX) was conducted from 1 February to 15 March 2022 to better understand how multiscale processes influence the variability and predictability of p-type and amount under near-0°C surface conditions. WINTRE-MIX took place near the U.S.–Canadian border, in northern New York and southern Quebec, a region with plentiful near-0°C precipitation influenced by terrain. During WINTRE-MIX, existing advanced mesonets in New York and Quebec were complemented by deployment of 1) surface instruments, 2) the National Research Council Convair-580 research aircraft with W- and X-band Doppler radars and in situ cloud and aerosol instrumentation, 3) two X-band dual-polarization Doppler radars and a C-band dual-polarization Doppler radar from the University of Illinois, and 4) teams collecting manual hydrometeor observations and radiosonde measurements. Eleven intensive observing periods (IOPs) were coordinated. Analysis of these WINTRE-MIX IOPs is illuminating how synoptic dynamics, mesoscale dynamics, and microscale processes combine to determine p-type and its predictability under near-0°C conditions. WINTRE-MIX research will contribute to improving nowcasts and forecasts of near-0°C precipitation through evaluation and refinement of observational diagnostics and numerical forecast models.

On a Problem of Marine Current Velocity Estimation from Microwave Radar Data

The paper is devoted to the problem of estimating marine current velocity from microwave radar data, one of the important tasks of sea remote sensing. We present some results of simultaneous measurements of radar scatterers velocities and sea current and wind velocities. Radar scatterers velocities were measured using a dual-polarized (VV/HH) Doppler radar operating in S/C/X bands. The experiments were carried out in the coastal zone of the Black Sea at moderate incidence angles (30–70 degrees). It was obtained that the subsurface current velocity (current in the upper layer of ten centimeters) retrieved from the Bragg component of the radar return can be used to estimate changes in marine current (a part of the sea current that is not related to the wind) at constant wind speed. The subsurface current velocity is found as a vector sum of the current velocity measured at a depth of 1 m and the wind component equal to 1–3% of the wind speed. Possibilities of estimating the current velocity from VV/HH/PD data are analyzed.

Dual-Frequency Radar Retrievals of Snowfall Using Random Forest

The microphysical parameters of snowfall directly impact hydrological and atmospheric models. During the International Collaborative Experiment hosted at the Pyeongchang 2018 Olympic and Paralympic Winter Games (ICE-POP 2018), dual-frequency radar retrievals of particle size distribution (PSD) parameters were produced and assessed over complex terrain. The NASA Dual-frequency Dual-polarized Doppler Radar (D3R) and a collection of second-generation Particle Size and Velocity (PARSIVEL2) disdrometer observations were used to develop retrievals. The conventional look-up table method (LUT) and random forest method (RF) were applied to the disdrometer data to develop retrievals for the volume-weighted mean diameter (Dm), the shape factor (mu), the normalized intercept parameter (Nw), the ice water content (IWC), and the snowfall rate (S). Evaluations were performed between the D3R radar and disdrometer observations using these two methods. The mean errors of the retrievals based on the RF method were small compared with those of the LUT method. The results indicate that the RF method is a promising way of retrieving microphysical parameters, because this method does not require any assumptions about the PSD of snowfall.

An Inverse Method for Drop Size Distribution Retrieval from Polarimetric Radar at Attenuating Frequency

A method that formulates the retrieval of drop size distribution (DSD) parameters from polarimetric radar variables at attenuating frequency as the solution of an inverse problem is presented. The DSD in each radar bin is represented by a normalized Gamma distribution defined by three parameters (Dm,N0*,μ). The direct problem that describes polarimetric radar observables—scattering and propagation terms—and their dependency on DSD parameters is analyzed based on T-matrix scattering simulations. The inverse algorithm and its application to the DSD retrieval are then presented. The inverse method is applied to an African Monsoon Multidisciplinary Analysis (AMMA) field campaign that deployed an X-band dual-polarization Doppler radar and optical disdrometers in Benin, West Africa, in 2006 and 2007. The dataset is composed of X-band polarimetric radar PPIs and disdrometer data for 15 organized convective systems observed in 2006. A priori information on DSD parameters (benchmark method) is derived from the polarimetric radar observables by applying power law relationships. The proposed retrieval method of DSD parameters leads to the following results as compared to the benchmark: (i) we found a better spatial consistency of the retrieved parameters, (ii) the reconstructed polarimetric radar observables are closer to the observations, (iii) The validation with disdrometer data confirms an improved estimation of the DSD parameters.

