• Atmosphere
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• v.19 no.2
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• pp.155-168
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• 2009

Characteristics of seasonal mean diurnal temperature range (DTR) and their causes over South Korea are investigated using the 60 stations data of Korea Meteorological Administration from 1976 to 2005. In general, the seasonal mean DTR is greatest during spring (in inland area) and least during summer (urban and coastal area). The spatial and seasonal variations of DTR are closely linked with the land surface conditions (especially vegetation activity and soil moisture) and atmospheric conditions (cloud amount, precipitation, local circulation). The seasonal mean DTR shows a decreasing trend at the major urban areas and at the north-eastern part of South Korea. Whereas, it shows an increasing trend at the central area of the southern part. Decreasing and increasing trends of DTR are more significant during summer and fall, and during spring and winter. The decrease (increase) of DTR is mainly caused by the stronger increase of daily minimum (maximum) temperature than daily maximum (minimum) temperature. The negative effects of precipitation and cloud amount on the DTR are greater during spring and at the inland area than during winter and at the coastal area. And the effect of daytime precipitation on the DTR is greater than that of nighttime precipitation.

• Korean Journal of Remote Sensing
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• v.38 no.2
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• pp.179-188
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• 2022

Global warming causes climate change and increases extreme weather events worldwide, and the occurrence of heatwaves and droughts is also increasing in Korea. For the monitoring of extreme weather, various satellite data such as LST (Land Surface Temperature), TCI (Temperature Condition Index), NDVI (Normalized Difference Vegetation Index), VCI (Vegetation Condition Index), and VHI (Vegetation Health Index) have been used. VHI, the combination of TCI and VCI, represents the vegetation stress affected by meteorological factors like precipitation and temperature and is frequently used to assess droughts under climate change. TCI and VCI require historical reference values for the LST and NDVI for each date and location. So, it is complicated to produce the VHI from the recent satellite GK2A (Geostationary Korea Multi-Purpose Satellite-2A). This study examined the retrieval of VHI using GK2A AMI (Advanced Meteorological Imager) by referencing the historical data from VIIRS (Visible Infrared Imaging Radiometer Suite) NDVI and LST as a proxy data. We found a close relationship between GK2A and VIIRS data needed for the retrieval of VHI. We produced the TCI, VCI, and VHI for GK2A during 2020-2021 at intervals of 8 days and carried out the interpretations of recent extreme weather events in Korea. GK2A VHI could express the changes in vegetation stress in 2020 due to various extreme weather events such as heatwaves (in March and June) and low temperatures (in April and July), and heavy rainfall (in August), while NOAA (National Oceanic and Atmospheric Administration) VHI could not well represent such characteristics. The GK2A VHI presented in this study can be utilized to monitor the vegetation stress due to heatwaves and droughts if the historical reference values of LST and NDVI can be adjusted in a more statistically significant way in the future work.

• Journal of Korea Water Resources Association
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• v.37 no.4
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• pp.315-328
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• 2004

Recent increase of green house gases may increase the frequency of meteorological extremes. In this study, using the index and meteorological data generated by the Markov chain model under the condition of GCM predictions, the possible width of variability of flood and drought occurrences were predicted. As results, we could find that the frequency of both floods and droughts would be increased to make the water resources planning and management more difficult. Thus, it is recommended to include the effect of climate change on water resources in the related policy making.

• Korean Journal of Remote Sensing
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• v.29 no.1
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• pp.115-121
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• 2013

The first geostationary satellite in Korea, COMS (Communication, Ocean, and Meteorological Satellite), has been operating properly since its successful completion of the IOT (In Orbit Test). COMS MI (Meteorological Imager) acquires Earth observation images from visible and infrared channels. This paper describes a method to compute the degradation of the COMS visible detectors and the result of the degradation during the two years of the operation. The visible channel detectors' performance was determined based on the comparison between the instrument-based measurements and ROLO model-based values. The degradation rate of the visible channel detectors of COMS MI showed a normal condition.

• Atmosphere
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• v.23 no.1
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• pp.13-21
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• 2013

In this study, the effects of atmospheric stability and surface temperature on the microscale local airflow are investigated in a hydrological suburban area using a computational fluid dynamics (CFD) model. The model domain includes the river and industrial complex for analyzing the effect of water system and topography on local airflow. The surface boundary condition is constructed using a geographic information system (GIS) data in order to more accurately build topography and buildings. In the control experiment, it is shown that the topography and buildings mainly determine the microscale airflow (wind speed and wind direction). The sensitivity experiments of atmospheric stability (neutral, stable, and unstable conditions) represent the slight changes in wind speed with the increase in vertical temperature gradient. The differential heating of ground and water surfaces influences on the local meteorological factors such as air temperature, heat flow, and airflow. These results consequentially suggest that the meteorological impact assessment is accompanied by the changes of background land and atmospheric conditions. It is also demonstrated that the numerical experiments with very high spatial resolution can be useful for understanding microscale local meteorology.

