Coupling X-band dual-polarized mini-radars and hydro-meteorological forecast models: the HYDRORAD project

Abstract. Hydro-meteorological hazards like convective outbreaks leading to torrential rain and floods are among the most critical environmental issues world-wide. In that context weather radar observations have proven to be very useful in providing information on the spatial distribution of rainfall that can support early warning of floods. However, quantitative precipitation estimation by radar is subjected to many limitations and uncertainties. The use of dual-polarization at high frequency (i.e. X-band) has proven particularly useful for mitigating some of the limitation of operational systems, by exploiting the benefit of easiness to transport and deploy and the high spatial and temporal resolution achievable at small antenna sizes. New developments on X-band dual-polarization technology in recent years have received the interest of scientific and operational communities in these systems. New enterprises are focusing on the advancement of cost-efficient mini-radar network technology, based on high-frequency (mainly X-band) and low-power weather radar systems for weather monitoring and hydro-meteorological forecasting. Within the above context, the main objective of the HYDRORAD project was the development of an innovative \\mbox{integrated} decision support tool for weather monitoring and hydro-meteorological applications. The integrated system tool is based on a polarimetric X-band mini-radar network which is the core of the decision support tool, a novel radar products generator and a hydro-meteorological forecast modelling system that ingests mini-radar rainfall products to forecast precipitation and floods. The radar products generator includes algorithms for attenuation correction, hydrometeor classification, a vertical profile reflectivity correction, a new polarimetric rainfall estimators developed for mini-radar observations, and short-term nowcasting of convective cells. The hydro-meteorological modelling system includes the Mesoscale Model 5 (MM5) and the Army Corps of Engineers Hydrologic Engineering Center hydrologic and hydraulic modelling chain. The characteristics of this tool make it ideal to support flood monitoring and forecasting within urban environment and small-scale basins. Preliminary results, carried out during a field campaign in Moldova, showed that the mini-radar based hydro-meteorological forecasting system can constitute a suitable solution for local flood warning and civil flood protection applications

Application of the variational method for correction of wet ice attenuation for X-band dual-polarized radar

2011 Fall.Includes bibliographical references.In recent years there has been a huge interest in the development and use of dual-polarized radar systems operating at X-band (~10 GHz) region of the electromagnetic spectrum. This is due to the fact that these systems are smaller and cheaper allowing for a network to be built, for example, for short range (typically < 30-40 km) hydrological applications. Such networks allow for higher cross-beam spatial resolutions while cheaper pedestals supporting a smaller antenna also allows for higher temporal resolution as compared with large S-band (long range) systems used by the National Weather Service. Dual-polarization radar techniques allow for correction of the strong attenuation of the electromagnetic radar signal due to rain at X-band and higher frequencies. However, practical attempts to develop reliable correction algorithms have been cumbered by the need to deal with the rather large statistical fluctuations or "noise" in the measured polarization parameters. Recently, the variational method was proposed, which overcomes this problem by using the forward model for polarization variables, and uses iterative approach to minimize the difference between modeled and observed values, in a least squares sense. This approach also allows for detection of hail and determination of the fraction of reflectivity due to the hail when the precipitation shaft is composed of a mixture of rain and hail. It was shown that this approach works well with S-band radar data. The purpose of this research is to extend the application of the variational method to the X-band dual-polarization radar data. The main objective is to correct for attenuation caused by rain mixed with wet ice hydrometeors (e.g., hail) in deep convection. The standard dual-polarization method of attenuation-correction using the differential propagation phase between H and V polarized waves cannot account for wet ice hydrometeors along the propagation path. The ultimate goal is to develop a feasible and robust variational-based algorithm for rain and hail attenuation correction for the Collaborate Adaptive Sensing of the Atmosphere (CASA) project

Development and validation of an X-band dual polarization Doppler weather radar test node for a tropical network, The

2012 Fall.Includes bibliographical references.An automated network of three X-band dual polarization Doppler weather radars is in process of being deployed and operational on the western coast of Puerto Rico. Colorado State University and the University of Puerto Rico at Mayaguez have collaborated to install the first polarimetric weather radar network in a tropical environment, known as TropiNet, to observe the lowest 2 km of the troposphere where the National Weather Service NEXRAD radar in Cayey, PR (TJUA) has obstructed views of the west coast, below 1.5 km due to terrain blockage and the Earth curvature problem. The CSU-X25P radar test node was developed, validated, and deployed to Mayaguez, PR in early 2011 to make first observations of this tropical region, and served as a pilot project to verify the infrastructure of the TropiNet network. This research describes the CSU-X25P radar test node, presenting the radar system specifications and an overview of the data acquisition and signal processing sub-systems, and the antenna positioner and control sub-system. The development and validation process included integration, sub-system calibration and test, and a final evaluation by conducting end-to-end calibration of the radar system. Validation of the calculated data moments, include Doppler velocity, reflectivity, differential reflectivity, differential propagation phase, and specific differential phase. The validation was accomplished by comparative analysis of data from coordinated scans between CSU-X25P and the well-established CSU-CHILL S-band polarimetric Doppler weather radar, in Greeley, CO. Upon validation, CSU-X25P was disassembled, packaged, and shipped to Puerto Rico to be fully deployed for operation in a tropical seaside environment. This research presents select observations of severe weather events, such as tropical storms and hurricanes, which attest to the robustness of the radar test node, and the TropiNet network infrastructure

