The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform
Tanvir Islam - One of the best experts on this subject based on the ideXlab platform.
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sensitivity associated with bright band Melting Layer location on radar reflectivity correction for attenuation at c band using differential propagation phase measurements
Atmospheric Research, 2014Co-Authors: Tanvir Islam, Dawei Han, Miguel A Ricoramirez, Prashant K. SrivastavaAbstract:Abstract The modern rain profiling algorithms in reflectivity (ZH) correction for two way path integrated attenuation (AH) using dual polarization radar at attenuating frequencies rely on differential propagation phase (ΦDP) measurements. To retrieve corrected reflectivity profiles from the measured profiles, these algorithms impose an external constraint in the inversion processes which is provided by total differential phase shifts (∆ΦDP) valid for rain cells only. However, there is a possibility of radar beams propagating through and beyond the bright band/Melting Layer region hence may observe non-rainy cells. In light of this, the present study explores the variation of reflectivity correction in different ∆ΦDP scenarios by varying the rain cells locality by +/− 500 m with respect to the “reference” rain cells location derived from a numerical weather prediction (NWP) model output. To implement this, the well-known ZPHI algorithm from the rain profiling algorithms group is applied to several rainfall events from a C-band dual polarization radar. Before applying the algorithms, a total of 162,415 raindrop spectra have been used to retrieve the algorithm coefficients through T-matrix scattering simulated dual polarized signatures. It is revealed that, in some cases, when the ΦDP profile in an attenuated beam is in increasing gradient near the rain Layer top region, there could be a variation of about 1–2 dB in comparison with the “reference” attenuation corrected reflectivity. Such phenomenon is in accord with the reflectivity statistics when comparing with one neighboring C-band single polarization radar derived reflectivity data. Additionally, the remarkable agreement between the reflectivity profiles lends the applicability of the ZPHI algorithm in the attenuation correction with known rain/Melting Layer information.
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Fuzzy logic based Melting Layer recognition from 3 GHz dual polarization radar: appraisal with NWP model and radio sounding observations
Theoretical and Applied Climatology, 2013Co-Authors: Tanvir Islam, Miguel A. Rico-ramirez, Dawei Han, Michaela Bray, Prashant K. SrivastavaAbstract:The advent of polarimetry makes it possible to categorize hydrometeor inferences more accurately by providing detailed information of the scattering properties. In light of this, the authors have developed a fuzzy logic based system for the recognition of Melting Layer in the atmosphere. The fuzzy system is based on characterizing Melting Layer scatterers from non-Melting scatterers using five crisp inputs, namely, horizontal reflectivity ( Z _H), differential reflectivity ( Z _DR), co-polar correlation coefficient ( ρ _HV), linear depolarization ratio (LDR) and height of radar measurements ( H ). For the implementation of Melting Layer recognition, the study employs the dual polarized signatures from the 3 GHz Chilbolton Advanced Meteorological Radar (CAMRA). Furthermore, a simple but effective averaging procedure for Melting level estimation from a volume RHI scan is proposed. The proposed scheme has been evaluated with Weather Research and Forecasting (WRF) model simulated and radio soundings retrieved Melting level height over a total of 84 RHI scan-based bright band cases. The results confirm that the estimated Melting level heights from the proposed method are in good agreement with the WRF model and radio sounding observations. The 3 GHz radar Melting level height estimates correspond with the R ^2 and RMSE values of 0.92 and 0.24 km, respectively, when compared to the radio soundings, and 0.93 and 0.21 km, respectively, when compared to the WRF model results. Moreover, the related R ^2 and RMSE values are reported as 0.93 and 0.22 km respectively between the WRF and radio soundings retrievals. This implies that the downscaled WRF modelled Melting level height may also be used for operational or research needs.
V. Chandrasekar - One of the best experts on this subject based on the ideXlab platform.
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hydrometeor profile characterization and drop size distribution retrieval algorithms for global precipitation measurement mission
International Geoscience and Remote Sensing Symposium, 2013Co-Authors: V. ChandrasekarAbstract:The dual-frequency precipitation radar (DPR) on board GPM core satellite collects Ku and Ka band vertical profiles which allow us to investigate the microphysics using the difference between two frequency observations (measured dual frequency ratio or DFRm). DFRm has been shown in the literature to be rich in information and can be used to perform Melting Layer detection and estimate drop size distribution (DSD) parameters. This paper summarizes the candidate algorithms to perform Melting Layer detection and DSD retrieval for GPM-DPR. Hurricane Earl observations collected by airborne precipitation radar were used to demonstrate the application.
