• 한국기후변화학회지
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• 제9권3호
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• pp.209-221
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• 2018

The characteristics of heat wave events in Seoul are analyzed using weather station data from Korea Meteorological Administration (KMA) and European Centre for Medium-Range Weather Forecast (ECMWF) ERA-Interim reanalysis data from 1979 to 2016. Heat waves are defined as events in the upper 10th percentile of the daily maximum temperatures. The associated synoptic weather patterns are then classified into six clusters through Self-Organizing Map (SOM) analysis for sea-level pressure anomalies in East Asia. Cluster 1 shows an anti-cyclonic circulation and weak troughs in southeast and west of Korea, respectively. This synoptic pattern leads to southeasterly winds that advect warm and moist air to the Korean Peninsula. Both clusters 2 and 3 are associated with southerly winds formed by an anti-cyclonic circulation over the east of Korea and cyclonic circulation over the west of Korea. Cluster 4 shows a stagnant weather pattern with weak winds and strong insolation. Clusters 5 and 6 are associated with F?hn wind resulting from an anti-cyclonic circulation in the north of the Korean Peninsula. In terms of long-term variations, event frequencies of clusters 4 and 5 show increasing and decreasing trends, respectively. However, other clusters do not show any long-term trends, indicating that the mechanisms that drive heat wave events in Seoul have remained constant over the last four decades.

• 대기
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• 제33권1호
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• pp.49-59
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• 2023

Blocking refers to a class of weather phenomena appearing in the mid and high latitudes, whose characteristics are blocked airflow of persistence. Frequently found over the Pacific and Atlantic regions of the Northern Hemisphere, blocking affects severe weather in the surrounding areas with different mechanisms depending on the type of blocking patterns. Along with lots of studies about persistent weather extremes focusing on the specific types of blocking, a new categorization using Rossby wave breaking has emerged. This study aims to apply this concept to the classification of blockings over the Pacific and examine how different wave breakings specify the associated cold weather in the Korean peninsula. At the same time, we investigate a strongly developing ridge around the Pacific by designing a new detection algorithm, where a reversal method is modified to distinguish ridge-type blocking patterns. As result, Kamchatka blocking (KB) and strong ridge over the Central Pacific are observed the most frequently during 20 years (2001~2020) of the studied period, and anomalous low pressures with cold air over the Korean Peninsula are accompanied by blocking events. When it considers the Rossby wave breaking, cyclonic wave-breaking is dominant in KB, which generates low-pressure anomalies over the Korean Peninsula. However, KB with anticyclone wave breaking appears with the high-pressure anomalies over the Korean Peninsula and it generates the warm temperature anomaly. Lastly, the low-pressure anomalies are also generated by the strong ridge over the Central Pacific, which persists for approximately three days and give a significant impact on cold surge on the Korean Peninsula.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.1224-1226
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• 2003

Dust-storm is one of the heaviest hazardous weather which frequently affects most part of northern China in spring. Satellite multi-spectral observations can provide significant information for detecting and quantitative determining the property of dust-storm . An algorithm to monitor dust-storm automatically was developed based on satellite observation. The algorithm utilizes split widows technique and spectral classification technique and also developed a new dust remote sensing product Infra -red Difference Dust Index (IDDI) proxy dust-loading dataset using GMS-5.

• 대기
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• 제24권3호
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• pp.433-444
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• 2014