Master of Science

thesisTropical Measuring Mission (TRMM) precipitation radar (PR) 2A25 V7 retrievals show that precipitation features (PFs) with the tallest maximum 40 dBZ echo heights are rarely the same PFs that exhibit the most extreme near-surface rainfall rates. To investigate the impacts of potential weaknesses in the 2A25 V7 retrievals, due to potential attenuation of the Ku-band signal, 14 years of June-August retrievals are compared to June-August 2014 hourly Weather Surveillance Radar - 1988 Doppler (WSR-88D) dual-polarimetric S-band data for 28 radars over the southeastern United States (SEUS). For more direct comparison, TRMM Ku-band measurements are converted to S-band approximations. Rain rates for WSR-88D data are approximated using the CSU-HIDRO algorithm, which calculates rain rates from reflectivity (Z), differential reflectivity (ZDR), and specific differential phase (KDP) relationships. This research aims to not only investigate the difference between TRMM PR and WSR-88D retrievals of reflectivity and rain rate, but also to investigate how apparent differences relate to TRMM path integrated attenuation (PIA), and WSR-88D KDP, ZDR and calculated hail fraction. Tropics-wide TRMM retrievals confirm previous findings of a low overlap of extreme convective intensity and extreme near-surface rain rates. WSR-88D data also confirm that this overlap is low, but show that it is likely higher than TRMM PR retrievals indicate, approximately 30% higher in the SEUS for the 99th percentiles of maximum 40 dBZ heights and low-level rain rates. For maximum 40 dBZ echo heights that extend into regions likely containing ice, mean WSR-88D reflectivities are approximately 2 dBZ higher than TRMM PR reflectivities. Higher WSR-88D-retrieved rain rates for a given low-level reflectivity combine with these higher low-level reflectivities to produce much greater mean WSR-88D rainfall rates than TRMM PR as a function of maximum 40 dBZ height, for heights that extend into regions likely to have ice. Investigations of TRMM PR PIA, and WSR-88D KDP, ZDR, and hail fraction indicate that the TRMM PR 2A25 V7 algorithm is possibly misidentifying low-mid level hail or graupel as greater attenuating liquid, or vice versa. This possible misidentification results in 2A25 V7 Z-R relationships that likely produce low biased rain rates in intense convection

Performance Evaluation of a New Dual-Polarization Microphysical Algorithm Based on Long-Term X-Band Radar and Disdrometer Observations

Abstract Accurate estimation of precipitation at high spatial and temporal resolution of weather radars is an open problem in hydrometeorological applications. The use of dual polarization gives the advantage of multiparameter measurements using orthogonal polarization states. These measurements carry significant information, useful for estimating rain-path signal attenuation, drop size distribution (DSD), and rainfall rate. This study evaluates a new self-consistent with optimal parameterization attenuation correction and rain microphysics estimation algorithm (named SCOP-ME). Long-term X-band dual-polarization measurements and disdrometer DSD parameter data, acquired in Athens, Greece, have been used to quantitatively and qualitatively compare SCOP-ME retrievals of median volume diameter D0 and intercept parameter NW with two existing rain microphysical estimation algorithms and the SCOP-ME retrievals of rain rate with three available radar rainfall estimation algorithms. Error statistics for rain rate estimation, in terms of relative mean and root-mean-square error and efficiency, show that the SCOP-ME has low relative error if compared to the other three methods, which systematically underestimate rainfall. The SCOP-ME rain microphysics algorithm also shows a lower relative error statistic when compared to the other two microphysical algorithms. However, measurement noise or other signal degradation effects can significantly affect the estimation of the DSD intercept parameter from the three different algorithms used in this study. Rainfall rate estimates with SCOP-ME mostly depend on the median volume diameter, which is estimated much more efficiently than the intercept parameter. Comparisons based on the long-term dataset are relatively insensitive to path-integrated attenuation variability and rainfall rates, providing relatively accurate retrievals of the DSD parameters when compared to the other two algorithms

An Integrated Approach to Weather Radar Calibration and Monitoring Using Ground Clutter and Satellite Comparisons

