It is well known that atmospheric environments, including both meteorology and air quality, significantly affect public health, such as chronic lung disease and cancer, and respiratory infections. In this study, we have analyzed correlations between the number of daily respiratory outpatients and the atmospheric environments data for about ten years for the city of Busan, South Korea. The respiratory problem patients data have been categorized into two health-vulnerable groups by age over 65(DayPA_O65) and under 20(DayPA_U20), each of which shows relatively higher correlations with air quality and meteorology, respectively. However, time series analysis with factor separation results in that DayPA_O65 and DayPA_U20 show a higher relation with variance components and daily irregular factors of atmospheric concentrations, respectively.

To address the increase of weather hazards and the emergence of new types of such hazards, an optimization technique for three-dimensional (3D) representation of meteorological facts and atmospheric information was examined in this study as a novel method for weather analysis. The proposed system is termed as “meteorological and air quality information visualization engine” (MAIVE), and it can support several file formats and can implement high-resolution 3D terrain by employing a 30 m resolution digital elevation model. In this study, latest 3D representation techniques such as wind vector fields, contour maps, stream vector, stream line flow along the wind field and 3D volume rendering were applied. Implementation of the examples demonstrates that the results of numerical modeling are well reflected, and new representation techniques can facilitate the observation of meteorological factors and atmospheric information from different perspectives.

The present study analyzes the characteristics of 43 typhoons that affected the Korean Peninsula between 2002 and 2015. The analysis was based on 3-second gust measurements, which is the maximum wind speed relevant for typhoon disaster prevention, using a typhoon disaster prevention model. And the distribution and characteristics of the 3-second gusts of four typhoons, RUSA, MAEMI, KOMPASU, and BOLAVEN that caused great damage, were also analyzed. The analysis show that between May and October during which typhoons affected the Korean Peninsula, the month with the highest frequency was August(13 times), followed by July and September with 12 occurrences each. Furthermore, the 3-second gust was strongest at 21.2 m/s in September, followed by 19.6 m/s in August. These results show that the Korean Peninsula was most frequently affected by typhoons in August and September, and the 3-second gusts were also the strongest during these two months. Typhoons MAEMI and KOMPASU showed distribution of strong 3-second gusts in the right area of the typhoon path, whereas typhoons RUSA and BOLAVEN showed strong 3-second gusts over the entire Korean Peninsula. Moreover, 3-second gusts amount of the ratio of 0.7 % in case of RUSA, 0.8 % at MAEMI, 3.3 % at KOMPASU, and 21.8 % at BOLAVEN showed as "very strong", based on the typhoon intensity classification criteria of the Korea Meteorological Administration. Based on the results of this study, a database was built with the frequencies of the monthly typhoons and 3-second gust data for all typhoons that affected the Korean Peninsula, which could be used as the basic data for developing a typhoon disaster prevention system.

The purpose of this study is to quantitatively analyze the effects of a restoration project on the decrease in the temperature in the surrounding areas. The thermal environment characteristics of the investigation area were analyzed using the meteorological data from the Busanjin Automatic Weather System which is closest to the target area. The terrain data of the modeling domain was constructed using a digital map and the urban spatial information data, and the numerical simulation of the meteorological changes before and after the restoration of the stream was performed using the Envi-met model. The average temperature of the target area in 2016 was 15.2℃ and was higher than that of the suburbs. The monthly mean temperature difference was the highest at 1.1℃ in November and the lowest in June, indicating that the temperatures in the urban areas were high in spring and winter. From the Envi-met modeling results, reductions in temperature due to stream restoration were up to 1.7℃ in winter, and decreased to 3.5℃ in summer. The effect of temperature reduction was seen in the entire region where streams are being restored.