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

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

Identification of snowfall microphysical processes from Eulerian vertical gradients of polarimetric radar variables

Abstract. Polarimetric radar systems are commonly used to study the microphysics of precipitation. While they offer continuous measurements with a large spatial coverage, retrieving information about the microphysical processes that govern the evolution of snowfall from the polarimetric signal is challenging. The present study develops a new method, called process identification based on vertical gradient signs (PIVSs), to spatially identify the occurrence of the main microphysical processes (aggregation and riming, crystal growth by vapor deposition and sublimation) in snowfall from dual-polarization Doppler radar scans. We first derive an analytical framework to assess in which meteorological conditions the local vertical gradients of radar variables reliably inform about microphysical processes. In such conditions, we then identify regions dominated by (i) vapor deposition, (ii) aggregation and riming and (iii) snowflake sublimation and possibly snowflake breakup, based on the sign of the local vertical gradients of the reflectivity ZH and the differential reflectivity ZDR. The method is then applied to data from two frontal snowfall events, namely one in coastal Adélie Land, Antarctica, and one in the Taebaek Mountains in South Korea. The validity of the method is assessed by comparing its outcome with snowflake observations, using a multi-angle snowflake camera, and with the output of a hydrometeor classification, based on polarimetric radar signal. The application of the method further makes it possible to better characterize and understand how snowfall forms, grows and decays in two different geographical and meteorological contexts. In particular, we are able to automatically derive and discuss the altitude and thickness of the layers where each process prevails for both case studies. We infer some microphysical characteristics in terms of radar variables from statistical analysis of the method output (e.g., ZH and ZDR distribution for each process). We, finally, highlight the potential for extensive application to cold precipitation events in different meteorological contexts.

The relationship between lightning flash rate and ice-related volume derived from dual-polarization radar

To conduct accurate lightning prediction and nowcasting, it is important to clarify the relationship between electrification and microphysical properties in clouds. Using the dual-polarization Doppler radar with the hydrometeor classification algorithm and lightning observation, radar-derived microphysical properties related to lightning flash rate were investigated in terms of 10 isolated thunderstorm cases over the Kanto Plain, Japan, with 351 radar volume scans conducted every 5 min during the summer period. In this study, the ice-related particles within the 35 dBZ volume (V35IC) showed the highest correlation coefficient (r = 0.75) and the lowest normalized root mean square error (NRMSE = 8.3%) in relation to cloud-to-ground lightning (CG), and also best to intra-cloud lightning (IC, r = 0.69, NRMSE = 8.1%). The correlation between V35IC and CG flash rate was better than that of the mixed-phase (between 0 °C and − 40 °C) 35 dBZ volume (r = 0.64), without considering the microphysical particles. The second-best radar-derived microphysical property was the ice mass consisting of the radar grids of all the ice-related particles (r = 0.72). These results suggest that an effective lightning indicator in terms of a radar-derived property is the ice-related particle volume, in addition to the traditionally used graupel and hail. The ice-related particle volume in the colder region of the thunderstorm (air temperature lower than −10 °C) showed a higher correlation with CG and IC than that in the warmer region, especially in terms of IC. These results are consistent with the non-inductive charging theory that has been well accepted in previous studies. Following time-lag correlation analysis from 0 to −30 min every 5 min before thunderstorm initiation, it was found that the ice-related index of V35IC demonstrated the slowest decrease (r = 0.75–0.65 in 30 min) in the correlation coefficient with time lapse and may be suitable as a lightning nowcast indicator.

