An improved self-consistent approach to attenuation correction for C-band polarimetric radar measurements and its impact on quantitative precipitation estimation

AbstractThe accuracy of rain-rate estimation using polarimetric radar measurements has been improved as a result of better characterization of radar measurement quality and rain microphysics. In the literature, a variety of power-law relations between polarimetric radar measurements and rain rate are described because of the dynamic or varying nature of rain microphysics. A variational technique that concurrently takes into account radar observational error and dynamically varying rain microphysics is proposed in this study. Rain-rate estimation using the variational algorithm that uses event-based observational error and background rain climatological values is evaluated using observing system simulation experiments (OSSE), and its performance is demonstrated in the case of an epic Colorado flood event. The rain event occurred between 11 and 12 September 2013. The results from OSSE show that the variational algorithm with event-based observational error consistently estimates more accurate rain rate than does the “R(ZHH, ZDR)” power-law algorithm. On the contrary, the usage of ad hoc or improper observational error degrades the performance of the variational method. Furthermore, the variational algorithm is less sensitive to the observational error of differential reflectivity ZDR than is the R(ZHH, ZDR) algorithm. The variational quantitative precipitation estimation (QPE) retrieved more accurate rainfall estimation than did the power-law dual-polarization QPE in this particular event, despite the fact that both algorithms used the same dual-polarization radar measurements from the Next Generation Weather Radar (NEXRAD).

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Quantitative Precipitation Estimation with Operational Polarimetric Radar Measurements in Southern China: A Differential Phase–Based Variational Approach

Journal of Atmospheric and Oceanic Technology ◽

10.1175/jtech-d-17-0142.1 ◽

2018 ◽

Vol 35 (6) ◽

pp. 1253-1271 ◽

Cited By ~ 8

Author(s):

Hao Huang ◽

Kun Zhao ◽

Guifu Zhang ◽

Qing Lin ◽

Long Wen ◽

...

Keyword(s):

Variational Approach ◽

Southern China ◽

A Priori ◽

Polarimetric Radar ◽

Random Errors ◽

Differential Phase ◽

Quantitative Precipitation Estimation ◽

Precipitation Estimation ◽

Radar Measurements ◽

The Impact

AbstractQuantitative precipitation estimation (QPE) with polarimetric radar measurements suffers from different sources of uncertainty. The variational approach appears to be a promising way to optimize the radar QPE statistically. In this study a variational approach is developed to quantitatively estimate the rainfall rate (R) from the differential phase (ΦDP). A spline filter is utilized in the optimization procedures to eliminate the impact of the random errors in ΦDP, which can be a major source of error in the specific differential phase (KDP)-based QPE. In addition, R estimated from the horizontal reflectivity factor (ZH) is used in the a priori with the error covariance matrix statistically determined. The approach is evaluated by an idealized case and multiple real rainfall cases observed by an operational S-band polarimetric radar in southern China. The comparative results demonstrate that with a proper range filter, the proposed variational radar QPE with the a priori included agrees well with the rain gauge measurements and proves to have better performance than the other three approaches, that is, the proposed variational approach without the a priori included, the variational approach proposed by Hogan, and the conventional power-law estimator-based approach.

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Uncertainty in Retrieving Raindrop Size Distribution from Polarimetric Radar Measurements

Journal of Atmospheric and Oceanic Technology ◽

10.1175/jtech-d-18-0107.1 ◽

2019 ◽

Vol 36 (4) ◽

pp. 585-605 ◽

Cited By ~ 6

Author(s):

Hao Huang ◽

Guifu Zhang ◽

Kun Zhao ◽

Su Liu ◽

Long Wen ◽

...

