• Journal of computational fluids engineering
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• v.4 no.3
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• pp.44-51
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• 1999

A modified version of SST turbulence model is suggested to simulate unsteady separated flows over oscillating airfoils. The original SST model, which shows good performance in predicting various steady flows, often results in oscillatory behavior of aerodynamic loads in large separated flow regions. It is shown that this oscillatory behavior is due to the adoption of the absolute value of vorticity in generalizing the original model. As a remedy, a modification is made such that the vorticity in the original SST model is replaced by strain rate. The present model is verified for a mild separated airfoil flow at fixed angle of incidence and for unsteady flowfields about oscillating airfoils. The results are compared with BSL model and original SST model. It is illustrated that the present model gives a better agreement with the experimental results than other two models.

• Atmosphere
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• v.23 no.2
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• pp.161-169
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• 2013

We examine the effects of the sea surface temperature (SST) distribution on heavy snowfall over the Yellow Sea using high-resolution SST products and WRF (Weather Research and Forecasting) model simulations in 30 December 2010. First, we evaluate the model by comparing the simulated and observed fresh snowfall over the Korean peninsula (Ho-Nam province). The comparison shows that the model reproduces the distributions and magnitudes of the observed snowfall. We then conduct sensitivity model simulations where SST perturbations by ${\pm}1.1^{\circ}C$ relative to baseline SST values (averaged SST for $5{\sim}15^{\circ}C$) are uniformly specified over the region of interest. Results show that ${\pm}1.1^{\circ}C$ SST perturbation simulations result in changes of air temperature by $+0.37/-0.38^{\circ}C$, and by ${\pm}0.31^{\circ}C$ hPa for sea level pressure, respectively, relative to the baseline simulation. Atmospheric responses to SST perturbations are found to be relatively linear. The changes in SST appear to perturb precipitation variability accounting for 10% of snow and graupel, and 18% of snowfall over the Yellow Sea and Ho- Nam province, respectively. We find that anomalies of air temperature, pressure, and hydrometeors due to SST perturbation propagate to the upper part of cloud top up to 500 hPa and show symmetric responses with respect to SST changes.

• Journal of the Korean earth science society
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• v.28 no.3
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• pp.343-356
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• 2007

This paper explored the characteristics of the interannual sea surface temperature (SST) variability in the equatorial Pacific by analyzing the simulated data from a newly coupled general circulation model (CGCM). The CGCM simulates well the realistic ENSO variability as well as the mean climatologies including SST, seasonal cycle, precipitation, and subsurface structures. It is argued that the zonal gradient of SST in the equatorial Pacific is responsible for the over-energetic SST variability near the equatorial western boundary in the model. This variability could also be related to the strong westward propagation of SST anomalies which resulted from the enhanced the zonal advection feedback. The simple two-strip model supports this by sensitivity tests. Analysis of the relationship between zonal mean thermocline depth and NINO3 SST index suggested that the ENSO variability is controlled by the recharge-discharge oscillator of the model. The lead-lag regression result reveals that heat buildup process in the western equatorial Pacific associated with the increase of the barrier layer thickness (BLT) is a precedent condition for El $Ni\widetilde{n}o$ to develop.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.31 no.8
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• pp.1-7
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• 2003

The numerical simulation of flow-filed around a square cylinder near a wall with $\varepsilon$-SST turbulence model is carried out in this study. The newly suggested $\varepsilon$-SST turbulence model that modifies the original SST turbulence model is proved to yield more accurate results than the other 2-equation turbulence models in large separation region around a bluff body. Therefore, $\varepsilon$-SST turbulence model can be effectively applied for predicting the flow-fields with large separation. And it is found that vortex shedding is suppressed below the critical gap height, the Strouhal number is affected by the gap height and the wall boundary layer thickness.

• Korean Journal of Remote Sensing
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• v.17 no.2
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• pp.183-188
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• 2001

The NOAA AVHRR remotely sensed SST data, collected by the National Fisheries Research and Development Institute (NFRDI), are analyzed in order to understand the spatial and temporal distributions of SST in the sea near korea. Our study is based on 10-day SST images during last 7 years (1991-1997). For a time series analysis of multiple SST images, all of images must be consistent exactly at the same position by adjusting the scales and positions of each SST image. We devised an algorithm which automatically detects cloud pixels from multiple SST images. The cloud detection algorithm is based on a physical constraint that SST anomalies in the ocean do not exceed certain limits (we used $\pm$3$^{\circ}C$ as a criterion of SST anomalies). The remotely sensed SST data are tuned by comparing remotely sensed data with observed SST at coastal stations. Seasonal variations of SST are studied by harmonic fit of SST normals at each pixel and the SST anomalies are studied by statistical method. It was found that the SST anomalies are rather persistent for one or two months. Utilizing the persistency of SST anomalies, we devised an algorithm for a prediction of future SST. In the Markov lprocess model of SST anomalies, autoregression coefficients of SST anomalies during a time elapse of 10 days are between 0.5 and 0.7. The developed algorithm with automatic cloud pixel detection and rediction of future SST is expected to be incorporated to the operational real time service of SST around Korea.

