CSU CHILL Research Articles

Improved Precipitation Typing Using POSS Spectral Modal Analysis

AbstractThe Precipitation Occurrence Sensor System (POSS) is a small X-band Doppler radar that measures the Doppler velocity spectra from precipitation falling in a small volume near the sensor. The sensor records a 2D frequency of occurrence matrix of the velocity and power at the mode of each spectrum measured over 1 min. The centroid of the distribution of these modes, along with other spectral parameters, defines a data vector input to a multiple discriminant analysis (MDA) for classification of the precipitation type. This requires the a priori determination of a training set for different types, particle size distributions (PSDs), and wind speed conditions. A software model combines POSS system parameters, a particle scattering cross section, and terminal velocity models, to simulate the real-time Doppler signal measured by the system for different PSDs and wind speeds. This is processed in the same manner as the system hardware to produce bootstrap samples of the modal centroid distributions for the MDA training set. MDA results are compared to images from the Multi-Angle Snowflake Camera (MASC) at the MASCRAD site near Easton, Colorado, and to the CSU–CHILL X-band radar observations from Greeley, Colorado. In the four case studies presented, POSS successfully identified precipitation transitions through a range of types (rain, graupel, rimed dendrites, aggregates, unrimed dendrites). Also two separate events of hail were reported and confirmed by the images.

Resonance Scattering Detection Using the CSU–CHILL Dual-Wavelength, Dual-Polarization Radar

AbstractThe CSU–CHILL radar is a dual-wavelength, dual-polarization weather radar system operating at S and X band with coaxial beams. This radar system offers a unique environment to develop and/or validate algorithms that cut across its wavelengths and polarizations. This paper presents a method to retrieve resonance scattering regions from the difference in intrinsic reflectivities after attenuation correction, which is performed using measured reflectivity fields only. The algorithm to retrieve these regions dominated by non-Rayleigh scattering is applied to different storm events, and the obtained data field capturing the difference in S- and X-band reflectivities due to resonance effects (which we will call Mie signal for convenience) is compared to the collocated dual-polarization fields. The obtained Mie signal is also compared to hail reports. In both cases, the retrieved Mie signal is found to be consistent with the rest of the dual-polarization data fields, and in some situations, it is shown to bring information not directly discernible from the usual dual-polarization radar variables.

Ground Validation of Surface Snowfall Algorithm in GPM Dual-Frequency Precipitation Radar

AbstractExtensive evaluations have been performed on the dual-frequency classification module in the Global Precipitation Mission (GPM) Dual-Frequency Precipitation Radar (DPR) level-2 algorithm. Both rain type classification and melting-layer detection continue to show promising results in the validations. Surface snowfall identification is a feature newly added in the classification module to the recently released version to provide a surface snowfall flag for each qualified vertical profile. This algorithm is developed upon vertical features of Ku- and Ka-band reflectivity and dual-frequency ratio from DPR. In this paper, we validate this surface snowfall identification algorithm with ground radars including NEXRAD, NASA Polarimetric Radar (NPOL), and CSU–CHILL radar during concurrent precipitation events and GPM validation campaign Olympic Mountain Experiment (OLYMPEX). Other ground truth such as Precipitation Imaging Package (PIP) and ground report is also included in the validation. Based on 16 validation cases in the years 2014–18, the average match ratio between surface snowfall flag from space radar and ground radar is around 87.8%. Promising agreements are achieved with different validation sources. Algorithm limitation and potential improvement are discussed.

Dual-Polarized Radar and Surface Observations of a Winter Graupel Shower with Negative Zdr Column

AbstractComprehensive analysis of an unusual graupel-shower event recorded by an S-band polarimetric radar and two optical-imaging surface instruments is presented. The primary radar characteristic was negative differential reflectivity Zdr values along a vertical column. During the afternoon hours of 16 February 2015, a sequence of three showers that were composed primarily of small (8–15-mm diameter) graupel affected the ground instrumentation site that was established for the Multi-Angle Snowflake Camera and Radar (MASCRAD) experiment in the high plains of Colorado. While these showers passed the instrumentation site, the CSU–CHILL radar conducted high-time-resolution (~2.5-min cycle time) range–height indicator (RHI) scans from a range of 13 km. The RHI data show that the negative Zdr values extended vertically through much of the reflectivity cores, implying that the reflectivity-weighted mean axis ratios of the graupel particles in this event remained somewhat prolate throughout their lifetime. To be specific, the cores of the convective showers only extended to heights of ~3.5 km AGL and had fractionally negative (from ~−0.3 to −0.7 dB) Zdr levels in those cores. Particle-image data obtained by the MASC system and by a collocated 2D video disdrometer measured the diameters, shapes, and fall speeds of the graupel particles as they reached the surface. The graupel particles were found to be primarily of the lump type with a slightly prolate mean shape (especially for the larger-diameter particles). Microwave backscatter calculations confirm that the graupel-particle shape and orientation characteristics are consistent with the observed slightly, but consistently, negative Zdr values.

