• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.992-996
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• 2008

In this study, changes in precipitation across South Korea during snow seasons (November-April) and their potential are examined. Current (1973/74-2006/07) and future (2081-2100) time series of snow indices including snow season, snow-to-precipitation ratio, and snow impossible day are extracted from observed snow and precipitation data for 61 weather stations as well as observed and modeled daily temperature data. Analyses of linear trends reveal that snow seasons have shortened by 3-13 days/decade; that the snow-to-precipitation ratio (the percentage of snow days relative to precipitation days) has decreased by 4-8 %/decade. These changes are associated with pronounced formations of a positive pressure anomaly core over East Asia during the positive Arctic Oscillation winter years since the late 1980s. A snow-temperature statistical model demonstrates that the warming due to the positive core winter intensifies changes from snow to rain at the rate of $4.7cm/^{\circ}C$. The high pressure anomaly pattern has also contributed to decreases of air-sea thermal gradient which are associated with the reduction of snow could formation. Modeled data predict that a fingerprint of wintertime global warming causing changes from snow to rain will continue to be observed over the 21st century.

• Journal of Korean Society of Environmental Engineers
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• v.29 no.1
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• pp.113-125
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• 2007

To know the differences in ionic compositions in rain and snow as well as snow influence on the chemical characteristics of winter precipitation, precipitation samples were collected by the wet-only automatic precipitation sample, in winter(November-February) in the Iksan located in the northwest of Chonbuk from 1995 to 2000. The samples were analyzed for concentrations of water-soluble ion species, in addition to pH and electrical conductivity. The mean pH of winter precipitation was 4.72. According to the type of winter precipitation, the mean pH of rain was 4.67 and lower than 5.05 in snow. The frequencies of pH below 5.0 in rain were about 73%, while those in snow were about 30%. Snow contained 3 times higher concentrations of sea salt ion components originated from seawater than did rain in winter, mainly $Cl^-,\;Na^+$, and $Mg^{2+}$. Neglecting sea salt ion components, $nss-SO_4^{2-}$ and $NO_3^-$ were important anions and $NH_4^+$ and $nss-Ca^{2+}$ were important cations in both of rain and snow. Concentrations of $nss-SO_4^{2-}$ was 1.3 times higher in rain than in snow, while those of $nss-Ca^{2+}$ and $NO_3^-$ were 1.5 and 1.3 times higher in snow, respectively. The mean equivalent concentration ratio of $nss-SO_4^{2-}/NO_3^-$ in winter precipitation were 2.4, which implied that the relative contribution of sulfuric and nitric acids to the precipitation acidity was 71% and 29%, respectively. The ratio in rain was 2.7 and higher than 1.5 in snow. These results suggest that the difference of $NO_3^-$ in rain and snow could be due to the more effective scavenging of $HNO_3$ vapor than particulate sulfate or nitrate by snow. The lower ratio in snow than rain is consistent with the measurement results of foreign other investigators and with scavenging theory of atmospheric aerosols. Although substantial $nss-SO_4^{2-}$ and $NO_3^-$ were observed in both of rain and snow, the corresponding presence of $NH_4^+,\;nss-Ca^{2+},\;nss-K^+$ suggested the significant neutralization of rain and snow. Differences in chemical composition of non-sea salt ions and neutralizing rapacity of $NH_4^+,\;nss-Ca^{2+}$, and $nss-K^+$ between rain and snow could explain the acidity difference of rain and snow. Snow affected that winter precipitation could be less acidic due to its higher neutralizing rapacity.

• Journal of the Korean earth science society
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• v.41 no.1
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• pp.1-18
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• 2020

This study presented the effects of the assumed mass-size relationship for snow on the simulated surface precipitation by using cloud microphysics parameterizations in Weather Research and Forecasting (WRF) model. The selected cloud microphysics parameterizations are WRF Double-Moment 6-class (WDM6) and WRF Single-Moment 6-class (WSM6) in the WRF model. We replaced the mass-size relationship for snow in WDM6 and WSM6 with Thompson's mass-size relationship retrieved from measurement data. The sensitivity of the modified WDM6 and WSM6 was tested for the idealized 2-dimensional squall line and winter precipitation system over the Korean peninsula, respectively. The modified WDM6 and WSM6 resulted in the increase of graupel/rain mixing ratios and the decrease of snow mixing ratio in the low atmosphere. The changes of hydrometeor mixing ratio and surface precipitation could be due to the collision-coalescence process between raindrops and snow and the graupel melting process.

