• Atmosphere
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• v.22 no.1
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• pp.117-128
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• 2012

Does snow depth initialization have a quantitative impact on sub-seasonal to seasonal prediction skill? To answer this question, a snow depth initialization technique for seasonal forecast system has been implemented and the impact of the initialization on the seasonal forecast of surface air temperature during the wintertime is examined. Since the snow depth observation can not be directly used in the model simulation due to the large systematic bias and much smaller model variability, an anomaly rescaling method to the snow depth initialization is applied. Snow depth in the model is initialized by adding a rescaled snow depth observation anomaly to the model snow depth climatology. A suite of seasonal forecast is performed for each year in recent 12 years (1999-2010) with and without the snow depth initialization to evaluate the performance of the developed technique. The results show that the seasonal forecast of surface air temperature over East Asian region sensitively depends on the initial snow depth anomaly over the region. However, the sensitivity shows large differences for different timing of the initialization and forecast lead time. Especially, the snow depth anomaly initialized in the late winter (Mar. 1) is the most effective in modulating the surface air temperature anomaly after one month. The real predictability gained by the snow depth initialization is also examined from the comparison with observation. The gain of the real predictability is generally small except for the forecasting experiment in the early winter (Nov. 1), which shows some skillful forecasts. Implications of these results and future directions for further development are discussed.

• Ocean and Polar Research
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• v.26 no.3
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• pp.439-451
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• 2004

Total solar irradiance (750), total UV irradiunce (TUV) and erythemal UV irradiance (EUV) measured at King Sejong station $(62.22^{\circ}S,\;58.78^{\circ}W)$ in west Antarctica have been used together with total ozone, cloud amount and snow cover to examine the effects of ozone, cloud and snow surface on these surface solar inadiunce over the period of 1998-2003. The data of three solar components for each scan were grouped by cloud amount, n in oktas $(0{\leq}n<3,\;3{\leq}n<4,\;4{\leq}n<5,\;5{\leq}n<6,\;6{\leq}n<7\;and\;7{\leq}n<8)$ and plotted against solar zenith angle (SZA) over the range of $45^{\circ}\;to\;75^{\circ}$. The radiation amplification factor (RAE) is used to quantify ozone effect on EUV. RAF of EUV decreases from 1.51 to 0.94 under clear skies but increases from 0.94 to 1.85 under cloudy skies as SZA increases, and decreases from 1.51 to 1.01 as cloud amount increases. The effects of cloud amount and snow surface on EUV are estimated as a function of SZA and cloud amount after normalization of the data to the reference total ozone of 300 DU. In order to analyse the transmission of solar radiation by cloud, regression analyses have been performed for the maximum values of solar irradiance on clear sky conditions $(0{\leq}n<3)$ and the mean values on cloudy conditions, respectively. The maximum regression values for the clear sky cases were taken to represent minimum aerosol conditions fur the site and thus appropriate for use as a normalization (reference) factor for the other regressions. The overall features for the transmission of the three solar components show a relatively high values around SZAs of $55^{\circ}\;and\;60^{\circ}$ under all sky conditions and cloud amounts $4{\leq}n<5$ and $5{\leq}n<6$. The transmission is, in general, the largest in TUV and the smallest in EUV among the three components of the solar irradiance. If the ground is covered with snow on partly cloudy days $(6{\leq}n<7)$, EUV increases by 20 to 26% compared to snow-free surface around SZA $60^{\circ}-65^{\circ}$, due to multiple reflections and scattering between the surface and the clouds. The relative difference between snow surface and snow-free surface slowly increases from 9% to 20% as total ozone increases from 100 DU to 400 DU under partly cloud conditions $(3{\leq}n<6)$ at SZA $60^{\circ}$. The snow effects on TUV and TSO are relatively high with 32% and 34%, respectively, under clear sky conditions, while the effects changes to 36% and 20% for TUV and TSO, respectively, as cloud amount increases.

• Ocean and Polar Research
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• v.37 no.2
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• pp.141-147
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• 2015

Snow albedo can be decreased if there are any impurities on the snow surface other than the snow itself. Due to the decrease of snow albedo, melting rates of surface snow can increase, which is very crucial in climate change and hydrogeology in many parts of the world. Anthropogenic black carbons caused by the incomplete combustion of fossil fuel affect snow and tephra particles generated by geologic volcanic activities reduce snow albedo. In this study, we investigated isotopic compositions for snow covered by tephra particles and compared with this with clean snow. Isotopic compositions of snow with tephra statistically show more enriched than those of clean snow (p<0.02). This can be explained by the fact that snow becomes enriched in $^{18}O$ or D relative to meltwater as melting rates are increased. In addition, the slopes of the linear regression between oxygen and hydrogen for snow with tephra and clean snow are 6.7 and 8, respectively, and the latter is similar to that of the global meteoric water line of 8. Therefore, we can conclude that snow impurities control the isotopic compositions of snow, which is very crucial in the study of climate change and hydrogeology. To quantitatively explain these observations, melting experiments and numerical approaches are required.

