• Journal of Korean Society for Atmospheric Environment
• /
• v.10 no.E
• /
• pp.357-370
• /
• 1994

This paper introduces an Eulerian long- range transport model coupled with a mesoscale atmospheric model. The model has been applied to the simulation of tracer distribution during two cases of Cross Appalachian Tracer Experiment (CAPIEX). Meteorological fields are Predicted by CSU RAMS with four-dimensional assimilation and tracer transport is computed from an Eulerian dispersion model. The atmospheric model with a four-dimensional assimilation has produced meteorological fields that agree well with observation and has proved its high potential as a generator of meteorological data for a long-range transport model. The Present transport model Produces reasonable simulations of observed tracer transport although it was partially successful in the case with complicated structure in observed concentration. Model with Bott's 2nd-order scheme performs as well as that with Bott's 4th-order scheme and increased explicit horizontal diffusivity. Diagnosis of the model results indicates that the Present long-range transport model has a good potential as a framework for the acid deposition model with detailed cloud and chemical processes.

• Journal of Korean Society for Atmospheric Environment
• /
• v.14 no.3
• /
• pp.219-228
• /
• 1998

In the present investigation, a numerical model developed for the prediction of the wind flow over complex terrain is validated by comparing with the field experiments. For the solution of the Reynolds - Averaged Clavier- stokes equations which are the governing equations of the microscale atmospheric flow, the model is constructed based on the finite-volume formulation and the SIMPLEC pressure-correction algorithm for the hydrodynamic computation. The boundary- fitted coordinate system is employed for the detailed depiction of topography. The boundary conditions and the modified turbulence constants suitable for an atmospheric boundary- layer are applied together with the k- s turbulence model. The full- scale experiments of Cooper's Ridge, Kettles Hill and Askervein Hill are chosen as the validation cases . Comparisons of the mean flow field between the field measurements and the predicted results show good agreement. In the simulation of the wind flow over Askervein Hill , the numerical model predicts the three dimensional flow separation in the downslope of the hill including the blockage effect due to neighboring hills . Such a flow behavior has not been simulated by the theoretical predictions. Therefore, the present model may offer the most accurate prediction of flow behavior in the leeside of the hill among the existing theoretical and numerical predictions.

• Journal of Environmental Science International
• /
• v.4 no.5
• /
• pp.403-411
• /
• 1995

The atmospheric responses to a Sea Surface Temperature Anomaly(SSTA) over the equatorial eastern Pacific Ocean have been investigated using the horizontally fine resolution model based on OSU 2-layer Atmospheric General Circulation Model(AGCM). The SSTAS daring the peak phase of 1982-83 El Nino have been applied to the model as the boundary conditions of the experiment. The model simulates the eastward movement of the rising branch of the Walker circulation. That is, the major features associated with the El Nino such as the increase of the precipitation rate over the center of the Pacific and decrease over the Indonesia, and the 500hPa geopotential height anomaly in the middle latitude are properly describes in the fine resolution model experiment. The model results indicate that this horizontally fine resolution UM can successfully simulate the ENSO anomalies and be more effectivelly used for the study of the climate and the climate changes.

• Ocean Science Journal
• /
• v.43 no.4
• /
• pp.165-173
• /
• 2008

In this article, we describe a simple yet effective method for insertion of observational datasets in a mesoscale atmospheric model used in one-dimensional configuration through Nudging. To demonstrate the effectiveness of this technique, vertical profiles of meteorological parameters obtained from GLASS Sonde launches from a tiny island of Kaashidhoo in the Republic of Maldives are injected in a mesoscale atmospheric model - Advanced Regional Prediction System (ARPS), and model simulated parameters are compared with the available observational datasets. Analysis of one-time nudging in the model simulations over Kaashidhoo show that incorporation of this technique reasonably improves the model simulations within a time domain of +6 to +12 Hrs, while its impact on +18 Hrs simulations and beyond becomes literally null.

• Journal of Korean Society for Atmospheric Environment
• /
• v.5 no.2
• /
• pp.84-96
• /
• 1989

To evaluate the short term air pollution dispersion model, the diffusion experiment was conducted on the flat terrain near Chuncheon. Sulfur hexafluoride $(SF_6)$ gas was used to determine the horizontal spread of plume $(\sigmay)$ for calculated by CRSTER model. Results show that CRSTER model underestimates $\sigma$y because averaging time adjustment is not applied to calculate the $\sigma$y. The scheme that can estimate the atmospheric stability more accurate than Turner method, was presented.

