• 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.

• Journal of The Korean Astronomical Society
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• v.36 no.spc1
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• pp.83-91
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• 2003

There are terrestrial signatures of the solar activity cycle in ice core data (Ram & Stoltz 1999), but the variations in the sun's irradiance over the cycle seem too small to account for the signature (Lean 1997; Goode & Dziembowski 2003). Thus, one would expect that the signature must arise from an indirect effect(s) of solar activity. Such an indirect effect would be expected to manifest itself in the earth's reflectance. Further, the earth's climate depends directly on the albedo. Continuous observations of the earthshine have been carried out from Big Bear Solar Observatory since December 1998, with some more sporadic measurements made during the years 1994 and 1995. We have determined the annual albedos both from our observations and from simulations utilizing the Earth Radiation Budget Experiment (ERBE) scene model and various datasets for the cloud cover, as well as snow and ice cover. With these, we look for inter-annual and longer-term changes in the earth's total reflectance, or Bond albedo. We find that both our observations and simulations indicate that the albedo was significantly higher during 1994-1995 (activity minimum) than for the more recent period covering 1999-2001 (activity maximum). However, the sizes of the changes seem somewhat discrepant. Possible indirect solar influences on the earth's Bond albedo are discussed to emphasize that our earthshine data are already sufficiently precise to detect, if they occur, any meaningful changes in the earth's reflectance. Still greater precision will occur as we expand our single site observations to a global network.

• Journal of Soil and Groundwater Environment
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• v.20 no.5
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• pp.16-25
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• 2015

The City of Boulder is located at an average elevation of 1,655 m (5,430 feet), the foothills of the Rocky Mountains in Colorado. Its daily air temperature is much varying and snow is very frequent and heavy even in spring. This paper examines characteristics of shallow (surface and depth = 10 cm) soil temperatures measured from January to May 2015 in the high elevation city Boulder, Colorado. The surface soil temperature quickly responded to the air temperature with the strongest periodicity of 1 day while the subsurface soil temperatures showed a less correlation and delayed response with that. The short-time Fourier of the soil temperatures uncovered their very low frequencies characteristics in heavy snow days while it revealed high frequencies of their variations in warm spring season. The daily minimum air temperature exhibited high cross-correlations with the soil temperatures without lags unlike the maximum air temperature, which is derived from its higher and longer auto-correlation and stronger spectrums of low frequencies than the maximum air temperature. The snow depth showed an inverse relationship with the soil temperature variations due to snow's low thermal conductivity and high albedo. Multiple regression for the soil temperatures using the air temperature and snow depth presented its predicting possibility of them even though the multiple r² of the regression is not that much satisfactory (r² = 0.35-0.64).

• Journal of the Korean earth science society
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• v.33 no.2
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• pp.139-147
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• 2012

Mongolia's solar-meteorological resources map has been developed using satellite data and reanalysis data. Solar radiation was calculated using solar radiation model, in which the input data were satellite data from SRTM, TERA, AQUA, AURA and MTSAT-1R satellites and the reanalysis data from NCEP/NCAR. The calculated results are validated by the DSWRF (Downward Short-Wave Radiation Flux) from NCEP/NCAR reanalysis. Mongolia is composed of mountainous region in the western area and desert or semi-arid region in middle and southern parts of the country. South-central area comprises inside the continent with a clear day and less rainfall, and irradiation is higher than other regions on the same latitude. The western mountain region is reached a lot of solar energy due to high elevation but the area is covered with snow (high albedo) throughout the year. The snow cover is a cause of false detection from the cloud detection algorithm of satellite data. Eventually clearness index and solar radiation are underestimated. And southern region has high total precipitable water and aerosol optical depth, but high solar radiation reaches the surface as it is located on the relatively lower latitude. When calculated solar radiation is validated by DSWRF from NCEP/NCAR reanalysis, monthly mean solar radiation is 547.59 MJ which is approximately 2.89 MJ higher than DSWRF. The correlation coefficient between calculation and reanalysis data is 0.99 and the RMSE (Root Mean Square Error) is 6.17 MJ. It turned out to be highest correlation (r=0.94) in October, and lowest correlation (r=0.62) in March considering the error of cloud detection with melting and yellow sand.