Keyword(s):

Size Distribution ◽

Measurement Errors ◽

Distribution Model ◽

Fundamental Parameter ◽

Polarimetric Radar ◽

Quantitative Precipitation Estimation ◽

Raindrop Size Distribution ◽

Precipitation Estimation ◽

Radar Measurements ◽

Raindrop Size

AbstractDrop size distribution (DSD) is a fundamental parameter in rain microphysics. Retrieving DSDs from polarimetric radar measurements extends the capabilities of rain microphysics research and quantitative precipitation estimation. In this study, issues in rain DSD retrieval were studied with simulated and measured data. It was found that a three-parameter gamma distribution model was not suitable for directly retrieving DSD from polarimetric radar measurements. A statistical constraint, such as the shape–slope relation used in the constrained-gamma (C-G) distribution model, helped to reduce the uncertainties and errors in the retrieval. The inclusion of specific differential phase (KDP) measurements resulted in more accurate DSD retrieval and rain physical parameter estimation if the measurement errors were properly characterized in the error minimization analysis (EMA), which was verified using two real precipitation events. The study demonstrated the potential of using full polarimetric radar measurements to improve rain DSD retrieval.

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Polarimetric Radar Quantitative Precipitation Estimation

Radar Hydrology ◽

10.1201/b17921-3 ◽

2018 ◽

pp. 54-79

Keyword(s):

Polarimetric Radar ◽

Quantitative Precipitation Estimation ◽

Precipitation Estimation

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Application of Attenuation Correction to Quantitative Precipitation Estimation on C-Band Weather Radar in Bengkulu

IOP Conference Series Earth and Environmental Science ◽

10.1088/1755-1315/893/1/012054 ◽

2021 ◽

Vol 893 (1) ◽

pp. 012054

Author(s):

M F Handoyo ◽

M P Hadi ◽

S Suprayogi

Keyword(s):

Attenuation Correction ◽

Estimation Error ◽

Weather Radar ◽

Radar Data ◽

Signal Interference ◽

Active System ◽

Estimation Errors ◽

Rain Gauges ◽

Quantitative Precipitation Estimation ◽

Precipitation Estimation

Abstract A weather radar is an active system remote sensing tool that observes precipitation indirectly. Weather radar has an advantage in estimating precipitation because it has a high spatial resolution (up to 0.5 km). Reflectivity generated by weather radar still has signal interference caused by attenuation factors. Attenuation causes the Quantitative Precipitation Estimation (QPE) by the C-band weather radar to underestimate. Therefore attenuation correction on C-band weather radar is needed to eliminate precipitation estimation errors. This study aims to apply attenuation correction to determine Quantitative Precipitation Estimation (QPE) on the c-band weather radar in Bengkulu in December 2018. Gate-by-gate method attenuation correction with Kraemer approach has applied to c-band weather radar data from the Indonesian Agency for Meteorology and Geophysics (BMKG) weather radar network Bengkulu. This method uses reflectivity as the only input. Quantitative Precipitation Estimation (QPE) has obtained by comparing weather radar-based rain estimates to 10 observation rain gauges over a month with the Z-R relation equation. Root Mean Square Error (RMSE) is used to calculate the estimation error. Weather radar data are processed using Python-based libraries Wradlib and ArcGIS 10.5. As a result, the calculation between the weather radar estimate precipitation and the observed rainfall obtained equation Z=2,65R1,3. The attenuation correction process with Kreamer's approach on the c-band weather radar has reduced error in the Qualitative Precipitation Estimation (QPE). Corrected precipitation has a smaller error value (r = 0.88; RMSE = 8.38) than the uncorrected precipitation (r = 0.83; RMSE = 11.70).

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Analysis of Dual-Polarimetric Radar Variables and Quantitative Precipitation Estimators for Landfall Typhoons and Squall Lines Based on Disdrometer Data in Southern China

Atmosphere ◽

10.3390/atmos10010030 ◽

2019 ◽

Vol 10 (1) ◽

pp. 30 ◽

Cited By ~ 3

Author(s):

Yonghua Zhang ◽

Liping Liu ◽

Shuoben Bi ◽

Zhifang Wu ◽

Ping Shen ◽

...

