• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2001.06a
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• pp.61-64
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• 2001

대관령 인근 고랭지는 표고가 높아 여름철에도 서늘하여 오래 전부터 씨감자와 호냉성원예작물의 주산지로 발전되어 왔다. 이러한 저온기후자원을 이용하여 농업활동이 이루어지는 고랭지는 산지의 특이한 지형조건 때문에 날씨변화가 심하고 이에 따른 작물피해가 잦다. 기상청 자동기상관 측장치(automated weather station : AWS)가 일부 지점에 설치되어 있으나 기온과 바람 강우량만이 관측되고 있어 농업적인 이용에는 한계가 있다.(중략)

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.6B
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• pp.543-550
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• 2009

The traditional simple extrapolation type short term quantitative rainfall forecast can not realize the evolution of rainfall generating weather system. To overcome the drawback of the linear extrapolation type rainfall forecasting model, the history of a weather system from sequential weather radar information and a polynomial regression technique were used to generate forecast fileds of x-directional, y-directional velocities and radar reflectivity which considered the nonlinear behavior related to the evolution of weather systems. Results demonstrated that test statistics of forecasts using the developed model is better than that of 2-CAPPI forecast. However there is still a large room to improve the forecast of spatial and temporal evolution of local storms since the model is not based on a fully physical approach but a statistical approach.

• Journal of the Korean earth science society
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• v.22 no.3
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• pp.186-194
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• 2001

The operational meso-scale short range NWP system was developed for Cheju Regional Meteorological Office located at Cheju island, Korea. The Central Meteorological Service Center, KMA has reported the information on numerical weather prediction every 12 hours. But this information is not enough to determine the detail forecast for the regional meteorological office because the terrain of the Korean peninsula is very complex and the resolution of the numerical model provided by KMA headquarter is too coarse to resolve the local severe weather system such as heavy rainfall. LAPS and MM5 models were chosen for three-dimentional data assimilation and numerical weather prediction tools respectively. LAPS was designed to provide the initial data to all regional numerical prediction models including MM5. Synoptic observational data from GTS, satellite brightness temperature data from GMS-5 and the composite reflectivity data from 5 radar sites were used in the LAPS data assimilation for producing the initial data. MM5 was performed on PC-cluster based on 16 pentium CPUs which was one of the cheapest distributed parallel computer in these days. We named this system as Halla Short Range Prediction System (HSRPS). HSRPS was verified by heavy rainfall case in July 9, 1999, it showed that HSRPS well resolved local severe weather which was not simulated by 30 km MM5/KMA. Especially, the structure of rainfall amount was very close to the corresponding observation. HSRPS will be operating every 6 hours in the Cheju Regional Meteorological Office from April 2000.

• Journal of the Korean Data and Information Science Society
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• v.20 no.1
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• pp.57-64
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• 2009

In this paper, 30 main cities are clustered based on precipitation, temperature, wind speed, photo period, and humidity. We found that the resulting clusters has strong relationships with geographical locations. These results make sense because, although Korea is a small country, Korean weather is known to have strong locality. The largest number of clusters is found when wind speed is used as an interested variable for clustering and the smallest number of clusters is found when photo period is used. The large number of clusters based on wind speed indicates that wind speed is affected easily by local geography.

• International Journal of Computer Science & Network Security
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• v.21 no.5
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• pp.23-30
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• 2021

In recent years, hazardous flash flooding has caused deaths and damage to infrastructure in Saudi Arabia. In this paper, our aim is to assess patterns and trends in climate means and extremes affecting flash flood hazards and water resources in Saudi Arabia for the purpose to improve risk assessment for forecast capacity. We would like to examine temperature, precipitation climatology and trend magnitudes at surface stations in Saudi Arabia. Based on the assessment climate patterns maps and trends are accurately used to identify synoptic situations and tele-connections associated with flash flood risk. We also study local and regional changes in hydro-meteorological extremes over recent decades through new applications of statistical methods to weather station data and remote sensing based precipitation products; and develop remote sensing based high-resolution precipitation products that can aid to develop flash flood guidance system for the flood-prone areas. A dataset of extreme events has been developed using the multi-decadal station data, the statistical analysis has been performed to identify tele-connection indices, pressure and sea surface temperature patterns most predictive to heavy rainfall. It has been combined with time trends in extreme value occurrence to improve the potential for predicting and rapidly detecting storms. A methodology and algorithms has been developed for providing a well-calibrated precipitation product that can be used in the early warning systems for elevated risk of floods.

