scholarly journals X-band dual-polarized radar quantitative precipitation estimate analyses in the Midwestern United States

2017 ◽  
Author(s):  
Micheal J. Simpson ◽  
Neil I. Fox
Keyword(s):  
Ground Truth ◽  
Cost Effective ◽  
Radar Data ◽  
Radar Rainfall ◽  
Differential Phase Shift ◽  
Weather Radars ◽  
X Band ◽  
Precipitation Estimation ◽  
Estimate Quality ◽  
Radar Rainfall Estimate

Abstract. Over the past decade, polarized weather radars have been at the forefront of the search for a replacement of estimating precipitation over the spatially, and temporally inferior tipping buckets. However, many radar-coverage gaps exist within the Continental US (CONUS), proposing a dilemma in that radar rainfall estimate quality degrades with range. One possible solution is that of X-band weather radars. However, the literature as to their long-term performance is lacking. Therefore, the overarching objective of the current study was to analyze two year’s worth of radar data from the X-band dualpolarimetric MZZU radar in central Missouri at four separate ranges from the radar, utilizing tippingbuckets as ground-truth precipitation data. The conventional R(Z)-Convective equation, in addition to several other polarized algorithms, consisting of some combinations of reflectivity (Z), differential reflectivity (ZDR), and the specific differential phase shift (KDP) were used to estimate rainfall. Results indicated that the performance of the algorithms containing ZDR were superior in terms of the normalized standard error (NSE), missed and false precipitation amounts, and the overall precipitation errors. Furthermore, the R(Z,ZDR) and R(ZDR,KDP) algorithms were the only ones which reported NSE values below 100 %, whereas R(Z) and R(KDP) equations resulted in false precipitation amounts equal to or greater than 65 % of the total gauge recorded rainfall amounts. The results show promise in the utilization of the smaller, more cost-effective X-band radars in terms of quantitative precipitation estimation at ranges from 30 to 80 km from the radar.

scholarly journals Optimization of X-Band Radar Rainfall Retrieval in the Southern Andes of Ecuador Using a Random Forest Model

2019 ◽  
Vol 11 (14) ◽  
pp. 1632 ◽  
Author(s):  
Johanna Orellana-Alvear ◽  
Rolando Célleri ◽  
Rütger Rollenbeck ◽  
Jörg Bendix
Keyword(s):  
Random Forest ◽  
Correlation Coefficient ◽  
Radar Data ◽  
Rain Gauge ◽  
High Mountain ◽  
Radar Rainfall ◽  
Site Specific ◽  
High Attenuation ◽  
X Band ◽  
Precipitation Estimation

Despite many efforts of the radar community, quantitative precipitation estimation (QPE) from weather radar data remains a challenging topic. The high resolution of X-band radar imagery in space and time comes with an intricate correction process of reflectivity. The steep and high mountain topography of the Andes enhances its complexity. This study aims to optimize the rainfall derivation of the highest X-band radar in the world (4450 m a.s.l.) by using a random forest (RF) model and single Plan Position Indicator (PPI) scans. The performance of the RF model was evaluated in comparison with the traditional step-wise approach by using both, the Marshall-Palmer and a site-specific Z–R relationship. Since rain gauge networks are frequently unevenly distributed and hardly available at real time in mountain regions, bias adjustment was neglected. Results showed an improvement in the step-wise approach by using the site-specific (instead of the Marshall-Palmer) Z–R relationship. However, both models highly underestimate the rainfall rate (correlation coefficient < 0.69; slope up to 12). Contrary, the RF model greatly outperformed the step-wise approach in all testing locations and on different rainfall events (correlation coefficient up to 0.83; slope = 1.04). The results are promising and unveil a different approach to overcome the high attenuation issues inherent to X-band radars.

