• Journal of Environmental Science International
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• v.12 no.3
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• pp.257-263
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• 2003

Oceanographic features around Korean waters related to the global change were studied by analysis of the longterm variation of water temperature, dissolved oxygen, sea level of the surface layer with 1$^{\circ}C$ temperature, spatial position of the subpolar front in the East Sea/Japan Sea (the East sea hereafter) and the Wolf Sunspot Number. With the global warming, the temperature of Korean waters has been increased 0.5∼1.0$^{\circ}C$ for 33years (1968∼2000). In case of the dissolved oxygen in the East Sea has been decreased 0.46$m\ell$/$\ell$. Year to year vertical fluctuations of the monthly anomalies of the surface layer with 1$^{\circ}C$water in the East Sea have predominant periods with 15years as the longterm variation of Arctic climate, 12 and 18years as the El Nino-Southern Oscillation. Spatial position of the subpolar front in the East Sea moved to northern part of the sea from the southern part of the sea with the increasing sea surface temperature. The relationship between the number of Wolf Sunspot and the anomalies of sea surface temperature was very closer after the late of 1980s than those before the early of 1980s in Korean waters.

• Journal of Environmental Science International
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• v.23 no.8
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• pp.1481-1493
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• 2014

In order to understand the relation between the distribution of sea surface temperature and heavy snowfall over western coast of the Korean peninsula, several numerical assessments were carried out. Numerical model used in this study is WRF, and sea surface temperature data were FNL(National Center for Environment Prediction-Final operational global analysis), RTG(Real Time Global analysis), and OSTIA(Operational Sea Surface Temperature and Sea Ice Analysis). There were produced on the basis of remote sensing data, such as a variety of satellite and in situ observation. The analysis focused on the heavy snowfall over Honam districts for 2 days from 29 December 2010. In comparison with RTG and OSTIA SST data, sensible and latent heat fluexes estimated by numerical simulation with FNL data were higher than those with RTG and OSTIA SST data, due to higher sea surface temperature of FNL. General distribution of RTG and OSTIA SST showed similar, however, fine spatial differences appear in near western coast of the peninsula. Estimated snow fall amount with OSTIA SST was occurred far from the western coast because of higher SST over sea far from coast than that near coast. On the other hand, snowfall amount near coast is larger than that over distance sea in simulation with RTG SST. The difference of snowfall amount between numerical assessment with RTG and OSTIA is induced from the fine difference of SST spatial distributions over the Yellow sea. So, the prediction accuracy of snowfall amount is strongly associated with the SST distribution not only over near coast but also over far from the western coast of the Korean peninsula.

• Proceedings of the KSRS Conference
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• 2001.03a
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• pp.104-110
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• 2001

Ocean heat fluxes over a wide region are generally estimated by an aerodynamic bulk fromula. Though a remote sensing technique can be expected to estimated global heat flux, it is difficult to obtain air temperature and specific humidity at sea surface by a remote sensor. In this study present a new method with which to determine near-sea surface air temperature from in situ data. Also, These methods compared with other methods. A new method used a linear regression equation between sea surface temperature and air temperature of the buoys data. In this study new method is validated using observed monthly mean data at the Japan Meteorological Agency(JMA), National Data Buoy Center(NDBC) and Tropical Ocean-Global Atmosphere(TOGA)-Tropical Atmosphere Ocean(TAO) buoys. The result that bias and rmse are 0.28, 1.5$0^{\circ}C$ respectively. The correlation coefficient is 0.98. Also, to retrieve near-sea surface specific humidity(Q) from good nonlinear regression relationship between vapor pressure(Ea) of buoy data and air temperature, after obtained the third-order polynomial function, compared with that of estimated from SSM/I empirical equation by Schussel et al(1995). The result that bias and rmse are -1.42 and 1.75(g/kg).

• Journal of Environmental Science International
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• v.19 no.2
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• pp.171-184
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• 2010

Accurate simulation of the meteorological field is very important to assess the wind resources. Some researchers showed that sea surface temperature (SST) plays a leading role on the local meterological simulation. New Generation Sea Surface Temperature (NGSST), Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA), and Real-Time Global Sea Surface Temperature (RTG SST) have different spatial distribution near the coast and OSTIA shows the best accuracy compared with buoy data in the southeastern coast of the Korean Peninsula. Those SST products are used to initialize the Weather Research and Forecasting (WRF) Model for November 13-23 2008. The simulation of OSTIA shows better result in comparison with NGSST and RTG SST. NGSST shows a large difference with OSTIA in horizontal and vertical wind fields during the weak synoptic condition, but wind power density shows a large difference during strong synoptic condition. RTG SST shows the similar patterns but smaller the magnitude and the extent.

• Proceedings of the KSRS Conference
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• v.2
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• pp.880-883
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• 2006

Altimeter(Topex/Poseidon) and AVHRR(NOAA) data were used to study the variations and correlations of Sea Level(SL) and Sea Surface Temperature (SST) in the North East Asian Seas from November 1993 to May 1998. This region is influenced simultaneously to continental and oceanic climate as the border of the East Sea(Japan Sea). SL and SST have increased gradually every year because the global warming, and presented usually a strong annual variations in Kuroshio extension region with the influence of bottom topography.

