• Journal of Korean Society for Atmospheric Environment
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• v.19 no.6
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• pp.773-787
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• 2003

There are variations in the temperature Held due to urban heat island and anthropogenic heating so that regional scale meteorological field is changed. Therefore we simulate and predict the regional climate change according to surface characteristics through regional meteorological model. This study investigates the regional meteorological field by urbanization that influences in local circulation system using CSU-RAMS and simulates dry deposition velocity (V$_{d}$) using PNU/DEM which includes surface characteristics (such as albedo, surface hydrology and rough-ness length etc.) with calculated meteorological field. During the summer, horizontal distributions of V$_{d}$ were simulated using CSU-RAMS and PNU/DEM at Busan metropolitan area. The estimated values of V$_{d}$ were larger in forest and agricultural areas than water areas since ozone with low water solubility is destroyed slowly at wet surface or water.water.

• Journal of Environmental Impact Assessment
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• v.16 no.1
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• pp.89-98
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• 2007

In order to conduct the environmental assessment of long range transboundary air pollutants over East Asia, the moving pathways of air pollutants are of great importance, which are depending upon the meteorological weather patterns. Therefore regional scale modeling study requires the identified geopotential height distribution patterns to deal with behaviors of long range transport air pollutants for the effective long term atmospheric environmental assessment. In this study the synoptic meteorological classification using cluster analysis technique over Northeast Asia, and its previous applications of the regional scale air pollutant modeling studies were reviewed and summarized in detail. Other synoptic meteorological characteristics over Korean peninsula are also discussed.

• Journal of Korean Society for Atmospheric Environment
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• v.27 no.1
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• pp.30-40
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• 2011

Numerical simulations were carried out to investigate the impact of SST spatial distribution on the result of air quality modeling. Eulerian photochemical dispersion model CAMx (Comprehensive Air quality Model with eXtensions, version 4.50) was applied in this study and meteorological fields were prepared by RAMS (Regional Atmospheric Modeling System). Three different meteorological fields, due to different SST spatial distributions were used for air quality modeling to assess the sensitivity of CAMx modeling to the different meteorological input data. The horizontal distributions of surface ozone concentrations were analyzed and compared. In each case, the simulated ozone concentrations were different due to the discrepancies of horizontal SST distributions. The discrepancies of land-sea breeze velocity caused the difference of daytime and nighttime ozone concentrations. The result of statistic analysis also showed differences for each case. Case NG, which used meteorological fields with high resolution SST data was most successfully estimated correlation coefficient, root mean squared error and index of agreement value for ground level ozone concentration. The prediction accuracy was also improved clearly for case NG. In conclusion, the results suggest that SST spatial distribution plays an important role in the results of air quality modeling on high ozone episode at coastal region.

• Journal of Environmental Impact Assessment
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• v.21 no.1
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• pp.105-117
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• 2012

Future climate according to land-use change was simulated by regional climate model. The goal of study was to predict the distribution of meteorological elements using the Weather Research & Forecasting Model (WRF). The KME (Korea Ministry of Environment) medium-category land-use classification was used as dominant vegetation types. Meteorological modeling requires higher and more sophisticated land-use and initialization data. The WRF model simulations with HyTAG land-use indicated certain change in potential vegetation distribution in the future (2086-2088). Compared to the past (1986-1988) distribution, coniferous forest area was decreased in metropolitan and areas with complex terrain. The research shows a possibility to simulate regional climate with high resolution. As a result, the future climate was predicted to $4.5^{\circ}$ which was $0.5^{\circ}$ higher than prediction by Meteorological Administration. To improve future prediction of regional area, regional climate model with HyTAG as well as high resolution initial values such as urban growth and CO2 flux simulation would be desirable.

