Real-Time Adjustment of Range-Dependent Biases in WSR-88D Rainfall Estimates due to Nonuniform Vertical Profile of Reflectivity

Seo, Dong Jun; Breidenbach, Jay P.; Fulton, Richard; Miller, Dennis; O'Bannon, Timothy

doi:10.1175/1525-7541(2000)001<0222:rtaord>2.0.co;2

Cited by 110 publications

(72 citation statements)

References 17 publications

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“…We up to 230 km in range from a radar. While some studies discuss the quality of conventional radar rain estimates at large distances (e.g., Smith et al 1996;Seo et al 2000), the performance of polarimetric methods at distances greater than 100 km has not been well investigated. With few exceptions, the majority of the dual-polarization S-band radar-gauge comparisons have been made for warm-season precipitation and at distances of less than 100 km.…”

Section: Point Arealmentioning

confidence: 99%

The Joint Polarization Experiment: Polarimetric Rainfall Measurements and Hydrometeor Classification

Ryzhkov¹,

Schuur²,

Burgess³

et al. 2005

Bull. Amer. Meteor. Soc.

319

244

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Section: Point Arealmentioning

confidence: 99%

The Joint Polarization Experiment: Polarimetric Rainfall Measurements and Hydrometeor Classification

Ryzhkov¹,

Schuur²,

Burgess³

et al. 2005

Bull. Amer. Meteor. Soc.

319

244

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“…Several studies discuss the quality of conventional rainfall estimation with single-polarization radar to large distances (e.g., Fabry et al 1992;Smith et al 1996;Seo et al 2000;Krajewski and Ciach 2005). To obtain accurate surface rainfall measurements at longer distances, it is necessary to address the impact of meltinglayer and frozen-hydrometeor contamination on radar measurements.…”

Section: Introductionmentioning

confidence: 99%

Estimation of Rainfall Based on the Results of Polarimetric Echo Classification

Giangrande

Ryzhkov

2008

Journal of Applied Meteorology and Climatology

146

110

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The quality of polarimetric radar rainfall estimation is investigated for a broad range of distances from the polarimetric prototype of the Weather Surveillance Radar-1988 Doppler (WSR-88D). The results of polarimetric echo classification have been integrated into the study to investigate the performance of radar rainfall estimation contingent on hydrometeor type. A new method for rainfall estimation that capitalizes on the results of polarimetric echo classification (EC method) is suggested. According to the EC method, polarimetric rainfall relations are utilized if the radar resolution volume is filled with rain (or rain and hail), and multiple R(Z ) relations are used for different types of frozen hydrometeors. The intercept parameters in the R(Z ) relations for each class are determined empirically from comparisons with gauges. It is shown that the EC method exhibits better performance than the conventional WSR-88D algorithm with a reduction by a factor of 1.5-2 in the rms error of 1-h rainfall estimates up to distances of 150 km from the radar.

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“…These numbers should be interpreted in a qualitative sense rather than as a new benchmark. There are several other studies documented in the literature that have evaluated various aspects of the current technology performance (e.g., Smith et al 1996;Baeck and Smith 1998;Young et al 1999;Brandes et al 1999;Westrick et al 1999;Seo et al 2000;Ciach et al 2007) and cumulatively provided a much more comprehensive assessment. Efforts continue to improve operational quantitative precipitation estimation (QPE) products (e.g., Vasiloff et al 2007), likely resulting in better results than those indicated by our simple analysis.…”

Section: Resultsmentioning

confidence: 99%

RADAR-Rainfall Uncertainties

Krajewski¹,

Villarini²,

Smith³

2010

Bull. Amer. Meteor. Soc.

157

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Now is a good time to assess three decades of progress since Jim Wilson and Ed Brandes summarized the operational capability of radar to provide quantitative rainfall estimates with potential applications to hydrology. , and it was a comprehensive attempt to summarize the capabilities of weather radar to provide quantitative estimates of precipitation, which inspired a generation of radar hydrometeorologists in the United States and elsewhere. They discussed the numerous sources of uncertainties associated with radar-based rainfall estimates, including calibration, attenuation, bright band, anomalous propagation, beam blockage, ground clutter and spurious returns, random errors, and variability in the relation between reflectivity Z and rainfall rate R (Z-R relations). The authors also addressed the possible impact of the errors in rain gauge measurements of rainfall and sampling uncertainties (errors resulting from the approximation of an areal estimate using a point measurement). In particular, based on contemporary research (e.g., Huff 1970;Woodley et al. 1975) concerning the spatial sampling error, Wilson and Brandes (1979) reported that it "decreases with increasing area size, increasing time period, increasing gage density, and increasing rainfall amount." Based on more recent research, we have developed quantitative models that reflect how the spatial sampling errors decrease with increasing temporal and decreasing spatial scales, rain gauge network density, and rainfall amount (e.g., Ciach and Krajewski 1999;Zhang et al. 2007;Villarini et al. 2008;Villarini and Krajewski 2008).These uncertainties notwithstanding, Wilson and Brandes foresaw the operational utility of radarrainfall estimation and promoted its use in flash flood forecasting, noting that "radar can be of lifesaving usefulness by alerting forecasters to the potential for flash flooding."In this article, rather than trying to review the (sizable) literature of the different methods of radarrainfall estimation and their accompanying sources of uncertainties, our goal is to answer the question, How much better can we do now versus what was done 30 yr ago? To answer this question, we replicate,

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Real-Time Adjustment of Range-Dependent Biases in WSR-88D Rainfall Estimates due to Nonuniform Vertical Profile of Reflectivity

Cited by 110 publications

References 17 publications

The Joint Polarization Experiment: Polarimetric Rainfall Measurements and Hydrometeor Classification

The Joint Polarization Experiment: Polarimetric Rainfall Measurements and Hydrometeor Classification

Estimation of Rainfall Based on the Results of Polarimetric Echo Classification

RADAR-Rainfall Uncertainties

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