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.

Transformation of the CSU–CHILL Radar Facility to a Dual-Frequency, Dual-Polarization Doppler System

Abstract This paper describes the transformation of the Colorado State University–University of Chicago–Illinois State Water Survey (CSU–CHILL) National Radar Facility from a single-frequency (S band) dual-polarization Doppler weather radar system to a dual-frequency (S and X bands) dual-polarization Doppler system with coaxial beams. A brief history regarding the development of dual-wavelength radars is first presented. In the past, dual-wavelength measurements were used to detect hail using the dual-wavelength ratio defined as the ratio of intrinsic (or attenuation corrected) X-band reflectivity to the S-band reflectivity. Departures of this ratio from unity were taken to indicate the presence of hail, produced by Mie scattering at the shorter wavelength by hail. Most dual-wavelength radars were developed with attempts to match beams for S and X bands, which implies that the sample volumes for the two frequencies were essentially the same. The X-band channel of the CSU–CHILL radar takes a different approach, that of making use of the already existing dual-offset-fed antenna designed to give a 1° beamwidth at S band, resulting in an X-band beamwidth of approximately 0.3°, with very high gain. Thus, the X band provides about a factor of 3 more resolution than the S-band component while maintaining the same sensitivity as the S-band component. Examples of cold season and warm season data from the X-band and S-band radar components are presented, demonstrating the successful transformation of the CSU–CHILL radar into a unique multifrequency, multipolarization system. The new CSU–CHILL dual-wavelength, dual-polarization weather radar will serve as an important asset for the scientific community.

Observations of the 14 July 2011 Fort Collins Hailstorm: Implications for WSR-88D-Based Hail Detection and Warnings

Abstract The issuance of timely warnings for the occurrence of severe-class hail (hailstone diameters of 2.5 cm or larger) remains an ongoing challenge for operational forecasters. This study examines the application of two remotely sensed data sources between 0100 and 0400 UTC 14 July 2011 when pulse-type severe thunderstorms occurred in the jurisdiction of the Denver/Boulder National Weather Service (NWS) Forecast Office in Colorado. First, a developing hailstorm was jointly observed by the dual-polarization Colorado State University–University of Chicago–Illinois State Water Survey (CSU–CHILL) research radar and by the operational, single-polarization NWS radar at Denver/Front Range (KFTG). During the time period leading up to the issuance of the initial severe thunderstorm warning, the dual-polarization radar data near the 0 °C altitude contained a positive differential reflectivity ZDR column (indicating a strong updraft lofting supercooled raindrops above the freezing level). Correlation coefficient ρHV reductions to ~0.93, probably due to the presence of growing hailstones, were observed above the freezing level in portions of the developing >55-dBZ echo core. Second, data from the National Lightning Detection Network (NLDN), including the locations and polarity of cloud-to-ground (CG) discharges produced by several of the evening’s storms, were processed. Some association was found between the prevalence of positive CGs and storms that produced severe hail. The analyses indicate that the use of the dual-polarization data provided by the upgraded Weather Surveillance Radar-1988 Doppler (WSR-88D), in combination with the NLDN data stream, can assist operational forecasters in the real-time identification of thunderstorms that pose a severe hail threat.

Gaussian Model Adaptive Processing in Time Domain (GMAP-TD) for Weather Radars

Abstract The Gaussian model adaptive processing in the time domain (GMAP-TD) method for ground clutter suppression and signal spectral moment estimation for weather radars is presented. The technique transforms the clutter component of a weather radar return signal to noise. Additionally, an interpolation procedure has been developed to recover the portion of weather echoes that overlap clutter. It is shown that GMAP-TD improves the performance over the GMAP algorithm that operates in the frequency domain using both signal simulations and experimental observations. Furthermore, GMAP-TD can be directly extended for use with a staggered pulse repetition time (PRT) waveform. A detailed evaluation of GMAP-TD performance and comparison against the GMAP are done using simulated radar data and observations from the Colorado State University–University of Chicago–Illinois State Water Survey (CSU–CHILL) radar using uniform and staggered PRT waveform schemes.

