Estimation of Rainfall Drop Size Distributions from Dual-Frequency Wind Profiler Spectra Using Deconvolution and a Nonlinear Least Squares Fitting Technique

Schäfer, Robert; Avery, S. K.; May, Peter T.; Rajopadhyaya, Deepak K.; Williams, C. R.

doi:10.1175/1520-0426(2002)019<0864:eordsd>2.0.co;2

Cited by 37 publications

(34 citation statements)

References 20 publications

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“…Given a distinct clear air peak in the observed spectra, D o (and R) can be derived to within an error of 10% for D o < 3 mm (Kobayashi and Adachi). Estimation of the uncertainty in D o and R has been also discussed by Schafer et al (2002).…”

Section: Inter-comparison Of Resultsmentioning

confidence: 99%

“…A quality control procedure to remove such data may be needed. Further improvements in accuracy can only be achieved through use of dual-frequency profiler techniques (e.g., Schafer et al 2002). Finally, one caveat to note is that the C-band attenuation correction and the D o and R retrieval algorithms derived herein are applicable for this particular event and may not apply accurately for other rain regimes and/or climatologies.…”

Section: Discussionmentioning

confidence: 98%

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Rainfall Estimation from C-Band Polarimetric Radar in Okinawa, Japan: Comparisons with 2D-Video Disdrometer and 400 MHz Wind Profiler

Bringi

Thurai

Nakagawa

et al. 2006

Journal of the Meteorological Society of Japan

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This paper presents an inter-comparison of rainfall parameters (median volume diameter and rain rate) using C-band polarimetric radar, a 2D-video disdrometer and a 400 MHz profiler for the Baiu front event of 8-9 June 2005 in Okinawa, Japan. These instruments are part of the Okinawa Sub-Tropical Environment Remote Sensing Center, operated by the National Institute of Information and Communications Technology (NICT). The 2D-video disdrometer is used to derive the mean axis ratio of raindrops versus drop diameter, as well as the drop size distribution for the Baiu event. The data are then used to simulate various relations between polarimetric scattering parameters such as: specific attenuation ðA h Þ, and specific differential attenuation ðA dp Þ, versus specific differential phase ðK dp Þ which are required to correct the measured reflectivity at horizontal polarization ðZ h Þ, and the differential reflectivity ðZ dr Þ for rain attenuation. The 2D-video disdrometer data are also used to arrive at retrieval formulas for median volume diameter ðD o Þ from radar Z dr , and rain rate from radar K dp .The These inter-comparisons demonstrate the accuracy of C-band polarimetric radar to retrieve important rainfall parameters, as well as the accurate correction for rain attenuation using differential propagation phase.

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Section: Inter-comparison Of Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 98%

Rainfall Estimation from C-Band Polarimetric Radar in Okinawa, Japan: Comparisons with 2D-Video Disdrometer and 400 MHz Wind Profiler

Bringi

Thurai

Nakagawa

et al. 2006

Journal of the Meteorological Society of Japan

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“…In this study, the whole solution space is searched to find the global minimum to avoid the possibility of converging to a local minimum in the cost function. The convolution method has been used in many studies including Wakasugi et al (1986Wakasugi et al ( , 1987; Sato et al (1990); Currier et al (1992); Maguire and Avery (1994); Ragopadhyaya et al (1993Ragopadhyaya et al ( , 1998Ragopadhyaya et al ( , 1999; Schafer et al (2002);.…”

Section: Convolution Methodsmentioning

confidence: 99%

“…However, converting radar observations into the DSD domain is an inverse modeling problem and there is not a unique mapping from a given radar observation into a unique DSD. This study uses both the convolution and deconvolution numerical inverse modeling methodologies to estimate the DSD given a set of radar observations (Schafer et al, 2002;Lucas et al, 2004).…”

Section: Introductionmentioning

confidence: 99%

Raindrop size distribution variability estimated using ensemble statistics

Williams

Gage

2009

Ann. Geophys.

