• Journal of the Korean earth science society
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• v.38 no.3
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• pp.194-208
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• 2017

This study analyzed the correlation between tropical cyclone (TC) frequency and the western North Pacific monsoon index (WNPMI), which have both been influential in East China Sea during the summer season over the past 37 years (1977-2013). A high positive correlation was found between these two variables, but it did not change even if El $Ni{\tilde{n}}o$-Southern Oscillation (ENSO) years were excluded. To determine the cause of this positive correlation, the highest (positive WNPMI phase) and lowest WNPMIs (negative WNPMI phase) during an eleven-year period were selected to analyze the mean difference between them, excluding ENSO years. In the positive WNPMI phase, TCs were mainly generated in the eastern seas of the tropical and subtropical western North Pacific, passing through the East China Sea and moving northward toward Korea and Japan. In the negative phase, TCs were mainly generated in the western seas of the tropical and subtropical western North Pacific, passing through the South China Sea and moving westward toward China's southern regions. Therefore, TC intensity in the positive phase was stronger due to the acquisition of sufficient energy from the sea while moving a long distance up to East Asia's mid-latitude. Additionally, TCs occurred more in the positive phase. Regarding the difference in 850 hPa and 500 hPa stream flows between the two phases, anomalous cyclones were strengthened in the tropical and subtropical western North Pacific, whereas anomalous anticyclones were strengthened in East Asia's mid-latitude regions. Due to these two anomalous pressure systems, anomalous southeasterlies developed in East China Sea, which played a role in the anomalous steering flows that moved TCs into this region. Furthermore, due to the anomalous cyclones that developed in the tropical and subtropical western North Pacific, more TCs could be generated in the positive phase.

• Journal of the Korean Geographical Society
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• v.43 no.3
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• pp.324-336
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• 2008

This paper examines the recent changes of summer precipitation in the aspect of temporal and spatial features using long-term($1958{\sim}2007$) observed station data over South Korea. tong-term mean summer precipitation has revealed two precipitation peaks during summer(June to September); one is the Changma as the first peak, and the other is the post-Changma as the second peak. During the Changma period, the spatial distribution of the maximum precipitation areas is determined by the prevailing southwesterlies and the quasi-stationary front, which results in large amount of precipitation at the windward side of mountain regions over South Korea. However during the post-Changma period, the spatial distribution of the maximum precipitation areas is determined by the lower tropospheric circulation flows from the west and the southeast around the Korean peninsula, and the weather phenomena such as Typhoons, convective instability, and cyclones which are originated from the Yangtze river. The larger amount of precipitation is founded on the southern coastal region and mountain and coastal areas in Korea during the second peak. Time series of total summer precipitation shows a steady increase and the increasing trend is more obvious during the recent 10 years. Decadal variation in summer precipitation indicates a large increase of precipitation, especially in the recent 10 years both in the Changma and the post-Changma period. However, the magnitude of change and the period of the maximum peak presents remarkable contrasts among stations. The most distinct decadal change occurs at Seoul, Busan, and Gangnueng. The precipitation amount is increasing significantly during the post-Changma period at Gangnueng, while the precipitation increases in the period between two maximum precipitation peaks during summer at Seoul and Busan.

• Proceedings of the Korea Water Resources Association Conference
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• 2002.05a
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• pp.43-50
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• 2002

Accurate quantitative forecasting of rainfall for basins with a short response time is essential to predict streamflow and flash floods. Previously, neural networks were used to develop a Quantitative Precipitation Forecasting (QPF) model that highly improved forecasting skill at specific locations in Pennsylvania, using both Numerical Weather Prediction (NWP) output and rainfall and radiosonde data. The objective of this study was to improve an existing artificial neural network model and incorporate the evolving structure and frequency of intense weather systems in the mid-Atlantic region of the United States for improved flood forecasting. Besides using radiosonde and rainfall data, the model also used the satellite-derived characteristics of storm systems such as tropical cyclones, mesoscale convective complex systems and convective cloud clusters as input. The convective classification and tracking system (CCATS) was used to identify and quantify storm properties such as life time, area, eccentricity, and track. As in standard expert prediction systems, the fundamental structure of the neural network model was learned from the hydroclimatology of the relationships between weather system, rainfall production and streamflow response in the study area. The new Quantitative Flood Forecasting (QFF) model was applied to predict streamflow peaks with lead-times of 18 and 24 hours over a five year period in 4 watersheds on the leeward side of the Appalachian mountains in the mid-Atlantic region. Threat scores consistently above .6 and close to 0.8 ∼ 0.9 were obtained fur 18 hour lead-time forecasts, and skill scores of at least 4％ and up to 6％ were attained for the 24 hour lead-time forecasts. This work demonstrates that multisensor data cast into an expert information system such as neural networks, if built upon scientific understanding of regional hydrometeorology, can lead to significant gains in the forecast skill of extreme rainfall and associated floods. In particular, this study validates our hypothesis that accurate and extended flood forecast lead-times can be attained by taking into consideration the synoptic evolution of atmospheric conditions extracted from the analysis of large-area remotely sensed imagery While physically-based numerical weather prediction and river routing models cannot accurately depict complex natural non-linear processes, and thus have difficulty in simulating extreme events such as heavy rainfall and floods, data-driven approaches should be viewed as a strong alternative in operational hydrology. This is especially more pertinent at a time when the diversity of sensors in satellites and ground-based operational weather monitoring systems provide large volumes of data on a real-time basis.