Wideband Waveform Design Principles for Solid-State Weather Radars

Abstract The use of solid-state transmitters is becoming increasingly viable for atmospheric radars and is a key part of the strategy to realize any dense network of low-powered radars. However, solid-state transmitters have low peak powers and this necessitates the use of pulse compression waveforms. In this paper frequency diversity in a wideband waveform design is proposed to mitigate the low sensitivity of solid-state transmitters. In addition, the waveforms mitigate the range-eclipsing problem associated with long pulse compression. An analysis of the performance of pulse compression using mismatched compression filters designed to minimize sidelobe levels is presented. The impact of the range sidelobe level on the retrieval of Doppler moments is discussed. Realistic simulations are performed based on both the Colorado State University–University of Chicago–Illinois State Water Survey (CSU–CHILL) and the Center for Collaborative Adaptive Sensing of the Atmosphere (CASA) Integrated Project I (IP1) radar data.

Design and Performance Characteristics of the New 8.5-m Dual-Offset Gregorian Antenna for the CSU–CHILL Radar

Abstract The Colorado State University–University of Chicago–Illinois State Water Survey (CSU–CHILL) national weather radar facility has been operated by the Colorado State University under a cooperative agreement with the U.S. National Science Foundation from 1990 to the present. The radar is configured to measure the elements of the 3 × 3 polarimetric covariance matrix based on using a two-transmitter and two-receiver system in the horizontal–vertical polarization basis. This S-band Doppler, dual-polarized radar facility is used for observations of precipitation with the highest possible data quality. To achieve this, a new dual-offset 8.5-m Gregorian antenna was custom designed and built by VertexRSI (now General Dynamics SATCOM) in Kilgore, Texas, to replace the circa 1994 center-fed parabolic reflector antenna. Here, the design features used to achieve the stringent specifications in terms of the sidelobe envelope and off-axis cross-polar levels are described, and the way in which they were validated at the manufacturer’s long- and short-range pattern measurement facility. Measurements in several different storm types, including stratiform rain and an intense hailstorm, and ground clutter (from mountains) are used to illustrate the new antenna performance. The linear depolarization ratio (LDR) system limit is shown to be −40 dB or better, which should lead to more insights into the microphysics of convective precipitation at subfreezing temperatures (e.g., hail formation, improved hydrometeor-type classification), and in winter precipitation in general (e.g., aggregation processes, rimed versus unrimed particles). In the case of the intense hailstorm, it is shown that measurement artifacts resulting from strong cross-beam gradients of reflectivity, up to 40 dB km−1 at 40-km range, have been greatly reduced or eliminated. Previously noted measurement artifacts with the 1994 antenna at storm tops in intense convection have been eliminated with the dual-offset antenna. The ground (mountain) clutter example shows greatly reduced returns (in terms of near-zero mean Doppler velocity areas) because of rapid falloff in the sidelobe levels with increasing elevation angle. The greatly improved antenna performance as compared with the 1994 antenna are expected to result in corresponding data quality improvements leading to more accurate measurement of rain rate and hydrometeor classification.

S-Band Dual-Polarization Radar Observations of Winter Storms

AbstractThis study is based on analyses of dual-polarization radar observations made by the 11-cm-wavelength Colorado State University–University of Chicago–Illinois State Water Survey (CSU–CHILL) system during four significant winter storms in northeastern Colorado. It was found that values of specific differential phase KDP often reached local maxima of ∼0.15°–0.4° km−1 in an elevated layer near the −15°C environmental temperature isotherm. The passage of these elevated positive KDP areas is shown to be linked to increased surface precipitation rates. Calculations using a microwave scattering model indicate that populations of highly oblate ice particles with moderate bulk densities and diameters in the ∼0.8–1.2-mm range can generate KDP (and differential reflectivity ZDR) values that are consistent with the radar observations. The persistent correlation between the enhanced KDP level and the −15°C temperature regime suggests that rapidly growing dendrites likely played a significant role in the production of the observed KDP patterns. The detection of organized regions of S-band KDP values greater than ∼0.1°–0.2° km−1 in winter storms may therefore be useful in identifying regions of active dendritic particle growth, as a precursor to aggregate snowfall.

