Analysis of the Relationship of Water Vapor with Precipitation for the Winter ESSAY (Experiment on Snow Storms At Yeongdong) Period

Ko, A-Reum; Kim, Byung-Gon; Eun, Seung-Hee; Park, Young-San; Choi, Byoung-Cheol

doi:10.14191/atmos.2016.26.1.019

Cited by 7 publications

(6 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The Cold Low is the same type as the extratropical cyclone type (EC, Cheong et al, 2006) in which the precipitation is mainly produced by cold and warm fronts the extratropical cyclone that crosses the middle part of the Korean Peninsula. This pattern is called the low crossing type in the synoptic classification by Ko et al (2016). Song et al (2016) interprets this pattern as a low passing type, but it is close to a low crossing type based on their description of this type where a low-pressure system crosses the middle part of the Korean Peninsula.…”

Section: Cold Lowmentioning

confidence: 99%

Impact of wind pattern and complex topography on snow microphysics during ICE-POP 2018

Kim¹,

Bang²,

Chang³

et al. 2021

Preprint

View full text Add to dashboard Cite

Abstract. Snowfall in north-eastern part of South Korea is the result of complex snowfall mechanisms due to a highly-contrasting terrain combined with nearby warm waters and three synoptic pressure patterns. All these factors together create unique combinations, whose disentangling can provide new insights into the microphysics of snow in the planet. This study focuses on the impact of wind flow and topography on the microphysics drawing of twenty snowfall events during the ICE-POP 2018 (International Collaborative Experiment for Pyeongchang 2018 Olympic and Paralympic winter games) field campaign in the Gangwon region. The vertical structure of precipitation and size distribution characteristics are investigated with collocated MRR (Micro Rain Radar) and PARSIVEL (PARticle SIze VELocity) disdrometers installed across the mountain range. The results indicate that wind shear and embedded turbulence were the cause of the riming process dominating the mountainous region. As the strength of these processes weaken from the mountainous region to the coastal region, riming became less significant and gave way to aggregation. This study specifically analyzes the microphysical characteristics under three major synoptic patterns: air-sea interaction, cold low, and warm low. Air–sea interaction pattern is characterized by more frequent snowfall and vertically deeper precipitation systems in the windward side, resulting in significant aggregation in the coastal region, with riming featuring as a primary growth mechanism in both mountainous and coastal regions. The cold low pattern is characterized by a higher snowfall rate and vertically deep systems in mountainous region, with the precipitation system becoming shallower in the coastal region and strong turbulence being found in the layer below 2 km in the mountainous upstream region (linked with dominant aggregation). The warm low pattern features the deepest system: precipitation here is enhanced by the seeder–feeder mechanism with two different precipitation systems divided by the transition zone (easterly below and westerly above). Overall, it is found that strong shear and turbulence in the transition zone is a likely reason for the dominant riming process in mountainous region, with aggregation being important in both mountainous and coastal regions.

show abstract

Section: Cold Lowmentioning

confidence: 99%

Impact of wind pattern and complex topography on snow microphysics during ICE-POP 2018

Kim¹,

Bang²,

Chang³

et al. 2021

Preprint

View full text Add to dashboard Cite

show abstract

“…The cold low is the same type as the extratropical cyclone type (EC; Cheong et al, 2006) in which the precipitation is mainly produced by cold and warm fronts of the extratropical cyclone that crosses the middle part of the Korean Peninsula. This pattern is called the low crossing type in the synoptic classification by Ko et al (2016). Song et al (2016) interprets this pattern as a low passing type, but it is close to a low crossing type based on their description of this type where a low-pressure system crosses the middle part of the Korean Peninsula.…”

Section: Cold Lowmentioning

confidence: 99%

“…On the other hand, Song et al (2016) called it "cP high expansion" type or "cP high expansion type + trough" type, emphasizing the cold and dry air mass. It is also referred to as stagnation type (Ko et al, 2016) as is often related to an atmospheric blocking pattern (Rex, 1950).…”

Section: Air-sea Interactionmentioning

confidence: 99%

Impact of wind pattern and complex topography on snow microphysics during International Collaborative Experiment for PyeongChang 2018 Olympic and Paralympic winter games (ICE-POP 2018)