Rainfall and DSD Parameters Comparison between Micro Rain Radar, Two-Dimensional Video and Parsivel2 Disdrometers, and S-Band Dual-Polarization Radar

AbstractA well-designed deployment of well-maintained surface instruments as well as abundant rainfall provided an excellent dataset with which to evaluate the Micro Rain Radar (MRR) performance for estimating raindrop size distribution (DSD) and its integral rainfall parameters with respect to the consolidated devices during the Iowa Flood Studies (IFloodS) field campaign. The MRR was collocated with two-dimensional video disdrometer (2DVD) and Autonomous Parsivel2 Unit (APU) at three different sites located at 5–70-km distances from the National Aeronautics and Space Administration’s S-band dual-polarization Doppler radar (NPOL). A comparative study between MRR, 2DVD, APU, and NPOL was conducted including all rainy minutes as well as minutes of stratiform rain and convective rain. Considering 2DVD as a primary reference, a good agreement was evident for reflectivity between MRR’s lowest reliable height and 2DVD with an absolute bias of less than 2 dB even in convective rain except for one site. For rainfall rate, the percent absolute bias between MRR and 2DVD ranged between 25% and 35% in stratiform rain and about 10% higher in convective rain. Agreement for mean mass-weighted raindrop diameter was good (bias less than 0.1 mm), whereas MRR overestimated the normalized intercept parameter of the gamma DSD [mean bias among the three sites was −0.13 log(mm−1 m−3)]. The agreement between MRR and APU was slightly worse than the one between MRR and 2DVD. When the horizontal and differential reflectivities of NPOL were compared with the ones derived from the MRR DSD resampled within the radar volume, we found an absolute bias of approximately 3 and 0.4 dB, respectively.

Observational analysis of two waterspouts in northwestern Italy using an OPERA Doppler radar

Abstract Data from a C-band dual-polarization Doppler radar are used to analyze the evolution of two waterspouts in the Mediterranean Sea, observed in front of the coastal city of Sanremo, northwestern Italy, on December 1, 2017. The integration of reflectivity and wind data allows to identify a mesocyclone aloft, and a Doppler velocity couplet, corresponding to a change in wind speed and/or direction in two adjacent individual pixels on radar display, at two different elevations. The latter signal is classified as a Tornado Vortex Signature, suggesting the presence of two vortices moving northward through the coast near Sanremo. The reconstructed paths agree well with the damage and eyewitness evidence. Radar data also suggest that the two waterspouts developed in the region of convergence separating the incoming cold air from the warm and moist inflow.

S-Pol’s Polarimetric Data Reveal Detailed Storm Features (and Insect Behavior)

AbstractThe National Center for Atmospheric Research (NCAR) operates a state-of-the-art S-band dual-polarization Doppler radar (S-Pol) for the National Science Foundation (NSF). This radar has some similar and some distinguishing characteristics to the National Weather Service (NWS) operational Weather Surveillance Radar-1988 Doppler Polarimetric (WSR-88DP). One key difference is that the WSR-88DP is used for operational purposes where rapid 360° volumetric scanning is required to monitor rapid changes in storm characteristics for nowcasting and issuing severe storm warnings. Since S-Pol is used to support the NSF research community, it usually scans at much slower rates than operational radars. This results in higher resolution and higher data quality suitable for many research studies. An important difference between S-Pol and the WSR-88DP is S-Pol’s ability to use customized scan strategies including scanning on vertical surfaces ([range–height indicators (RHIs)], which are presently not done by WSR-88DPs. RHIs provide high-resolution microphysical structures of convective storms, which are central to many research studies. Another important difference is that the WSR-88DP simultaneously transmits horizontal (H) and vertical (V) polarized pulses. In contrast, S-Pol typically transmits alternating H and V pulses, which results in not only higher data quality for research but also allows for the cross-polar signal to be measured. The cross-polar signal provides estimates of the linear depolarization ratio (LDR) and the co- to cross-correlation coefficient that give additional microphysical information. This paper presents plots and interpretations of high-quality, high-resolution polarimetric data that demonstrate the value of S-Pol’s polarimetric measurements for atmospheric research.