This study intend to induce citizen's voluntary preliminary disaster prevention activity to reduce damage of typhoon that occurs every year. For this purpose, a survey was conducted to develop Typhoon information contents. The number of samples used in the survey was set to 500 people, and citizens living in Jeju, Busan, and Jeonlanam-do were surveyed for areas with high typhoon disasters in order to develop practical and efficient information. The survey consisted of perception about natural disaster, how to get and use weather information, satisfaction with typhoon information and requirements. The general public perceived the typhoon as the first natural disaster. As a result of responding to the method of obtaining and utilizing weather information, the frequency of collecting weather information at the time of issuance of typhoon special report is higher than usual. The purpose of using weather information is clear and the response rate is high for the purpose of disaster prevention. The medium mainly collecting weather information is Internet portal site and mobile phone besides television. The current satisfaction with typhoon weather information is 34.8%, in addition to the accuracy of prediction, it is necessary to improve the information (that is content) provided. Specific responses to the content were investigated not only for single meteorological factors, but also for possible damage and potential countermeasures in the event of a disaster such as a typhoon. As can be seen from the above results, people are requested to provide information that can be used to detect and cope with disasters. The development of new content using easy accessible media will contribute to the reduction of damages caused by the typhoon that will occur in the future, and also to the disaster prevention activity.

For this study, WRF numerical modeling was performed, using RDAPS information for input data on typhoons affecting the Korean peninsula to produce wind data of 700hPa. RAM numerical modeling was also used to calculate 3-second gusts as the extreme wind speed. After comparing wind speeds at an altitude of 10 m to evaluate the feasibility of WRF numerical modeling, modeled values were found to be similar with measured ones, reflecting change tendencies well. Therefore, the WRF numerical modeling results were verified. As a result of comparing and analyzing these wind speeds, as calculated through RAM numerical modeling, to evaluate applicability for disaster preparedness, change tendencies were observed to be similar between modeled and measured values. In particular, modeled values were slightly higher than measured ones, indicating applicability for the prevention of possible damage due to gales. Our analysis of 3-second gusts during the study period showed a high distribution of 3-second gusts in the southeast region of the Korean peninsula from 2002-2006. The frequency of 3-second gusts increased in the central north region of Korea as time progressed. Our analysis on the characteristics of 3-second gusts during years characterized by El Niño or La Nina showed greater strength during hurricanes that affected the Korean peninsula in El Niño years.

This study was conducted to determine correlations and similarity between the ozone and PM10 data of 19 air quality monitoring stations in Busan from 2013 to 2016, using correlation and cluster analyses. Ozone concentrations ranged from 0.0278±0.0148 ppm at Gwangbok to 0.0378±0.017 ppm at Taejongdae and were high in suburban areas, such as Yongsuri and Gijang, as well as in coastal areas, such as Jaw, Gwangan, Taejongdae and Noksan. PM10 concentrations ranged from 37.2±25.0 ug/m3 at Gijang to 58.3±32.2 ug/m3 at and Jangrim. PM10 concentrations were high in the west, exceeding the annual ambient air quality standard of 50 ug/m3. Positive correlations were observed for ozone at most stations, ranging from 0.61 between Taejongdae and Sujeong to 0.92 between Bugok and Myeongjang. The correlation coefficients of PM10 between stations ranged from 0.62 between Jangrim and Jaw to 0.9 between Gwangbok and Sujeong. Yeonsan, Daeyeon, and Myeongjang were highly correlated with other stations, so they needed to be reviewed for redundancy. Ozone monitoring stations were initially divided into two sections, north-western areas and suburban-coastal areas. The suburban-coastal areas were subsequently divided into three sections. PM10 monitoring stations were initially divided into western and remaining areas, and then the remaining areas were subsequently divided into three sections.

A model coupling a meteorological predictive model and a vegetation photosynthesis and respiration model was used to simulate CO2 concentrations over coastal basin areas, and modeling results were estimated with aircraft observations during a massive sampling campaign. Along with the flight tracks, the model captured the meteorological variables of potential temperature and wind speed with mean bias results of 0.8℃, and 0.2 m/s, respectively. These results were statistically robust, which allowed for further estimation of the model’s performance for CO2 simulations. Two high-resolution emission data sets were adopted to determine CO2 concentrations, and the results show that the model underestimated by 1.8 ppm and 0.9 ppm at higher altitude over the study areas during daytime and nighttime, respectively, on average. Overall, it was concluded that the model’s CO2 performance was fairly good at higher altitude over the study areas during the study period.