Polarimetric Spectral Filter for Adaptive Clutter and Noise Suppression

Abstract In this paper, spectral decompositions of differential reflectivity, differential phase, and copolar correlation coefficient are used to discriminate between weather and nonweather signals in the spectral domain. This approach gives a greater flexibility for discrimination between different types of scattering sources present in a radar observation volume. A spectral filter, which removes nonweather signals, is defined based on this method. The performance of this filter is demonstrated on the Colorado State University–University of Chicago–Illinois State Water Survey (CSU–CHILL) observations. It is shown that the resulting filter parameters are adaptively defined for each range sample and do not require an assumption on spectral properties of ground clutter.

Orthogonal Channel Coding for Simultaneous Co- and Cross-Polarization Measurements

Abstract Dual-polarization weather radars typically measure the radar reflectivity at more than one polarization state for transmission and reception. Historically, dual-polarization radars have been operated at copolar and cross-polar states defined with respect to the transmit polarization states. Recently, based on the improved understanding of the propagation properties of electromagnetic waves in precipitation media, the simultaneous transmit and receive (STAR) mode has become common to simplify the hardware. In the STAR mode of operation, horizontal and vertical polarization states are transmitted simultaneously and samples of both horizontal and vertical copolar returns are obtained. A drawback of the current implementation of STAR mode is its inability to measure parameters obtained from cross-polar signals such as linear depolarization ratio (LDR). In this paper, a technique to obtain cross-polar signals with STAR mode waveform is presented. In this technique, the horizontally and vertically polarized transmit waveforms are coded with orthogonal phase sequences. The performance of the phase-coded waveform is determined by the properties of the phase codes. This orthogonal phase coding technique is implemented in the Colorado State University–University of Chicago–Illinois State Water Survey (CSU–CHILL) radar. This paper outlines the methodology and presents the performance of the cross-polar and copolar parameter estimation based on the simulation as well as data collected from the CSU–CHILL radar.

Clutter Suppression for Staggered PRT Waveforms

Abstract This paper presents a clutter suppression methodology for staggered pulse repetition time (PRT) observations. It is shown that spectral moments of precipitation echoes can be accurately estimated even in cases where clutter-to-signal ratios are high by using a parametric time domain method (PTDM). Based on radar signal simulations, the accuracy of the proposed method is evaluated for various observation conditions. The performance of PTDM is demonstrated by the implementation of the staggered PRT at the Colorado State University–University of Chicago–Illinois State Water Survey (CSU–CHILL). Based on this study, it is found that the accuracy of the retrieval is comparable to the current state of the art methods applied to the uniformly sampled observations and that the estimated velocity is unbiased for the complete Nyquist range.

Retrieval of Reflectivity in a Networked Radar Environment

Abstract A system for reflectivity and attenuation retrieval for rain medium in a networked radar environment is described. Electromagnetic waves backscattered from a common volume in networked radar systems are attenuated differently along the different paths. A solution for the specific attenuation distribution is proposed by solving the integral equation for reflectivity and attenuation. The set of governing integral equations describing the backscatter and propagation of common resolution volume are solved simultaneously with constraints on total path attenuation. The proposed algorithm is evaluated based on simulated X-band radar observations synthesized from S-band measurements collected by the Colorado State University–University of Chicago–Illinois State Water Survey (CSU–CHILL) radar. Retrieved reflectivity and specific attenuation using the proposed method show good agreement with simulated reflectivity and specific attenuation. Preliminary demonstration of the network-based retrieval using data from the Center for Collaborative Adaptive Sensing of the Atmosphere (CASA) IP-1 radar network are also presented.

A Parametric Time Domain Method for Spectral Moment Estimation and Clutter Mitigation for Weather Radars

Abstract A parametric time domain method (PTDM) for clutter mitigation and precipitation spectral moments’ estimation for weather radars is introduced. Use of PTDM allows for the simultaneous estimation of clutter and precipitation echo spectral moments. It is shown that this approach leads to accurate estimates of precipitation spectral moments in the presence of clutter. Based on simulations, the PTDM performance is evaluated and compared against the clutter spectral filtering technique. In this study special attention is paid to the cases of strong clutter contamination. Furthermore, both methods, the PTDM and spectral clutter filter, are illustrated using the Colorado State University–University of Chicago–Illinois State Water Survey (CSU–CHILL) observations.

