scholarly journals Correction of Reflectivity in the Presence of Partial Beam Blockage over a Mountainous Region Using X-Band Dual Polarization Radar

2013 ◽  
Vol 14 (3) ◽  
pp. 744-764 ◽  
Author(s):  
Shakti P. C., ◽  
M. Maki ◽  
S. Shimizu ◽  
T. Maesaka ◽  
D.-S. Kim ◽  
...  
Keyword(s):  
Radar Data ◽  
Rain Gauge ◽  
Mountainous Region ◽  
Dual Polarization ◽  
Mountainous Regions ◽  
Ground Clutter ◽  
X Band ◽  
Elevation Model ◽  
Reflectivity Data ◽  
Good Agreement

Abstract Two approaches to correcting the partial beam blockage of radar reflectivity in mountainous areas were evaluated using X-band dual polarization radar data from the Hakone mountain region, Kanto, Japan. The comparatively simple digital elevation model (DEM) method calculates the power loss in the received signal based on the geometrical relationship between radar beams and a DEM. The second approach, the modified DEM method, attempts to account for unknown power losses related to ground clutter, hardware calibration errors, etc. Comparison between ground data and reflectivity data corrected by both methods suggests that the DEM method alone was insufficient to correct beam blockage problems but that the modified DEM data were in generally good agreement with the ground data. The authors also estimated 10-min rainfall amounts using reflectivity corrected by the modified DEM method and compared these with data from a network of rain gauges in the mountainous region. In general, the results show good agreement between radar estimates and rain gauge measurements. On the basis of their results, the authors conclude that the modified DEM method offers a suitable solution to the problem of beam blockage in mountainous regions, provided that the beam blockage rate is less than 80%.

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 Precipitation Classification and Quantification Using X-Band Dual-Polarization Weather Radar: Application in the Hydrometeorology Testbed

2013 ◽  
Vol 30 (9) ◽  
pp. 2108-2120 ◽  
Author(s):  
S. Lim ◽  
R. Cifelli ◽  
V. Chandrasekar ◽  
S. Y. Matrosov
Keyword(s):  
Quality Control ◽  
Phase Retrieval ◽  
Estimation Method ◽  
Rain Gauge ◽  
Dual Polarization ◽  
Rainfall Estimation ◽  
Differential Phase ◽  
Melting Region ◽  
X Band ◽  
Fuzzy Logic Technique

Abstract This paper presents new methods for rainfall estimation from X-band dual-polarization radar observations along with advanced techniques for quality control, hydrometeor classification, and estimation of specific differential phase. Data collected from the Hydrometeorology Testbed (HMT) in orographic terrain of California are used to demonstrate the methodology. The quality control and hydrometeor classification are specifically developed for X-band applications, which use a “fuzzy logic” technique constructed from the magnitude of the copolar correlation coefficient and the texture of differential propagation phase. In addition, an improved specific differential phase retrieval and rainfall estimation method are also applied. The specific differential phase estimation is done for both the melting region and rain region, where it uses a conventional filtering method for the melting region and a self-consistency-based method that distributes the total differential phase consistent with the reflectivity factor for the rain region. Based on the specific differential phase, rainfall estimations were computed using data obtained from the NOAA polarimetric X-band radar for hydrometeorology (HYDROX) and evaluated using HMT rain gauge observations. The results show that the methodology works well at capturing the high-frequency rainfall variations for the events analyzed herein and can be useful for mountainous terrain applications.

scholarly journals Rain-Rate Estimation in the Presence of Hail Using S-Band Specific Differential Phase and Other Radar Parameters

1995 ◽  
Vol 34 (2) ◽  
pp. 404-410 ◽  
Author(s):  
K. Aydin ◽  
V. N. Bringi ◽  
L. Liu
Keyword(s):  
Rain Rate ◽  
Rain Gauge ◽  
Heavy Rainfall Event ◽  
Rain Gauge Data ◽  
Differential Phase ◽  
X Band ◽  
Gauge Data ◽  
Radar Measurements ◽  
Multiparameter Radar ◽  
Good Agreement

Abstract Multiparameter radar measurements were made during a heavy rainfall event accompanied by hail in Colorado. Rainfall rates R and accumulation Σ for this event were estimated using S-band specific differential phase KDP, reflectivity factor ZH, and X-band specific attenuation AH3. These estimates were compared with measurements from a ground-based rain gauge. Both R–KDP and R–AH3 relations were in good agreement with the rain gauge data, that is, less than 10% difference in the rainfall accumulations. The R–Z relation produced similar results only when ZH was truncated at 55 dBZ. This study demonstrates the potential of KDP for estimating rainfall rates in severe storms that may have rain-hail mixtures.