During the research period, error analysis of the amount of daily precipitation was performed with data obtained from 2DVD, Parsivel, and AWS, and from the results, 79 days were selected as research days. According to the results of a synoptic meteorological analysis, these days were classified into ‘LP type, CF type, HE type, and TY type’. The dates showing the maximum daily precipitation amount and precipitation intensity were ‘HE type and CF type', which were found to be attributed to atmospheric instability causing strong ascending flow, and leading to strong precipitation events. Of the 79 days, most days were found to be of the LP type. On July 27, 2011 the daily precipitation amount in the Korean Peninsula reached over 80 mm (HE type). The leading edge of the Northern Pacific high pressure was located over the Korean Peninsula with unstable atmospheric conditions and inflow of air with high temperature and high humidity caused ascending flow, 120 mm/h with an average precipitation intensity of over 9.57 mm/h. Considering these characteristics, precipitation in these sample dates could be classified into the convective rain type. The results of a precipitation scale distribution analysis showed that most precipitation were between 0.4-5.0 mm, and ‘Rain’ size precipitation was observed in most areas. On July 9, 2011, the daily precipitation amount was recorded to be over 80 mm (CF type) at the rainy season front (Jangma front) spreading across the middle Korean Peninsular. Inflow of air with high temperature and high humidity created unstable atmospheric conditions under which strong ascending air currents formed and led to convective rain type precipitation.

To determine the effect of air pollution reduction policies, the long-term trend of air pollutants should be analyzed. Kolmogorov-Zurbenko (KZ) filter is a low-pass filter, produced through repeated iterations of a moving average to separate each variable into its temporal components. The moving average for a KZ(m, p) filter is calculated by a filter with window length m and p iterations. The output of the first pass subsequently becomes the input for the next pass. Adjusting the window length and the number of iterations makes it possible to control the filtering of different scales of motion. To break down the daily mean PM10 into individual time components, we assume that the original time series comprises of a long-term trend, seasonal variation, and a short-term component. The short-term component is attributable to weather and short-term fluctuations in precursor emissions, while the seasonal component is a result of changes in the solar angle. The long-term trend results from changes in overall emissions, pollutant transport, climate, policy and/or economics. The long-term trend of the daily mean PM10 decreased sharply from 59.6 ug/m3 in 2002 to 44.6 ug/m3 in 2015. This suggests that there was a long-term downward trend since 2005. The difference between the unadjusted and meteorologically adjusted long-term PM10 is small. Therefore, we can conclude that PM10 is unaffected by the meteorological variables (total insolation, daily mean temperature, daily mean relative humidity, daily mean wind speed, and daily mean local atmospheric pressure) in Busan.

Asthma deaths in Seoul peaked on the third, fifth, and second days after the PM concentration exceeded the daily average concentration standard. We classified the synoptic meteorological conditions, based on the days involving such cases, into three categories. Type 1 included the meteorological condition likely to cause high air pollution concentrations in the leeward region, the dominant wind direction of which is the northwest. Type 2 included the meteorological condition likely to cause high air pollution concentrations due to the weak wind velocity under stable atmospheric conditions. Type 3 was when the passage low atmospheric pressure and the expansion of high atmospheric pressure occurred at the rear, indicating a meteorological condition likely to cause high air pollution, in certain regions. Type 1 occurred 11 times, with high concentrations of over 100㎍/m³ being observed in the southeastern part of Seoul. Type 2 occurred 24 times, often accompanied by a PM concentration of 100~400 ㎍/m³. Type 3 occurred 11 times, and was accompanied by several days of yellow dust that accounted for the highest concentrations.