Keyword(s):

Drop Size ◽

Southern China ◽

Average Diameter ◽

Squall Line ◽

Polarimetric Radar ◽

Quantitative Precipitation Estimation ◽

Squall Lines ◽

Fitting Method ◽

Precipitation Estimation ◽

Differential Reflectivity

Typhoon rainstorms often cause disasters in southern China. Quantitative precipitation estimation (QPE) with the use of polarimetric radar can improve the accuracy of precipitation estimation and enhance typhoon defense ability. On the basis of the observed drop size distribution (DSD) of raindrops, a comparison is conducted among the DSD parameters and the polarimetric radar observation retrieved from DSD in five typhoon and three squall line events that occurred in southern China from 2016 to 2017. A new piecewise fitting method (PFM) is used to develop the QPE estimators for landfall typhoons and squall lines. The performance of QPE is evaluated by two fitting methods for two precipitation types using DSD data collected. Findings indicate that the number concentration of raindrops in typhoon precipitation is large and the average diameter is small, while the raindrops in squall line rain have opposite characteristics. The differential reflectivity (ZDR) and specific differential phase (KDP) in these two precipitation types increase slowly with the reflectivity factor (ZH), whereas the two precipitation types have different ZDR and KDP in the same ZH. Thus, it is critical to fit the rainfall estimator for different precipitation types. Enhanced estimation can be obtained using the estimators for specific precipitation types, whether the estimators are derived from the conventional fitting method (CFM) or PFM, and the estimators fitted using the PFM can produce better results. The estimators for the developed polarimetric radar can be used in operational QPE and quantitative precipitation foresting, and they can improve disaster defense against typhoons and heavy rains.

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Characterization of Mediterranean hail-bearing storms using an operational polarimetric X-band radar

Atmospheric Measurement Techniques ◽

10.5194/amt-8-4681-2015 ◽

2015 ◽

Vol 8 (11) ◽

pp. 4681-4698 ◽

Cited By ~ 14

Author(s):

G. Vulpiani ◽

L. Baldini ◽

N. Roberto

Keyword(s):

Phase Shift ◽

Attenuation Correction ◽

Convective System ◽

Polarimetric Radar ◽

Differential Phase Shift ◽

Differential Phase ◽

X Band ◽

Radar Measurements ◽

Storm Characteristics ◽

The City

Abstract. This work documents the effective use of X-band radar observations for monitoring severe storms in an operational framework. Two severe hail-bearing Mediterranean storms that occurred in 2013 in southern Italy, flooding two important Sicilian cities, are described in terms of their polarimetric radar signatures and retrieved rainfall fields. The X-band dual-polarization radar operating inside the Catania airport (Sicily, Italy), managed by the Italian Department of Civil Protection, is considered here. A suitable processing is applied to X-band radar measurements. The crucial procedural step relies on the differential phase processing, being preparatory for attenuation correction and rainfall estimation. It is based on an iterative approach that uses a very short-length (1 km) moving window, allowing proper capture of the observed high radial gradients of the differential phase. The parameterization of the attenuation correction algorithm, which uses the reconstructed differential phase shift, is derived from electromagnetic simulations based on 3 years of drop size distribution (DSD) observations collected in Rome (Italy). A fuzzy logic hydrometeor classification algorithm was also adopted to support the analysis of the storm characteristics. The precipitation field amounts were reconstructed using a combined polarimetric rainfall algorithm based on reflectivity and specific differential phase. The first storm was observed on 21 February when a winter convective system that originated in the Tyrrhenian Sea, marginally hit the central-eastern coastline of Sicily, causing a flash flood in Catania. Due to an optimal location (the system is located a few kilometers from the city center), it was possible to retrieve the storm characteristics fairly well, including the amount of rainfall field at the ground. Extemporaneous signal extinction, caused by close-range hail core causing significant differential phase shift in a very short-range path, is documented. The second storm, on 21 August 2013, was a summer mesoscale convective system that originated from a Mediterranean low pressure system lasting a few hours that eventually flooded the city of Syracuse. The undergoing physical process, including the storm dynamics, is inferred by analyzing the vertical sections of the polarimetric radar measurements. The high registered amount of precipitation was fairly well reconstructed, although with a trend toward underestimation at increasing distances. Several episodes of signal extinction were clearly manifested during the mature stage of the observed supercells.

