• Atmosphere
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• v.24 no.4
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• pp.541-554
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• 2014

Historical, RCP4.5 and RCP8.5 scenarios from HadGEM2-AO are dynamically downscaled over the northeast East Asia with WRFV3.4. The horizontal resolution of the produced data is 12.5 km and the periods of integration are 1979~2010 for historical and 2019~2100 for both RCP4.5 and RCP8.5. We analyze the time series, climatology, EOF and extreme climate in terms of 2 m-temperature and precipitation during 30-year for the Historical (1981~2010) and RCP4.5 and RCP8.5 (2071~2100) scenarios. According to the result, the temperature of the northeast Asia centered at the Korean Peninsula increase 2.9 and $4.6^{\circ}C$ in the RCP4.5 and RCP8.5 scenarios, respectively, by the end of the 21st century. The temperature increases with latitude and the increase is larger in winter rather than in summer. The annual mean precipitation is expected to increase by about $0.3mm\;day^{-1}$ in RCP4.5 scenario and $0.5mm\;day^{-1}$ in RCP8.5 scenario. The EOF analysis is also performed for both temperature and precipitation. For temperature, the EOF $1^{st}$ modes of all scenarios in summer and winter show that temperature increase with latitude. The $2^{nd}$ mode of EOF of each scenario shows the natural variability, exclusive of the global warming. The summer precipitation over the Korean Peninsula projected increases in EOF $1^{st}$ modes of all scenarios. For extreme climate, the increment of the number of days with daily maximum temperature above $30^{\circ}C$ per year ($DAY_{TX30}$) is 25.3 and 49.7 days in RCP4.5 and RCP8.5 respectively over the Korean Peninsula. The number of days with daily precipitation above $20mm\;day^{-1}$ per year ($DAY_{PR20}$) also increases 3.1 and 3.5 days in RCP4.5 and RCP8.5 respectively.

• Journal of Korea Water Resources Association
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• v.42 no.5
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• pp.365-374
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• 2009

Probability plotting positions are used for the graphical display of annual maximum rainfall or flood series and the estimation of exceedance probability of those values. In addition, plotting positions allow a visual examination of the fitness of probability distribution provided by frequency analysis for a given data. Therefore, the graphical approach using plotting position has been applied to many fields of hydrology and water resources planning. In this study, the plotting position formula for the Gumbel distribution is derived by using the order statistics and the probability weight moment of the Gumbel distribution for various sample sizes. And then, the parameters of plotting position formula for the Gumbel distribution are estimated by using genetic algorithm. The appropriate plotting position formulas for the Gumbel distribution are examined by the comparison of root mean square errors and biases between theoretical reduced Gumbel variates and those calculated from derived and existing plotting position formulas. As the results, Gringorten's plotting position formula has the smaller root mean square errors and biases than any other formulas.

• Journal of Korean Society for Atmospheric Environment
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• v.34 no.1
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• pp.1-15
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• 2018

Nation-wide systematic and comprehensive measurements of air quality criteria species have been made over 340 sites currently in Korea since 1990. Using these data, temporal and spatial trends of $SO_2$, $PM_{10}$, $NO_2$, $O_3$, CO and $O_x(NO_2+O_3)$ were analyzed to characterize and evaluate implementing efficiency of air quality policy and regulations. Due to strict and effective policy to use cleaner fuels in late 1980s and 1990s, the primary pollutants, such as $SO_2$, CO, and $PM_{10}$ decreased sharply by early 2000s in all parts of Korea. After this period, their concentrations declined with much lower rates in most parts of Korea. In addition, isolated but noticeable numbers of places, especially in major ports, newly developing towns and industrial parks, sustained high levels or even showed further degradation. Despite series of emission control strategies were enforced since early 1990s, $NO_2$ concentrations haven't changed much till 2005, due to significant increase in number of automobiles. Nevertheless, we confirmed that the staggering levels of $NO_2$ and $PM_{10}$ improved evidently after 2005, especially in Seoul Metropolitan Area (SMA), where enhanced regulations for $NO_2$ and $PM_{10}$ emissions was imposed to automobiles and large emission sources. However, their decreasing trends were much lessened in recent years again as current air quality improvement strategies has been challenged to revise further. In contrast to these primary species, annual $O_3$, which is secondary product from $NO_2$ and volatile organic compounds (VOCs), has increased consistently with about 0.6 ppbv per year in every urban part of Korea, while yearly average of daily maximum 8-hour $O_3$ in summer season had a much higher rate of 1.2 ppbv per year. Increase of $O_3$ can be explained mainly by reductions of NO emission. Rising background $O_3$ in the Northeast Asia and increasing oxidizing capacity by changing photochemistry were likely causes of observed $O_3$ increase. The future air quality policy should consider more effective ways to lower alarming level of $O_3$ and $PM_{10}$.

• Korean Journal of Remote Sensing
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• v.13 no.1
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• pp.1-12
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• 1997

The western equatorial Pacific Ocean, where sea surface temperature is the warmest on the globe, is characterized by numerous convective systems and large annual precipitation. In this region, the cloudiness data with tops higher than 8km level obtained from the GMS-IR data are used to investigate the diurnal variation of cloudiness. The amplitude and phase of diurnal and semi-diurnal cycles are mainly investigated to examine details on the temporal and spatial structure of clouds. Cloudiness variation has typical cycles and each cycle is associated with the air-sea interactive phenomena. Spectral analysis on the cloudiness time series data indicates that 30-60 day, 17-20day, 7-8 day, diurnal and semi diurnal cycle are peaked. During Northern Winter and Southern Summer, the large cloudiness exsists over New Guinea, the adjacent seas of North Australia, and the open oceanic regions east of $160^{\circ}$E. Cloudiness diurnal variability over the lands and their adjacent seas is about 2.0 times larger than that over the open sea regions. That may be due to the difference of specific heat between the land and sea. The maximum and minimum cloudiness appeared at 18:00 and 09:00 hours over the land, and at noon and 21:00 hours over the sea, respectively. The amplitude of diurnal component over the land is 4,7 times larger than that of semi-diurnal component, and 1.5 times over the sea.