The stability and accuracy of weather radar reflectivity calibration are imperative for quantitative applications, such as rainfall estimation, severe weather monitoring and nowcasting, and assimilation in numerical weather prediction models. Various radar calibration and monitoring techniques have been developed, but only recently have integrated approaches been proposed, that is, using different calibration techniques in combination. In this paper the following three techniques are used: 1) ground clutter monitoring, 2) comparisons with spaceborne radars, and 3) the self-consistency of polarimetric variables. These techniques are applied to a C-band polarimetric radar (CPOL) located in the Australian tropics since 1998. The ground clutter monitoring technique is applied to each radar volumetric scan and provides a means to reliably detect changes in calibration, relative to a baseline. It is remarkably stable to within a standard deviation of 0.1 dB (decibels). To obtain an absolute calibration value, CPOL observations are compared to spaceborne radars on board TRMM (Tropical Rainfall Measuring Mission) and GPM (Global Precipitation Measurement) using a volume-matching technique. Using an iterative procedure and stable calibration periods identified by the ground echoes technique, we improve the accuracy of this technique to about 1 dB. Finally, we review the self-consistency technique and constrain its assumptions using results from the hybrid TRMM-GPM and ground echo technique. Small changes in the self-consistency parameterization can lead to 5 dB of variation in the reflectivity calibration. We find that the drop-shape model of Brandes et al. with a standard deviation of the canting angle of 12 degrees best matches our dataset

Development of a polarimetric radar based hydrometeor classification algorithm for winter precipitation

2012 Fall.Includes bibliographical references.The nation-wide WSR-88D radar network is currently being upgraded for dual-polarized technology. While many convective, warm-season fuzzy-logic hydrometeor classification algorithms based on this new suite of radar variables and temperature have been refined, less progress has been made thus far in developing hydrometeor classification algorithms for winter precipitation. Unlike previous studies, the focus of this work is to exploit the discriminatory power of polarimetric variables to distinguish the most common precipitation types found in winter storms without the use of temperature as an additional variable. For the first time, detailed electromagnetic scattering of plates, dendrites, dry aggregated snowflakes, rain, freezing rain, and sleet are conducted at X-, C-, and S-band wavelengths. These physics-based results are used to determine the characteristic radar variable ranges associated with each precipitation type. A variable weighting system was also implemented in the algorithm's decision process to capitalize on the strengths of specific dual-polarimetric variables to discriminate between certain classes of hydrometeors, such as wet snow to indicate the melting layer. This algorithm was tested on observations during three different winter storms in Colorado and Oklahoma with the dual-wavelength X- and S-band CSU-CHILL, C-band OU-PRIME, and X-band CASA IP1 polarimetric radars. The algorithm showed success at all three frequencies, but was slightly more reliable at X-band because of the algorithm's strong dependence on specific differential phase. While plates were rarely distinguished from dendrites, the latter were satisfactorily differentiated from dry aggregated snowflakes and wet snow. Sleet and freezing rain could not be distinguished from rain or light rain based on polarimetric variables alone. However, high-resolution radar observations illustrated the refreezing process of raindrops into ice pellets, which has been documented before but not yet explained. Persistent, robust patterns of decreased correlation coefficient, enhanced differential reflectivity, and an inflection point around enhanced reflectivity occurred over the exact depth of the surface cold layer indicated by atmospheric soundings during times when sleet was reported at the surface. It is hypothesized that this refreezing signature is produced by a modulation of the drop size distribution such that smaller drops preferentially freeze into ice pellets first. The melting layer detection algorithm and fall speed spectra from vertically pointing radar also captured meaningful trends in the melting layer depth, height, and mean correlation coefficient during this transition from freezing rain to sleet at the surface. These findings demonstrate that this new radar-based winter hydrometeor classification algorithm is applicable for both research and operational sectors

Use of Dual Polarization Radar in Validation of Satellite Precipitation Measurements: Rationale and Opportunities

Dual-polarization weather radars have evolved significantly in the last three decades culminating in the operational deployment by the National Weather Service. In addition to operational applications in the weather service, dual-polarization radars have shown significant potential in contributing to the research fields of ground based remote sensing of rainfall microphysics, study of precipitation evolution and hydrometeor classification. Furthermore the dual-polarization radars have also raised the awareness of radar system aspects such as calibration. Microphysical characterization of precipitation and quantitative precipitation estimation are important applications that are critical in the validation of satellite borne precipitation measurements and also serves as a valuable tool in algorithm development. This paper presents the important role played by dual-polarization radar in validating space borne precipitation measurements. Starting from a historical evolution, the various configurations of dual-polarization radar are presented. Examples of raindrop size distribution retrievals and hydrometeor type classification are discussed. The quantitative precipitation estimation is a product of direct relevance to space borne observations. During the TRMM program substantial advancement was made with ground based polarization radars specially collecting unique observations in the tropics which are noted. The scientific accomplishments of relevance to space borne measurements of precipitation are summarized. The potential of dual-polarization radars and opportunities in the era of global precipitation measurement mission is also discussed