Dual-Polarization Radar-Based Quantitative Precipitation Estimation of Mountain Terrain Using Multi-Disdrometer Data

You, Cheol‐Hwan; Suh, Sung-Ho; Jung, Woonseon; Kim, Hyeon-Joon; Lee, Dong‐In

doi:10.3390/rs14102290

Cited by 5 publications

(5 citation statements)

References 42 publications

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“…R classes have an important impact on the performance of dual-polarization radar QPE estimators [53,55,69] as well as radar bands [53,55,69]. To quantify the performance of QPE estimators under different R classes and different radar bands, we used CC, RMSE, and NMAE to evaluate the performance of these QPE estimators in detail.…”

Section: Qpe Relations Under Different Rain Rate Classesmentioning

confidence: 99%

“…Furthermore, the performance of the dual-parameter estimators in the C-band was better than that in the S-and X-bands for all R classes, and the performance of the R(Z h ,Z dr ) estimator was better compared to the R(K dp ,Z dr ) estimator at lower R classes (C1 to C4, R less than 5 mm h −1 ), while the performance of the R(K dp ,Z dr ) estimator was better compared to the R(Z h ,Z dr ) estimator at higher rainfall rates (C5 to C6, R greater than 5 mm h −1 ) for the C-band. It is worth noting that previous studies have shown the importance of selecting suitable estimators for actual dual-polarization radar QPEs, and suitable estimators need to be provided for different regions and different band radars [55,[69][70][71]. For a dual-polarization radar QPE estimator in the Tianshan Mountains, we plan to conduct the relevant research based on dual-polarization radar observational data in the future.…”

Section: Qpe Relations Under Different Rain Rate Classesmentioning

confidence: 99%

“…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]. However, the previous studies mentioned above have mostly focused on the impact of one or two of the three factors, namely the R class, radar wavelength, and QPE scheme, on the QPE of dual-polarization radars.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

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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Section: Qpe Relations Under Different Rain Rate Classesmentioning

confidence: 99%

Section: Qpe Relations Under Different Rain Rate Classesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

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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“…Hence, it is necessary to have simultaneous rainfall observations with higher temporal and spatial resolution. Polarimetric weather radars are preferred over rain gauges and satellites in producing Quantitative Precipitation Estimates (QPE) because of their ability to cover a larger spatial range and provide real-time rainfall information (You et al, 2022). Weather radars estimate rainfall by measuring the resulting reflectivity (Z) scattered by raindrops within a scanning volume measured in decibels relative to Z (dBZ).…”

Section: Introductionmentioning

confidence: 99%

Development of Dual-polarimetric QPE relations based on Disdrometer measurements in Metro Manila, Philippines

Ibanez,

Martirez,

Pura

et al. 2023

Preprint

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Quantitative precipitation estimates (QPE) can be further improved using estimation algorithms derived from localized raindrop size distribution (DSD) observations. In this study, DSD measurements from two disdrometer stations within Metro Manila during the Southwest monsoon (SWM) period were used to investigate the microphysical properties of rainfall and develop localize dual-polarimetric relations for different radar bands and rainfall types. Observations show that the DSD in Metro Manila is more distributed to larger diameters compared to Southern Luzon and neighboring countries in the Western Pacific. This is reflected by the relatively higher mass-weighted mean diameter (Dm) and smaller shape (μ) and slope (Λ) parameters measured in the region. The average values of Dm and normalized intercept parameter (Nw) in convective rain samples also suggest that convective rains in Metro Manila are highly influenced by both continental and oceanic convective processes. Dual-polarimetric variables simulated using the T-matrix scattering method showed good agreement with disdrometer-derived reflectivity (ZH) values. The 0.5 dB and 0.3° km-1 thresholds for the differential reflectivity (ZDR) and specific differential phase (KDP) based on the blended algorithm of Cifelli et al. (2011) and Thompson et al. (2017) are proven to be useful since the utility of the dual-polarimetric variables as rainfall estimators are shown to have dependencies on the radar band and rainfall type. Evaluation of the QPE products with respect to the C-band shows that R (KDP, ZDR) has the best performance among the dual-pol relations and statistically outperformed the conventional Marshall & Palmer relation [R(ZMP)]. The results show that dual-polarimetric variables such as ZDR and KDP can better represent the DSD properties compared to one-dimensional Z, hence providing more accurate QPE products than the conventional R(Z) relations.

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“…Among the metaheuristic optimization algorithms applied to structural optimization, the harmony search algorithm stands out as one of the most widely used techniques. Besides structural optimization, the harmony search technique has been applied to various areas of science and engineering such as transportation engineering [ 36 , 37 , 38 , 39 ], environmental engineering [ 40 , 41 ], healthcare systems [ 42 ], bioinformatics [ 43 , 44 , 45 ], and cloud computing [ 46 ].…”

Section: Introductionmentioning

confidence: 99%

Optimization and Predictive Modeling of Reinforced Concrete Circular Columns

et al. 2022

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Metaheuristic optimization techniques are widely applied in the optimal design of structural members. This paper presents the application of the harmony search algorithm to the optimal dimensioning of reinforced concrete circular columns. For the objective of optimization, the total cost of steel and concrete associated with the construction process were selected. The selected variables of optimization include the diameter of the column, the total cross-sectional area of steel, the unit costs of steel and concrete used in the construction, the total length of the column, and applied axial force and the bending moment acting on the column. By using the minimum allowable dimensions as the constraints of optimization, 3125 different data samples were generated where each data sample is an optimal design configuration. Based on the generated dataset, the SHapley Additive exPlanations (SHAP) algorithm was applied in combination with ensemble learning predictive models to determine the impact of each design variable on the model predictions. The relationships between the design variables and the objective function were visualized using the design of experiments methodology. Applying state-of-the-art statistical accuracy measures such as the coefficient of determination, the predictive models were demonstrated to be highly accurate. The current study demonstrates a novel technique for generating large datasets for the development of data-driven machine learning models. This new methodology can enhance the availability of large datasets, thereby facilitating the application of high-performance machine learning predictive models for optimal structural design.

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Dual-Polarization Radar-Based Quantitative Precipitation Estimation of Mountain Terrain Using Multi-Disdrometer Data

Cited by 5 publications

References 42 publications

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

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

Development of Dual-polarimetric QPE relations based on Disdrometer measurements in Metro Manila, Philippines

Optimization and Predictive Modeling of Reinforced Concrete Circular Columns

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