Average concentration of PM in Seoul metropolitan area satisfied the Korean air quality standard in 2010. Furthermore, concentration of PM in all boroughs across Seoul met the air environment standard in 2012. PM10 concentration was relatively higher in center of Seoul in comparison to the rest, while PM2.5 concentration showed exactly the contrary result. We analyzed the effect that PM emissions from vehicles would have on PM concentrations across Seoul. The results showed that average annual PM concentration recently decreased in Seoul although the number of vehicles registered annually continued its upward trend. By contrast, average fine dust concentrations in Seoul showed a decline which suggested that correlation between annual average PM concentrations and number of registered vehicles remained low. However, year-on-year vehicle registration rate recently showed a declining tendency in the same way as the trend of changes in average PM concentrations. Particularly, the upward trend in annual average PM concentrations in 2002 and 2007 was consistent with the increase in vehicle registration rate, suggesting that vehicle registration rate was closely associated with changes in PM concentrations.

As a result of broadcasters' websites, there were more reports during the typhoon Bolaven/Tembin in 2012 than in 2002 and 2003. Checking related press releases of each broadcaster on NAVER, YTN reports are 3 times more than KBS. Considering great technology progress in the Internet and smart phone user environment compared to the past, it is thought to be rather regretful in that KBS has been the supervising broadcaster over Korean disaster. As a result of daily reports, the year 2002 typhoon Rusa was reported from the date of its arrival on Korean Peninsular to 3 days, but the information required to be provided for disaster prevention before its arrival was too scarce. 2003 typhoon Maemi was reported as many times as the 2002 typhoon, but its information was provided before its arrival. This is meaningful because the information provision was intended for disaster prevention unlike the past. In 2012, the number of weather forecast broadcast on the typhoon Bolaven/Tembin increased greatly compared to 2002 and 2003. This was also determined to be due to abundant information provided by broadcasters and the Internet portal sites as a result of great progress in Korea internet industry.

As a result of dividing typhoon that affected Korean Peninsular between 1999 and 2012 into 7 types of path and entering forecast field and analysis field of RDAPS, until 36 hours from the time of forecast, it is reliable to use the forecast field of RDAPS to predict typhoon and for each typhoon path, the difference between the forecast and the analysis shows normal distribution, which is usable for weather forecast until the 36th hour. In the 48th hour from the time of forecast, the difference of result depending on each typhoon path increased, which was analyzed to be due to errors in the forecast. It was expected that relatively reasonable results should be shown if the 36th hour forecast is used to predict the strength and distribution of strong wind. As a result of using Korean RAM and observing the difference of the maximum damage, reliability was secured up to 36 hours and after 48hours, it was expected that the fluctuation of results may become more severe.

This study analyze the synoptic meteorological cause of rainfall, rainfall intensity, drop size distribution(DSD), fall velocity and oblateness measured by the 2D-Video distrometer(2DVD) by comparing two cases which are heavy rainfall event case and a case that is not classified as heavy rainfall but having more than 30 mm h-1 rainrate in July, 2014 at Gimhae region. As a results; Over the high pressure edge area where strong upward motion exists, the convective rain type occurred and near the changma front, convective and frontal rainfall combined rain type occurred. Therefore, rainrate varies based on the synoptic meteorological condition. The most rain drop distribution appeared in the raindrops with diameters between 0.4 mm and 0.6 mm and large particles appeared for the convective rain type since strong upward motion provide favorable conditions for the drops to grow by colliding and merging so the drop size distribution varies based on the location or rainfall types. The rainfall phases is mainly rain and as the diameter of the raindrop increase the fall velocity increase and oblateness decrease. The equation proposed based on the 2DVD tends to underestimated both fall velocity and oblateness compared with observation. Since these varies based on the rainfall characteristics of the observation location, standard equation for fall velocity and oblateness fit for Gimhae area can be developed by continuous observation and data collection hereafter.