A Comparative Study of Rainfall Retrievals Based on Specific Differential Phase Shifts at X- and S-Band Radar Frequencies

2006 ◽  
Vol 23 (7) ◽  
pp. 952-963 ◽  
Author(s):  
Sergey Y. Matrosov ◽  
Robert Cifelli ◽  
Patrick C. Kennedy ◽  
Steven W. Nesbitt ◽  
Steven A. Rutledge ◽  
...  
Keyword(s):  
Comparative Study ◽  
Radar Data ◽  
Drop Diameter ◽  
Horizontal Polarization ◽  
Differential Phase Shift ◽  
Phase Measurements ◽  
Differential Phase ◽  
X Band ◽  
Raindrop Size ◽  
Differential Reflectivity

Abstract A comparative study of the use of X- and S-band polarimetric radars for rainfall parameter retrievals is presented. The main advantage of X-band polarimetric measurements is the availability of reliable specific differential phase shift estimates, KDP, for lighter rainfalls when phase measurements at the S band are too noisy to produce usable KDP. Theoretical modeling with experimental raindrop size distributions indicates that due to some non-Rayleigh resonant effects, KDP values at a 3.2-cm wavelength (X band) are on average a factor of 3.7 greater than at 11 cm (S band), which is a somewhat larger difference than simple frequency scaling predicts. The non-Rayleigh effects also cause X-band horizontal polarization reflectivity, Zeh, and differential reflectivity, ZDR, to be larger than those at the S band. The differences between X- and S-band reflectivities can exceed measurement uncertainties for Zeh starting approximately at Zeh &gt; 40 dBZ, and for ZDR when the mass-weighted drop diameter, Dm, exceeds about 2 mm. Simultaneous X- and S-band radar measurements of rainfall showed that consistent KDP estimates exceeding about 0.1° km−1 began to be possible at reflectivities greater than ∼26–30 dBZ while at the S band such estimates can generally be made if Zeh &gt; ∼35–39 dBZ. Experimental radar data taken in light-to-moderate stratiform rainfalls with rain rates R in an interval from 2.5 to 15 mm h−1 showed availability of the KDP-based estimates of R for most of the data points at the X band while at the S band such estimates were available only for R greater than about 8–10 mm h−1. After correcting X-band differential reflectivity measurements for differential attenuation, ZDR measurements at both radar frequency bands were in good agreement with each other for Dm &lt; 2 mm, which approximately corresponds to ZDR ≈ 1.6 dB. The ZDR-based retrievals of characteristic raindrop sizes also agreed well with in situ disdrometer measurements.

scholarly journals The New French Operational Polarimetric Radar Rainfall Rate Product

2013 ◽  
Vol 52 (8) ◽  
pp. 1817-1835 ◽  
Author(s):  
Jordi Figueras i Ventura ◽  
Pierre Tabary
Keyword(s):  
Radar Data ◽  
Rain Gauge ◽  
Rainfall Rate ◽  
Superior Performance ◽  
Radar Rainfall ◽  
Rain Gauge Data ◽  
Frequency Bands ◽  
Radar Network ◽  
Significant Events ◽  
X Band

AbstractIn 2012 the Météo France metropolitan operational radar network consists of 24 radars operating at C and S bands. In addition, a network of four X-band gap-filler radars is being deployed in the French Alps. The network combines polarimetric and nonpolarimetric radars. Consequently, the operational radar rainfall algorithm has been adapted to process both polarimetric and nonpolarimetric data. The polarimetric processing chain is available in two versions. In the first version, now operational, polarimetry is only used to correct for attenuation and filter out clear-air echoes. In the second version there is a more extensive use of polarimetry. In particular, the specific differential phase Kdp is used to estimate rainfall rate in intense rain. The performance of the three versions of radar rainfall algorithms (conventional, polarimetric V1, and polarimetric V2) at different frequency bands (S, C, and X) is evaluated by processing radar data of significant events offline and comparing hourly radar rainfall accumulations with hourly rain gauge data. The results clearly show a superior performance of the polarimetric products with respect to the nonpolarimetric ones at all frequency bands, but particularly at higher frequency. The second version of the polarimetric product, which makes a broader use of polarimetry, provides the best overall results.