Although the Radar-AWS Rainrate (RAR) calculation system operated by Korea Meteorological Administration estimated precipitation using 2-dimensional composite components of single polarization radars, this system has several limitations in estimating the precipitation accurately. To to overcome limitations of the RAR system, the Korea Meteorological Administration developed and operated the RMQ (Radar-based Multi-sensor Quantitative Precipitation Estimation) system, the improved version of NMQ (National Mosaic and Multi-sensor Quantitative Precipitation Estimation) system of NSSL (National Severe Storms Laboratory) for the Korean Peninsula. This study introduced the RMQ system domestically for the first time and verified the precipitation estimation performance of the RMQ system. The RMQ system consists of 4 main parts as the process of handling the single radar data, merging 3D reflectivity, QPE, and displaying result images. The first process (handling of the single radar data) has the pre-process of a radar data (transformation of data format and quality control), the production of a vertical profile of reflectivity and the correction of bright-band, and the conduction of hydrid scan reflectivity. The next process (merger of 3D reflectivity) produces the 3D composite reflectivity field after correcting the quality controlled single radar reflectivity. The QPE process classifies the precipitation types using multi-sensor information and estimates quantitative precipitation using several Z-R relationships which are proper for precipitation types. This process also corrects the precipitation using the AWS position with local gauge correction technique. The last process displays the final results transformed into images in the web-site. This study also estimated the accuracy of the RMQ system with five events in 2012 summer season and compared the results of the RAR (Radar-AWS Rainrate) and RMQ systems. The RMQ system ($2.36mm\;hr^{-1}$ in RMSE on average) is superior to the RAR system ($8.33mm\;hr^{-1}$ in RMSE) and improved by 73.25% in RMSE and 25.56% in correlation coefficient on average. The precipitation composite field images produced by the RMQ system are almost identical to the AWS (Automatic Weather Statioin) images. Therefore, the RMQ system has contributed to improve the accuracy of precipitation estimation using weather radars and operation of the RMQ system in the work field in future enables to cope with the extreme weather conditions actively.

• 한국전자파학회논문지
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• 제27권6호
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• pp.521-530
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• 2016

기상레이다는 전자기파를 대기 중에 방사하여 목표물에 부딪혀서 되돌아오는 후방산란 신호를 수신하는 기상장비이다. 기상청의 기상레이다는 도플러 관측 기능을 가지고 있기 때문에 목표물의 시선속도를 산출할 수 있다. 그러나 기상레이다의 넓은 관측 반경을 확보하려면 관측 속도 범위가 작아져 이를 넘어서는 시선속도는 접힘 현상이 발생한다. 따라서 최대 관측 반경을 유지한 채 관측 속도 범위를 넓히기 위해서는 high PRF와 low PRF 두 개의 서로 다른 PRF로 신호를 송 수신하는 dual PRF(Pulse Repetition Frequency) 모드 기능을 이용해야 한다. Dual PRF 모드를 이용하면 high와 low PRF로 관측된 두 최대 속도의 최소공배수만큼 관측 속도 범위를 넓힐 수 있다. 이를 위해 본 연구에서는 high PRF와 low PRF로 관측된 시선속도의 차이값과 이에 대한 오차를 고려한 분류 기준을 만들고, 분류된 영역별로 보정 인자를 산출하여 시선속도 펼침을 수행하는 시선속도 접힘 풀기 알고리즘을 개발하였다. 이를 용인테스트베드레이다에 적용한 결과, 기존에 산출되는 시선속도보다 개선된 성능을 보였다.

• The Korean Journal of Ecology
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• 제19권5호
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• pp.403-416
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• 1996

Global natural vegetation mapping (GNVM) system was developed for estimating potential forest area of the globe. With input of monthly mean temperature and monthly precipitation observed at weather stations, the system spherically interpolates them into 1°×1°grid points on a blobe, converts them into vegetation types, and produces a potential vegetation map and a potenital vegetation area. The spherical interpolation was based on negative exponential function fed from the constant radius stations with oval weighing method which is latitudinally elongated weighing in temperature and longitudinally elongated weighing in precipitation. The temperature values were corrected for altitude by applying a linear lapse-rate (0.65℃ / 100m) with reference to a built-in digital terrain map of the globe. The vegetation classification was based upon Koppen’s sKDICe. The potential forest area is estimated for 6.96 Gha (46.24％) of the global land area (15.05 Gha).

