• Atmosphere
• /
• v.17 no.2
• /
• pp.207-216
• /
• 2007

The Moving-nest Typhoon Model (MTM) was installed on the Korea Meteorological Administration (KMA)'s CRAY X1E in 2006 and started its test operation in August 2006 to provide track and intensity forecasts of tropical cyclones. In this study, feasibility of the MTM forecast is compared with the Global Data Assimilation and Prediction System (GDAPS) of the KMA and the operational typhoon forecast models in the Japan Meteorological Agency (JMA), from the sixth tropical cyclone to the twentieth in 2006. Forecast skills in terms of the storm position error of the two KMA models were comparable, but MTM showed a slightly better ability. While both GDAPS and MTM produced larger errors than JMA models in track forecast, the predicted intensity was much improved by MTM, making it comparable to the JMA's typhoon forecast model. It is believed that the Geophysical Fluid Dynamics Laboratory (GFDL) bogus initialization method in MTM improves the ability to forecast typhoon intensity.

• Atmosphere
• /
• v.30 no.3
• /
• pp.209-220
• /
• 2020

Seasonal predictability and variability of tropical storms (TCs) simulated in the Global Seasonal Forecast System version 5 (GloSea5) of the Korea Meteorological Administration (KMA) is assessed in Northern Hemisphere in 1996~2009. In the KMA, the GloSea5-Global Atmosphere version 3.0 (GloSea5-GA3) that was previously operated was switched to the GloSea5-Global Coupled version 2.0 (GloSea5-GC2) with data assimilation system since May 2016. In this study, frequency, track, duration, and strength of the TCs in the North Indian Ocean, Western Pacific, Eastern Pacific, and North Atlantic regions derived from the GloSea5-GC2 and GloSea5-GA3 are examined against the best track data during the research period. In general, the GloSea5 shows a good skill for the prediction of seasonally averaged number of the TCs in the Eastern and Western Pacific regions, but underestimation of those in the North Atlantic region. Both the GloSea5-GA3 and GC2 are not able to predict the recurvature of the TCs in the North Western Pacific Ocean (NWPO), which implies that there is no skill for the prediction of landfalls in the Korean peninsula. The GloSea5-GC2 has higher skills for predictability and variability of the TCs than the GloSea5-GA3, although continuous improvements in the operational system for seasonal forecast are still necessary to simulate TCs more realistically in the future.

• Atmosphere
• /
• v.21 no.1
• /
• pp.45-55
• /
• 2011

A definition on the tropical cyclone (TC) that influenced the Korean Peninsula (KP), the KP-influence TC, is widely used in the TC communities, but its criterion is not clear mainly due to the ambiguity and subjectiveness of the term such as 'influence', which led to the inconsistent TC statistical analysis. This study suggests a definition and criterion on the TC approaching to the KP (KP-approach TC) additionally, which is more obvious and objective than the KP-influence TC. In this study, the criterion on the KP-approach TC is determined when the TC's center from the RSMC best track data encounters the box areas of $28^{\circ}N{\sim}40^{\circ}N$ and $120^{\circ}E{\sim}138^{\circ}E$. The range is chosen by finding a minimum area that includes all official KP-influence TCs except three TCs that affected the KP as a tropical depression (TD). Statistical analysis reveals that, among total 1,537 TCs that occur in the western North Pacific during 1951-2008, the KP-approach TC was 472, the KP-influence TC was 187, and the KP-landfall TC was 87. August was the month that the largest TCs approach and influence to the KP. Finally, this paper suggests to determine the KP-influence TC by the strong wind and heavy rain advisories in the KP based on the observation after the storm's passage.

• Journal of Korean Society of Coastal and Ocean Engineers
• /
• v.25 no.5
• /
• pp.335-347
• /
• 2013

In February 2008, high storm waves due to a developed atmospheric low pressure system propagating from the west off Hokkaido, Japan, to the south and southwest throughout the East Sea (ES) caused extensive damages along the central coast of Japan and along the east coast of Korea. This study consists of two parts. In the first part, we estimate extreme storm wave characteristics in the Toyama Bay where heavy coastal damages occurred, using a non-hydrostatic meteorological model and a spectral wave model by considering the extreme conditions for two factors for wind wave growth, such as wind intensity and duration. The estimated extreme significant wave height and corresponding wave period were 6.78 m and 18.28 sec, respectively, at the Fushiki Toyama. In the second part, we perform numerical experiments on wave-structure interaction in the Fushiki Port, Toyama Bay, where the long North-Breakwater was heavily damaged by the storm waves in February 2008. The experiments are conducted using a non-linear shallow-water equation model with adaptive mesh refinement (AMR) and wet-dry scheme. The estimated extreme storm waves of 6.78 m and 18.28 sec are used for incident wave profile. The results show that the Fushiki Port would be overtopped and flooded by extreme storm waves if the North-Breakwater does not function properly after being damaged. Also the storm waves would overtop seawalls and sidewalls of the Manyou Pier behind the North-Breakwater. The results also depict that refined meshes by AMR method with wet-dry scheme applied capture the coastline and coastal structure well while keeping the computational load efficiently.

