자료동화 시스템의 초기 입력자료(First Guess)을 만드는 입력자료 중 라디오존데, 항공기, 레이더 등 3차원 기 상정보는 정확한 기상 예측을 위한 유용한 정보이다. 이러한 관측자료는 대기 중 기상인자에 대한 연직분포를 제공하며, 수 치예보의 성능을 향상시키는 데 크게 기여한다. 특히, 기상항공기에 탑재된 관측장비 중 드롭존데(Dropsonde), 항공기 통합기상관측시스템(Airborne Integrated Meteorological Measurement System, AIMMS), 해상풍 측정 마이크로파복사계 (Stepped Frequency Microwave Radiometer, SFMR) 등은 항공기 이착륙 및 비행경로에 따른 기상정보의 관측·수집을 통해 수치예보모델의 예측성에 큰 영향을 주는 것으로 알려져 있으며 해상 관측 공백 지역의 해소를 위한 관측수행과 자료수집이 가능하다는 장점이 있다. 이에 본 연구에서는 보다 효율적인 항공 관측 업무 수행 및 수치예보 연구를 수 행하기 위하여 기상항공기에 탑재된 기상요소를 관측하는 장비인 드롭존데, AIMMS의 자료동화 적용 및 모델 결과 간 모의 성능 비교 실험을 수행하였다. 수치모의를 위해 사용된 모델은 현업에서 사용하는 중규모 모델인 KIM-Meso (Korea Integrated Model-Mesoscale version)와 동일한 물리과정으로 구성된 WRF (Weather Research and Forecasting Model) 로 도메인 1 , 2의 수평해상도는 각각 3 , 1 km이며 격자 크기는 690×650, 409×562로 설정하였다. 연구 사례일 은 4가지 위험기상임무(Severe Weather-01, 02, 03, 04) 중 관측자료와 수치모델 검증(SW-04)을 위한 임무로 수행된 태 풍 힌남노 영향 종료 후 고기압의 영향을 받는 비교적 안정한 사례 및 태풍 예측진로에 따른 전향지역의 연직기상구조 변동성 분석(SW-02)을 위한 사례로 한반도 전역에 강수와 강한 바람을 일으켜 피해를 주었던 오마이스 사례로 선정하 였다. 초기 입력자료 개선을 위해 적용한 자료동화 기법은 3차원변분법(3 Dimensional VARiational, 3DVAR)으로 미국 국립환경예측센터(National Centers for Environmental Prediction, NCEP)에서 제공하는 FNL (Final analyses) 재분석장 을 모델의 초기/경계조건으로 사용하였고, 예측 시간은 총 144시간(6일)으로 설정하였다. 아울러 사례기간 동안 모델의 예측 성능을 평가하기 위해 대상지역에 위치한 ASOS (Automated Synoptic Observing System)의 기상변수를 사용하였 으며 관측 및 모의 수치를 통계적으로 비교하였다. 전반적으로 대부분의 관측지점에서 자료동화를 적용한 DA (Data Assimilation) 실험 결과가 자료동화를 적용하지 않은 CTL (Control) 실험에 비해 향상된 예측정확도를 보였다. 특히, 기온은 모든 자료동화 적용 실험(DROP, AIMMS, DROP+AIM)에서 향상된 결과를 보였으며 풍속은 A IMMS , D ROP, DROP+AIM 결과에서 향상된 모의 결과를 보였다. 상대습도의 경우 관측값의 다소 건조한 대기상태를 모델이 일부 모 의하지 못한 것으로 나타났으나, 대체로 CTL 실험에 비해 자료동화 적용 실험의 모의 결과가 향상된 것을 확인할 수 있었다.

In this study, the contributions of emissions (foreign and domestic) and atmospheric physical and chemical processes to PM2.5 concentrations were evaluated during a high PM2.5 episode (March 24-26, 2018) observed on the Jeju Island in the spring of 2018. These analyses were performed using the community multi-scale air quality (CMAQ) modeling system using the brute-force method and integrated process rate (IPR) analysis, respectively. The contributions of domestic emissions from South Korea (41-45%) to PM2.5 on the Jeju Island were lower than those (81-89%) of long-range transport (LRT) from China. The substantial contribution of LRT was also confirmed in conjunction with the air mass trajectory analysis, indicating that the frequency of airflow from China (58-62% of all trajectories) was higher than from other regions (28-32%) (e.g., South Korea). These results imply that compared to domestic emissions, emissions from China have a stronger impact than domestic emissions on the high PM2.5 concentrations in the study area. From the IPR analysis, horizontal transport contributed substantially to PM2.5 concentrations were dominant in most of the areas of the Jeju Island during the high PM2.5 episode, while the aerosol process and vertical transport in the southern areas largely contributed to higher PM2.5 concentrations.