• Journal of the Korean Geographical Society
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• v.43 no.1
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• pp.1-19
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• 2008

This study intends to clarify the characteristics and causes of current changes in wintertime precipitation in Korea and to predict the future directions based on surface observational $(1973/04\sim2006/07)$ and modeled (GFDL 2.1) climate data. Analyses of surface observation data demonstrate that without changes in the total amount of precipitation, snowfall in winter (November-April) has reduced by 4.3cm/decade over the $1973\sim2007$ period. Moreover, the frequency and intensity of snowfall have decreased; the duration of snow season has shortened; and the snow-to-rain day ratio (STDR) has decreased. These patterns indicate that the type of wintertime precipitation has changed from snow to rain in recent decades. The snow-to-rain change in winter is associated with the increases of air temperature (AT) over South Korea. Analyses of synoptic charts reveal that the warming pattern is associated with the formation of a positive pressure anomaly core over northeast Asia by a hemispheric positive winter Arctic Oscillation (AO) mode. Moreover, the differentiated warming of AT versus sea surface temperature (SST) under the high pressure anomaly core reduces the air-sea temperature gradient, and subsequently it increases the atmospheric stability above oceans, which is associated with less formation of snow cloud. Comparisons of modeled data between torrent $(1981\sim2000)$ and future $(2081\sim2100)$ periods suggest that the intensified warming with larger anthropogenic greenhouse gas emission in the $21^{st}$ century will amplify the magnitude of these changes. More reduction of snow impossible days as well as more abbreviation of snow seasons is predicted in the $21^{st}$ century.

• Journal of the Korean Data and Information Science Society
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• v.28 no.3
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• pp.483-492
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• 2017

Precipitation is one of key components in hydrological modeling and water balance studies. A comprehensive, optimized and sustainable water balance monitoring requires the availability of accurate precipitation data. The amount of precipitation measured in a gauge is less than the actual precipitation reaching the ground. The objective of this study is to determine the wind-induced under-catch of solid precipitation and develop a continuous adjustment function for measurements of all types of winter precipitation (from rain to dry snow), which can be used for operational measurements based on data available at standard automatic weather stations. This study provides Bayesian analysis for the systematic structure of catch ratio in precipitation measurement.

• Atmosphere
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• v.33 no.5
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• pp.457-475
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• 2023

Accurately predicting localized heavy rainfall is challenging without high-resolution mesoscale cloud information in the numerical model's initial field, as precipitation intensity and amount vary significantly across regions. In the Korean Peninsula, the radar observation network covers the entire country, providing high-resolution data on hydrometeors which is suitable for data assimilation (DA). During the pre-processing stage, radar reflectivity is classified into hydrometeors (e.g., rain, snow, graupel) using the background temperature field. The mixing ratio of each hydrometeor is converted and inputted into a numerical model. Moreover, assimilating saturated water vapor mixing ratio and decomposing radar radial velocity into a three-dimensional wind vector improves the atmospheric dynamic field. This study presents radar DA experiments using a numerical prediction model to enhance the wind, water vapor, and hydrometeor mixing ratio information. The impact of radar DA on precipitation prediction is analyzed separately for each radar component. Assimilating radial velocity improves the dynamic field, while assimilating hydrometeor mixing ratio reduces the spin-up period in cloud microphysical processes, simulating initial precipitation growth. Assimilating water vapor mixing ratio further captures a moist atmospheric environment, maintaining continuous growth of hydrometeors, resulting in concentrated heavy rainfall. Overall, the radar DA experiment showed a 32.78% improvement in precipitation forecast accuracy compared to experiments without DA across four cases. Further research in related fields is necessary to improve predictions of mesoscale heavy rainfall in South Korea, mitigating its impact on human life and property.

• Korean Journal of Remote Sensing
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• v.34 no.6_1
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• pp.1025-1032
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• 2018

Snow Cover is a form of precipitation that is defined by snow on the surface and is the single largest component of the cryosphere that plays an important role in maintaining the energy balance between the earth's surface and the atmosphere. It affects the regulation of the Earth's surface temperature. However, since snow cover is mainly distributed in area where human access is difficult, snow cover detection using satellites is actively performed, and snow cover detection in forest area is an important process as well as distinguishing between cloud and snow. In this study, we applied the Normalized Difference Snow Index (NDSI) and the Normalized Difference Vegetation Index (NDVI) to the geostationary satellites for the snow detection of forest area in existing polar orbit satellites. On the rest of the forest area, the snow cover detection using $R_{1.61{\mu}m}$ anomaly technique and NDSI was performed. As a result of the indirect validation using the snow cover data and the Visible Infrared Imaging Radiometer (VIIRS) snow cover data, the probability of detection (POD) was 99.95 % and the False Alarm Ratio (FAR) was 16.63 %. We also performed qualitative validation using the Himawari-8 Advanced Himawari Imager (AHI) RGB image. The result showed that the areas detected by the VIIRS Snow Cover miss pixel are mixed with the area detected by the research false pixel.