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Utilization of a C-band Polarimetric Radar for Severe Rainfall Event Analysis in Complex Terrain over Eastern China

Remote Sensing ◽

10.3390/rs11010022 ◽

2018 ◽

Vol 11 (1) ◽

pp. 22 ◽

Cited By ~ 13

Author(s):

Yabin Gou ◽

Yingzhao Ma ◽

Haonan Chen ◽

Jiapeng Yin

Keyword(s):

Eastern China ◽

Liquid Water Content ◽

Feedback Mechanism ◽

Rainfall Event ◽

Event Analysis ◽

Polarimetric Radar ◽

Quantitative Precipitation Estimation ◽

Correction Technique ◽

Precipitation Estimation ◽

Rain Drop

Polarimetric radar measurements and products perform as the cornerstones of modern severe weather warning and nowcast systems. Two radar quantitative precipitation estimation (QPE) frameworks, one based on a radar-gauge feedback mechanism and the other based on standard rain drop size distribution (DSD)-derived rainfall retrieval relationships, are both evaluated and investigated through an extreme severe convective rainfall event that occurred on 23 June 2015 in the mountainous region over eastern China, using the first routinely operational C-band polarimetric radar in China. Complex rainstorm characteristics, as indicated by polarimetric radar observables, are also presented to account for the severe rainfall field center located in the gap between gauge stations. Our results show that (i) the improvements of the gauge-feedback-derived radar QPE estimator can be attributed to the attenuation correction technique and dynamically adjusted Z–R relationships, but it greatly relies on the gauge measurement accuracy. (ii) A DSD-derived radar QPE estimator based on the specific differential phase (KDP) performs best among all rainfall estimators, and the interaction between the mesocyclone and the windward slope of the mountainous terrain can account for its apparent overestimation. (iii) The rainstorm is mainly dominated by small-sized and moderate-sized raindrops, with the mean volume diameter being less than 2 mm, but its KDP column (KDP > 3°·km−1) has a liquid water content that is higher than 2.4815 g·m−3, and a high raindrop concentration (Nw) with log10(Nw) exceeding 5.1 mm−1m−3. In addition, small hailstones falling and melting are also found in this event, which further aggregates Nw upon the severe rainfall center in the gap between gauge stations.

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

Journal of Hydrometeorology ◽

10.1175/jhm-d-17-0016.1 ◽

2017 ◽

Vol 18 (12) ◽

pp. 3199-3215 ◽

Cited By ~ 5

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.

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Using Microwave Backhaul Links to Optimize the Performance of Algorithms for Rainfall Estimation and Attenuation Correction

Journal of Atmospheric and Oceanic Technology ◽

10.1175/jtech-d-14-00016.1 ◽

2014 ◽

Vol 31 (8) ◽

pp. 1748-1760 ◽

Cited By ~ 16

Author(s):

Silke Trömel ◽

Michael Ziegert ◽

Alexander V. Ryzhkov ◽

Christian Chwala ◽

Clemens Simmer

Keyword(s):

Attenuation Correction ◽

Rainfall Estimation ◽

A Algorithm ◽

Quantitative Precipitation Estimation ◽

Microwave Radio ◽

Precipitation Estimation ◽

Raindrop Size ◽

Factor Α ◽

Key Parameter ◽

Ku Band

Abstract The variability in raindrop size distributions and attenuation effects are the two major sources of uncertainty in radar-based quantitative precipitation estimation (QPE) even when dual-polarization radars are used. New methods are introduced to exploit the measurements by commercial microwave radio links to reduce the uncertainties in both attenuation correction and rainfall estimation. The ratio α of specific attenuation A and specific differential phase KDP is the key parameter used in attenuation correction schemes and the recently introduced R(A) algorithm. It is demonstrated that the factor α can be optimized using microwave links at Ku band oriented along radar radials with an accuracy of about 20%–30%. The microwave links with arbitrary orientation can be utilized to optimize the intercepts in the R(KDP) and R(A) relations with an accuracy of about 25%. The performance of the suggested methods is tested using the polarimetric C-band radar operated by the German Weather Service on Mount Hohenpeissenberg in southern Germany and two radially oriented Ku-band microwave links from Ericsson GmbH.

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