• Journal of Korean Society for Atmospheric Environment
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• v.8 no.4
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• pp.213-220
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• 1992

Simple correlation analysis, factor analysis, and multi-variate analysis have been performed to analyze the relationship between air pollution and meteorological factors for air pollution and meteorological data measured at Kwanghwamun in Seoul during the period of one year(January 1990 $\sim$ December 1990). As a result of simple correlation and factor analysis, $SO_2$, TSP and CO concentrations have shown high negative correlation with temperature and among these indicating that these are related with pollutant emission trend based upon heating fuel usage. Ozone has a good corrleation with solar radiation and relative humidity to have a closed relation with $O_3$ generation reaction mechanism. The result of multi-variate correlation analysis shows that the concentration of $SO_2$ and CO are adequate for correlation model with ambient temperature and wind speed and $O_3$ concentrations are adequate for that with solar radiation and wind speed. $SO_2$ and CO levels are considered to be affected first of all by heating fuel usage as a emssion source and wind speed as a dispersion effect. The $SO_2$ concentration in the condition that the temperature fall below zero is explained by multilicative model with wind speed, only one variable.

• Journal of Environmental Science International
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• v.18 no.3
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• pp.271-281
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• 2009

In order to reduce the uncertainties and improve the air flow field, objective analysis using observational data is chosen as a method that enhances the reality of meteorology. To improve the meteorological components, the radius influence and nudging coefficient of the objective analysis should perform a adequate value on complex area for the objective analysis technique which related to data reliability and error suppression. Several numerical experiments have been undertaken in order to clarify the impacts of the radius influence and nudging coefficient of the objective analysis on meteorological environments. By analyzing practical urban ground conditions, we revealed that there were large differences in the meteorological differences in each case. In order to understand the quantitative impact of each run, the Statistical analysis by estimated by MM5 revealed the differences by the synoptic conditions. The strengthening of the synoptic wind condition tends to be well estimated when using quite a wide radius influence and a small nudging coefficient. On the other hand, the weakening of the synoptic wind is opposite.

• Journal of the Korea Institute of Military Science and Technology
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• v.11 no.5
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• pp.84-91
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• 2008

The spectral radiance received by a remote sensor at a given temperature and wavelength region is consisted of the self-emitted component directly from the object surface, the reflected component of the solar irradiation at the object surface, and the scattered component by the atmosphere without ever reaching the object surface. The IR image of a ship is mainly affected by location, meteorological condition(atmosphere temperature, wind direction and velocity, humidity etc.), atmospheric transmittance, solar position and ship surface temperature etc. Computer simulations for prediction of the IR signatures of ships are very useful to examine the effects of various meteorological conditions. In this paper, we have acquired the IR signature for different meteorological conditions by using two different computer programs. The numerical results show that the IR image contrast as compared to the background sea considering the atmosphere temperature and wind velocity.

• Journal of Korean Society for Atmospheric Environment
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• v.10 no.4
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• pp.260-280
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• 1994

The STEM II(Sulfur Transport Eulerian Model II) was adapted to simulate transport/ chemistry/deposition of air Pollutants in the Eastern China and Korea. A 32 hour model simulation starting from 9 A.M. of 1989 November 25 during which no preciptation was observed. The Prevailing wind direction is from west to east. The MM4(Meteorological Model Version 4) was used to generate meteorological data such as temperatures, horizontal wind velocities and directions, humidities, air densities. Eddy diffusivities, dry deposition velocities and vertical wind velocities were calculated from the meteorological data. The initial condition and the emission data base were constructed from the measurements and governmental reports respectively. The model predictions of NO, NO$_2$, SO$_2$, $O_3$ at Seoul, Inchon and Pusan agree reasonably well with measurements. The model's predictability for the primary air pollutants is improved considerably as the time passes. Thus, it is concluded that the model's predictability can be significantly enhanced by reducing the uncertainties of initial conditions.

• Journal of Korean Society for Atmospheric Environment
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• v.24 no.5
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• pp.604-612
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• 2008

The ozone concentration is one of the important environmental issue for measurement of the atmospheric condition of the country. This study focuses on applying the Autoregressive Error (ARE) model for analyzing the ozone data at middle part of the Gyeonggi-Do, Anyang monitoring site in Korea. In the ARE model, eight meteorological variables and four pollution variables are used as the explanatory variables. The eight meteorological variables are daily maximum temperature, wind speed, amount of cloud, global radiation, relative humidity, rainfall, dew point temperature, and water vapor pressure. The four air pollution variables are sulfur dioxide $(SO_2)$, nitrogen dioxide $(NO_2)$, carbon monoxide (CO), and particulate matter 10 (PM10). The result shows that ARE models both overall and monthly data are suited for describing the oBone concentration. In the ARE model for overall ozone data, ozone concentration can be explained about 71% to by the PM10, global radiation and wind speed. Also the four types of ARE models for high level of ozone data (over 80 ppb) have been analyzed. In the best ARE model for high level of ozone data, ozone can be explained about 96% by the PM10, daliy maximum temperature, and cloud amount.