Rain‐rate estimation algorithm using signal attenuation of Ka‐band cloud radar

Oh, Su‐Bin; Kollias, Pavlos; Lee, Jeong‐Soon; Lee, Seung‐Woo; Lee, Yong Hee; Jeong, Jong‐Hoon

doi:10.1002/met.1825

Cited by 6 publications

(5 citation statements)

References 37 publications

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“…Oh et al. (2018, 2019) have attempted to develop a QC method to render observation data reliable. However, the product of their QC method was not very satisfactory.…”

Section: Methodsmentioning

confidence: 99%

“…An example of a time series of original radar moment data and their contoured frequency by altitude diagram (CFAD) are shown in Figure 2, where band-shaped horizontal noises and clutters near the ground are indicated by the two red boxes. Oh et al (2018Oh et al ( , 2019 have attempted to develop a QC method to render observation data reliable. However, the product of their QC method was not very satisfactory.…”

Section: Bswo Data and Quality Controlmentioning

confidence: 99%

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Climatology of Melting Layer Heights Estimated From Cloud Radar Observations at Various Locations

et al. 2021

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A melting layer (ML) detection algorithm for cloud radar with polarimetric capability was developed and applied to the cloud radar data collected from five different sites around the world for several years. The retrieved melting layer top height (MLH) showed a very good correspondence with the ECMWF Reanalysis 5 zero degree level data for all five sites. The ML characteristics were distinctively different for different sites, revealing climatological characteristics of ML forming clouds in different regions. Generally, ML tended to occur more frequently in summer than in winter except for a maritime site, where low stratiform clouds formed frequently in summer, the top of which might be lower than the freezing level. In contrast, at two Arctic sites, ML occurred almost exclusively in summer because it was too cold to have an ML in the other seasons. The MLH also varied significantly from site to site but generally was higher during warmer seasons. Based on MLH, two new indices, bulk temperature lapse rate (BLR) and relative depth (RD) of liquid cloud below MLH (RD) were developed, which were useful to explain the environmental characteristics of the five sites. BLR generally increased with the surface temperature at all sites except at the marine site that showed an opposite trend, where a unique synoptic pattern in winter generated high BLR in this cold season. These findings confirm that studies on thermodynamic structures using cloud radars can be broadened, taking advantage of BLR and RD information, as these indices can represent environmental thermodynamic characteristics of the clouds that have ML.

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“…Oh et al. (2018, 2019) have attempted to develop a QC method to render observation data reliable. However, the product of their QC method was not very satisfactory.…”

Section: Methodsmentioning

confidence: 99%

Section: Bswo Data and Quality Controlmentioning

confidence: 99%

Climatology of Melting Layer Heights Estimated From Cloud Radar Observations at Various Locations

et al. 2021

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“…Meanwhile, for radars, the typical bands used for meteorological observation include S-, C-, X-, Ka-, and W-bands, and these bands were all considered in our simulation to find an optimal combination scheme. The key parameters of these radars refer to several classic papers [51,52], as shown in Table 1. To improve the credibility of this simulation, noncoherent and coherent accumulation were adopted for lidar and radars, respectively, and the number of accumulated pulses followed a time resolution of 0.5 s. Notably, the complex refractive index m plays an important role in the computation of electromagnetic characteristics, and it is determined by both the component of the substance and the frequency of the incident wave.…”

Section: Key Parametersmentioning

confidence: 99%

Detection Performance Analysis of Marine Wind by Lidar and Radar under All-Weather Conditions

Peng,

Wu,

Shen

et al. 2024

Remote Sensing

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Accurate marine wind detection under all-weather conditions is crucial for maritime activities. The joint detection of lidar and radar is supposed to be a potential way to carry out the all-weather sensing of wind. However, their performance analysis has not been well studied, particularly in the far sea area, where the wind-tracing particles are quite different from those inland. Based on the particle distributions above the sea surface under different weather conditions, this study investigated the scattering and attenuation effects of lidar and radar waves in open sea areas with the Mie theory and T-matrix method. Then, the maximum detection range and velocity accuracies of lidar/radar were comprehensively analyzed based on detection principles to optimize the combination of lidar and radar. According to the simulation results, it was difficult to maintain the detection capability of a single lidar/radar under all-weather conditions, and 1.55 μm lidar and W-band radar presented a promising joint detection scheme, as they exhibited optimal weather adaptability in clear sky and precipitation conditions, respectively.

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“…A rain-rate-retrieval algorithm was designed using radar reflectivity derived from the rain rate in [ 55 ]. Based on the Doppler velocity, the derived radar reflectivity was classified as low-and high-rain cases.…”

Section: Preliminariesmentioning

confidence: 99%

A Survey of Rain Attenuation Prediction Models for Terrestrial Links—Current Research Challenges and State-of-the-Art

Samad

Diba

Choi

2021

Sensors

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Millimeter-wave (30–300 GHz) frequency is a promising candidate for 5G and beyond wireless networks, but atmospheric elements limit radio links at this frequency band. Rainfall is the significant atmospheric element that causes attenuation in the propagated wave, which needs to estimate for the proper operation of fade mitigation technique (FMT). Many models have been proposed in the literature to estimate rain attenuation. Various models have a distinct set of input parameters along with separate estimation mechanisms. This survey has garnered multiple techniques that can generate input dataset for the rain attenuation models. This study extensively investigates the existing terrestrial rain attenuation models. There is no survey of terrestrial rain mitigation models to the best of our knowledge. In this article, the requirements of this survey are first discussed, with various dataset developing techniques. The terrestrial links models are classified, and subsequently, qualitative and quantitative analyses among these terrestrial rain attenuation models are tabulated. Also, a set of error performance evaluation techniques is introduced. Moreover, there is a discussion of open research problems and challenges, especially the exigency for developing a rain attenuation model for the short-ranged link in the E-band for 5G and beyond networks.

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Rain‐rate estimation algorithm using signal attenuation of Ka‐band cloud radar

Cited by 6 publications

References 37 publications

Climatology of Melting Layer Heights Estimated From Cloud Radar Observations at Various Locations

Climatology of Melting Layer Heights Estimated From Cloud Radar Observations at Various Locations

Detection Performance Analysis of Marine Wind by Lidar and Radar under All-Weather Conditions

A Survey of Rain Attenuation Prediction Models for Terrestrial Links—Current Research Challenges and State-of-the-Art

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