scholarly journals Influence of the Subgrid Variability of the Raindrop Size Distribution on Radar Rainfall Estimators

2012 ◽  
Vol 51 (4) ◽  
pp. 780-785 ◽  
Author(s):  
Joël Jaffrain ◽  
Alexis Berne
Keyword(s):  
Size Distribution ◽  
Rain Rate ◽  
Power Laws ◽  
Radar Data ◽  
Sampling Uncertainty ◽  
Radar Rainfall ◽  
Differential Phase Shift ◽  
Raindrop Size Distribution ◽  
Raindrop Size ◽  
Pixel Scale

AbstractThis work aims at quantifying the variability of the parameters of the power laws used for rain-rate estimation from radar data, on the basis of raindrop size distribution measurements over a typical weather radar pixel. Power laws between the rain rate and the reflectivity or the specific differential phase shift are fitted to the measured values, and the variability of the parameters is analyzed. At the point scale, the variability within this radar pixel cannot be solely explained by the sampling uncertainty associated with disdrometer measurements. When parameters derived from point measurements are applied at the radar pixel scale, the resulting error in the rain amount varies between −2% and +15%.

Investigation of the relationship between differential phase shift and path integrated attenuation in the melting layer of precipitation of X-band radar

2021 ◽  
Author(s):  
Anil Kumar Khanal ◽  
Guy Delrieu ◽  
Brice Boudevillain ◽  
Frédéric Cazenave ◽  
Nan Yu
Keyword(s):  
Phase Shift ◽  
Complex Terrain ◽  
High Mountain ◽  
Differential Phase Shift ◽  
Melting Layer ◽  
Differential Phase ◽  
Quantitative Precipitation Estimation ◽  
X Band ◽  
Precipitation Estimation ◽  
The Relationship

&lt;p&gt;The RadAlp experiment at the Grenoble region in the French Alps aims to advance the radar remote sensing techniques of precipitation in high mountain regions. Since 2016, two dual-polarimetric X-band radars, one on top of Mt Moucherotte (1901 m asl) and another in the Grenoble valley (220 m asl) are operated by Metro France and IGE respectively. High spatio-temporal variability of precipitation (e.g. intensity and phase) in the complex terrain requires high-resolution observations. X-band radar provides high spatial and temporal resolution imagery which makes it ideal for use in complex terrain but also comes with significant attenuation problems during heavy precipitation and in the melting layer (ML). The development of polarimetric techniques, especially differential phase shift (&amp;#981;DP) has helped to mitigate the power signal attenuation problem to a certain extent. The &amp;#981;DP is immune to attenuation due to rainfall, radar calibration errors and partial beam blockage, making it an attractive parameter for quantitative precipitation estimation (QPE) through attenuation correction of the reflectivity (Z). The &amp;#981;DP, however, is quite noisy and requires regularization. An iterative algorithm based on maximum allowed step sizes provides a robust solution in &amp;#981;DP regularization. In this study, we aim to understand the relationship between differential phase shift (&amp;#981;DP) and path integrated attenuation (PIA) at X-band. This relationship is crucial for quantitative precipitation estimation (QPE) using polarimetric techniques. Furthermore, this relationship is still poorly documented within the melting layer due to the complexity of the hydrometeors' distributions in terms of phase, size, shape and density. We use the mountain reference technique (MRT) for direct PIA estimations associated with the decrease in returns from mountain targets during precipitation events as compared to dry periods. The quasi-vertical profiles from the valley-based radar (XPORT) help to identify, characterize and follow the evolution of the melting layer. For the mountaintop radar (MOUC) stratiform events (59 days between Nov 2016 to Dec 2019) where the O&amp;#176; elevation angle beam passes through the melting layer are considered.&amp;#160; The PIA/ &amp;#981;DP ratios at different strata of the ML, snow-ML interface and ML-rain interface are studied. Initial results show that the PIA/ &amp;#981;DP ratio peaks at the levels of cross-correlation coefficient (&amp;#961;HV) minima, remains strong in the upper part of the ML and tends to 0 towards the top of ML. Additionally, its value in rain (0.32 dB per deg) below the ML matches closely with the specific attenuation vs specific phase (k-KDP) relationship (0.29) derived from the disdrometer at ground level.&amp;#160; Its value increases steadily in the lower part of ML (peaks around 0.70 dB per deg), remains strong in the upper part of ML (0.5 - 0.6 dB per degree), and decreases rapidly to 0.13 dB per degree above the ML (in snow).&lt;/p&gt;