Temporal and spatial characteristics of the frequency of several weather types and the change in air pollutant concentrations according to these weather types were analyzed over a decade (2007-2016) in seven major cities and a remote area in Korea. This analysis was performed using hourly (or daily) observed data of weather types (e.g., mist, haze, fog, precipitation, dust, and thunder and lighting) and air pollutant criteria (PM10, PM2.5, O3, NO2, CO, and SO2). Overall, the most frequent weather type across all areas during the study period was found to be mist (39%), followed by precipitation (35%), haze (17%), and the other types (≤ 4%). In terms of regional frequency distributions, the highest frequency of haze (26%) was in Seoul (especially during winter and May-June), possibly due to the high population and air pollutant emission sources, while that of precipitation (47%) was in Jeju (summer and winter), due to its geographic location with the sea on four sides and a very high mountain. PM10 concentrations for dust and haze were significantly higher in three cities (up to 250 μg/m3 for dust in Incheon), whereas those for the other four types were relatively lower. The concentrations of PM2.5 and its major precursor gases (NO2 and SO2) were higher (up to 69 μg/m3, 48 ppb, and 16 ppb, respectively, for haze in Incheon) for haze and/or dust than for the other weather types. On the other hand, there were no distinct differences in the concentrations of O3 and CO for the weather types. The overall results of this study confirm that the frequency of weather types and the related air quality depend on the geographic and environmental characteristics of the target areas.

The classification of airflow patterns during high ozone (O3) and PM10 episodes on Jeju Island in recent years (2009-2015), as well as their correlation with meteorological conditions according to classified airflow patterns were investigated in this study. The airflow patterns for O3 and PM10 were classified into four types (Types A-D) and three types (Types E-G), respectively, using the HYbrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model and synoptic weather charts. Type A was the most dominant airflow pattern for O3 episodes, being characterized by the transport of airflows from urban and industrial areas in China with the highest frequency (about 69%, with a mean of 67 ppb). With regard to the PM10 episodes, Type E was the most dominant airflow pattern, and was mostly associated with long distance transport from Asian dust source regions along northwesterly winds, having the highest frequency (about 92%, with a mean of 136 μg/m3). The variations in the concentration of O3 and PM10 during the study period were clarified in correlation with two pollutant and meteorological variables; for example, the high (low) O3 and PM10 concentrations with high (low) air temperature and/or wind speed and vice versa for precipitation. The contribution of long-range transport to the observed PM10 levels in urban sites for different airflow patterns (Types E-F), if estimated in comparison to the data from the Gosan background site, was found to account for approximately 87-93% (on average) of its input. The overall results of the present study suggest that the variations in O3 and PM10 concentrations on Jeju Island are mainly influenced by the transport effect, as well as the contribution of local emissions.

Long-term variations of PM10 and the characteristics of local meteorology related to its concentration changes were analyzed at 4 air quality sites (Ido-dong, Yeon-dong, Donghong-dong, and Gosan) in Jeju during two different periods, such as PI (2001-2006) and PII (2007-2013), over a 13-year period. Overall, the long-term trend of PM10 was very slightly downward during the whole study period, while the high PM10 concentrations in PII were observed more frequently than those in PI. The concentration variations of PM10 during the study period was clarified in correlation between PM10 and meteorological variables, e.g. the low (high) PM10 concentration with large (small) precipitation or high (low) radiation and in part high PM10 concentrations (especially, Donghong-dong and Gosan) with strong wind speed and the westerly/northwesterly winds. This was likely to be caused by the transport effect (from the polluted regions of China) rather than the contribution of local emission sources. The PM10 concentrations in “Asian dust” and “Haze” weather types were higher, whereas those in “Precipitation”, “Fog”, and “Thunder and Lighting” weather types were lower. The contribution of long-range transport to the observed PM10 levels in the urban center (Ido-dong, Yeon-dong, and Donghong-dong), if estimated by comparison to the data of the background site (Gosan), was found to explain about 80% (on average) of its input.

The characteristics of meteorological conditions related to changes in atmospheric environment on Jeju Island were investigated during recent years (2010-2012). This analysis was performed using the hourly observed data of meteorological variables (air temperature, wind speed and direction) and air pollutants (O3, PM10, SO2, NO2, and CO). Out of 5 pollutants, O3 and PM10 concentrations have frequently exceeded national environmental standards in the study area during the study period, with relatively higher concentrations than the others. The concentrations of O3 and PM10 in 2010 and 2011 were somewhat higher than those in 2012, and their highest concentrations were mostly observed in spring followed by fall. Nighttime O3 concentrations (with relatively high concentration levels) were almost similar to its daytime concentrations, due to less O3 titration by very low NO concentrations in the target area and in part to O3 increase resulting from atmospheric transport processes. The transport effect related to the concentration variations of O3 and PM10 was also clarified in correlation between these pollutants and meteorological variables, e.g. the high exceedance frequency of concentration criteria with strong wind speed and the high concentrations with the westerly/northwesterly winds (e.g., transport from the polluted regions of China). The overall results of this study suggest that the changes in atmospheric environment in the study area were likely to be caused by the transport effect (horizontal and vertical) due to the meteorological conditions rather than the contribution of local emission sources.