• Journal of Korea Water Resources Association
• /
• v.33 no.2
• /
• pp.229-235
• /
• 2000

Characteristics of hail occurred during 1989-1998 is studied. Hail is observed mainly at west coast, southwest inland, and Taegwallyong. Average diameter of hailstone is 0.6 cm, and 70% of the occurrence frequency of hail is observed at west coast. During winter and spring, the wet -bulb zero height (WBZ) is low enough to prevent the melting process of hail. But the lack of available low-level moisture (mean mixing ratio in lowest 100 hPa) makes the size of hail small. As a result, smaller size hail is observed frequently over west coast. On the contrary, WBZ is higher during summer, it means that hail is melted before it reaches ground, but the size of hail is bigger. Thus the larger hail is observed mainly Taegwallyong during summer. Hail is observed from 1100 LST to 1500 LST over west coast and around 1800 LST over Taegwallyong. It suggest that thermally driven mesoscale circulations such as land-sea breeze and mountain ridge-valley circulation aid in the formation of hail. Upper and surface air temperature is related to formation of hailstorm. Before formation of hailstorm in November 1998, the upper air temperature decreases. And hails is observed in the spot of strong temperature and dew point temperature gradient coincidently.

• Journal of Korea Water Resources Association
• /
• v.43 no.12
• /
• pp.1011-1027
• /
• 2010

In hydrologic modeling, prediction uncertainty generally stems from various uncertainty sources associated with model structure, data, and parameters, etc. This study aims to assess the parameter uncertainty effect on hydrologic prediction results. For this objective, a distributed rainfall-sediment yield-runoff model, which consists of rainfall-runoff module for simulation of surface and subsurface flows and sediment yield module based on unit stream power theory, was applied to the mesoscale mountainous area (Cheoncheon catchment; 289.9 $km^2$). For parameter uncertainty evaluation, the model was calibrated by a multi-objective optimization algorithm (MOSCEM) with two different objective functions (RMSE and HMLE) and Pareto optimal solutions of each case were then estimated. In Case I, the rainfall-runoff module was calibrated to investigate the effect of parameter uncertainty on hydrograph reproduction whereas in Case II, sediment yield module was calibrated to show the propagation of parameter uncertainty into sedigraph estimation. Additionally, in Case III, all parameters of both modules were simultaneously calibrated in order to take account of prediction uncertainty in rainfall-sediment yield-runoff modeling. The results showed that hydrograph prediction uncertainty of Case I was observed over the low-flow periods while the sedigraph of high-flow periods was sensitive to uncertainty of the sediment yield module parameters in Case II. In Case III, prediction uncertainty ranges of both hydrograph and sedigraph were larger than the other cases. Furthermore, prediction uncertainty in terms of spatial distribution of erosion and deposition drastically varied with the applied model parameters for all cases.

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

• Proceedings of the KSRS Conference
• /
• v.2
• /
• pp.1011-1014
• /
• 2006

Coarse resolution (9 - 50 km pixels) Sea Surface Temperature satellite data are frequently considered adequate for open ocean research. However, coastal regions, including coral reef, estuarine and mesoscale upwelling regions require high-resolution (1-km pixel) SST data. The AVHRR SST data often suffer from navigation errors of several kilometres and still require manual navigation adjustments. The second serious problem is faulty and ineffective cloud-detection algorithms used operationally; many of these are based on radiance thresholds and moving window tests. With these methods, increasing sensitivity leads to masking of valid pixels. These errors lead to significant cold pixel biases and hamper image compositing, anomaly detection, and time-series analysis. Here, after manual navigation of over 40,000 AVHRR images, we implemented a new cloud filter that differs from other published methods. The filter first compares a pixel value with a climatological value built from the historical database, and then tests it against a time-based median value derived for that pixel from all satellite passes collected within ${\pm}3$ days. If the difference is larger than a predefined threshold, the pixel is flagged as cloud. We tested the method and compared to in situ SST from several shallow water buoys in the Florida Keys. Cloud statistics from all satellite sensors (AVHRR, MODIS) shows that a climatology filter with a $4^{\circ}C$ threshold and a median filter threshold of $2^{\circ}C$ are effective and accurate to filter clouds without masking good data. RMS difference between concurrent in situ and satellite SST data for the shallow waters (< 10 m bottom depth) is < $1^{\circ}C$, with only a small bias. The filter has been applied to the entire series of high-resolution SST data since1993 (including MODIS SST data since 2003), and a climatology is constructed to serve as the baseline to detect anomaly events.

