Classification of rain types using drop size distributions and polarimetric radar: Case study of a 2014 flooding event in Korea

You, Cheol‐Hwan; Lee, D.-I.; Kang, Miyoung; Kim, H.-J.

doi:10.1016/j.atmosres.2016.06.024

Cited by 15 publications

(18 citation statements)

References 38 publications

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“…Rainfall is generally classified into stratiform and convective regimes [1][2][3] based on the spatial and temporal scales and vertical velocity of the cloud system [4]. Stratiform rains have relatively weak vertical velocity fields, greater horizontal homogeneity, and lower rainfall intensity, whereas convective rains are associated with strong vertical velocity fields, low areal coverage, and high rainfall intensities [1,5].…”

Section: Introductionmentioning

confidence: 99%

“…Thompson et al [14] also reported that log 10 N w − D 0 relationship was superior to the BR09 method over the equatorial Indian and west Pacific Oceans. You et al [4] (YOU16) proposed a new classification method for Korean climatological precipitation, after comparing the TS96, Bringi et al [15] (BR03), Caracciolo et al [16] (CA08), and BR09 methods.…”

Section: Introductionmentioning

confidence: 99%

“…Korea, in particular, is still lacking in detailed DSDs and rainfall classification information. A few previous studies have concentrated on the south of Korea, either on rainfall classification or rainfall characteristics (e.g., [4,[42][43][44]). However, a comparison between DSD parameters by rainfall types is needed to understand the overall characteristics of rainfall in the central part of Korea.…”

Section: Introductionmentioning

confidence: 99%

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Classification of Rainfall Types Using Parsivel Disdrometer and S-Band Polarimetric Radar in Central Korea

et al. 2020

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Tools to identify and classify stratiform and convective rains at various times of the 12 days from June 2015 to March 2016 in Jincheon, Korea, were developed by using a Parsivel disdrometer and S-band polarimetric (S-POL) radar data. Stratiform and convective rains were identified using three different methods (vertical profile of reflectivity (VPR), the method proposed by Bringi et al. (BR03), and a combination of the two (BR03-VPR)) by using a Parsivel disdrometer for its applications to radar as a reference. BR03-VPR exhibits a better classification scheme than the VPR and BR03 methods. The rain types were compared using the drop size distribution (DSD) retrieved from polarimetric variables and reflectivity only. By using the DSD variables, a new convective/stratiform classification line of the log-normalized droplet number concentration ( log 10 N w ) − median volume diameter ( D 0 ) was derived for this area to classify the rainfall types using DSD variables retrieved from the polarimetric radar. For the radar variables, the method by Steiner et al. (SHY95) was found to be the best method, with 0.00% misclassification of the stratiform rains. For the convective rains, the DSD retrieval method performed better. However, for both stratiform and convective rains, the fuzzy method performed better than the SHY95 and DSD retrieval methods.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Classification of Rainfall Types Using Parsivel Disdrometer and S-Band Polarimetric Radar in Central Korea

et al. 2020

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“…The following relations between D 0 and each of Z DR and Z H /N w proposed by You et al [22] were used to classify rainfall types and retrieve D 0 and N w using observed polarimetric variables from radar:…”

Section: Classifications Of Precipitation Types Using Disdrometer Andmentioning

confidence: 99%

“…Recently, Thompson et al [21] showed that the logN w -D 0 separation line is more accurate than the Bringi et al [16] technique in the equatorial Indian and West Pacific Oceans. You et al [22] proposed new separation lines between convective and stratiform rainfall using both disdrometer and polarimetric radar in Korea.…”

Section: Introductionmentioning

confidence: 99%

Rainfall Estimates with Respect to Rainfall Types Using S-Band Polarimetric Radar in Korea

2019

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To investigate the impact of rainfall type on rainfall estimation using polarimetric variables, rainfall relations such as those between rain rate (R) and specific differential phase (KDP), between R and KDP/differential reflectivity (ZDR), and between R and reflectivity (Z)/ZDR, were examined with respect to the precipitation type classified using drop size distributions (DSDs) measured by a disdrometer. The classification of rainfall type was assessed using four different methods: temporal rainfall variation; and the relations between intercept parameter (N0) and R; normalized intercept parameter (Nw) and median diameter (D0); and slope parameter (Λ) and R. The logN0–R relation discriminated between convective and stratiform rain with less standard deviation than the other methods as shown by the Z–ZDR scatter with respect to the rainfall types. The transition type from convective to stratiform and vice versa occurred in the stratiform rain region for all methods. To apply the classified rainfall relations to radar rainfall estimation, logNw and D0 were retrieved from polarimetric variables to discriminate the rainfall types in the radar domain. The DSD classification was verified with the vertical profile of reflectivity extracted at two positions corresponding to gage sites. Statistical analysis of four different rainfall events showed that rainfall estimation using the relations with precipitation type were better than those obtained without classification. The R(KDP,ZDR) relation with classification performed best on rainfall estimation for all rainfall events. The greatest improvement in rainfall estimation was obtained from R(Z,ZDR) with classification. We conclude that the classification of rainfall type leads to more accurate rainfall estimation. The different relations R(KDP), R(KDP,ZDR), and R(Z,ZDR) with respect to the rain types using polarimetric radar show improvement compared to estimation without consideration of rainfall type, in Korea.

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Characteristics of Raindrop Size Distribution in Seoul, South Korea According to Rain and Weather Types

Jwa

Jin

Lee

et al. 2020

Asia-Pacific J Atmos Sci

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Classification of rain types using drop size distributions and polarimetric radar: Case study of a 2014 flooding event in Korea

Cited by 15 publications

References 38 publications

Classification of Rainfall Types Using Parsivel Disdrometer and S-Band Polarimetric Radar in Central Korea

Classification of Rainfall Types Using Parsivel Disdrometer and S-Band Polarimetric Radar in Central Korea

Rainfall Estimates with Respect to Rainfall Types Using S-Band Polarimetric Radar in Korea

Characteristics of Raindrop Size Distribution in Seoul, South Korea According to Rain and Weather Types

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