• Korean Journal of Remote Sensing
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• v.25 no.2
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• pp.193-203
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• 2009

Snow cover is one of the important parameters since it determines surface energy balance and its variation. To classify snow and cloud from satellite data is very important process when inferring land surface information. Generally, misclassified cloud and snow pixel can lead directly to error factor for retrieval of surface products from satellite data. Therefore, in this study, we perform algorithm for detecting snow cover area with remote sensing data. We just utilize visible reflectance, and infrared channels rather than using NDSI (Normalized Difference Snow Index) which is one of optimized methods to detect snow cover. Because COMS MI (Meteorological Imager) channels doesn't include near infra-red, which is used to produce NDSI. Detecting snow cover with visible channel is well performed over clear sky area, but it is difficult to discriminate snow cover from mixed cloudy pixels. To improve those detecting abilities, brightness temperature difference (BTD) between 11 and 3.7 is used for snow detection. BTD method shows improved results than using only visible channel.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.517-520
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• 2003

The snow-fatting measurement system including the snow sensor applying the photo-coupler is investigated in this study and using this snow sensor the height of snow fallen is measured. To measure the snow depth, five photo sensors are arranged with 5 mm distance. The snow-falling measurement system, which is measuring the motor revolution controlled with stepping motor, is mounted above the snow surface. From this work, it is feasible to measure quantitatively the snow on real time. Its software implements a proven method to achieve valid measurements also under difficult conditions as future study. In cases where the snow sensor is applieded to the prediction of snow in the meteorological observation system and the snow removing system, it is recommend the GRS-Option in order to improve the quality of snow measurements for better compensation.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.319-322
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• 1999

Land surface hydrological conditions have been considered to play an important role in the global and regional climate variability. Especially, snow, soil moisture, surface temperature, vegetation and rain are the key parameters which should be observed in the global scale. In this paper, new algorithms for these land surface hydrological parameters have been developed by introducing frequency and polarization dependencies of these parameters in the microwave radiative-transfer equations. The algorithms were applied to the TRMM Microwave Radiometer. (TMI) and validated by using the ground data obtained in the Tibetan Plateau. The estimated snow, soil moisture, surface temperature, water content of vegetation and rain patterns corresponded reasonably to the observed ones.

• 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.

• Proceedings of the Korea Concrete Institute Conference
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• 1997.04a
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• pp.663-668
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• 1997

In Korea, the temperature of winter seasons are really severe and cause lot's of snow-falling and iceing in the pavements. Several de-iceing mehtod have generally been adopted to melt the ice on the surface of pavement. Therefore, the Study of experimental in the first stage was given to the verification of the icers's effects. First, Contrete and asphalt pavement specimens were made and scattered with a CaC2-deicers. then 3cm and 5cm thickness of artificial snow were prepared on the surface of specimens. It reveals that the early calorification due to de- icers as high as the temperature of laboratory increases within about 10 minutes and last for more then 2 hours and the test of ice-formation on the surface of contrete and asphalt specimen due to snow leads to the similar rate of freezing time about 20 minutes. Second, three kinds of de-icers, such as CaC2 CaC2+Nacl, Cacl Flaket are rested in the snowy highway to check the iceing-resistance. The CaC2 is proved to be the most effective de-icers so far.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.294-298
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• 2008

Snow cover is a potential water resource for later spring and summer seasons as well as a thermal mirror with high reflectivity causing decreases of surface air temperature during cold winter seasons. In this study, current and future changes in Northern Hemisphere snow extent and their potential linkages with atmospheric circulation are examined. The NOAA AVHRR visible snow extent (1967-2006) data as well as observational (NCEP-DOE 1979-2006) and modeled (GFDL 2.1 2081-2100) pressure and surface air temperature data are used. Analyses of observational data demonstrate that the snow extent in meteorological spring (March to April) and summer (June to August) has significantly decreased since the late 1980s. The offset of snow seasons (the timing of snow melt in spring) have also significantly advanced particularly in Europe, East Asia, and northwestern North America. Analyses of pressure fields reveal that the spatial patterns of the earlier snow melt are associated with changes in atmospheric circulation such as the Arctic Oscillation (AO). In the positive winter AO years, multiple positive pressure departure cores in the upper troposphere (200hPa) are observed over the mid-latitude regions from March to mid-April, while a negative pressure departure core (70hPa) prevails over the Arctic Ocean. The reversed anomaly patterns related to later snow melt occur in negative winter AO years. The comparison between current and future thermal spring onsets suggest that snow melt patterns will intensify with larger greenhouse gas emissions, indicating earlier hydrological spring onset.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.325-328
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• 2007

We discuss the Normalized Difference Vegetation Index (NDVI) of the forest canopy and floor separately based on airborne spectral reflectance measurements and simultaneous airborne land surface images acquired around Yakutsk, Siberia in 2000. The aerial land surface images were visually classified into four forest types: no-green canopy and snow floor (Type-1), green canopy and snow floor (Type-2), no-green canopy and no-snow floor (Type-3), and green canopy and no-snow floor (Type-4). The mean NDVI was calculated for these four types. Although Type-2 had green canopy, the NDVI was rather small (0.17) because of high reflection from the snow cover on the floor. Type-3, which had no green canopy, indicated considerably large NDVI (0.45) due to the greenness of the floor. Type-4 had the largest NDVI (0.75) because of the greenness of both the canopy and floor. These results reveal that the NDVI depends considerably on forest floor greenness and snow cover in addition to canopy greenness.