• Journal of Electrical Engineering and Technology
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• 제13권3호
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• pp.1377-1382
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• 2018

In the marine environment, many clutters have similar features with the marine targets due to the diverse changes of the air temperature, water temperature, various weather and seasons. Also, the clutters in the ground environment have similar features due to the same reason. In this paper, we proposed a robust Hybrid Machine Character (HMC) method to classify the targets from the clutters in the infrared images for the various environments. The proposed HMC method adopts human's multiple personality utilization and the CNN ensemble method to classify the targets in the ground and marine environments. This method uses an advantage of the each environmental training model. Experimental results demonstrate that the proposed method has better success rate to classify the targets and clutters than previously proposed CNN classification method.

• 대한원격탐사학회지
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• 제40권2호
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• pp.179-190
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• 2024

This study aims to compare supervised classification methods with phenology-based approaches, specifically pixel-based and segment-based methods, for accurate crop mapping in agricultural landscapes. We utilized Sentinel-2A imagery, which provides multispectral data for accurate crop mapping. 31 normalized difference vegetation index (NDVI) images were calculated from the Sentinel-2A data. Next, we employed phenology-based approaches to extract valuable information from the NDVI time series. A set of 10 phenology metrics was extracted from the NDVI data. For the supervised classification, we employed the maximum likelihood (MaxLike) algorithm. For the phenology-based approaches, we implemented both pixel-based and segment-based methods. The results indicate that phenology-based approaches outperformed the MaxLike algorithm in regions with frequent rainfall and cloudy conditions. The segment-based phenology approach demonstrated the highest kappa coefficient of 0.85, indicating a high level of agreement with the ground truth data. The pixel-based phenology approach also achieved a commendable kappa coefficient of 0.81, indicating its effectiveness in accurately classifying the crop types. On the other hand, the supervised classification method (MaxLike) yielded a lower kappa coefficient of 0.74. Our study suggests that segment-based phenology mapping is a suitable approach for regions like South Korea, where continuous cloud-free satellite images are scarce. However, establishing precise classification thresholds remains challenging due to the lack of adequately sampled NDVI data. Despite this limitation, the phenology-based approach demonstrates its potential in crop classification, particularly in regions with varying weather patterns.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2004년도 춘계학술발표회
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• pp.600-605
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• 2004

The road construction with horizontal expansion of country using and augmentation of traffic demand is advanced actively and it accompanies hereupon, the above of 70% of the country is formed at the mountain in our country where the hazard cut slope has been created. In this study, It is prepared a effective management countermeasure of cut slope introduced priority investigation decision method against hazard cut slope which is influenced by abnormally rainfall by an unusual change in the weather such as a guerilla rainfall character. In meaning link, It was executed collapse cause by failure character analysis in the cut slope which has failed for the last five years and it is prepared the hazard grade criterion from E to A grade according to collapse cause. It is decided that a maintenance management grade by the hazard grade classification criterion of cut slope. So It is possible to hazard cut slope. It is established failure protection counter countermeasure by effective maintenance management through the hazard grade c1assification criterion and it will be able to dispose to advanced nation level like Hong Kong and Japanese.

• 대기
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• 제16권3호
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• pp.235-246
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• 2006

Remote sensing techniques using satellites or the scanning weather radars depend mostly on the presence of clouds or precipitation, and leave the extensive regions of clear air unobserved. But wind profilers provide the most direct measurements of mesoscale vertical air motion in the troposphere, even in the context of heavy precipitation. In this paper, the precipitation events during the Changma period was classified into 4 precipitation types - stratiform, mixed stratiform/ convective, deep convective, and shallow convective. The parameters for the classification of analysis are the vertical structure of reflectivity, Doppler velocity, and spectral width measured with the wind profiler at Haenam for a three-year period (2003-2005). In addition, the synoptic fields and total amount of precipitation were analyzed using the Global Final Analyses (FNL) data and the Global Precipitation Climatology Project (GPCP) data. During the Changma period, the results show that the stratiform type was dominant under the moist-neutral atmosphere in 2003, whereas the deep convective type was under the moist unstable condition in 2004. The stratiform type was no less popular than the deep convective type among four seasons because the moist neutral layer was formed by the convergence between the upper-level jet and the low-level jet, and by the moisture transport along the western rim of the North Pacific subtropical anticyclone.