A comparison study of raindrop size distribution among five sites at the urban scale during the East Asian rainy season

Pu, Kang; Liu, Xichuan; Yi, Wu; Zhou, Tianjun; Liu, Lei; Gao, Taichang

doi:10.1016/j.jhydrol.2020.125500

Cited by 16 publications

(9 citation statements)

References 74 publications

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“…Nanjing is located in the subtropical southeast monsoon region; in this area, the southeast monsoon blowing from the Pacific Ocean brings much warm and humid airflow, which frequently meets cold air sourced from the subpolar westerlies, thus providing favorable conditions for the formation of heavy rain (Cao and Zhao, 2020;Pu et al, 2020). In June and July, the Yangtze River basin experiences a long period of continuous rainy days, with long rainfall duration and heavy precipitation (Fan et al, 2014;Zhou T. et al, 2021).…”

Section: Study Area and Data Collectionmentioning

confidence: 99%

Combining catastrophe technique and regression analysis to deduce leading landscape patterns for regional flood vulnerability: A case study of Nanjing, China

2022

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Urbanization leads to changes in land use, and the expansion of impervious surfaces leads to an increase in flood vulnerability. Predicting and analyzing these landscape pattern changes are important in the early stages of urban planning. In practice, the threshold for obtaining comprehensive and detailed hydrological and meteorological data is high, which makes it difficult for landscape and urban planners to quickly evaluate urban floods. To compensate for these trends, we took Nanjing, China, as the study site and discussed the leading flood vulnerability landscape patterns based on quantitative assessments. We introduced catastrophe theory to integrate three indicators and seven subfactors for flood vulnerability assessment: exposure, including precipitation; sensitivity, including elevation, slope, soil and drainage density; and adaptability, including land use and forest coverage. Then, we calculated the landscape pattern metrics (shape index, fractal dimension index, related circumscribing circle, contiguity index and landscape division index) at the class level. Finally, we divided the city into four subregions, established regression models for the subregions and the whole city, and deduced the leading flood vulnerability landscape patterns in each region and the whole city. We found that the leading landscape patterns varied among different regions. According to the research results, the landscape pattern indexes identified in this paper can be interpreted intuitively, which can provide a reference for modifying the planning layout of regional green infrastructure, optimizing the vulnerability of urban floods, and providing a basis for further improving Nanjing urban planning and alleviating the urban flood vulnerability. The methods proposed herein also will benefit land use and green infrastructure management in other regions lacking meteorological and hydrological data.

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Section: Study Area and Data Collectionmentioning

confidence: 99%

Combining catastrophe technique and regression analysis to deduce leading landscape patterns for regional flood vulnerability: A case study of Nanjing, China

2022

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“…China is a vast country with significant differences in climatic characteristics among its different regions. Researchers have conducted detailed surveys of DSD in the southern [21,22], eastern [23][24][25][26], northern [27][28][29], and Tibetan Plateau [30,31] regions of China directly affected by the monsoon system and obtained the characteristics of DSD in these regions. However, the research on Xinjiang, which accounts for one-sixth of China's total land area and is characterized by an arid climate, is insufficient.…”

Section: Introductionmentioning

confidence: 99%

“…However, the accuracy of the QPE for single-polarization radars is lower than that for dual-polarization radars [49][50][51][52]. Therefore, in recent years, the QPE relationships for dual-polarization radars have been established in different regions of China and have shown significantly better QPE capabilities than single-polarization radars [23,24,[26][27][28][29]53,54]. More importantly, both the microphysical characteristics of the DSD and the QPE of the dual-polarization radar are closely related to the rain rate classes [17,18,28,55], and the QPE of the dual-polarization radar is very sensitive to the radar wavelength [24,53].…”

Section: Introductionmentioning

confidence: 99%

Microphysical Characteristics of Raindrop Size Distribution and Implications for Dual-Polarization Radar Quantitative Precipitation Estimations in the Tianshan Mountains, China