• Journal of Environmental Science International
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• v.10 no.3
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• pp.187-194
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• 2001

For the purpose of predicting air pollutants concentration in Pusan coastal urban, we used an Eulerian model of flow and dispersion/chemistry/deposition process considering SST effects which estimate through POM. The results of air quality model including emission from various sources show that the seasonal variation pattern of respective pollutants was affected by the seasonal SST fields and local circulation. Horizontal deviation of diurnal SST was 2.5~4K, especially large gradients in coastal region. Through numerical simulation of wind fields we predicted that local circulation prevailed during daytime in summer and nighttime in winter. So high concentration distribution showed toward inland in spring and summer seasons, while high concentration distribution showed at inland near coast in autumn and winter.

• Journal of Korean Society for Atmospheric Environment
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• v.15 no.6
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• pp.767-777
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• 1999

In the coastal region air flow changes due to the abrupt change of surface temperature between land and sea. So a numerical simulation for atmospheric flow fields must be considered the correct fields of sea surface temperature(SST). In this study, we used variables such as latent heat flux, sensible heat flux, short and long wave radiation of ocean and atmosphere which exchanged across the sea surface between atmosphere and ocean model. We found that this consideration simulated the more precise SST fields by comparing with those of the observated results. Simulated horizontal SST differences in season were 2.5~4$^{\circ}C$. Therefore we simulated the more precise atmospheric flow fields and the movement and dispersion of the pollutants with the Lagrangian particle dispersion model. In the daytime dispersion pattern of the pollutants emitted from ship sources moved toward inland, in the night time moved toward sea by land/sea breeze criculation. But air pollutants dispersion can be affected by inland topography, especially Yangsan and coastal area because of nocturnal wind speed decrease.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.236-241
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• 1998

The NOAA AVHRR remote sense SST data, collected by the National Fisheries Research and Development Institute (NFRDI), are analyzed in order to understand the spatial and temporal distributions of SST in the seas adjacent to Korea. Our study is based on 10-day SST images during last 7 years (1991-1997). For a time series analysis of multiple 557 images, all of images must be aligned exactly at the same position by adjusting the scales and positions of each SST image. We devised an algorithm which yields automatic detections of cloud pixels from multiple SST images. The cloud detection algorithm is based on a physical constraint that SST anomalies in the ocean do not exceed certain limits (we used $\pm$ 3$^{\circ}C$ as a criterion of SST anomalies). The remote sense SST data are tuned by comparing remote sense data with observed SST at coastal stations. Seasonal variations of SST are studied by harmonic fit of SST normals at each pixel. The SST anomalies are studied by statistical method. We found that the SST anomalies are rather persistent with time scales between 1 and 2 months. Utilizing the persistency of SST anomalies, we devised an algorithm for a prediction of future SST Model fit of SST anomalies to the Markov process model yields that autoregression coefficients of SST anomalies during a time elapse of 10 days are between 0.5 and 0.7. We plan to improve our algorithms of automatic cloud pixel detection and prediction of future SST. Our algorithm is expected to be incorporated to the operational real time service of SST around Korea.

• Korean Journal of Remote Sensing
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• v.6 no.1
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• pp.39-47
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• 1990

The first Marine Observation Satellite(MOS) was launched by National Space Development Agency of Japan on February 19, 1987, and it is equipped with three sensons covering visible, infrared, and microwave region. One of them is Visible and Thermal Infrared Radiometer(VTIR) whose main objective is to detect the Sea Surface Temperature(SST). The objective of this study was to process the MOS data using Cray-2 supercomputer, and to assess the SST in the Yellow Sea. In order to implement this objective, the linear regression model between the ground truth data and the corresponding digital number of VTIR in MOS was used to establish the relationship. After testing the significance of the regression model, the SST map of the whole Yellow Sea was derived based on the model. The digital SST map representing the study area showed certain pattern about the SST of Yellow Sea in March and April. In conclusion, the VTIR data in MOS is also useful in investigating SST which provides the information about the Yellow Sea water current in the spring.

• 한국해양학회지
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• v.27 no.1
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• pp.35-45
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• 1992

This paper is concerned with the development and application of a stochastic model for predicting E1 nino phenomenon. For this, first a general criterion for determining E1 nino phenomenon, including period and strength, which is based on partial sum of monthly sea surface temperatures (SST) anomalies, is proposed, Secondly, the annual fluctuations, periodicity and dependence of monthly mean of equatorial Pacific SST during the period 1951-1990 are analyzed. Based on these, time series nonlinear regression model for the prediction of SST have been derived. A statistical procedure for using the model to predict the SST have been derived. A statistical procedure for using the model to predict the SST level is also proposed.