X-band Polarimetric Radar Rainfall Measurements in Keys Area Microphysics Project

2006 ◽  
Vol 63 (1) ◽  
pp. 187-203 ◽  
Author(s):  
Emmanouil N. Anagnostou ◽  
Mircea Grecu ◽  
Marios N. Anagnostou
Keyword(s):  
Phase Shift ◽  
Attenuation Correction ◽  
Doppler Radar ◽  
Model Parameters ◽  
Dual Polarization ◽  
Radar Rainfall ◽  
Differential Phase Shift ◽  
Differential Phase ◽  
X Band ◽  
Filter Noise

Abstract The Keys Area Microphysics Project (KAMP), conducted as part of NASA’s Fourth Convective and Moisture Experiment (CAMEX-4) in the lower Keys area, deployed a number of ground radars and four arrays of rain gauge and disdrometer clusters. Among the various instruments is an X-band dual-polarization Doppler radar on wheels (XPOL), contributed by the University of Connecticut. XPOL was used to retrieve rainfall rate and raindrop size distribution (DSD) parameters to be used in support of KAMP science objectives. This paper presents the XPOL measurements in KAMP and the algorithm developed for attenuation correction and estimation of DSD model parameters. XPOL observations include the horizontal polarization reflectivity ZH, differential reflectivity ZDR, and differential phase shift ΦDP. Here, ZH and ZDR were determined to be positively biased by 3 and 0.3 dB, respectively. A technique was also applied to filter noise and correct for potential phase folding in ΦDP profiles. The XPOL attenuation correction uses parameterizations that relate the path-integrated specific (differential) attenuation along a radar ray to the filtered-ΦDP (specific attenuation) profile. Attenuation-corrected ZH and specific differential phase shift (derived from filtered ΦDP profiles) data are then used to derive two parameters of the normalized gamma DSD model, that is, intercept (Nw) and mean drop diameter (D0). The third parameter (shape parameter μ) is calculated using a constrained μ–Λ relationship derived from the measured raindrop spectra. The XPOL attenuation correction is evaluated using coincidental nonattenuated reflectivity fields from the Key West Weather Surveillance Radar-1988 Doppler (WSR-88D), while the DSD parameter retrievals are statistically assessed using DSD parameters calculated from the measured raindrop spectra. Statistics show that XPOL DSD parameter estimation is consistent with independent observations. XPOL estimates of water content and Nw are also shown to be consistent with corresponding retrievals from matched ER-2 Doppler radar (EDOP) profiling observations from the 19 September airborne campaign. Results shown in this paper strengthen the applicability of X-band dual-polarization high resolution observations in cloud modeling and precipitation remote sensing studies.

Comparison of various X-band radar products over the Paris area

2020 ◽  
Author(s):  
Wiam Salih ◽  
Auguste Gires ◽  
Ioulia Tchiguirinskaia ◽  
Daniel Schertzer
Keyword(s):  
Power Law ◽  
Rain Rate ◽  
Dynamic Models ◽  
Weather Conditions ◽  
Radar Data ◽  
Morphological Comparison ◽  
Differential Phase Shift ◽  
X Band ◽  
Wide Range ◽  
Paris Area

