• Korean Journal of Remote Sensing
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• v.13 no.1
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• pp.1-12
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• 1997

The western equatorial Pacific Ocean, where sea surface temperature is the warmest on the globe, is characterized by numerous convective systems and large annual precipitation. In this region, the cloudiness data with tops higher than 8km level obtained from the GMS-IR data are used to investigate the diurnal variation of cloudiness. The amplitude and phase of diurnal and semi-diurnal cycles are mainly investigated to examine details on the temporal and spatial structure of clouds. Cloudiness variation has typical cycles and each cycle is associated with the air-sea interactive phenomena. Spectral analysis on the cloudiness time series data indicates that 30-60 day, 17-20day, 7-8 day, diurnal and semi diurnal cycle are peaked. During Northern Winter and Southern Summer, the large cloudiness exsists over New Guinea, the adjacent seas of North Australia, and the open oceanic regions east of $160^{\circ}$E. Cloudiness diurnal variability over the lands and their adjacent seas is about 2.0 times larger than that over the open sea regions. That may be due to the difference of specific heat between the land and sea. The maximum and minimum cloudiness appeared at 18:00 and 09:00 hours over the land, and at noon and 21:00 hours over the sea, respectively. The amplitude of diurnal component over the land is 4,7 times larger than that of semi-diurnal component, and 1.5 times over the sea.

• Atmosphere
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• v.31 no.2
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• pp.229-240
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• 2021

The Global Ocean Data Assimilation and Prediction System (GODAPS) in operation at the KMA (Korea Meteorological Administration) is introduced. GODAPS consists of ocean model, ice model, and 3-d variational ocean data assimilation system. GODAPS assimilates conventional and satellite observations for sea surface temperature and height, observations of sea-ice concentration, as well as temperature and salinity profiles for the ocean using a 24-hour data assimilation window. It finally produces ocean analysis fields with a resolution of 0.25 ORCA (tripolar) grid and 75-layer in depth. This analysis is used for providing a boundary condition for the atmospheric model of the KMA Global Seasonal Forecasting System version 5 (GloSea5) in addition to monitoring on the global ocean and ice. For the purpose of evaluating the quality of ocean analysis produced by GODAPS, a one-year data assimilation experiment was performed. Assimilation of global observing system in GODAPS results in producing improved analysis and forecast fields with reduced error in terms of RMSE of innovation and analysis increment. In addition, comparison with an unassimilated experiment shows a mostly positive impact, especially over the region with large oceanic variability.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.36 no.1
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• pp.49-63
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• 2016

In this study, we analyzed the effects of regional hydrologic variability during warm season (June-September) in South Korea due to ENSO (El $Ni{\tilde{n}}o$-Southern Oscillation) pattern changes over the Tropical Pacific Ocean (TPO). We performed composite analysis (CA) and statistical significance test by Student's t-test using observed hydrologic data (such as, precipitation and streamflow) in the 113 sub-watershed areas over the 5-Major River basin, in South Korea. As a result of this study, during the warm-pool (WP) El $Ni{\tilde{n}}o$ year shows a significant increasing tendency than normal years. Particularly, during the cold-tongue (CT) El $Ni{\tilde{n}}o$ decaying years clearly decreasing tendency compared to the normal years was appeared. In addition, the La $Ni{\tilde{n}}a$ years tended to show a slightly increasing tendency and maintain the average year state. In addition, from the result of scatter plot of the percentage anomaly of hydrologic variables during warm season, it is possible to identify the linear increasing tendency. Also the center of the scatter plot shows during the WP El $Ni{\tilde{n}}o$ year (+17.93%, +26.99%), the CT El $Ni{\tilde{n}}a$ year (-8.20%, -15.73%), and the La $Ni{\tilde{n}}a$ year (+8.89%, +15.85%), respectively. This result shows a methodology of the tele-connection based long-range water resources prediction for reducing climate forecasting uncertainty, when occurs the abnormal SSTA (such as, El $Ni{\tilde{n}}o$ and La $Ni{\tilde{n}}a$) phenomenon in the TPO region. Furthermore, it can be a useful data for water managers and end-users to support long-range water-related policy making.