Nonparametric Estimation of Raindrop Size Distributions from Dual-Polarization Radar Spectral Observations

This paper presents a method to retrieve raindrop size distributions (DSD) from slant profile dual-polarization Doppler spectra observations. It is shown that using radar measurements taken at a high elevation angle raindrop size distributions can be retrieved without making an assumption on the form of a DSD. In this paper it is shown that drop size distributions can be retrieved from Doppler power spectra by compensating for the effect of spectrum broadening and mean velocity shift. To accomplish that, spectrum deconvolution is used where the spectral broadening kernel width and wind velocity are estimated from spectral differential reflectivity measurements. Since convolution kernel is estimated from dual-polarization Doppler spectra observations and does not require observation of a clear-air signal, this method can be used by most radars capable of dual-polarization spectra measurements. To validate the technique, sensitivity of this method to the underlying assumptions and calibration errors is evaluated on realistic simulations of radar observations. Furthermore, performance of the method is illustrated on Colorado State University–University of Chicago–Illinois State Water Survey radar (CSU–CHILL) measurements of stratiform precipitation.

Dual-Polarization Spectral Analysis for Retrieval of Effective Raindrop Shapes

Abstract Dual-polarization radar observations of precipitation depend on size–shape relations of raindrops. There are several studies presented in literature dedicated to the investigation of this relation. In this work a new approach of investigating raindrop size–shape relation on short time and spatial scales from radar observations is presented. The presented method is based on the use of dual-polarization Doppler power spectral analysis. By measuring complete Doppler spectra at a sufficiently high elevation angle at two polarization settings, namely, horizontal and vertical, it is possible to retrieve drop size distribution (DSD) parameters, ambient air velocity, spectral broadening, and the slope of the assumed linear dependence of raindrop size–shape relation. This paper is mainly focused on the development of the retrieval algorithm and analysis of its performance. As a part of the proposed method an efficient algorithm for DSD parameter retrieval was developed. It is shown that the DSD parameter retrieval method, which usually requires the solution of five-parameter nonlinear optimization problems, can be simplified to a three-parameter nonlinear least squares problem. Furthermore, the performance of the proposed retrieval technique is illustrated on the dual-polarization measurements collected by the S-band Transportable Atmospheric Radar (TARA) at Cabauw, Netherlands, and by the Colorado State University–University of Chicago–Illinois State Water Survey (CSU–CHILL) radar from Greeley, Colorado.

Characterization and Evaluation of Hybrid Polarization Observation of Precipitation

Abstract Transmitting an arbitrary state of polarization while receiving horizontal–vertical polarization states is termed the hybrid polarization mode of operation. A theoretical model is developed for hybrid mode dual-polarization measurements in terms of the covariance matrix under linear horizontal–vertical polarization basis. The cross polarization encountered introduces biases in the copolar parameters estimated in the hybrid mode. Such biases are investigated for different precipitation types and propagation effects resulting from hydrometeor orientation and antenna properties. Polarimetric data measured by the Colorado State University–University of Chicago–Illinois State Water Survey (CSU–CHILL) radar transmitting horizontal–vertical polarization states is alternately used to demonstrate the measurement accuracy that would be expected in different storm scenarios observed in the hybrid mode.

Studies of the Polarimetric Covariance Matrix. Part I: Calibration Methodology

Abstract A procedure for calibration of the radar covariance matrix for the Colorado State University–University of Chicago–Illinois State Water Survey (CSU–CHILL) radar and S-Band Dual-Polarization Doppler Radar (S-Pol) systems is described. Two relative magnitudes and three offset phases are determined that allow for the calibrated covariance matrix to be constructed. Precise calibration of Zdr is accomplished with use of only sun calibration measurements and crosspolar power measurements from precipitation. No assumptions about the precipitation medium are made. It is also shown how to determine the co-to-cross phase offsets for the CSU–CHILL radar from precipitation data. A novel method for calculating linear depolarization ratio (LDR) that is effective in low signal-to-noise-ratio regions and that requires no knowledge of the background noise temperature is given. This technique utilizes the cross-to-cross covariances. CSU–CHILL data from the Severe Thunderstorm Electrification and Precipitation Stud...