&lt;p&gt;Optimized management of storm water management in the Paris area is needed to both avoid urban flooding and maximize water depollution. Such management requires improving the ability to measure and model hydro-meteorological events at the highest possible resolution. Hence, the interest of meteorological radars, given their unique ability to measure rainfall in both space and time.&lt;/p&gt;&lt;p&gt;In this study, we focus on the data collected by a dual polarimetric X-band radar data operated by Ecole des Ponts ParisTech in the framework of the Fresnel Platform is used. The space resolution is of 250 m and the time one is of 3 min and 25 seconds. Seven rainfall events that occurred in 2018 are studied. They cover a wide range of meteorological situations, including hail. More precisely several products are compared; some relying on a simple Marshall Palmer power law relation between the measured reflectivity and the rain rate; and others using the dual polarization capabilities for heavy rainfall through a power law relation between the measured specific differential phase shift and the rain rate. Constant and varying parameters for these laws are tested. In addition, these radar products are compared with various products obtained with a C-band radar operated by Meteo-France and 8 rain gauges. Temporal evolutions of rain rates are compared and classical metrics (Nash Sutcliff, correlation&amp;#8230;) are computed. In addition, outputs of hydro-dynamic models&amp;#8217; simulations using this rainfall data are compared.&lt;/p&gt;&lt;p&gt;It appears that the results strongly depend on rainfall event, and even given peaks, with no clear tendency between the radar products. In addition, a strong dependency on the radar data processing, and especially the coefficients of the radar relation, is found. This suggests that further work should be done to improve their determination for this area and depending on the weather conditions. In addition, this study highlights the need to develop morphological comparison techniques that would be valid not only at a single scale but across scales.&lt;/p&gt;&lt;p&gt;Authors greatly acknowledge support of the chair Hydrology for Chair of Hydrology for Resilient Cities (endowed by Veolia) of the Ecole des Ponts ParisTech.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;

scholarly journals Correction of Radar Reflectivity and Differential Reflectivity for Rain Attenuation at X Band. Part II: Evaluation and Application

2005 ◽  
Vol 22 (11) ◽  
pp. 1633-1655 ◽  
Author(s):  
S-G. Park ◽  
M. Maki ◽  
K. Iwanami ◽  
V. N. Bringi ◽  
V. Chandrasekar
Keyword(s):  
Drop Size ◽  
Earth Science ◽  
Radar Data ◽  
Rain Gauge ◽  
Radar Rainfall ◽  
X Band ◽  
Rain Events ◽  
Differential Reflectivity ◽  
Rainfall Estimates ◽  
Good Agreement

Abstract In this paper, the attenuation-correction methodology presented in Part I is applied to radar measurements observed by the multiparameter radar at the X-band wavelength (MP-X) of the National Research Institute for Earth Science and Disaster Prevention (NIED), and is evaluated by comparison with scattering simulations using ground-based disdrometer data. Further, effects of attenuation on the estimation of rainfall amounts and drop size distribution parameters are also investigated. The joint variability of the corrected reflectivity and differential reflectivity show good agreement with scattering simulations. In addition, specific attenuation and differential attenuation, which are derived in the correction procedure, show good agreement with scattering simulations. In addition, a composite rainfall-rate algorithm is proposed and evaluated by comparison with eight gauges. The radar-rainfall estimates from the uncorrected (or observed) ZH produce severe underestimation, even at short ranges from the radar and for stratiform rain events. On the contrary, the reflectivity-based rainfall estimates from the attenuation-corrected ZH does not show such severe underestimation and does show better agreement with rain gauge measurements. More accurate rainfall amounts can be obtained from a simple composite algorithm based on specific differential phase KDP, with the R(ZH_cor) estimates being used for low rainfall rates (KDP ≤ 0.3° km−1 or ZH_cor ≤ 35 dBZ). This improvement in accuracy of rainfall estimation based on KDP is a result of the insensitivity of the rainfall algorithm to natural variations of drop size distributions (DSDs). The ZH, ZDR, and KDP data are also used to infer the parameters (median volume diameter D0 and normalized intercept parameter Nw) of a normalized gamma DSD. The retrieval of D0 and Nw from the corrected radar data show good agreement with those from disdrometer data in terms of the respective relative frequency histograms. The results of this study demonstrate that high-quality hydrometeorological information on rain events such as rainfall amounts and DSDs can be derived from X-band polarimetric radars.

