• 대기
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• 제26권4호
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• pp.599-615
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• 2016

This study investigates the accuracy of short-term ocean predictions during the development of ocean stratification for the Korea Meteorological Administration (KMA) Global Seasonal Forecast System version 5 (GloSea5) as well as the effect of atmosphere-ocean coupling on the predictions through a series of sensitive numerical experiments. Model performance is evaluated using the marine meteorological buoys at seas around the Korean peninsular (KP), Tropical Atmosphere Ocean project (TAO) buoys over the tropical Pacific ocean, and ARGO floats data over the western North Pacific for boreal winter (February) and spring (May). Sensitive experiments are conducted using an ocean-atmosphere coupled model (i.e., GloSea5) and an uncoupled ocean model (Nucleus for European Modelling of the Ocean, NEMO) and their results are compared. The verification results revealed an overall good performance for the SST predictions over the tropical Pacific ocean and near the Korean marginal seas, in which the Root Mean Square Errors (RMSE) were $0.31{\sim}0.45^{\circ}C$ and $0.74{\sim}1.11^{\circ}C$ respectively, except oceanic front regions with large spatial and temporal SST variations (the maximum error reached up to $3^{\circ}C$). The sensitive numerical experiments showed that GloSea5 outperformed NEMO over the tropical Pacific in terms of bias and RMSE analysis, while NEMO outperformed GloSea5 near the KP regions. These results suggest that the atmosphere-ocean coupling substantially influences the short-term ocean forecast over the tropical Pacific, while other factors such as atmospheric forcing and the accuracy of simulated local current are more important than the coupling effect for the KP regions being far from tropics during the development of ocean stratification.

• 한국환경과학회지
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• 제5권4호
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• pp.429-440
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• 1996

A global carbon cycle model (GCCM), that incorporates interaction among the terrestrial biosphere, ocean, and atmosphere, was developed to study the carbon cycling aid global carbon budget, especially due to anthropogenic $CO_2$ emission. The model that is based on C, 13C and 14C mass balance, was calibrated with the observed $CO_2$ concentration, $\delta$13C and $\Delta$14C in the atmosphere, Δ14C in the soil, and $\Delta$14C in the ocean. Also, GCCM was constrained by the literature values of oceanic carbon uptake and CO, emissions from deforestation. Inputs (forcing functions in the model) were the C, 13C and 14C as $CO_2$ emissions from fossil fuel use, and 14C injection into the stratosphere by bomb-tests. The simulated annual carbon budget of 1980s due to anthropoRenic $CO_2$ shows that the global sources were 5.43 Gt-C/yr from fossil fuel use and 0.91 Gt-C/yr from deforestation, and the sinks were 3.29 Gt-C/yr in the atmosphere, 0.90 Gt-C/yr in the terrestrial biosphere and 2.15 Gt-C/yr in the ocean. The terrestrial biosphere is currently at zero net exchange with the atmosphere, but carbon is lost cia organic carbon runoff to the ocean. The model could be utilized for a variety of studies in $CO_2$ policy and management, climate modeling, $CO_2$ impacts, and crop models.

• 한국대기환경학회지
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• 제15권6호
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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.

• 한국환경과학회지
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• 제8권6호
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• pp.645-652
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• 1999

In order to simulate and investigate the major characteristics of El Nino/Southern Oscillation(ENSO) and Madden Jullian Oscillation(MJO), an intermediate type atmosphere-ocean coupled model is developed and their results are examined. The atmosphere model is a time-dependent non-linear perturbation moist model which can determine the internal heating for itself. The counterpart of the atmosphere model is GCM-type tropical ocean model which has fine horizontal and vertical grid resolutions. In the coupled experiment, warm SST anomaly and increased precipitation and eastward wind and current anomalies associated with ENSO and MJO are properly simulated in Pacific and Indian Oceans. In spite of some discrepancies in simulation MJO, the observed atmospheric and oceanic low-frequency characteristics in the tropics are successfully identified. Among them, positive SST anomalies centered at the 100m-depth of tropical eastern-central Pacific due to the eastward advection of warm water and reduced equatorial upwelling, and negative anomalies in the Indian and western Pacific seem to be the fundamental features of tropical low-frequency oscillations.

