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        검색결과 6

        1.
        2009.03 KCI 등재 구독 인증기관 무료, 개인회원 유료
        본 연구에서는 동계에 한랭 건조한 대륙성 기단이 서해를 통과할 때 서해 연안지역인 인천, 군산, 목포의 적설량과 해양기상요소와의 관련성에 대하여 조사하였다. 한반도 서해 연안지역인 인천, 군산, 목포의 동계(12월~2월) 평균 적설량은 군산이 12.7cm로 가장 많았으며, 목포(9.0cm), 인천(7.8cm) 순으로 나타났다. 특히, 세 지역에서 적설량은 12월과 2월에 지역적인 차이를 나타내었다. 이와 같은 지역적인 적설량의 차이는 대륙성 고기압의 확장과 관계하였다. 대륙성고기압은 12월에 중국 화남지방에 중심을 두고 산동반도 및 한반도 서부연안지역을 통과하고, 1월에는 중국 화북지방에서 한반도 중부지방으로 확장하며, 2월에는 중국의 북쪽지방에서 발해만과 요동반도를 통과하여 한반도의 중부지방으로 확장하였다. 이 대륙성고기압의 확장과 관련하여 인천은 적설이 2월이 12월보다 많았고, 군산과 목포는 12월이 2월보다 많은 적설을 나타내었다. 세 지역에서 대설은 열손실이 100 w/m2 이상일 때 나타났다. 또한, 대설은 대륙성 고기압과 저기압의 배치가 서부지역에 전선이 형성되는 서고동저형일 때 발생하였고, 이때 바람은 4-8m/sec 세기의 북서풍 또는 북풍이 우세하였다.
        4,000원
        2.
        2008.01 KCI 등재 서비스 종료(열람 제한)
        Temporal and spatial variabilities of chlorophyll a (Chl-a) in the northern East China Sea (ECS) are described, using both 8-day composite images of the SeaWiFS (Sea-viewing Wide Field-of-view Sensor) and in-situ data investigated in August and September during 2000-2005. Ocean color imagery showed that Chl-a concentrations on the continental shelf within the 50 m depth in the ECS were above 10 times higher than those of the Kuroshio area throughout the year. Higher concentrations (above 5 mg/m3) of yearly mean Chl-a were observed along the western part of the shelf near the coast of China. The standard deviation also showed the characteristics of the spatial variability near 122-124°E, where the western region of the East China Sea was grater than that of the eastern region. Particularly the significant concentration of Chl-a, up to 9 mg/m3, was found at the western part of 125°E in the in-situ data of 2002. The higher Chl-a concentrations of in-situ data were consistent with low salinity waters of below 30 psu. It means that there were the close relationship between the horizontal distribution of Chl-a and low salinity water.
        4.
        2001.12 KCI 등재 서비스 종료(열람 제한)
        Variations in phytoplankton concentrations result from changes of the ocean color caused by phytoplankton pigments. Thus, ocean spectral reflectance for low chlorophyll waters are blue and high chlorophyll waters tend to have green reflectance. In the Korea region, clear waters and the open sea in the Kuroshio regions of the East China Sea have low chlorophyll. As one moves even closer to the northwestern part of the East China Sea, the situation becomes much more optically complicated, with contributions not only from higher concentrations of phytoplankton, but also from sediments and dissolved materials from terrestrial and sea bottom sources. The color often approaches yellow-brown in the turbidity waters (Case Ⅱ waters). To verify satellite ocean color retrievals, or to develop new algorithms for complex case Ⅱ regions requires ship-based studies. In this study, we compared the chlorophyll retrievals from NASA's SeaWiFS sensor with chlorophyll values determined with standard fluorometric methods during two cruises on Korean NFRDI ships. For the SeaWiFS data, we used the standard NASA SeaWiFS algorithm to estimate the chlorophyll a distribution around the Korean waters using Orbview/ SeaWiFS satellite data acquired by our HPRT station at NFRDI. We studied to find out the relationship between the measured chlorophyll a from the ship and the estimated chlorophyll a from the SeaWiFS satellite data around the northern part of the East China Sea, in February, and May, 2000. The relationship between the measured chlorophyll_a and the SeaWiFS chlorophyll_a shows following the equations (1) in the northern part of the East China Sea. Chlorophyll_a=0.121Ln(X) + 0.504, R2 = 0.73 (1) We also determined total suspended sediment mass (SS) and compared it with SeaWiFS spectral band ratio. A suspended solid algorithm was composed of in-situ data and the ratio (LWN(490 nm)/LWN(555 nm)) of the SeaWiFS wavelength bands. The relationship between the measured suspended solid and the SeaWiFS band ratio shows following the equation (2) in the northern part of the East China Sea. SS=-0.703 Ln(X) + 2.237, R2 = 0.62 (2) In the near future, NFRDI will develop algorithms for quantifying the ocean color properties around the Korean waters, with the data from regular ocean observations using its own research vessels and from three satellites, KOMPSAT/OSMI, Terra/MODIS and Orbview/SeaWiFS.
        5.
        2001.04 KCI 등재 서비스 종료(열람 제한)
        The magnitudes of sea surface temperature (SST) anomalies at 13 coastal stations along the Korean peninsula in the summer and winter for the past 29years (1969-1997) are more larger than those in the spring and autumn. The periods of positive SST anomalies (negative SST anomalies) longer than 1℃ were 75(74.5) months in the eastern coast of Korea, 47.8(51.6) months in the southern coast of Korea and 69.5(69.8) months in the western coast of Korea during the past 348 months (1969-1997). The predominant periods of the low-pass filtered monthly SST anomalies are 3 years or 13 months, even another predominant period is 24 months. The spatial variation of SST anomalies were confined by regional seas of the Korean peninsula, such as the East Sea, the South Sea and the West Sea itself.
        6.
        2000.08 KCI 등재 서비스 종료(열람 제한)
        The relationship between air temperature and sea surface temperature are studied using the daily air temperature and sea surface temperature data for 25 years (1970∼1994) at 9 coastal stations in Korea. Seasonal variations of air temperature have larger amplitudes than those of sea surface temperature. The seasonal variations of air temperature leads those of sea surface temperature by 2 to 3 weeks. The anomalies of sea surface temperature and air temperature are positively correlated. The long term anomalies of sea surface temperature and air temperature with time scales more than 1 month are more highly correlated than those of short term, with time scales less than 1 month. Accumulated monthly anomalies of sea surface temperature and air temperature for 6 months showed higher correlation than the anomalies of each month. The magnitudes of sea surface temperature and air temperature anomalies are related with the duration of anomalies. Their magnitudes are large when the durations of anomalies are long.