Zeng

Yang

et al. 2023

Remote Sensing

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In order to improve the understanding of the microphysical characteristics of raindrop size distribution (DSD) under different rainfall rates (R) classes, and broaden the knowledge of the impact of radar wavelengths and R classes on the QPE of dual-polarization radars in the Tianshan Mountains, a typical arid area in China, we investigated the microphysical characteristics of DSD across R classes and dual-polarimetric radar QPE relationships across radar wavelengths and R classes, based on the DSD data from a PARSIVEL2 disdrometer at Zhaosu in the Tianshan Mountains during the summers of 2020 and 2021. As the R class increased, the DSD became wider and flatter. The mean value of the mass-weighted mean diameters (Dm) increased, while the mean value of logarithm normalized intercept parameters (log10 Nw) decreased after increasing from C1 to C3, as the R class increased. The largest contributions to R and the radar reflectivity factor from large raindrops (diameter > 3 mm) accounted for approximately 50% and 97%, respectively, while 84% of the total raindrops were small raindrops (diameter < 1 mm). Dual-polarization radars—horizontal polarization reflectivity (Zh), differential reflectivity (Zdr), and specific differential phase (Kdp)—were retrieved based on the DSD data using the T-matrix scattering method. The DSD-based polarimetric radar QPE relations of a single-parameter (R(Zh), R(Kdp)), and double-parameters (R(Zh,Zdr), R(Kdp,Zdr)) on the S-, C-, and X-bands were derived and evaluated. Overall, the performance of the R(Kdp) (R(Kdp,Zdr)) scheme was better than that of R(Zh) (R(Zh,Zdr)) for the QPE in the three bands. Furthermore, we have for the first time confirmed and quantified the performance differences in the QPE relationship of dual-polarization radars under different schemes, radar wavelengths, and R classes in typical arid areas of China. Therefore, selecting an appropriate dual-polarization radar band and QPE scheme for different R classes is necessary to improve the QPE ability compared with an independent scheme under all R classes.

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“…Raindrop size distribution (DSD) is an important feature that characterizes the microphysical process of precipitation [1-3] and is mainly affected by climatic characteristics and precipitation types [3][4][5][6][7][8][9]. In recent years, disdrometer DSD measurements have been widely used to study the microphysical characteristics of precipitation [4,[10][11][12][13][14]. Many DSD observations and analyses have been carried out in different regions of China.…”

Section: Introductionmentioning

confidence: 99%

Seasonal Variation in Microphysical Characteristics of Precipitation at the Entrance of Water Vapor Channel in Yarlung Zangbo Grand Canyon

Wang

Zhou

et al. 2022

Remote Sensing

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Mêdog is located at the entrance of the water vapor channel in the Yarlung Zangbo Grand Canyon (YGC). This area has the largest annual accumulated rainfall totals and precipitation frequency on the Tibetan Plateau (TP). This paper investigates the seasonal variation in raindrop size distribution (DSD) characteristics in Mêdog based on disdrometer observations from 1 July 2019 to 30 June 2020. The DSD characteristics are examined under six rain rate classes and two rainfall types (stratiform and convective) in the winter, premonsoon, monsoon and postmonsoon periods. The highest (lowest) concentration of small raindrops is observed in monsoon (winter) precipitation, whereas large raindrops predominate in premonsoon precipitation. For stratiform rainfall, the mean mass-weighted mean diameter (Dm) exhibits overlooked differences in the four periods, while the mean normalized intercept parameter (Nw) is significantly higher in the monsoon period than in the other three periods. The convective rainfall in the monsoon and postmonsoon periods is characterized by a high concentration of limited-size drops and can be classified as maritime-like. This is probably attributed to abundant warm and humid airflow transported by the Indian Ocean monsoon into Mêdog. The westerly winds prevail over the TP during the premonsoon period, and thereby the premonsoon convective rainfall in Mêdog has a larger mean Dm and a lower mean Nw. In addition, the relationships of radar reflectivity Z and rain rate R for different precipitation types in different periods are also derived. A better understanding of the seasonal variation in the microphysical characteristics of precipitation in Mêdog is important for improving the microphysical parameterization scheme and the precipitation forecast of models on the TP.

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A comparison study of raindrop size distribution among five sites at the urban scale during the East Asian rainy season

Cited by 16 publications

References 74 publications

Combining catastrophe technique and regression analysis to deduce leading landscape patterns for regional flood vulnerability: A case study of Nanjing, China

Combining catastrophe technique and regression analysis to deduce leading landscape patterns for regional flood vulnerability: A case study of Nanjing, China

Microphysical Characteristics of Raindrop Size Distribution and Implications for Dual-Polarization Radar Quantitative Precipitation Estimations in the Tianshan Mountains, China

Seasonal Variation in Microphysical Characteristics of Precipitation at the Entrance of Water Vapor Channel in Yarlung Zangbo Grand Canyon

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