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hydrometeor profile characterization method for dual frequency precipitation radar onboard the gpm
IEEE Transactions on Geoscience and Remote Sensing, 2013Co-Authors: V. ChandrasekarAbstract:Profile classification is a critical module in the microphysics retrieval algorithm for the dual-frequency precipitation radar (DPR) that will be onboard the Global Precipitation Measurement (GPM) Core satellite. Hydrometeor profile characterization (HPC or Melting region detection) is an important part of profile classification. To accomplish this classification, characteristics of measured dual-frequency ratio DFRm, defined as the difference between measured reflectivity at two frequency channels (Ku- and Ka-bands), were studied for different hydrometeor phases. This paper shows that a DFRm profile can be used to detect the frozen, mixed-phase, and liquid regions. An HPC model is developed in this paper for DPR profile classification using DFRm and its range variability along the height. Data collected by the Second Generation Airborne Precipitation Radar (APR-2) in NASA African Monsoon Multidisciplinary Analysis, Genesis and Rapid Intensification Processes, and Wakasa Bay campaigns are employed in model validation. Signatures of Doppler velocity, as well as the linear depolarization ratio at Ku-band, available for APR-2 data, are used for cross-validation purpose. Comparison of the Melting Layer top and bottom between the HPC model and the velocity-based estimates shows that they compare well, with a 2% bias. The performance of the HPC method at GPM-DPR observation resolution is evaluated and is shown to be applicable to observation at GPM-DPR resolution. It can be inferred from the analysis presented that the methodology developed in this paper using DFRm is a good candidate for HPC for GPM-DPR.
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a new technique to categorize and retrieve the microphysical properties of ice particles above the Melting Layer using radar dual polarization spectral analysis
Journal of Atmospheric and Oceanic Technology, 2008Co-Authors: A Spek, V. Chandrasekar, H W J Russchenberg, Christine Unal, Dmitri Moisseev, Y DufournetAbstract:Abstract In this study, a dual-polarization spectral analysis for retrieval of microphysical properties of ice hydrometeors is developed. It is shown that, by using simultaneous Doppler polarimetric observations taken at a 45° elevation angle, it is possible to discriminate between different types of ice particles. Particle size distribution parameters for maximally two dominating types of ice particles (aggregates and plates) observed above the Melting Layer are retrieved. Prior to the retrieval algorithm, a selection of possible types of ice particles based on environmental conditions is carried out. The retrieval procedure is based on a least squares optimization that simultaneously minimizes fit residuals in a Doppler power spectrum and spectral differential reflectivity. The proposed method is illustrated on transportable atmospheric radar (TARA) observations of stratiform rain collected on 19 September 2001 at Cabauw, Netherlands.
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Hydrometeor classification system using dual-polarization radar measurements: model improvements and in situ verification
IEEE Transactions on Geoscience and Remote Sensing, 2005Co-Authors: V. Chandrasekar, V. N. BringiAbstract:A hydrometeor classification system based on a fuzzy logic technique using dual-polarization radar measurements of precipitation is presented. In this study, five dual-polarization radar measurements (namely horizontal reflectivity, differential reflectivity, specific differential phase, correlation coefficient, and linear depolarization ratio) and altitude relating to environmental Melting Layer are used as input variables of the system. The hydrometeor classification system chooses one of nine different hydrometeor categories as output. The system presented in this paper is a further development of an existing hydrometeor classification system model developed at Colorado State University (CSU). The hydrometeor classification system is evaluated by comparing inferred results from the CSU CHILL Facility dual-polarization radar measurements with the in situ sample data collected by the T-28 aircraft during the Severe Thunderstorm Electrification and Precipitation Study.
Sergey Y Matrosov - One of the best experts on this subject based on the ideXlab platform.