• The Journal of the Korea Contents Association
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• v.16 no.11
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• pp.488-498
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• 2016

Much of the information is stored as data, research has been activated for analyzing the data and predicting the special circumstances. In the case of power data, the studies, such as research of renewable energy utilization, power prediction depending on site characteristics, smart grid, and micro-grid, is actively in progress. In this paper, we propose a power prediction model using the substation environment data. In this case, we try to verify the power prediction result to reflect the multiple arguments on the power and weather data, rather than a simple power data. The validation process is the effect of multiple factors compared to other two methods, one of power prediction result considering power data and the other result using power pattern data that have been made in the similar weather data. Our system shows that it can achieve max prediction error of less than 15%.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.5
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• pp.897-904
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• 2006

The eastern coast of northeastern Brazil (NEB), a coastal land-strip up to 300 km wide and stretching out from Rio Grande do Norte $(5^{\circ}S)$ State down to the south of Bahia State $(17^{\circ}S)$, experiences different rain producing systems, such as distrubances in the south-east trade winds, frontal systems penetration, land-sea breeze circulation and local convection associated with the topography and moisture flux convergence. The annual total rainfall ranges from 600 inland to 3000 mm on the coast. Rainfall totals 5 to 12 times the focal climatic means were recorded in various regions of Alagoas state in January 2004. It was estimated that 46,000 people were homeless, with material damages exceeding US$10 million as a consequence of the ensuing floods. GOES infrared images analysis showed that the main weather system responsible for this anomalously high rainfall totals was an Upper Troposphere Cyclonic Vortex (UTCV), which formed at about a $27^{\underline{\circ}}W\;e\;12^{\underline{\circ}}S$ and remained active for the entire month of January over NEB.

• Journal of KIISE:Software and Applications
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• v.34 no.10
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• pp.929-936
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• 2007

The novel vision-based scheme for real-time extracting traffic parameters is proposed in this paper. Detecting and tracking of vehicle is processed at local region installed by operator. Local region is divided to segmented regions by edge and frame difference, and the segmented regions are classified into vehicle, road, shadow and headlight by statistical and geometrical features. Vehicle is detected by the result of the classification. Traffic parameters such as velocity, length, occupancy and distance are estimated by tracking using template matching at local region. Because background image are not used, it is possible to utilize under various conditions such as weather, time slots and locations. It is performed well with 90.16% detection rate in various databases. If direction, angle and iris are fitted to operating conditions, we are looking forward to using as the core of traffic monitoring systems.

• Journal of the Society of Disaster Information
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• v.14 no.2
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• pp.154-164
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• 2018

Purpose: Recent climate change makes weather-related disasters such as summer storms, heavy rains, winter snowfall disasters, and extreme cold temperature increase in trend. Heavy snowfall disasters requires speedy response due to various effects to traffic flows, buildings, and infrastructure. Heavy snowfall disaster response of South Korea is insufficient, even though heavy snowfall disasters affect urban safety. There have been lack of policy studies for heavy snowfall disasters. Method: This research analyzes case studies and explores implications using Information system technologies to snow removal vehicles and equipments for speedy snow removal during the heavy snowfall disasters. Results: Information system technology attachment to snow removal equipments can identify locations of snow removal vehicles and equipments for emergency period to support snow removal of adjacent jurisdictions. Conclusion: Case studies of this research can be further used for efficient application of snow removal tools of local governments.

• Journal of Astronomy and Space Sciences
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• v.26 no.4
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• pp.521-528
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• 2009

While it is well known that space environment can produce spacecraft anomaly, defining space environment effects for each anomalies is difficult. This is caused by the fact that spacecraft anomaly shows various symptoms and reproducing it is impossible. In this study, we try to find the conditions of when spacecraft failures happen more frequently and give satellite operators useful information. Especially, our study focuses on the geosynchronous satellites which cost is high and required high reliability. We used satellite anomaly data given by Satellite News Digest which is internet newspaper providing space industry news. In our analysis, 88 anomaly cases occurred from 1997 to 2008 shows bad corelation with Kp index. Satellite malfunctions were likely to happen in spring and fall and in local time from midnight to dawn. In addition, we found the probability of anomaly increase when high energy electron flux is high. This is more clearly appeared in solar minimum than maximum period.