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 Multifractal Comparison of Reflectivity and Polarimetric Rainfall Data from C- and X-Band Radars and Respective Hydrological Responses of a Complex Catchment Model

2017 ◽  
Author(s):  
Igor Paz ◽  
Bernard Willinger ◽  
Auguste Gires ◽  
Laurent Monier ◽  
Christophe Zobrist ◽  
...  
Keyword(s):  
Hydrological Model ◽  
Radar Data ◽  
Rain Gauge ◽  
Distributed Hydrological Model ◽  
Space Resolution ◽  
Rain Gauges ◽  
X Band ◽  
Distributed Simulations ◽  
Rain Gauge Network ◽  
Catchment Model

This paper presents a comparison between rain gauges, C-band and X-band radar data over an instrumented and regulated catchment of the Paris region, as well as their respective hydrological impacts with the help of flow observations and a semi-distributed hydrological model. Both radars confirm the high spatial variability of the rainfall down to their space resolution (respectively one kilometer and 250 m) and therefore underscore limitations of semi-distributed simulations. The use of the polarimetric capacity of the Météo-France C-band radar was limited to corrections of the horizontal reflectivity and its rainfall estimates are adjusted with the help of a rain gauge network. On the contrary, neither calibration was performed for the polarimetric X-band radar of the Ecole des Ponts ParisTech (below called ENPC X-band radar), nor any optimization of its scans. In spite of that and the non-negligible fact that the catchment was much closer to the C-band radar than to the X-band radar (20 km vs. 40 km), the latter seems to perform at least as well as the former, but with a higher scale resolution. This characteristic was best highlighted with the help of a multifractal analysis of the respective radar data, which also shows that the X-band radar was able to pick up a few extremes that were smoothed out by the C-band radar.

scholarly journals Validation of SRTM X Band DEM over Himalayan Mountain

2014 ◽  
Vol XL-4 ◽  
pp. 71-74 ◽  
Author(s):  
R. D. Gupta ◽  
M. K. Singh ◽  
S. Snehmani ◽  
A. Ganju
Keyword(s):  
High Resolution ◽  
Accuracy Assessment ◽  
Mountainous Regions ◽  
Digital Elevation ◽  
X Band ◽  
Global Positioning ◽  
Himalayan Mountain ◽  
Elevation Model ◽  
First Time ◽  
The Himalaya

The present research study assesses the accuracy of the SRTM X band DEM with respect to high accuracy photogrammetric Digital Elevation Model (DEM) for parts of the Himalaya. The high resolution DEM was generated for Manali and nearby areas using digital aerial photogrammetric survey data of 40 cm Ground Sampling Distance (GSD) captured through airborne ADS80 pushbroom camera for the first time in Indian Himalayan context. This high resolution DEM was evaluated with Differential Global Positioning System (DGPS) points for accuracy assessment. The ADS80-DEM gave root mean square error (RMSE) of ~<1m and linear error of 1.60 m at 90 % confidence (LE 90) when compared with the DGPS points. The overall RMSE in vertical accuracy was 73.36 m while LE 90 was 75.20 m with regard to ADS80 DEM. It is observed that the accuracy achieved for part of Himalayan region is far less as compared to the values officially claimed. Thus, SRTM X band DEM should be used with due care in mountainous regions of Himalaya.

scholarly journals Geostatistical Merging of a Single-Polarized X-Band Weather Radar and a Sparse Rain Gauge Network over an Urban Catchment

Atmosphere ◽  
2018 ◽  
Vol 9 (12) ◽  
pp. 496 ◽  
Author(s):  
Ibrahim Seck ◽  
Joël Van Baelen
Keyword(s):  
Mean Field ◽  
Radar Data ◽  
Rain Gauge ◽  
Rain Gauge Data ◽  
Rain Gauges ◽  
X Band ◽  
Distance Weighting ◽  
Field Bias ◽  
The Mean ◽  
Inverse Distance