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assessment of radar signal attenuation caused by the Melting hydrometeor Layer
IEEE Transactions on Geoscience and Remote Sensing, 2008Co-Authors: Sergey Y MatrosovAbstract:Attenuation of radar signals by Melting hydrometeors is studied using modeling approaches and comparisons of simulated and observed results. In spite that the Melting Layer in precipitating systems is usually relatively thin ( ~ 500 m), this attenuation can be substantial at X-band frequencies for low elevation angles and at millimeter-wavelength frequencies that are used by the U.S. Department of Energy's Atmospheric Radiation Measurement Program and CloudSat radars operating at vertical/nadir incidence. Melting Layer attenuation is stronger than the attenuation in the resultant rain at comparable path lengths and needs to be accounted for in remote sensing methods that use radar reflectivity measurements for retrieving cloud and precipitation parameters if the radar beam penetrates this Layer. The choice of the mixing rule for calculating dielectric constants of Melting hydrometeors determines, to a significant degree, the magnitude of the modeled attenuation values. A relatively simple Wiener mixing rule provides results that are consistent with Melting Layer reflectivity enhancements and attenuation estimates from the X-band radar observations. The total Melting Layer attenuation A is related to the resultant rain rate R in an approximately linear manner at X- and Kalpha-band frequencies, whereas at W-band, the Melting Layer attenuation increase with rain rate is slower due to strong non-Rayleigh scattering effects. Typical A-R relations are suggested, and the variability of these relations is discussed. This paper is mostly concerned with precipitating systems associated with snowflakes that are unrimed or only slightly rimed above the freezing level, as indicated by relatively low values of vertical Doppler velocities.
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cloudsat spaceborne 94 ghz radar bright bands in the Melting Layer an attenuation driven upside down lidar analog
Geophysical Research Letters, 2007Co-Authors: Kenneth Sassen, Sergey Y Matrosov, James R CampbellAbstract:[1] The CloudSat satellite supports a W-band (94 GHz) cloud profiling radar. At this 3.2 mm wavelength, ground-based measurements of rainfall associated with Melting snowflakes do not show the radar reflectivity peak that is characteristic of bright band measurements at longer (Rayleigh scattering-dominated) wavelengths. Nonetheless, examination of downward-looking CloudSat returns in precipitation often indicate an obvious signal peak in the Melting region. Through Melting Layer microphysical and scattering model simulations, we demonstrate that this downward-viewing radar feature is analogous to the lidar bright band observed from the ground in that it owes its existence to strong attenuation. In the upward-looking lidar case, the strong attenuation comes from large low-density snowflakes. In the downward-looking 94 GHz radar case, it is due to the effects of the greater refractive index of water particles compared to ice: it is comparable to an upside-down lidar bright band. A W-band radar dark band, which contributes to the visibility of the bright band, is shown to be due to attenuation in the snowfall. For comparison, the bright and dark bands for an upward viewing lidar are also modeled: the latter is simulated by a reduction in light backscattering efficiency of ice-containing raindrops.
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a polarimetric radar approach to identify rain Melting Layer and snow regions for applying corrections to vertical profiles of reflectivity
Journal of Applied Meteorology and Climatology, 2007Co-Authors: Sergey Y Matrosov, Kurt A Clark, David E KingsmillAbstract:Abstract This article describes polarimetric X-band radar-based quantitative precipitation estimations (QPE) under conditions of low freezing levels when, even at the lowest possible elevation angles, radar resolution volumes at longer ranges are in Melting-Layer or snow regions while it rains at the ground. A specifically adjusted vertical-profile-of-reflectivity (VPR) approach is introduced. The mean VPR is constructed based on the range–height indicator scans, and the effects of smoothing of brightband (BB) features with range are accounted for. A principal feature of the suggested QPE approach is the determination of the reflectivity BB boundaries and freezing-level heights on a beam-by-beam basis using the copolar correlation coefficient ρhv, which is routinely available from the X-band radar measurements. It is shown that this coefficient provides a robust discrimination among the regions of rain, Melting hydrometeors, and snow. The freezing-level estimates made using ρhv were within 100–200 m from ...
Prashant K. Srivastava - One of the best experts on this subject based on the ideXlab platform.