• Korean Journal of Remote Sensing
• /
• v.29 no.4
• /
• pp.423-441
• /
• 2013

On 21 September 2010, one of Chuseok holidays in Korea, localized heavy rainfalls occurred over the midwestern region of the Korean peninsula. In this study MTSAT-2 infrared and water vapor channel imagery are examined to find out some features which are obvious in each stage of the life cycle of convective cell for this heavy rain event. Also the kinematic and thermodynamic features probably associated with them are investigated. The first clouds related with the Chuseok heavy rain are detected as low-level multicell cloud (brightness temperature: $-15{\sim}0^{\circ}C$) in the middle of the Yellow sea at 1630~1900 UTC on 20 Sept., which are probably associated with the convergence at 1000 hPa. Convective cells are initiated in the vicinity of Shantung peninsula at 1933 UTC 20, which have developed around the edge of the dark region in water vapor images. At two times of 0033 and 0433 UTC 21 the merging of two convective cells happens near midwestern coast of the peninsula and then they have developed rapidly. From 0430 to 1000 UTC 21, key features of convective cell include repeated formation of secondary cell, slow horizontal cloud motion, persistence of lower brightness temperature ($-75{\sim}-65^{\circ}C$), and relatively small cloud size (${\leq}-50^{\circ}C$) of about $30,000km^2$. Radar analysis showed that this heavy rain is featured by a narrow line-shaped rainband with locally heavy rainrate (${\geq}50$ mm/hr), which is located in the south-western edge of the convective cell. However there are no distinct features in the associated synoptic-scale dynamic forcing. After 1000 UTC 21 the convective cell grows up quickly in cloud size and then is dissipated. These satellite features may be employed for very short range forecast and nowcasting of mesoscale heavy rain system.

• Journal of Environmental Science International
• /
• v.11 no.5
• /
• pp.419-436
• /
• 2002

The current paper reports on the enhancement of O$_3$, CO, NO$_2$, and aerosols during the Asian dust event that occurred over Korea on 1 May 1999. To confirm the origin and net flux of the O$_3$, CO, NO$_2$, and aerosols, the meteorological parameters of the weather conditions were investigated using Mesoscale Meteorological Model 5(MM5) and the TOMS total ozone and aerosol index, the back trajectory was identified using the Hybrid Single-Particle Lagrangian Integrated Trajectory Model(HYSPLIT), and the ozone and ozone precursor concentrations were determined using the Urban Ashed Model(UAM). In the presence of sufficiently large concentrations of NO$\sub$x/, the oxidation of CO led to O$_3$ formation with OH, HO$_2$, NO, and NO$_2$ acting as catalysts. The sudden enhancement of O$_3$, CO, NO$_2$ and aerosols was also found to be associated with a deepening cut-off low connected with a surface cyclone and surface anticyclone located to the south of Korea during the Asian dust event. The wave pattern of the upper trough/cut-off low and total ozone level remained stationary when they came into contact with a surface cyclone during the Asian dust event. A typical example of a stratosphere-troposphere exchange(STE) of ozone was demonstrated by tropopause folding due to the jet stream. As such, the secondary maxima of ozone above 80 ppbv that occurred at night in Busan, Korea on 1 May 2001 were considered to result from vertical mixing and advection from a free troposphere-boundary layer exchange in connection with an STE in the upper troposphere. Whereas the sudden enhancement of ozone above 100 ppbv during the day was explained by the catalytic reaction of ozone precursors and transport of ozone from a slow-moving anticyclone area that included a high level of ozone and its precursors coming from China to the south of Korea. The aerosols identified in the free troposphere over Busan, Korea on 1 May 1999 originated from the Taklamakan and Gobi deserts across the Yellow River. In particular, the 1000m profile indicated that the source of the air parcels was from an anticyclone located to the south of Korea. The net flux due to the first invasion of ozone between 0000 LST and 0600 LST on 1 May 1999 agreed with the observed ground-based background concentration of ozone. From 0600 LST to 1200 LST, the net flux of the second invasion of ozone was twice as much as the day before. In this case, a change in the horizontal wind direction may have been responsible for the ozone increase.