• Nuclear Engineering and Technology
• /
• v.55 no.6
• /
• pp.2305-2314
• /
• 2023

The governing equations of atmospheric dispersion most often taking the form of a second-order partial differential equation (PDE). Currently, typical computational codes for predicting atmospheric dispersion use the Gaussian plume model that is an analytic solution. A Gaussian model is simple and enables rapid simulations, but it can be difficult to apply to situations with complex model parameters. Recently, a method of solving PDEs using artificial neural networks called physics-informed neural network (PINN) has been proposed. The PINN assumes the latent (hidden) solution of a PDE as an arbitrary neural network model and approximates the solution by optimizing the model. Unlike a Gaussian model, the PINN is intuitive in that it does not require special assumptions and uses the original equation without modifications. In this paper, we describe an approach to atmospheric dispersion modeling using the PINN and show its applicability through simple case studies. The results are compared with analytic and fundamental numerical methods to assess the accuracy and other features. The proposed PINN approximates the solution with reasonable accuracy. Considering that its procedure is divided into training and prediction steps, the PINN also offers the advantage of rapid simulations once the training is over.

• Atmosphere
• /
• v.27 no.2
• /
• pp.235-249
• /
• 2017

This paper describes methodology verifying near-surface predictability of numerical weather prediction models against the surface synoptic weather station network (SYNOP) observation. As verification variables, temperature, wind, humidity-related variables, total cloud cover, and surface pressure are included in this tool. Quality controlled SYNOP observation through the pre-processing for data assimilation is used. To consider the difference of topographic height between observation and model grid points, vertical inter/extrapolation is applied for temperature, humidity, and surface pressure verification. This verification algorithm is applied for verifying medium-range forecasts by a global forecasting model developed by Korea Institute of Atmospheric Prediction Systems to measure the near-surface predictability of the model and to evaluate the capability of the developed verification tool. It is found that the verification of near-surface prediction against SYNOP observation shows consistency with verification of upper atmosphere against global radiosonde observation, suggesting reliability of those data and demonstrating importance of verification against in-situ measurement as well. Although verifying modeled total cloud cover with observation might have limitation due to the different definition between the model and observation, it is also capable to diagnose the relative bias of model predictability such as a regional reliability and diurnal evolution of the bias.

• Korean Journal of Remote Sensing
• /
• v.23 no.1
• /
• pp.7-14
• /
• 2007

Atmospheric correction is one of critical procedures to extract quantitative information related to biophysical variables from hyperspectral imagery. Most atmospheric correction algorithms developed for hyperspectral data have been based upon atmospheric radiative transfer (RT) codes, such as MODTRAN. Because of the difficulty in acquisition of atmospheric data at the time of image capture, the complexity of RT model, and large volume of hyperspectral data, atmospheric correction can be very difficult and time-consuming processing. In this study, we attempted to develop an efficient method for the atmospheric correction of EO-1 Hyperion data. This method uses the pre-calculated look-up-table (LUT) for fast and simple processing. The pre-calculated LUT was generated by successive running of MODTRAN model with several input parameters related to solar and sensor geometry, radiometric specification of sensor, and atmospheric condition. Atmospheric water vapour contents image was generated directly from a few absorption bands of Hyperion data themselves and used one of input parameters. This new atmospheric correction method was tested on the Hyperion data acquired on June 3, 2001 over Seoul area. Reflectance spectra of several known targets corresponded with the typical pattern of spectral reflectance on the atmospherically corrected Hyperion image, although further improvement to reduce sensor noise is necessary.

• Korean Journal of Remote Sensing
• /
• v.24 no.5
• /
• pp.417-425
• /
• 2008

An image-based atmospheric correction software ATC is implemented using MATLAB and SML (Spatial Modeler Language in ERDAS IMAGINE), and it was tested using Landsat TM/ETM+ data. This ATC has two main functional modules, which are composed of a semiautomatic type and an automatic type. The semi-automatic functional module includes the Julian day (JD), Earth-Sun distance (ESD), solar zenith angle (SZA) and path radiance (PR), which are programmed as individual small functions. For the automatic functional module, these parameters are computed by using the header file of Landsat TM/ETM+. Three atmospheric correction algorithms are included: The apparent reflectance model (AR), one-percent dark object subtraction technique (DOS), and cosine approximation model (COST). The ACT is efficient as well as easy to use in a system with MATLAB and SML.

• Atmosphere
• /
• v.21 no.2
• /
• pp.151-162
• /
• 2011

One-layer solar radiation(GWNU; Gangneung-Wonju National University) model is developed in order to resolve the lack of vertical observations and fast calculation with high resolution. GWNU model is based on IQBAL(Iqbal, 1983) and NREL(National Renewable Energy Laboratory) methods and corrected by precise multi-layer LBL(Line-by-line) model. Input data were used 42 atmospheric profiles from Garand et al.(2001) for calculation of global radiation by the Multi-layer and one-layer solar radiation models. GWNU model has error of about -0.10% compared with LBL model while IQBAL and NREL models have errors of about -3.92 and -2.57%, respectively. Global solar radiation was calculated by corrected GWNU solar model with satellites(MODIS, OMI and MTSAT-1R), RDPS model prediction data in Korea peninsula in 2009, and the results were compared to surface solar radiation observed by 22 KMA solar sites. All models have correlation($R^2$) of 0.91 with the observed hourly solar radiation, and root mean square errors of IQBAL, NREL and GWNU models are 69.16, 69.74 and $67.53W/m^2$, respectively.