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sensitivity associated with bright band Melting Layer location on radar reflectivity correction for attenuation at c band using differential propagation phase measurements
Atmospheric Research, 2014Co-Authors: Tanvir Islam, Dawei Han, Miguel A Ricoramirez, Prashant K. SrivastavaAbstract:Abstract The modern rain profiling algorithms in reflectivity (ZH) correction for two way path integrated attenuation (AH) using dual polarization radar at attenuating frequencies rely on differential propagation phase (ΦDP) measurements. To retrieve corrected reflectivity profiles from the measured profiles, these algorithms impose an external constraint in the inversion processes which is provided by total differential phase shifts (∆ΦDP) valid for rain cells only. However, there is a possibility of radar beams propagating through and beyond the bright band/Melting Layer region hence may observe non-rainy cells. In light of this, the present study explores the variation of reflectivity correction in different ∆ΦDP scenarios by varying the rain cells locality by +/− 500 m with respect to the “reference” rain cells location derived from a numerical weather prediction (NWP) model output. To implement this, the well-known ZPHI algorithm from the rain profiling algorithms group is applied to several rainfall events from a C-band dual polarization radar. Before applying the algorithms, a total of 162,415 raindrop spectra have been used to retrieve the algorithm coefficients through T-matrix scattering simulated dual polarized signatures. It is revealed that, in some cases, when the ΦDP profile in an attenuated beam is in increasing gradient near the rain Layer top region, there could be a variation of about 1–2 dB in comparison with the “reference” attenuation corrected reflectivity. Such phenomenon is in accord with the reflectivity statistics when comparing with one neighboring C-band single polarization radar derived reflectivity data. Additionally, the remarkable agreement between the reflectivity profiles lends the applicability of the ZPHI algorithm in the attenuation correction with known rain/Melting Layer information.
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Fuzzy logic based Melting Layer recognition from 3 GHz dual polarization radar: appraisal with NWP model and radio sounding observations
Theoretical and Applied Climatology, 2013Co-Authors: Tanvir Islam, Miguel A. Rico-ramirez, Dawei Han, Michaela Bray, Prashant K. SrivastavaAbstract:The advent of polarimetry makes it possible to categorize hydrometeor inferences more accurately by providing detailed information of the scattering properties. In light of this, the authors have developed a fuzzy logic based system for the recognition of Melting Layer in the atmosphere. The fuzzy system is based on characterizing Melting Layer scatterers from non-Melting scatterers using five crisp inputs, namely, horizontal reflectivity ( Z _H), differential reflectivity ( Z _DR), co-polar correlation coefficient ( ρ _HV), linear depolarization ratio (LDR) and height of radar measurements ( H ). For the implementation of Melting Layer recognition, the study employs the dual polarized signatures from the 3 GHz Chilbolton Advanced Meteorological Radar (CAMRA). Furthermore, a simple but effective averaging procedure for Melting level estimation from a volume RHI scan is proposed. The proposed scheme has been evaluated with Weather Research and Forecasting (WRF) model simulated and radio soundings retrieved Melting level height over a total of 84 RHI scan-based bright band cases. The results confirm that the estimated Melting level heights from the proposed method are in good agreement with the WRF model and radio sounding observations. The 3 GHz radar Melting level height estimates correspond with the R ^2 and RMSE values of 0.92 and 0.24 km, respectively, when compared to the radio soundings, and 0.93 and 0.21 km, respectively, when compared to the WRF model results. Moreover, the related R ^2 and RMSE values are reported as 0.93 and 0.22 km respectively between the WRF and radio soundings retrievals. This implies that the downscaled WRF modelled Melting level height may also be used for operational or research needs.
