Snowfall Estimation Using Dual-wavelength Radar during the Pyeongchang 2018 Olympics and Paralympic Winter Games

Yu, Ting; Chandrasekar, V.; Xiao, Hui; Joshil, Shashank S.

doi:10.2151/jmsj.2021-004

Cited by 6 publications

(3 citation statements)

References 30 publications

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“…Every 60 s, total particle numbers that were less than 10 were deleted to eliminate noise. The requirements for data quality control were the same as those in the previous investigation [54,55].…”

Section: Instrumentsmentioning

confidence: 99%

“…The goal of this research is to investigate if the random forest technique can be used to obtain microphysical snowfall parameters, such as the mass-weighted diameter, S, IWC, and PSD parameters (shape factor µ and normalized intercept parameter N w ). As for the density of snowfall, we adopted the method proposed before [54,55]. In Section 2, the data and method used to produce and evaluate the algorithm are described.…”

Section: Introductionmentioning

confidence: 99%

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Dual-Frequency Radar Retrievals of Snowfall Using Random Forest

Chandrasekar

Xiao

et al. 2022

Remote Sensing

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The microphysical parameters of snowfall directly impact hydrological and atmospheric models. During the International Collaborative Experiment hosted at the Pyeongchang 2018 Olympic and Paralympic Winter Games (ICE-POP 2018), dual-frequency radar retrievals of particle size distribution (PSD) parameters were produced and assessed over complex terrain. The NASA Dual-frequency Dual-polarized Doppler Radar (D3R) and a collection of second-generation Particle Size and Velocity (PARSIVEL2) disdrometer observations were used to develop retrievals. The conventional look-up table method (LUT) and random forest method (RF) were applied to the disdrometer data to develop retrievals for the volume-weighted mean diameter (Dm), the shape factor (mu), the normalized intercept parameter (Nw), the ice water content (IWC), and the snowfall rate (S). Evaluations were performed between the D3R radar and disdrometer observations using these two methods. The mean errors of the retrievals based on the RF method were small compared with those of the LUT method. The results indicate that the RF method is a promising way of retrieving microphysical parameters, because this method does not require any assumptions about the PSD of snowfall.

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Section: Instrumentsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Dual-Frequency Radar Retrievals of Snowfall Using Random Forest

Chandrasekar

Xiao

et al. 2022

Remote Sensing

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“…Due to the high spatio‐temporal resolutions of Doppler radars, they can provide more abundant atmospheric information and effectively detect the evolution of precipitation systems in combination with satellite cloud images, mostly applied in the forecast and early warning of various disastrous weather (Nan et al, 2018). However, scholars mainly carry out studies on quantitative snowfall estimation, and there are fewer studies on the phase transformation of rain and snow (Matrosov et al, 2009; Nakai et al, 2022; Tao et al, 2020; Yu et al, 2020). In recent years, Doppler radars have been gradually upgraded in China.…”

Section: Introductionmentioning

confidence: 99%

A contrastive analysis on the causes of two regional snowstorm processes influenced by the southern branch trough in Hunan in early 2022

Hu,

Chen,

Wang

et al. 2023

Atmospheric Science Letters

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In early 2022, there were four low‐temperature weather processes with rain and snow in Hunan Province, China. Two processes occurred on January 28–29 (referred to as the “0128” process) and February 6–7 (referred to as the “0206” process), and they have overlapping areas of heavy snowfall and high intensity of short‐term snowfall. Multi‐source observation data and the National Centers for Environmental Prediction (NCEP) reanalysis data are used to analyze the characteristics of circulation background and mesoscale. In addition, the causes of heavy snowfall processes under the influence of the southern branch trough are discussed based on the dual‐polarization radar products at Changsha station. The results show that two processes are characterized by the rapid phase transformation of rain and snow, concentrated snowfall periods, and heavy snowfall at night. The short‐term snowfall intensity of the “0206” process is greater than that of the “0128” process. The high‐latitude blocking high of the “0206” process is stronger than that of the “0128” process, and the water vapor transport of the southerly jet in low levels in the “0206” process is also stronger. The organized development of cold cloud clusters from the meso‐β scale to the meso‐α scale indicates that the snowfall intensifies, and the maximum blackbody temperature gradient corresponds well to the center of heavy snowfall. The propagation that is similar to the train effect is an important reason for the heavy snowfall process. The vertical variation of the ZH and the bright band of dual‐polarization parameters can determine the phase transformation between rain and snow. When the ZH and ZDR bright bands are 1–3 km away from the ground, the phase state is rain if the ZH near the ground is greater than 0 dBZ and the CC is close to 1; the phase state is the rain‐snow mixed phase if the CC is less than 0.95. When the bottom of the ZH bright band decreases, the CC/ZDR bright band disappears, the near‐surface CC is greater than 0.99 and the ZDR is less than 1 dB, the rain turns to snow. Compared with the “0128” process, the characteristics of the bright ring during the rainfall period of the “0206” process are more obvious, the precipitation intensity judged from the larger ZH and KDP is larger, and the phase transformation is faster due to more significant cooling effect caused by precipitation.

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Overview of the D3R Observations During the ICE-POP Field Campaign With Emphasis on Snow Studies

Joshil

Chandrasekar

Wolff

2023

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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The International Collaborative Experiment during the PyeongChang Olympics and Paralympic winter games 2018 took place in the PyeongChang region of South Korea. The main goal of this field campaign was to study winter precipitation in an environment that has complex terrain. The NASA dual-frequency, dual-polarization, Doppler radar (D3R) was calibrated and deployed in this field campaign. The positioning error of the radar was calibrated to be within 0.1°. The D3R was deployed for more than four months and was able to capture many interesting snowfall events along with a few rain events. In this article, the deployment and performance of the D3R during the campaign are discussed. The snowfall events captured by the D3R are discussed in detail to interpret the microphysics from a radar's perspective. The reflectivity-snowfall rate relationship is derived at the Ku band, and the snow accumulation computed is in good agreement with a precipitation gauge that was deployed near the radar. The benefit of the dual-frequency ratio for identifying the precipitation particle types is briefly introduced using the data from a large snow event on 28th February 2018. The vertical profile D3R data for this snow event are studied for detecting the presence of pristine-oriented ice crystals in the mixed hydrometeor phase conditions. Various other instruments, such as X-band radar and disdrometers, were deployed in the campaign. The D3R data are compared with the MxPOL X-band radar, and the reflectivity values match within a couple of dB in the common volume region.

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Snowfall Estimation Using Dual-wavelength Radar during the Pyeongchang 2018 Olympics and Paralympic Winter Games

Cited by 6 publications

References 30 publications

Dual-Frequency Radar Retrievals of Snowfall Using Random Forest

Dual-Frequency Radar Retrievals of Snowfall Using Random Forest

A contrastive analysis on the causes of two regional snowstorm processes influenced by the southern branch trough in Hunan in early 2022

Overview of the D3R Observations During the ICE-POP Field Campaign With Emphasis on Snow Studies

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