Optimal Quantitative Precipitation Estimation (QPE) of rainfall is crucial to the accuracy of hydrological models, especially over urban catchments. Small-to-medium size towns are often equipped with sparse rain gauge networks that struggle to capture the variability in rainfall over high spatiotemporal resolutions. X-band Local Area Weather Radars (LAWRs) provide a cost-effective solution to meet this challenge. The Clermont Auvergne metropolis monitors precipitation through a network of 13 rain gauges with a temporal resolution of 5 min. 5 additional rain gauges with a 6-minute temporal resolution are available in the region, and are operated by the national weather service Météo-France. The LaMP (Laboratoire de Météorologie Physique) laboratory’s X-band single-polarized weather radar monitors precipitation as well in the region. In this study, three geostatistical interpolation techniques—Ordinary kriging (OK), which was applied to rain gauge data with a variogram inferred from radar data, conditional merging (CM), and kriging with an external drift (KED)—are evaluated and compared through cross-validation. The performance of the inverse distance weighting interpolation technique (IDW), which was applied to rain gauge data only, was investigated as well, in order to evaluate the effect of incorporating radar data on the QPE’s quality. The dataset is comprised of rainfall events that occurred during the seasons of summer 2013 and winter 2015, and is exploited at three temporal resolutions: 5, 30, and 60 min. The investigation of the interpolation techniques performances is carried out for both seasons and for the three temporal resolutions using raw radar data, radar data corrected from attenuation, and the mean field bias, successively. The superiority of the geostatistical techniques compared to the inverse distance weighting method was verified with an average relative improvement of 54% and 31% in terms of bias reduction for kriging with an external drift and conditional merging, respectively (cross-validation). KED and OK performed similarly well, while CM lagged behind in terms of point measurement QPE accuracy, but was the best method in terms of preserving the observations’ variance. The correction schemes had mixed effects on the multivariate geostatistical methods. Indeed, while the attenuation correction improved KED across the board, the mean field bias correction effects were marginal. Both radar data correction schemes resulted in a decrease of the ability of CM to preserve the observations variance, while slightly improving its point measurement QPE accuracy.

scholarly journals Nowcasting Rainfall Fields Derived from Specific Differential Phase

2012 ◽  
Vol 51 (11) ◽  
pp. 1950-1959 ◽  
Author(s):  
Evan Ruzanski ◽  
V. Chandrasekar
Keyword(s):  
Lead Time ◽  
Skill Score ◽  
Rain Gauge ◽  
Differential Phase ◽  
Adaptive Sensing ◽  
Radar Network ◽  
X Band ◽  
The Difference ◽  
Reflectivity Data ◽  
Automated Forecasting

AbstractShort-term automated forecasting (nowcasting) of precipitation has traditionally been done using radar reflectivity data; recent research, however, indicates that using specific differential phase Kdp has several advantages over using reflectivity for estimating rainfall. This paper presents an evaluation of the characteristics of nowcasting Kdp-based rainfall fields using the Collaborative Adaptive Sensing of the Atmosphere Kdp estimation and nowcasting methods applied to approximately 42 h of X-band radar network data. The results show that Kdp-based rainfall fields exhibit lifetimes of ~17 min as compared with ~15 min for rainfall fields derived from reflectivity Zh in a continuous (cross correlation based) sense. Categorical (skill score based) lifetimes of ~26 min were observed for Kdp-based rainfall fields as compared with ~30 min for Zh-based rainfall fields. Radar–rain gauge verification showed that Kdp-based rainfall estimates consistently outperformed Zh-based estimates out to a lead time of 30 min, but the difference between the two estimators decreased in terms of normalized standard error with increasing lead time.

scholarly journals Precipitation and Microphysical Processes Observed by Three Polarimetric X-Band Radars during HOPE

2016 ◽  
Author(s):  
Xinxin Xie ◽  
Raquel Evaristo ◽  
Clemens Simmer ◽  
Jan Handwerker ◽  
Silke Troemel
Keyword(s):  
Daily Rainfall ◽  
Rain Gauge ◽  
The Other ◽  
High Definition ◽  
Rain Gauges ◽  
X Band ◽  
Independent Observations ◽  
Microphysical Processes ◽  
Close Distance ◽  
Good Agreement

Abstract. This study presents a first analysis of precipitation and related microphysical processes observed by three polarimetric X-band Doppler radars (BoXPol, JuXPol and KiXPol) in conjunction with a ground-based network of disdrometers, rain gauges and vertically pointing micro rain radars (MRR) during the High Definition Clouds and Precipitation for advancing Climate Prediction (HD(CP)2) Observational Prototype Experiment (HOPE) during April and May 2013 in Germany. While JuXPol and KiXPol were continuously observing the central HOPE area near Forschungszentrum Juelich at a close distance, BoXPol observed the area from a distance of about 48.5 km. MRRs were deployed in the central HOPE area and one MRR close to BoXPol in Bonn, Germany. Seven disdrometers and three rain gauges providing point precipitation observations were deployed at five locations within a 5×5 km2 region, while another three disdrometers were collocated with the MRR in Bonn. The daily rainfall accumulation at each rain gauge/disdrometer location estimated from the three X-band polarimetric radar observations showed a very good agreement. Accompanying microphysical processes during the evolution of precipitation systems were well captured by the polarimetric X-band radars and corroborated by independent observations from the other ground-based instruments.

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