• Journal of Soil and Groundwater Environment
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• v.13 no.4
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• pp.62-68
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• 2008

The Low Temperature Thermal Desorption (LTTD) System equipped with a soil transfer unit, a rotary kiln, RTO, cyclones and a bag filter etc. was developed. The LTTD system was designed to be economically operated using LPG as a fuel and recirculating the discharged gas from the LTTD system through RTO. For the performance test of LTTD system the soil contaminated with light and heavy oils (2,690 mg TPH/kg soil) and with particle sizes below 50 mm was fed into the rotary kiln of LTTD system at 7$m^3$/hr with retention time of 15 minutes. Operation temperatures of LTTD system for the removal of soil TPH were $567^{\circ}C$ and $692^{\circ}C$. The residual TPH after treatment was 46 mg/kg and 32mg/kg respectively at each temperature condition, which shows high TPH removal efficiencies of the developed LTTD as 98.3% and 98.9%.

• Journal of the Korean earth science society
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• v.29 no.1
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• pp.29-44
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• 2008

This study investigates the influence of the developing and decaying El $Ni{\tilde{n}}o$-Southern Oscillation (ENSO) on the relation between typhoon intensity and its formation. From the long-tenn data of 57 years ($1950{\sim}2006$), we first defined the developing El $Ni{\tilde{n}}o$ years and the neutral years. During the developing El Nino years, the typhoon intensity has a strong relationship with formation region of the tropical cyclone, which results in an increase of the accumulated cyclone energy and intensity of energy of typhoon. During the developing El $Ni{\tilde{n}}o$ year based on $Ni{\tilde{n}}o$ 3.4 SST, the locations for the formation of the category 4+5 typhoon move to the eastward region. The genesis potential function and the low-level cyclonic vorticity have an important role on the formation of strong tropical cyclones, which eventually develop as a typhoon class. In this study, the dynamic potential (DP) function (Gray, 1977) and EOF 1 and EOF 2 time series (RMM 1 and RMM 2) of real-time multivariate MJO (Wheeler and Hendon, 2004) are used to measure the genesis potential and the low-level cyclonic vorticity, respectively. To investigate the influence of the developing and decaying ENSO, we defined the Type I case of the decaying El $Ni{\tilde{n}}o$ that turnovers to La Nina, and the Type II case of the recovering years to the neutral condition. During the decaying El $Ni{\tilde{n}}o$ years as Type I, the locations of the strong DP, RMM 1 and RMM 2 move to the westward more prominently to induce retard of the strong typhoon developing.

• Atmosphere
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• v.24 no.4
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• pp.565-571
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• 2014

A long-range prediction system of tropical cyclone (TC) activity over the western North Pacific (WNP) has been operated in the National Typhoon Center of the Korea Meteorological Administration since 2012. The model forecasts the spatial distribution of TC tracks averaged over the period June~October. In this study, we separately developed TC prediction models for summer (June~August) and autumn (September~November) period based on the current operating system. To perform the three-month WNP TC activity prediction procedure readily, we modified the shell script calling in environmental variables automatically. The user can apply the model by changing these environmental variables of namelist parameter in consideration of their objective. The validations for the two seasons demonstrate the great performance of predictions showing high pattern correlations between hindcast and observed TC activity. In addition, we developed a post-processing script for deducing TC activity in the Korea emergency zone from final forecasting map and its skill is discussed.

• Journal of Korea Water Resources Association
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• v.47 no.12
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• pp.1187-1198
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• 2014

Strong winds and heavy rainfall from tropical cyclones (TCs) that occur in the Northwestern Pacific cause significant human and material damage to the Korean peninsula and East Asia. Hence, it is important to establish early warning systems and conduct preparedness activities in advance of a TC. This study suggests a technique to extract the value of uniform TC-induced rainfall considering the TC track and TC size. To validate our technique, we compare it to existing TC rainfall techniques using the spatial domain. To determine the TC size required for extracting TC-induced rainfall, this research analyzed the mean of TC-induced rainfall by TC size (1973-2012). As a result of this analysis, the maximum amount of mean of TC-induced rainfall was found for a TC with a radius of 700 km. Other techniques have limitations which this new technique addresses; it can extract TC-induced rainfall in each administrative area and minimize systematic biases of other extraction methods. The result of this study can be utilized in the preparation of rainfall forecasts, designing hydraulic structures, and predicting landslide and debris flows using TC-induced rainfall and downpours.