• Journal of Environmental Science International
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• v.18 no.5
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• pp.489-499
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• 2009

In an effort to examine the Regional Atmospheric Modeling System (RAMS ver. 4.3) to the initial meteorological input data, detailed observational data of NOAA satellite SST (Sea Surface Temperature) was employed. The NOAA satellite SST which is currently provided daily as a seven-day mean value with resolution of 0.1 $^{\circ}$ grid spacing was used instead of the climatologically derived monthly mean SST using in RAMS. In addition, the RAMS SST data must be changed new one because it was constructed in 1993. For more realistic initial meteorological fields, the NOAA satellite SST was incorporated into the RAMS-preprocess package named ISentropic Analysis package (ISAN). When the NOAA SST data was imposed to the initial condition of prognostic RAMS model, the resultant performance of near surface atmospheric fields was discussed and compared with that of default option of SST. We got the good results that the new SST data was made in a standard RAMS format and showed the detailed variation of SST. As the modeling grid became smaller, the SST differences of the NOAA SST run and the RAMS SST43 (default) run in diurnal variation were very minor but this research can apply to further study for the realistic SST situation and the development in predicting regional atmospheric field which imply the regional circulation due to differential surface heating between sea and land or climatological phenomenon.

• Journal of Climate Change Research
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• v.2 no.4
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• pp.269-281
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• 2011

In this review, numerical model results from global and regional climate models are introduced to regional detailed climate changes over East Asia and Korea. In particular, regional climate change scenarios in this region, which are created by several research groups in Korea based on Special Report on Emissions Scenarios (SRES) of IPCC 4th assessment report are introduced and characteristics of the scenarios are investigated. Despite slight differences in intensity, all scenarios reveal prominent warming over the Korean peninsula in future climate. Changes in precipitation amount vary with given scenarios and periods, but the frequency and intensity of heavy precipitation generally tend to increase in all scenarios. South Korea except for mountainous regions is expected to change into subtropical climate in future, which accompanies distinct changes in ecosystems and seasons.

• Journal of Environmental Impact Assessment
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• v.22 no.6
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• pp.609-626
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• 2013

Air quality models have been widely used to study and simulate many air quality issues. In the simulation, it is important to raise the accuracy of meteorological predicted data because the results of air quality modeling is deeply connected with meteorological fields. Therefore in this study, we analyzed the effects of meteorological fields on the air quality simulation. This study was designed to evaluate MM5 predictions by using different initial condition data and different observations utilized in the data assimilation. Among meteorological scenarios according to these input data, the results of meteorological simulation using National Centers for Environmental Prediction (Final) Operational Global Analysis data were in closer agreement with the observations and resulted in better prediction on ozone concentration. And in Seoul, observations from Regional Meteorological Office for data assimilations of MM5 were suitable to predict ozone concentration. In other areas, data assimilation using both observations from Regional Meteorological Office and Automatical Weather System provided valid method to simulate the trends of meteorological fields and ozone concentrations. However, it is necessary to vertify the accuracy of AWS data in advance because slightly overestimated wind speed used in the data assimilation with AWS data could result in underestimation of high ozone concentrations.

• Journal of Climate Change Research
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• v.2 no.1
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• pp.55-68
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• 2011

The Intergovernmental Panel on Climate Change(IPCC) has identified the causes of climate change and come up with measures to address it at the global level. Its key component of the work involves developing and assessing future climate change scenarios. The IPCC Expert Meeting in September 2007 identified a new greenhouse gas concentration scenario "Representative Concentration Pathway(RCP)" and established the framework and development schedules for Climate Modeling (CM), Integrated Assessment Modeling(IAM), Impact Adaptation Vulnerability(IAV) community for the fifth IPCC Assessment Reports while 130 researchers and users took part in. The CM community at the IPCC Expert Meeting in September 2008, agreed on a new set of coordinated climate model experiments, the phase five of the Coupled Model Intercomparison Project(CMIP5), which consists of more than 30 standardized experiment protocols for the shortterm and long-term time scales, in order to enhance understanding on climate change for the IPCC AR5 and to develop climate change scenarios and to address major issues raised at the IPCC AR4. Since early 2009, fourteen countries including the Korea have been carrying out CMIP5-related projects. Withe increasing interest on climate change, in 2009 the COdinated Regional Downscaling EXperiment(CORDEX) has been launched to generate regional and local level information on climate change. The National Institute of Meteorological Research(NIMR) under the Korea Meteorological Administration (KMA) has contributed to the IPCC AR4 by developing climate change scenarios based on IPCC SRES using ECHO-G and embarked on crafting national scenarios for climate change as well as RCP-based global ones by engaging in international projects such as CMIP5 and CORDEX. NIMR/KMA will make a contribution to drawing the IPCC AR5 and will develop national climate change scenarios reflecting geographical factors, local climate characteristics and user needs and provide them to national IAV and IAM communites to assess future regional climate impacts and take action.