V. N. Bringi - One of the best experts on this subject based on the ideXlab platform.
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drop size distribution measurements in outer rainbands of hurricane dorian at the nasa wallops precipitation research facility
Atmosphere, 2020Co-Authors: Merhala Thurai, V. N. Bringi, David B Wolff, David A Marks, Charanjit S PablaAbstract:Hurricane rainbands are very efficient rain producers, but details on drop size distributions are still lacking. This study focuses on the rainbands of hurricane Dorian as they traversed the densely instrumented NASA precipitation-research facility at Wallops Island, VA, over a period of 8 h. Drop size distribution (DSD) was measured using a high-resolution meteorological particle spectrometer (MPS) and 2D video disdrometer, both located inside a double-fence wind shield. The shape of the DSD was examined using double-moment normalization, and compared with similar shapes from semiarid and subtropical sites. Dorian rainbands had a superexponential shape at small normalized diameter values similar to those of the other sites. NASA’s S-band polarimetric radar performed range height-indicator (RHI) scans over the disdrometer site, showing some remarkable signatures in the Melting Layer (bright-band reflectivity peaks of 55 dBZ, a dip in the copolar correlation to 0.85 indicative of 12–15 mm wet snow, and a staggering reflectivity gradient above the 0 °C level of −10 dB/km, indicative of heavy aggregation). In the rain Layer at heights < 2.5 km, polarimetric signatures indicated drop break-up as the dominant process, but drops as large as 5 mm were detected during the intense bright-band period.
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separating stratiform and convective rain types based on the drop size distribution characteristics using 2d video disdrometer data
Atmospheric Research, 2016Co-Authors: Merhala Thurai, Patrick Gatlin, V. N. BringiAbstract:Abstract A technique for separating stratiform and convective rain types using the characteristics of two of the main drop size distribution (DSD) parameters is presented. The method was originally developed based on observations from dual-frequency profiler and dual-polarization radar observations in Darwin, Australia. In this paper, we will present the testing of the method using data from 2D video disdrometers (2DVD) from two very different locations, namely, Ontario, Canada, and Huntsville, Alabama, USA. One-minute DSDs from 2DVD are used as input to a gamma-fitting procedure and our separation technique uses the fitted values of log 10 ( N W ) and D 0 (where N W is the scaling parameter and D 0 is the median volume diameter) and an “index” to quantify where the points lie in the log 10 ( N W ) versus D 0 domain. For the Ontario location, the output of the classification is compared with simultaneous observations from a collocated, vertically pointing, X-band Doppler radar. A “bright-band” detection algorithm is used to classify each height profile as either stratiform or convective, depending on whether or not a clearly defined Melting Layer is present at an expected height. If present, the maximum reflectivity within the Melting Layer and the corresponding height are determined. Similar testing is carried out for two events in Huntsville and compared with observations from a collocated UHF profiler (with Doppler capability). Additional case studies are required, but these results indicate our separation technique seems to be applicable to many different locations and climatologies based on previously published data.
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Hydrometeor classification system using dual-polarization radar measurements: model improvements and in situ verification
IEEE Transactions on Geoscience and Remote Sensing, 2005Co-Authors: V. Chandrasekar, V. N. BringiAbstract:A hydrometeor classification system based on a fuzzy logic technique using dual-polarization radar measurements of precipitation is presented. In this study, five dual-polarization radar measurements (namely horizontal reflectivity, differential reflectivity, specific differential phase, correlation coefficient, and linear depolarization ratio) and altitude relating to environmental Melting Layer are used as input variables of the system. The hydrometeor classification system chooses one of nine different hydrometeor categories as output. The system presented in this paper is a further development of an existing hydrometeor classification system model developed at Colorado State University (CSU). The hydrometeor classification system is evaluated by comparing inferred results from the CSU CHILL Facility dual-polarization radar measurements with the in situ sample data collected by the T-28 aircraft during the Severe Thunderstorm Electrification and Precipitation Study.
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polarimetric signatures in the stratiform region of a mesoscale convective system
Journal of Applied Meteorology, 1993Co-Authors: Dusan S. Zrnic, V. N. Bringi, N Balakrishnan, C L Ziegler, K Aydin, T MatejkaAbstract:Four polarimetric measurands were collected in the stratiform region of a mesoscale convective system. The four are the reflectivity factor, the differential reflectivity, the correlation coefficient between orthogonal copolar echoes, and the differential propagation constant. Most striking is a signature of large aggregates (about 10 mm in size) seen in the differential phase through the Melting Layer. Another significant feature is an abrupt notch in the correlation coefficient that occurs towards the bottom of the bright band. Aircraft observations and a one-dimensional cloud model are used to explain some polarimetric measurements and to infer the presence of aggregates, graupel, and supercooled cloud water in the stratiform region. These unique observations and model data provide inferences concerning the presence of graupel and the growth of large aggregates in the Melting Layer.