• Atmosphere
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• v.25 no.4
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• pp.611-622
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• 2015

Heavy rainfall ($>30mm\;hr^{-1}$) over the Korean Peninsula is examined in order to understand thermo-dynamic characteristics of the atmosphere, using radiosonde observational data from seven upper-air observation stations during the last 17 years (1997~2013). A total of 82 heavy rainfall cases during the summer season (June-August) were selected for this study. The average values of thermo-dynamic indices of heavy rainfall events are Total Precipitable Water (TPW) = 60 mm, Convective Available Potential Energy (CAPE) = $850J\;kg^{-1}$, Convective Inhibition (CIN) = $15J\;kg^{-1}$, Storm Relative Helicity (SRH) = $160m^2s^{-2}$, and 0~3 km bulk wind shear = $5s^{-1}$. About 34% of the cases were associated with a Changma front; this pattern is more significant than other synoptic pressure patterns such as troughs (22%), migratory cyclones (15%), edges of high-pressure (12%), typhoons (11%), and low-pressure originating from Changma fronts (6%). The spatial distribution of thermo-dynamic conditions (CAPE and SRH) is similar to the range of thunderstorms over the United States, but extreme conditions (supercell thunderstorms and tornadoes) did not appear in the Korean Peninsula. Synoptic conditions, vertical buoyancy (CAPE, CIN), and wind parameters (SRH, shear) are shown to discriminate among the environments of the three types. The first type occurred with high CAPE and low wind shear by the edge of the high pressure pattern, but Second type is related to Changma front and typhoon, exhibiting low CAPE and high wind shear. The last type exhibited characteristics intermediate between the first and second types, such as moderate CAPE and wind shear near the migratory cyclone and trough.

• Atmosphere
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• v.16 no.2
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• pp.97-110
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• 2006

This study investigates the response of a typhoon model to the change of the sea surface temperature (SST) throughout the model integration. The SST change is parameterized as a formulae of which the magnitude is given as a function of not only the intensity and the size but the moving speed of tropical cyclone. The formulae is constructed by referring to many previous observational and numerical studies on the SST cooling with the passage of tropical cyclones. Since the parameterized cooling formulae is based on the mathematical expression, the resemblance between the prescribed SST cooling and the observed one during the period of the numerical experiment is not complete nor satisfactory. The agreements between the prescribed and the observed SST even over the swath of the typhoon passage differ from case to case. Numerical experiments are undertaken with and without prescribing the SST cooling. The results with the SST cooling do not show clear evidence in improving the track prediction compared to those of the without-experiments. SST cooling in the model shows its swath along the incomplete simulated track so that the magnitude and the distribution of the sea surface cooling does not resemble completely with the observed one. However, we have observed a little improvement in the intensity prediction in terms of the central pressure of the tropical cyclone in some cases. In case where the model without the SST treatment is not able to yield a correct prediction of the filling of the tropical cyclone especially in the decaying stage, the pulling effect given by the SST cooling alleviates the over-deepening of the model so that the central pressure approaches toward the observed value. However, the opposite case when the SST treatment makes the prediction worse may also be possible. In general when the sea surface temperature is reduced, the amount of the sensible and the latent heat from the ocean surface become also reduced, which results in the weakening of the storms comparing to the constant SST case. It turns out to be the case also in our experiments. The weakening is realized in the central pressure, maximum wind, horizontal temperature gradient, etc.

• Journal of the Korean Data and Information Science Society
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• v.28 no.4
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• pp.797-810
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• 2017

The Korean peninsula is exposed to typhoons every year. Typhoons cause huge socioeconomic damage because tropical cyclones tend to occur with strong winds and heavy precipitation. In order to understand the complex dependence structure between strong winds and heavy precipitation, the copula links a set of univariate distributions to a multivariate distribution and has been actively studied in the field of hydrology. In this study, we carried out analysis using data of wind speed and precipitation collected from the weather stations in Busan and Jeju. Log-Normal, Gamma, and Weibull distributions were considered to explain marginal distributions of the copula. Kolmogorov-Smirnov, Cramer-von-Mises, and Anderson-Darling test statistics were employed for testing the goodness-of-fit of marginal distribution. Observed pseudo data were calculated through inverse transformation method for establishing the copula. Elliptical, archimedean, and extreme copula were considered to explain the dependence structure between strong winds and heavy precipitation. In selecting the best copula, we employed the Cramer-von-Mises test and cross-validation. In Busan, precipitation according to average wind speed followed t copula and precipitation just as maximum wind speed adopted Clayton copula. In Jeju, precipitation according to maximum wind speed complied Normal copula and average wind speed as stated in precipitation followed Frank copula and maximum wind speed according to precipitation observed Husler-Reiss copula.