scholarly journals Toward a Polarimetric Radar Classification Scheme for Coalescence-Dominant Precipitation: Application to Complex Terrain

2017 ◽  
Vol 18 (12) ◽  
pp. 3199-3215 ◽  
Author(s):  
Leonardo Porcacchia ◽  
P. E. Kirstetter ◽  
J. J. Gourley ◽  
V. Maggioni ◽  
B. L. Cheong ◽  
...  
Keyword(s):  
Complex Terrain ◽  
Classification Scheme ◽  
Flash Flood ◽  
Radar Data ◽  
High Elevation ◽  
Rain Gauge ◽  
Polarimetric Radar ◽  
Quantitative Precipitation Estimation ◽  
X Band ◽  
Precipitation Estimation

Abstract Accurate quantitative precipitation estimation over mountainous basins is of great importance because of their susceptibility to natural hazards. It is generally difficult to obtain reliable precipitation information over complex areas because of the scarce coverage of ground observations, the limited coverage from operational radar networks, and the high elevation of the study sites. Warm-rain processes have been observed in several flash flood events in complex terrain regions. While they lead to high rainfall rates from precipitation growth due to collision–coalescence of droplets in the cloud liquid layer, their characteristics are often difficult to identify. X-band mobile dual-polarization radars located in complex terrain areas provide fundamental information at high-resolution and at low atmospheric levels. This study analyzes a dataset collected in North Carolina during the 2014 Integrated Precipitation and Hydrology Experiment (IPHEx) field campaign over a mountainous basin where the NOAA/National Severe Storm Laboratory’s X-band polarimetric radar (NOXP) was deployed. Polarimetric variables are used to isolate collision–coalescence microphysical processes. This work lays the basis for classification algorithms able to identify coalescence-dominant precipitation by merging the information coming from polarimetric radar measurements. The sensitivity of the proposed classification scheme is tested with different rainfall-rate retrieval algorithms and compared to rain gauge observations. Results show the inadequacy of rainfall estimates when coalescence identification is not taken into account. This work highlights the necessity of a correct classification of collision–coalescence processes, which can lead to improvements in quantitative precipitation estimation. Future studies will aim at generalizing this scheme by making use of spaceborne radar data.

scholarly journals Quasi-Vertical Profiles—A New Way to Look at Polarimetric Radar Data

2016 ◽  
Vol 33 (3) ◽  
pp. 551-562 ◽  
Author(s):  
Alexander Ryzhkov ◽  
Pengfei Zhang ◽  
Heather Reeves ◽  
Matthew Kumjian ◽  
Timo Tschallener ◽  
...  
Keyword(s):  
Continuous Monitoring ◽  
Radar Data ◽  
Vertical Profiles ◽  
Remote Sensors ◽  
Weather Radars ◽  
X Band ◽  
Potential Benefits ◽  
High Vertical Resolution ◽  
Microphysical Processes ◽  
Differential Reflectivity

AbstractA novel methodology is introduced for processing and presenting polarimetric data collected by weather surveillance radars. It involves azimuthal averaging of radar reflectivity Z, differential reflectivity ZDR, cross-correlation coefficient ρhv, and differential phase ΦDP at high antenna elevation, and presenting resulting quasi-vertical profiles (QVPs) in a height-versus-time format. Multiple examples of QVPs retrieved from the data collected by S-, C-, and X-band dual-polarization radars at elevations ranging from 6.4° to 28° illustrate advantages of the QVP technique. The benefits include an ability to examine the temporal evolution of microphysical processes governing precipitation production and to compare polarimetric data obtained from the scanning surveillance weather radars with observations made by vertically looking remote sensors, such as wind profilers, lidars, radiometers, cloud radars, and radars operating on spaceborne and airborne platforms. Continuous monitoring of the melting layer and the layer of dendritic growth with high vertical resolution, and the possible opportunity to discriminate between the processes of snow aggregation and riming, constitute other potential benefits of the suggested methodology.

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