• Atmosphere
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• v.16 no.1
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• pp.33-48
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• 2006

A classification of snowfall type based on development mechanism is proposed using previous snowfall studies, operational experiences, etc. Five types are proposed: snowfall caused by 1) airmass transformation (AT type), 2) terrain effects in a situation of expanding Siberian High (TE type), 3) precipitation systems associated with extratropical cyclones (EC type), 4) indirect effects of extratropical cyclones passing over the sea to the south of the Korean peninsula (ECS type), and 5) combined effects of TE and ECS types (COM type). Snowfall events during 1981-2001 are classified according to the 5 types mentioned above. For this, 118 events, with at least one station with daily snowfall depth greater than 20 cm, are selected. For the classification, synoptic weather charts, satellite images, and precipitation data are used. For TE and COM types, local sea-level pressure chart is also used to confirm the presence of condition for TE type (this is done for events in 1990 and thereafter). The classification shows that 109 out of 118 events can be classified as one of the 5 types. In the remaining 8 events, heavy snowfall occurred only in Ullung Island. Its occurrence may be due to one or more of the following mechanism: airmass transformation, mesoscale cyclones and/or mesoscale convergence over the East Sea, etc. Each type shows different characteristics in location of snowfall and composition of precipitation (i.e., dry snow, rain, and mixed precipitation). The AT-type snowfall occurs mostly in the west coast, Jeju and Ullung Islands whereas the TE-type snowfall occurs in the East coast especially over the Young Dong area. The ECS-type snowfall occurs mostly over the southern part of the peninsula and some east cost area (sometimes, whole south Korea depending on the location of cyclones). The EC- and COM-type snowfalls occur in wider area, often whole south Korea. Precipitation composition also varies with the type. The AT-type has a snow ratio (SR) higher than the mean value. The TE- and EC-type have SR similar to the mean. The ECS- and COM-type have SR values smaller than the mean. Generally the SR values at high latitude and mountainous areas are higher than those at the other areas. The SR value informs the characteristics of the precipitation composition. An SR value larger than 10 means that all precipitation is composed of snow whereas a zero SR value means that all precipitation is composed of rain.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.44 no.2
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• pp.99-103
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• 2011

This study was performed to determine the optimal hydrolysis conditions for the production of a flavoring from the precipitation of snow crab cooker effluent (PSCCE) with commercial proteases. Based on cost-per-enzyme activity and sensory evaluations, Flavourzyme$^{(R)}$ 500 MG plus Protamex$^{(R)}$ (1:1 ratio, w/w) were selected as suitable enzymes. Three independent variables consisting of the substrate concentration (S), enzyme-to-substrate ratio (E/S), and hydrolysis time (T) were examined using response surface methodology (RSM). A model equation obtained from RSM was used to predict the degree of hydrolysis (DH) as follows: % DH = 52.285 - 6.371[S] + 5.469[E/S] + 7.599[T] - $5.818[S]^2$ - $5.633[E/S]^2$ - $6.528[T]^2$ - 3.265[E/S][S] - 5.415[T][S] + 4.315[T][E/S]. From the ridge analysis, the conditions favoring the highest degree of hydrolysis were pH 7.45, $55^{\circ}C$, a S of 21.82%, an E/S of 0.50%, and a T of 3.74 h.

• Korean Journal of Remote Sensing
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• v.34 no.2_1
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• pp.237-248
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• 2018

The vertical distribution of hydrometeor before precipitation near the cloud base has been analyzed using a scanning lidar, rawinsonde data, and Cloud-Resolving Storm Simulator (CReSS). This study mostly focuses on 13 Desember 2016 only. The typical synoptic pattern of lake-effect snowstorm induced easterly in the Yeongdong region. Clouds generated due to high temperature difference between 850 hPa and sea surface (SST) penentrated in the Yeongdong region along with northerly and northeasterly, which eventually resulted precipitation. The cloud base height before the precipitation changed from 750 m to 1,280 m, which was in agreement with that from ceilometer at Sokcho. However, ceilometer tended to detect the cloud base 50 m ~ 100 m below strong signal of lidar backscattering coefficient. As a result, the depolarization ratio increased vertically while the backscattering coefficient decreased about 1,010 m~1,200 m above the ground. Lidar signal might be interpreted to be attenuated with the penetration depth of the cloud layer with of nonspherical hydrometeor (snow, ice cloud). An increase in backscattering signal and a decrease in depolarization ratio occured in the layer of 800 to 1,010 m, probably being associated with an increase in non-spherical particles. There seemed to be a shallow liquid layer with a low depolarization ratio (<0.1) in the layer of 850~900 m. As the altitude increases in the 680 m~850 m, the backscattering coefficient and depolarization ratio increase at the same time. In this range of height, the maximum value (0.6) is displayed. Such a result can be inferred that the nonspherical hydrometeor are distributed by a low density. At this time, the depolarization ratio and the backscattering coefficient did not increase under observed melting layer of 680 m. The lidar has a disadvantage that it is difficult for its beam to penetrate deep into clouds due to attenuation problem. However it is promising to distinguish hydrometeor morphology by utilizing the depolarization ratio and the backscattering coefficient, since its vertical high resolution (2.5 m) enable us to analyze detailed cloud microphysics. It would contribute to understanding cloud microphysics of cold clouds and snowfall when remote sensings including lidar, radar, and in-situ measurements could be timely utilized altogether.