• Water Engineering Research
• /
• v.3 no.2
• /
• pp.123-134
• /
• 2002

A developed Quantitative Flood Forecasting (QFF) model was applied to the mid-Atlantic region of the United States. The model incorporated the evolving structure and frequency of intense weather systems of the study area 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 associated with synoptic atmospheric conditions as Input. Here, we present results from the application of the Quantitative Flood Forecasting (QFF) model in 2 small watersheds along the leeward side of the Appalachian Mountains in the mid-Atlantic region. Threat scores consistently above 0.6 and close to 0.8 ∼ 0.9 were obtained fur 18 hour lead-time forecasts, and skill scores of at least 40% and up to 55 % were obtained.

• Proceedings of KOSOMES biannual meeting
• /
• 2006.11a
• /
• pp.193-199
• /
• 2006

This article reviews several microwave instruments employed in observation and analysis of tropical cyclones (TCs), typhoon, and hurricanes. Microwave signals are useful for observing tropical cyclones with severe storms since it isn't severely absorbed by the clouds and rain in the storm. The instruments discussed include scatterometers, microwave radiometers, synthetic aperture radars (SARs), and rain radar from space. The date such as winds, rainfall and cloud-distribution in the TCs obtained by microwave instruments provide important informations for forecasting the intensity and path of the typhoon. For example, there're wind-distribution provided by SSM/I which has a wide swath, detailed wind fields from ERS-1, 2 scatterometers and RADARSAT-1 SAR and TRMM's rain radar pro 떠 ding high resolution. Operational satellite instruments lunched recently have improved upon the problems of low resolution and narrow swath indicated at the beginning microwave remote sensing. Understanding and practical using sufficiently about the microwave instruments will serve for searching the features such as generation and development of the TCs.

• Journal of Korean Society of Coastal and Ocean Engineers
• /
• v.27 no.3
• /
• pp.168-174
• /
• 2015

Characteristics of high waves occurred in winter season on the west coast of Korea were investigated by analyzing the wave data observed at five observation locations. Records of four different high waves were subjected to the analysis together with the corresponding meteorological data during those time periods. The significant wave height reached its maximum of 6.42 m on December 4th, 2005. It was clarified that the high waves occurred due to strong wind fields that were formed over the west sea of Korea when the extra-tropical cyclone was excessively developed. Characteristics of the high waves generated in the west sea seemed to be predominantly wind sea as the temporal variation of the wave height at the coast were closely related to those of the wind speed measured at neighboring weather stations.

• Korean Journal of Remote Sensing
• /
• v.14 no.4
• /
• pp.315-324
• /
• 1998

The total precipitable water fields derived from HIRS(High Resolution Infrared Radiometer Sounder)and MSU(Microwave Sounding Unit) measurements of TOVS and brightness temperature of SSM/I were used to investigate the evolution of moisture fields for the Typhoon WALT(9407) which after landing in Japan it became tropical depression in Korea-Japan Strait, and FAYE(9503) which was the first tropical storm of 1995 to became a typhoon, respectively. The total precipitable water derived from TOVS observations is delineated according to the evolutions of WALT and FAYE movements because total precipitable water fields of TY WALT(9407) and FAYE9\(9503) were largely controlled by horizontal transport of water vapor over the Northwest Pacific Ocean which dominantly plays an important role in maintaining and accelerating their intensities toward Korea and Japan . These fields demonstrated that two major bands, which imply the rain bands, were locally well-organized and similar to the thick convective cloud features over Japan and the Korean peninsula while WALT and FAYE were approaching away and to. But the values of derived TOVS total precipitable water have shown the underestimate of those of SSM/I total comparatively for two typhoons.

• Parasites, Hosts and Diseases
• /
• v.54 no.2
• /
• pp.233-238
• /
• 2016

The 65th Medical Brigade and Public Health Command District-Korea, in collaboration with the Migratory Bird Research Center, National Park Research Institute, conducted migratory bird tick surveillance at Sogugul and Gaerin Islands (small rocky bird nesting sites), Jeollanam-do (Province), Republic of Korea (ROK), on 30 July and 1 August 2009. Breeding seabirds captured by hands in their nesting burrows were banded, identified to species, and carefully examined for ticks during the nesting season. A total of 9 Ornithodoros sawaii larvae were removed from 4 adult Hydrobates monorhis (Swinhoe's storm petrel). The identification of the larvae of O. sawaii collected from migratory seabirds were molecularly confirmed using mitochondrial 16S rDNA primer sets.

• 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.