• Atmosphere
• /
• v.26 no.3
• /
• pp.413-421
• /
• 2016

Climate Analysis Seoul (CAS) which provides gridded data relevant for thermal assessment was applied to one of the urban green areas, the Seonjeongneung, in Seoul, Korea. The thermal environment in the Seonjeongneung was evaluated from the CAS simulation for the five heat-wave issued cases during the last five years (2011~2015). The CAS has been improved continuously since it was developed. An updated version with a higher resolution of the CAS simulation domain and an addition of the vegetation information was used in this study. The influence of vegetation in the Seonjeongneung is estimated through the amount of the cold air generation ($Q_{ca}$) and air temperature deviation at each grid points, which are calculated by incorporating Geographic Information System (GIS) analysis on the simulation domain and meteorological analysis with the METeorology and atmospheric PHOtochemistry mesoscale MODel (MetPhoMod) in the CAS. The average amount of the cold air generation ($Q_{ca}$) at the Seonjeongneung is about $25.5m^3m^{-2}h^{-1}$ for the whole cases, and this value is similar to the ones in a forest or a well-wooded region. The average value of the total air temperature deviation (TD) is $-2.54^{\circ}C$ at the Seonjeongneung for the five cases. However, this cooling effect of the urban green area disappeared when the region is replaced by high-rise buildings in the CAS simulation. The $Q_{ca}$ drastically decreases to about $1.1m^3m^{-2}h^{-1}$ and the average TD shows an increase of $1.14^{\circ}C$ for the same events. This result shows that the vegetation in the Seonjeongneung supposes to keep down temperature during the heat-wave issued day and the average cooling effect of the green region is $3.68^{\circ}C$ quantitatively from the TD difference of the two simulations. The cooling effect represented with the TD difference is larger than $0.3^{\circ}C$ within 200 m distance from the boundary of the Seonjeongneung. Further improvements of the thermodynamical and advection processes above the model surface are required to consider more accurate assessment of the cooling effect for the urban green area.

• Atmosphere
• /
• v.13 no.4
• /
• pp.57-70
• /
• 2003

The National Center for Intensive Observation of Severe Weathers (NCIO) as a part of METRI's principal project "Korea Enhanced Observing Period; KEOP" was established at Haenam Weather Observatory in order to effectively monitor and observe heavy rainfall in summer, which is essential for the identification of the structure and evolution mechanism of mesoscale severe weather system. The intensive field-based experiments in 2002 within southwestern Korea toward various meteorological phenomena ranging from heavy rainfall to snowfall were conducted in collaboration with KMA(Korea Meteorological Administration) and universities. In this study, preliminary analysis results using intensive observation data obtained from these experiments are presented together with the introduction of NCIO and its operational structure.

• Journal of Korea Water Resources Association
• /
• v.34 no.5
• /
• pp.511-519
• /
• 2001

Global warming has begun since the industrial revolution and it is getting worse recently. Even though the increase of greenhouse gases such as $CO_2$is thought to be the main cause for glogal warming, its impact on global climate has not been revealed clearly in rather quantitative manners. The objective of this research is to predict the hydrological environment changes in the Daechung Dam basin due to the global warming. A mesoscale atmospheric/hydrologic model (IRSHAM96 model) is used to predict the possible changes in precipitation and temperature in the Daechun Dam basin. The simulation results of IRSHAM96 model and a conceptual water balance model are used to analyze the changes in soil moisture, evapotranspiration and runoff in the Daechung Dam basin. From the simulation results using the water balance model for 1x$CO_2$and 2x$CO_2$situations, it has been found that the runoff would be decreased in dry season, but increased in wet season due to the global warming. Therefore, it is predicted that the frequency of drought and flood occurrences in the Daechung Dam basin would be increased in 2x$CO_2$condition.

• Proceedings of the KSRS Conference
• /
• 1998.09a
• /
• pp.286-291
• /
• 1998

SAR has provided weather independent images on land and sea surface, which can be used for extracting various useful informations. Recently attempts to estimate wind field parameters from SAR images over the oceans have been made by various groups over the world. Although scatterometer loaded in ERS-1 and ERS-2 observes the global wind vector field at spatial resolution of 50 Km with accuracies of $\pm$2m/s in speed, the spatial resolution may not be good enough for applications in coastal regions. It is weil known the sea surface roughness is closely correlated to the wind field, but the wind retrieval algorithms from SAR images are yet in developing stage. Since the radar backscattering properties of the SAR images are principally the same as that of scatterometer, some previous studies conducted by other groups report the success in mesoscale coastal wind field retrievals using ERS SAR images. We have tested SWA (SAR Wind Algorithm) and CMOD4 model for estimation of wind speed using an ERS-1 SAR image acquired near Cheju Island, Korea, in October 11, 1994. The precise estimation of sigma nought and the direction of wind are required for applying the CMOD4 model to estimate wind speed. The wind speed in the test sub-image is estimated to be about 10.5m/s, which relatively well agrees to the observed wind speed about 9.0m/s at Seoguipo station. The wind speed estimation through the SWA is slightly higher than that of CMOD4 model. The sea surface condition may be favorable to SWA on the specific date. Since the CMOD4 model requires either wind direction or wind speed to retrieve the wind field, we should estimate the wind speed first using other algorithm including SWA. So far, it is not conclusive if the SWA can be used to provide input wind speed data for CMOD4 model or not. Since it is only initial stage of implementing the wind field retrieval algorithms and no in-situ observed data is currently avaliable, we are not able to evaluate the accuracy of the results at the moment. Therefore verification studies should be followed in the future to extract reliable wind field information in the coastal region using ERS SAR images.