• 한국환경과학회지
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• 제3권2호
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• pp.129-140
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• 1994

An intermediate atmosphere-ocean coupled model appropnate for the study of El Nino has been developed. The model is not only economic to use but also contains several most important physical processes. The geometrical effects which were not confided in the previous intermediate model study of Ahn (1990), are included in the model for more realistic simulation of the event. The results show that the individual models respond appropriately to the given boundary conditions. At the same time, in the coupled model experiment, ENSO-like oceanic and atmospheric anomalies are also well simulated under an external triggering similar to the initiation forcing of ENSO. It is expected that this type of model can be effectively used for the. study and simulation of El Nido. More improvement of modeling may be Possible after inclusion of subsequent processes such as inclusion of ocean mixed layer dynamics.

• 한국측량학회지
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• 제39권2호
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• pp.93-101
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• 2021

Recently, with the urban redevelopment and the spread of the planned cities, there is increasing interest in the wind environment, which is related not only to design of buildings and landscaping but also to the comfortability of pedestrians. Numerical analysis for wind environment prediction is underway in many fields, such as dense areas of high-rise building or composition of the apartment complexes, a precisive 3D building model is essentially required in this process. Many studies conducted for wind environment analysis have typically used the method of creating a 3D model by utilizing the building layer included in the GIS (Geographic Information System) data. These data can easily and quickly observe the flow of atmosphere in a wide urban environment, but cannot be suitable for observing precisive flow of atmosphere, and in particular, the effect of a complicated structure of a single building on the flow of atmosphere cannot be calculated. Recently, drone photogrammetry has shown the advantage of being able to automatically perform building modeling based on a large number of images. In this study, we applied photogrammetry technology using a drone to evaluate the flow of atmosphere around two buildings located close to each other. Two 3D models were made into an automatic modeling technique and manual modeling technique. Auto-modeling technique is using an automatically generates a point cloud through photogrammetry and generating models through interpolation, and manual-modeling technique is a manually operated technique that individually generates 3D models based on point clouds. And then the flow of atmosphere for the two models was compared and analyzed. As a result, the wind environment of the two models showed a clear difference, and the model created by auto-modeling showed faster flow of atmosphere than the model created by manual modeling. Also in the case of the 3D mesh generated by auto-modeling showed the limitation of not proceeding an accurate analysis because the precise 3D shape was not reproduced in the closed area such as the porch of the building or the bridge between buildings.

• 한국환경과학회지
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• 제11권8호
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• pp.773-781
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• 2002

The natural carbon cycle has been perturbed since the mid-19th century by anthropogenic CO$_2$emissions from fossil fuel combustion and deforestation due to population growth and industrialization. The current study simulated the global carbon cycle for the past 42 years using an eight-box carbon cycle model. The results showed that since the terrestrial biospheric carbon sink was roughly offset by the deforestation source, the fossil fuel emission source was partitioned between the atmospheric and oceanic sinks. However, the partitioning ratio between the atmosphere and the ocean exhibited a change, that is, the carbon accumulation rate was faster in the atmosphere than in the ocean, due to a decrease in the so-called ocean buffering capacity. It was found that the ocean buffering capacity to take up excess CO$_2$decreased by 50% in terms of the buffer factor over the past 42 years. Accordingly, these results indicate that if the current CO$_2$emission trend continues, the future rate of increase in the atmospheric CO$_2$concentration will accelerate.

• 한국해안해양공학회:학술대회논문집
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• 한국해안해양공학회 2008년도 발표논문집
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• pp.208-211
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• 2008

• 한국해안해양공학회:학술대회논문집
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• 한국해안해양공학회 2008년도 발표 논문집 제17권
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• pp.208-211
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• 2008

• 한국환경과학회지
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• 제31권7호
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• pp.617-635
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• 2022

The effect of coupled data assimilation (DA) on the meteorological prediction in the west coastal region of Korea was evaluated using a coupled atmosphere-ocean model (e.g., COAWST) in the spring (March 17-26) of 2019. We performed two sets of simulation experiments: (1) with the coupled DA (i.e., COAWST_DA) and (2) without the coupled DA (i.e., COAWST_BASE). Overall, compared with the COAWST_BASE simulation, the COAWST_DA simulation showed good agreement in the spatial and temporal variations of meteorological variables (sea surface temperature, air temperature, wind speed, and relative humidity) with those of the observations. In particular, the effect of the coupled DA on wind speed was greatly improved. This might be primarily due to the prediction improvement of the sea surface temperature resulting from the coupled DA in the study area. In addition, the improvement of meteorological prediction in COAWST_DA simulation was also confirmed by the comparative analysis between SST and other meteorological variables (sea surface wind speed and pressure variation).