Diurnal Preconditioning of Subtropical Coastal Convective Storm Environments

Boundary layer evolution in response to diurnal forcing is manifested at the mesobeta and smaller scales of the atmosphere. Because this variability resides on subsynoptic scales, the potential influence upon convective storm environments is often not captured in coarse observational and modeling datasets, particularly for complex physical settings such as coastal regions. A detailed observational analysis of diurnally forced preconditioning for convective storm environments of South East Queensland, Australia (SEQ), during the Coastal Convective Interactions Experiment (2013–15) is presented. The observations used include surface-based measurements, aerological soundings, and dual-polarization Doppler radar. The sea-breeze circulation was found to be the dominant influence; however, profile modification by the coastward advection of the continental boundary layer was found to be an essential mechanism for favorable preconditioning of deep convection. This includes 1) enhanced moisture in the city of Brisbane, potentiality due to an urban heat island–enhanced land–sea thermal contrast, 2) significant afternoon warming and moistening above the sea breeze resulting from the advection of the inland convective boundary layer coastward under prevailing westerly flow coupled with the sea-breeze return flow, and 3) substantial variations in near-surface moisture likely associated with topography and land use. For the 27 November 2014 Brisbane hailstorm, which caused damages exceeding $1.5 billion Australian dollars (AUD), the three introduced diurnal preconditioning processes are shown to favor a mesoscale convective environment supportive of large hailstone growth. The hybrid high-precipitation supercell storm mode noted for this event and previous similar events in SEQ is hypothesized to be more sensitive to variations in near-surface and boundary layer instability in contrast to contemporary supercell storms.

Differential Reflectivity Calibration and Antenna Temperature

AbstractTemporal differential reflectivity bias variations are investigated using the National Center for Atmospheric Research (NCAR) S-band dual-polarization Doppler radar (S-Pol). Using data from the Multi-Angle Snowflake Camera-Ready (MASCRAD) Experiment, S-Pol measurements over extended periods reveal a significant correlation between the ambient temperature at the radar site and the bias. Using radar scans of the sun and the ratio of cross-polar powers, the components of the radar that cause the variation of the bias are identified. It is postulated that the thermal expansion of the antenna is likely the primary cause of the observed bias variation. The cross-polar power (CP) calibration technique, which is based on the solar and cross-polar power measurements, is applied to data from the Plains Elevated Convection at Night (PECAN) field project. The bias from the CP technique is compared to vertical-pointing bias measurements, and the uncertainty of the bias estimates is given. An algorithm is derived to correct the radar data for the time- and temperature-varying bias. Bragg scatter measurements are used to corroborate the CP technique bias measurements.

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.

The Convective Precipitation Experiment (COPE): Investigating the Origins of Heavy Precipitation in the Southwestern United Kingdom

Abstract The Convective Precipitation Experiment (COPE) was a joint U.K.–U.S. field campaign held during the summer of 2013 in the southwest peninsula of England, designed to study convective clouds that produce heavy rain leading to flash floods. The clouds form along convergence lines that develop regularly as a result of the topography. Major flash floods have occurred in the past, most famously at Boscastle in 2004. It has been suggested that much of the rain was produced by warm rain processes, similar to some flash floods that have occurred in the United States. The overarching goal of COPE is to improve quantitative convective precipitation forecasting by understanding the interactions of the cloud microphysics and dynamics and thereby to improve numerical weather prediction (NWP) model skill for forecasts of flash floods. Two research aircraft, the University of Wyoming King Air and the U.K. BAe 146, obtained detailed in situ and remote sensing measurements in, around, and below storms on several days. A new fast-scanning X-band dual-polarization Doppler radar made 360° volume scans over 10 elevation angles approximately every 5 min and was augmented by two Met Office C-band radars and the Chilbolton S-band radar. Detailed aerosol measurements were made on the aircraft and on the ground. This paper i) provides an overview of the COPE field campaign and the resulting dataset, ii) presents examples of heavy convective rainfall in clouds containing ice and also in relatively shallow clouds through the warm rain process alone, and iii) explains how COPE data will be used to improve high-resolution NWP models for operational use.

Robust Linear Depolarization Ratio Estimation for Dual-Polarization Weather Radar

Linear depolarization ratio (LDR) is often difficult to measure in low and moderate signal-to-noise ratio conditions because the cross-polar echo power is typically two to three orders of magnitude weaker than the copolar echo power. For radars operating at attenuating frequencies such as X-, Ku-, and Ka-bands, differential attenuation must be accounted for to accurately estimate the LDR. A method for robust estimation of the LDR is introduced and evaluated that addresses both of these issues. In practice, the “enhanced” LDR offers robust LDR estimation over current estimation methods. The enhanced LDR is insensitive to noise, radar calibration error, and path-integrated attenuation. The proposed estimator is experimentally validated using Ku-band observations from the National Aeronautics and Space Administration dual-frequency dual-polarization Doppler radar (D3R).