et al. 2021

View full text Add to dashboard Cite

Abstract. Snowfall in the northeastern part of South Korea is the result of complex snowfall mechanisms due to a highly contrasting terrain combined with nearby warm waters and three synoptic pressure patterns. All these factors together create unique combinations, whose disentangling can provide new insights into the microphysics of snow on the planet. This study focuses on the impact of wind flow and topography on the microphysics drawing of 20 snowfall events during the ICE-POP 2018 (International Collaborative Experiment for PyeongChang 2018 Olympic and Paralympic winter games) field campaign in the Gangwon region. The vertical structure of precipitation and size distribution characteristics are investigated with collocated MRR (micro rain radar) and PARSIVEL (particle size velocity) disdrometers installed across the mountain range. The results indicate that wind shear and embedded turbulence were the cause of the riming process dominating the mountainous region. As the strength of these processes weakens from the mountainous region to the coastal region, riming became less significant and gave way to aggregation. This study specifically analyzes the microphysical characteristics under three major synoptic patterns: air–sea interaction, cold low, and warm low. Air–sea interaction pattern is characterized by more frequent snowfall and vertically deeper precipitation systems on the windward side, resulting in significant aggregation in the coastal region, with riming featuring as a primary growth mechanism in both mountainous and coastal regions. The cold-low pattern is characterized by a higher snowfall rate and vertically deep systems in the mountainous region, with the precipitation system becoming shallower in the coastal region and strong turbulence being found in the layer below 2 km in the mountainous upstream region (linked with dominant aggregation). The warm-low pattern features the deepest system: precipitation here is enhanced by the seeder–feeder mechanism with two different precipitation systems divided by the transition zone (easterly below and westerly above). Overall, it is found that strong shear and turbulence in the transition zone is a likely reason for the dominant riming process in the mountainous region, with aggregation being important in both mountainous and coastal regions.

show abstract

“…Using satellite passive microwave observations at highfrequency channels, snowfall may be retrieved due to the scattering of upwelling radiation by snowflakes (Katsumata et al, 2000;Bennartz and Bauer, 2003;Skofronick-Jackson and Johnson, 2011;Gong and Wu, 2017). Retrieval algorithms have been developed both in research mode (Kim et al, 2008;Kongoli et al, 2015;Liu and Seo, 2013;Noh et al, 2006;Skofronick-Jackson et al, 2004) and for operations (Kummerow et al, 2015;Meng et al, 2017). Skofronick-Jackson et al (2004) and Kim et al (2008) developed phys-ically based retrieval algorithms which seek the best match between radiative transfer model simulated and satellite observed brightness temperatures.…”

Section: Introductionmentioning

confidence: 99%

“…Skofronick-Jackson et al (2004) and Kim et al (2008) developed phys-ically based retrieval algorithms which seek the best match between radiative transfer model simulated and satellite observed brightness temperatures. The Liu and Seo (2013) and Kongoli et al (2015) algorithms are mostly statistical, and many pairs of radar and/or gauge-measured snowfall and satellite measured brightness temperatures are used to develop their statistical relations. The Noh et al (2006) and Kummerow et al (2015) snowfall algorithms are based on the Bayesian theorem; an a priori database linking snowfall and brightness temperatures needs to be prepared before conducting retrievals.…”

Section: Introductionmentioning

confidence: 99%

Microphysical properties of three types of snow clouds: implication for satellite snowfall retrievals

et al. 2020

View full text Add to dashboard Cite

Abstract. Ground-based radar and radiometer data observed during the 2017–2018 winter season over the Pyeongchang area on the east coast of the Korean Peninsula were used to simultaneously estimate both the cloud liquid water path and snowfall rate for three types of snow clouds: near-surface, shallow, and deep. Surveying all the observed data, it is found that near-surface clouds are the most frequently observed cloud type with an area fraction of over 60 %, while deep clouds contribute the most in snowfall volume with about 50 % of the total. The probability distributions of snowfall rates are clearly different among the three types of clouds, with the vast majority hardly reaching 0.3 mm h−1 (liquid water equivalent snowfall rate) for near-surface, 0.5 mm h−1 for shallow, and 1 mm h−1 for deep clouds. However, the liquid water paths in the three types of clouds all have the substantial probability to reach 500 g m−2. There is no clear correlation found between snowfall rate and the liquid water path for any of the cloud types. Based on all observed snow profiles, brightness temperatures at Global Precipitation Measurement Microwave Imager (GPM/GMI) channels are simulated, and the ability of a Bayesian algorithm to retrieve snowfall rate is examined using half the profiles as observations and the other half as an a priori database. Under an idealized scenario, i.e., without considering the uncertainties caused by surface emissivity, ice particle size distribution, and particle shape, the study found that the correlation as expressed by R2 between the “retrieved” and “observed” snowfall rates is about 0.32, 0.41, and 0.62, respectively, for near-surface, shallow, and deep snow clouds over land surfaces; these numbers basically indicate the upper limits capped by cloud natural variability, to which the retrieval skill of a Bayesian retrieval algorithm can reach. A hypothetical retrieval for the same clouds but over ocean is also studied, and a major improvement in skills is found for near-surface clouds with R2 increasing from 0.32 to 0.52, while a smaller improvement is found for shallow and deep clouds. This study provides a general picture of the microphysical characteristics of the different types of snow clouds and points out the associated challenges in retrieving their snowfall rate from passive microwave observations.

show abstract

Analysis of the Relationship of Water Vapor with Precipitation for the Winter ESSAY (Experiment on Snow Storms At Yeongdong) Period

Cited by 7 publications

References 13 publications

Impact of wind pattern and complex topography on snow microphysics during ICE-POP 2018

Impact of wind pattern and complex topography on snow microphysics during ICE-POP 2018

Impact of wind pattern and complex topography on snow microphysics during International Collaborative Experiment for PyeongChang 2018 Olympic and Paralympic winter games (ICE-POP 2018)

Microphysical properties of three types of snow clouds: implication for satellite snowfall retrievals

Contact Info

Product

Resources

About