• Korean Journal of Remote Sensing
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• v.23 no.1
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• pp.59-63
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• 2007

Altimeter (Topex/Poseidon) and AVHRR (NOAA) data were used to study the variations and correlations of Sea Level (SL) and Sea Surface Temperature (SST) in the North East Asian Seas from November 1993 to May 1998. This region is influenced simultaneously to continental and oceanic climate as the border of the East Sea (Japan Sea). SL and SST have increased gradually every year because the global warming, and presented usually a strong annual variations in Kuroshio extension region with the influence of bottom topography.

• Journal of information and communication convergence engineering
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• v.1 no.1
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• pp.58-60
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• 2003

Altimeter(Topex/Poseidon) and AVHRR(NOAA) data were used to study the variations and correlations of Sea Level(SL) and Sea Surface Temperature (SST) in the North East Asian Seas from November 1993 to May 1998. This region is influenced simultaneously to continental and oceanic climate. SL and SST have increased gradually every year because the global warming, and presented usually a strong annual variations in Kuroshio extension region with the influence of bottom topography.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.76-82
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• 1998

Increase of greenhouse gas due to $CO_2$ and CH$_4$ gases would cause the global warming in the atmosphere. According to the global circulation model, it is pointed out in the Okhotsk Sea that the large increase of atmospheric temperature might be occurredin this region by global warming due to the doubling of greenhouse effectgases. Therefore, it is very important to monitor the sea ice extents in the Okhotsk Sea. To improve the sea ice extents and concentration with more highly accuracy, the field experiments have begun to comparewith Airborne Microwave Radiometer (AMR) and video images installed on the aircraft (Beach-200). The sea ice concentration is generally proportional to the brightness temperature and accurate retrieval of sea ice concentration from the brightness temperature is important because of the sensitivity of multi-channel data with the amount of open water in the sea ice pack. During the field experiments of airborned AMR the multi-frequency data suggest that the sea ice concentration is slightly dependending on the sea ice types since the brightness temperature is different between the thin and small piece of sea ice floes, and a large ice flow with different surface signatures. On the basis of classification of two sea ice types, it is cleary distinguished between the thin ice and the large ice floe in the scatter plot of 36.5 and 89.0GHz, but it does not become to make clear of the scatter plot of 18.7 and 36.5GHz Two algorithms that have been used for deriving sea ice concentrations from airbomed multi-channel data are compared. One is the NASA Team Algorithm and the other is the Bootstrap Algorithm. Intrercomparison on both algorithms with the airborned data and sea ice concentration derived from video images bas shown that the Bootstrap Algorithm is more consistent with the binary maps of video images.

• Atmosphere
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• v.29 no.2
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• pp.149-164
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• 2019

The purpose of this study is to introduce the improvement of current operational climate prediction system of KMA and to compare previous and improved that. Whereas the previous system is based on GloSea5GA3, the improved one is built on GloSea5GC2. GloSea5GC2 is a fully coupled global climate model with an atmosphere, ocean, sea-ice and land components through the coupler OASIS. This is comprised of component configurations Global Atmosphere 6.0 (GA6.0), Global Land 6.0 (GL6.0), Global Ocean 5.0 (GO5.0) and Global Sea Ice 6.0 (GSI6.0). The compositions have improved sea-ice parameters over the previous model. The model resolution is N216L85 (~60 km in mid-latitudes) in the atmosphere and ORCA0.25L75 ($0.25^{\circ}$ on a tri-polar grid) in the ocean. In this research, the predictability of each system is evaluated using by RMSE, Correlation and MSSS, and the variables are 500 hPa geopotential height (h500), 850 hPa temperature (t850) and Sea surface temperature (SST). A predictive performance shows that GloSea5GC2 is better than GloSea5GA3. For example, the RMSE of h500 of 1-month forecast is decreased from 23.89 gpm to 22.21 gpm in East Asia. For Nino3.4 area of SST, the improvements to GloSeaGC2 result in a decrease in RMSE, which become apparent over time. It can be concluded that GloSea5GC2 has a great performance for seasonal prediction.

• Journal of Environmental Science International
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• v.7 no.5
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• pp.725-733
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• 1998

Three numerical experiments are done using IAP(Institute of Atmospheric Physics) global spectral model(T42L9) to investigate the influence of the surface temperatures on the 7-day simulation. Particularly, the response of the subtropical High in summer to the variation of soil temperature and sea surface temperature(SST) was emphasized through a series of experiments. Experiment 1 uses the June climate data as the earth surface conditions. Experiment 2 is similar to Experiment 1 except for the soil surface temperature. Experiment 3 is the same as Experiment 1 except for the modified SST, which is much warmer than the June climate SST on the sea around the Korean peninsula. The main finding in 7-day simulation is that the response of the subtropical high in summer to the variation of the sell surface temperature was much more than that to the variation of the SST. It is implied that the proper treatment of sell surface temperature is more important than that of the SST for the better 7-day simulation of the subtropical high in summer.