There were 35 typhoons affecting Korean Peninsula from 1999 to 2009(The average annual number of typhoon is 3.18). Among these typhoons, the number of typhoon passing through the Yellow sea, the Southern sea and the East sea were 14, 6 and 15 respectively. Wind speed on the height of 10 m can be finally estimated using the surface roughness after we calculate wind speed on the height of 300 m from the data on the surface of 700 hPa. From the wind speeds on the height of 10 m, we can understand the regional distributions of strong wind speed are very different according to the typhoon tracks. Wind speed range showing the highest frequency is 10~20 m/s(45.69%), below 10 m/s(30.72%) and 20~30 m/s(17.31%) in high order. From the analysis of the wind speed on the hight of 80 m, we can know the number of occurrence of wind speed between 50 and 60 m/s that can affect wind power generation are 104(0.57%) and those of between 60 and 70 m/s that can be considered as extreme wind speed are even 8(0.04%).

Comparing to the other air pollutants like SO2, CO, the number of exceedance of the ozone national ambient air quality standard(NAAQS) and the ozone warning increased recently in Busan. The purpose of this study is to find out the preliminary symptoms for high ozone days in Busan area. In order to find out the preliminary symptoms, the hourly ozone data at air quality monitoring stations and the hourly meterological parameters at Busan regional meteorological 2007 to 2013 were used for the analysis. Averaged daily max ozone concentration was the highest(0.055 ppm) at Noksan and Youngsuri in the ozone season from 2007 to 2013. The horizontal distributions of daily max. ozone including all stations in Busan at high ozone days(the day exceeding 0.1 ppm of ozone concentration at least one station) were classified from two to five clusters by hierarchial cluster analysis. The meteorological variables showing strong correlation with daily max. ozone were the daily mean dew point temperature, averaged total insolation, the daily mean relative humidity and the daily mean cloud amount. And the most frequent levels were 19-23℃ in dew point temperature, 21-24 MJ/m2 in total insolation on the day before, 2.6-3.0 MJ/m2 on the very day, 67-80% in relative humidity and 0-3 in cloud amount.

The production of highly concentrated PM10 is in the spotlight as a social issue, and it increases the attack rate of Asthma. This study aimed to analyze the characteristics of concentration and distribution for PM10 from 2000 to 2011, and investigate its correlation with the death from Asthma. Furthermore, this study was designed to analyze it by dividing into two cases like including Asian dust and excluding Asian dust because it presented the high concentration when Asian dust was occurred in the spring. This study has found that the annual average concentration distribution of PM10 in Seoul was higher in the central area than the peripheral area. The annual average concentration of PM10 and death from asthma displayed the tendency to gradually decrease. The correlation coefficient for all period was 0.92(p=0.000), and the correlation was 0.84(p=0.001) in case of remove Asian dust. The monthly average concentration of PM10 has increased in the winter and decreased in the summer. The death from Asthma and correlation coefficient for all period was 0.588(p=0.044) and 0.640(p=0.025) in case of removing Asian dust. Although the causes of Asthma had a great diversity, the similar tendency by a factor of PM10 meant that the correlation was high.

This study was conducted to investigate the correlation between the distribution chart and input data of the predicted 3-second gust and damage cost, by using the forecast field and analysis field of Regional Data Assimilation Prediction System (RDAPS) as initial input data of Korea risk assessment model (RAM) developed in the preceding study. In this study the cases of typhoon Rusa which caused occurred great damage to the Korean peninsula was analyzed to assess the suitability of initial input data. As a result, this study has found out that the distribution chart from the forecast field and analysis field predicted from the point where the effect due to the typhoon began had similarity in both 3-second gust and damage cost with the course of time. As a result of examining the correlation, the 3-second gust had over 0.8, and it means that the forecast field and analysis field show similar results. This study has shown that utilizing the forecast field as initial input data of Korea RAM could suit the purpose of pre-disaster prevention.