Real-Time Noise Estimation and Correction in Dual-Polarization Radar Systems

Accurate noise-power estimation in dual-polarization weather radar is necessary for the correction of all power-based moments in low signal-to-noise ratio environments. A method of real-time noise-power estimation for dual-polarization radar systems using copolar correlation and receiver power is introduced. This real-time noise-power estimation algorithm is implemented in the NASA dual-frequency dual-polarization Doppler radar, and the performance results are presented.

Overview of the D3R Observations during the IFloodS Field Experiment with Emphasis on Rainfall Mapping and Microphysics

Abstract The NASA dual-frequency, dual-polarization Doppler radar (D3R) was deployed as part of the GPM Iowa Flood Studies (IFloodS) ground validation field campaign from 1 May through 15 June 2013. The D3R participated in a multi-instrument targeted investigation of convective initiation and hydrological response in the midwestern United States. An overview of the D3R’s calibration and observations is presented. A method for attenuation correction of Ka-band observations using Ku-band results is introduced. Dual-frequency ratio estimates in stratiform rain and ice are presented and compared with theoretical values. Ku-band quantitative precipitation estimation results are validated against IFloodS ground instruments.

Estimation of Light Rainfall Using Ku-Band Dual-Polarization Radar

The light rain (less than or equal to a few mm hr-1) is critical to the Earth's ecosystem due to the high occurrence rate, particularly in middle and high latitude (over 80%). However, it is challenging to use rainfall gauge to measure light rain due to the sampling time and bucket volume resolution. Dual-polarization radar has become an important tool for quantitative precipitation estimation because of its relatively large covering area and ability to fill the sampling void. This paper presents the application of Ku-band dual-polarization radar for light rainfall estimation. The Ku-band radar rainfall algorithms and their error structure are described. The Ku-band observations from the National Aeronautics and Space Administration (NASA) Dual-frequency Dual-polarization Doppler Radar (D3R) during the NASA Iowa Flood Studies (IFoodS) field campaign are used to derive the rainfall products. The comparisons are performed between radar rainfall estimates and ground rainfall measurements from rain gauge and Autonomous Parsivel Unit (APU). It is shown here that the radar rainfall measurements at different timescales (i.e., 5, 10, and 15 min) agree with the APU observations very well. The normalized difference error is about 26.1%, 24.8%, and 23.7%, for 5-min, 10-min, and 15-min rainfall accumulations, respectively. The excellent performance of Ku-band rainfall algorithm for light rain estimation indicates the great potential of using D3R as a ground validation tool for the Global Precipitation Measurement (GPM) satellite precipitation product evaluations.

FROST-2014 project and meteorological support of the Sochi-2014 Olympics

In order to provide weather services to the 2014 Winter Olympics, the observational network in the Sochi region was strengthened with more than 40 automatic weather stations, the dual polarization Doppler radar, temperature and wind profilers, micro-rain radars, ets. These observation facilities allowed using the Sochi testbed for the development, testing, and intercomparison of various technologies of nowcasting and short-range numerical weather forecast. It was accomplished in the framework of the international project of the World Weather Research Program of WMO called FROST-2014 (Forecast and Research in the Olympic Sochi Testbed). The prognostic products of the FROST-2014 project was used for the operational meteorological servicing of Olympic events. Presented are the main research directions and the project preliminary results.

Polarimetric Variables Retrieval with Clutter Suppression for Staggered PRT Sequences

AbstractThis paper presents a procedure to filter ground clutter from dual-polarized staggered pulse repetition time (PRT) radar data in simultaneous and alternating transmission modes for polarimetric variables retrieval. The filter is designed in the time domain so that polarimetric variables such as the differential phase () and the copolar correlation coefficient () can be estimated directly from clutter-filtered time series data using a conventional method. In the case of the simultaneous mode, a single filter is used for both channels to maintain the signal correlation after filtering. For the alternating mode, because the polarizations are transmitted in different waveforms, two separate filters are required. However, the filters are designed so that the responses of the filters to the signals are identical within the extended Doppler range. Based on radar simulation, it is shown that the method can provide accurate retrieval of polarimetric variables even in the case of strong clutter contamination. Also, the performance of the method is illustrated on dual-polarized staggered PRT ⅔ data from the NASA dual-frequency dual-polarized Doppler radar (D3R).