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Abstract. Before radar estimates of the raindrop size distribution (DSD) can be assimilated into numerical weather prediction models, the DSD estimate must also include an uncertainty estimate. Ensemble statistics are based on using the same observations as inputs into several different models with the spread in the outputs providing an uncertainty estimate. In this study, Doppler velocity spectra from collocated vertically pointing profiling radars operating at 50 and 920 MHz were the input data for 42 different DSD retrieval models. The DSD retrieval models were perturbations of seven different DSD models (including exponential and gamma functions), two different inverse modeling methodologies (convolution or deconvolution), and three different cost functions (two spectral and one moment cost functions).Two rain events near Darwin, Australia, were analyzed in this study producing 26 725 independent ensembles of massweighted mean raindrop diameter D m and rain rate R. The mean and the standard deviation (indicated by the symbols x and σ {x}) of D m and R were estimated for each ensemble. For small ranges of D m or R , histograms of σ {D m } and σ {R} were found to be asymmetric, which prevented Gaussian statistics from being used to describe the uncertainties. Therefore, 10, 50, and 90 percentiles of σ {D m } and σ {R} were used to describe the uncertainties for small intervals of D m or R . The smallest D m uncertainty occurred for D m between 0.8 and 1.8 mm with the 90th and 50th percentiles being less than 0.15 and 0.11 mm, which correspond to relative errors of less than 20% and 15%, respectively. The uncertainty increased for smaller and larger D m values. The uncertainty of R increased with R . While the 90th percentile uncertainty approached 0.6 mm h −1 for a 2 mm h −1 rain rate (30% relative error), the median uncertainty was less than 0.15 mm h −1 at the same rain rate (less Correspondence to: C. R. Williams (christopher.williams@colorado.edu) than 8% relative error). This study addresses retrieval error and does not attempt to quantify absolute or representativeness errors.

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“…Previous investigators (Wakasugi et al, 1986;Cifelli et al, 2000;Schafer et al, 2002) have utilized combined UHF and VHF wind profiler data to deconvolve the Bragg scattering portion of the observed Doppler spectrum under the simplifying assumption of Gaussian turbulence (Tennekes and Lumley, 1973). Here, we utilize a method first proposed by Teshiba et al (2009) in which the fallspeed relation given by Eq.…”

Section: Vertical Velocity Estimationmentioning

confidence: 99%

Microphysical retrievals from simultaneous polarimetric and profiling radar observations

et al. 2009

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Abstract. The character of precipitation detected at the surface is the final product of many microphysical interactions in the cloud above, the combined effects of which may be characterized by the observed drop size distribution (DSD). This necessitates accurate retrieval of the DSD from remote sensing data, especially radar as it offers large areal coverage, high spatial resolution, and rigorous quality control and testing. Combined instrument observations with a UHF wind profiler, an S-band polarimetric weather radar, and a video disdrometer are analyzed for two squall line events occuring during the calendar year 2007. UHF profiler Doppler velocity spectra are used to estimate the DSD aloft, and are complemented by DSDs retrieved from an exponential model applied to polarimetric data. Ground truth is provided by the disdrometer. A complicating factor in the retrieval from UHF profiler spectra is the presence of ambient air motion, which can be corrected using the method proposed by Teshiba et al. (2009), in which a comparison between idealized Doppler spectra calculated from the DSDs retrieved from KOUN and those retrieved from contaminated wind profiler spectra is performed. It is found that DSDs measured using the distrometer at the surface and estimated using the wind profiler and polarimetric weather radar generally showed good agreement. The DSD retrievals using the wind profiler were improved when the estimates of the vertical wind were included into the analysis, thus supporting the method of Teshiba et al. (2009). Furthermore, the the study presents a method of investigating the time and height structure of DSDs.

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Estimation of Rainfall Drop Size Distributions from Dual-Frequency Wind Profiler Spectra Using Deconvolution and a Nonlinear Least Squares Fitting Technique

Cited by 37 publications

References 20 publications

Rainfall Estimation from C-Band Polarimetric Radar in Okinawa, Japan: Comparisons with 2D-Video Disdrometer and 400 MHz Wind Profiler

Rainfall Estimation from C-Band Polarimetric Radar in Okinawa, Japan: Comparisons with 2D-Video Disdrometer and 400 MHz Wind Profiler

Raindrop size distribution variability estimated using ensemble statistics

Microphysical retrievals from simultaneous polarimetric and profiling radar observations

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