• Atmosphere
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• v.31 no.4
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• pp.421-431
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• 2021

The Yeongdong region is frequently vulnerable to heavy snowfall in winter in terms of societal and economical damages. By virtue of a lot of previous efforts, snowfall forecast has been significantly improved, but the performance of light snowfall forecast is still poor since it is very conducive to synoptic and mesoscale interactions, largely attributable to Taeback mountains and East Sea effects. An intensive observation has been made in cooperation with Gangwon Regional Meteorological Office and National Institute of Meteorological Studies in winter seasons since 2019. Two distinctive Cold Air Damming (CAD) events (14 February 2019 and 6 February 2020) were observed for two years when the snowfall forecast was wrong specifically in its location and timing. For two CAD events, lower-level temperature below 2 km ranged to lowest limit in comparisons to those of the previous 6-years (2014~2019) rawinsonde soundings, along with the stronger inversion strength (> 2.0℃) and thicker inversion depth (> 700 m). Further, the northwesterly was predominant within the CAD layer, whereas the weak easterly wind was exhibited above the CAD layer. For the CAD events, strong cold air accumulation along the east side of Taeback Mountains appeared to prevent snow cloud and convergence zone from penetrating into the Yeongdong region. We need to investigate the influence of CAD on snowfall in the Yeongdong region using continuous intensive observation and modeling studies altogether. In addition, the effect of synoptic and mesoscale interactions on snowfall, such as nighttime drainage wind and land breeze, should be also examined.

• Journal of Korean Society for Atmospheric Environment
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• v.31 no.2
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• pp.181-194
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• 2015

Spatial-temporal meteorological features of the Ulsan metropolitan region (UMR) were analyzed using observations and high-resolution numerical modeling. Long-term trend analysis (1970~2013) showed a significant increase of $0.033^{\circ}Cyr^{-1}$ in the 5-year moving average temperature, although detailed short-term features varied, whereas wind speed and relative humidity over the same period displayed clear decreases of $-0.007ms^{-1}$ and $-0.29%yr^{-1}$, respectively. These trends indicate the effects of regional climate change and urbanization in the UMR. Seasonal variations averaged for the most recent three years, 2011~2013, showed that temperatures in three different regions (urban/industrial, suburban, coastal areas) of the UMR had similar seasonality, but significant differences among them were observed for a certain season. Urban and industrial complex regions were characterized by relatively higher temperatures with large differences (max.: $3.6^{\circ}C$) from that in the coastal area in summer. For wind speed, strong values in the range from 3.3 to $3.9ms^{-1}$ occurred in the coastal areas, with large differences clearly shown between the three regions in September and October. Diurnal variations of temperature were characterized by pronounced differences during the daytime (in summer) or nighttime (in winter) between the three regions. Results from the WRF modeling performed for four months of 2012 showed large variations in gridaverage temperature and winds in the UMR, which displayed significant changes by season. Especially, a clear temperature rise in the urban center was identified in July ($0.6^{\circ}C$ higher than nearby urban areas), and overall, relatively weak winds were simulated over urban and inland suburban regions in all seasons.