• 대기
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• 제21권3호
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• pp.319-336
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• 2011

The objective of this study was to assess the meteorological capability of Korea by comparing with that of the U.S. and Japan as of 2010. The research was conducted based on various indices and surveys, and quantified the results using the Gordon's scoring model. The index assessment used 11 items derived from 9 segments - surface observation, advanced observation and observations quality in the observation field; data assimilation, numerical model and infrastructure in the data processing field; forecast accuracy in the forecast field; climate prediction and climate change in the climate field - in this research, we classified the meteorological technology into four fields. In the survey assessment, another 10 items in addition to the above 11 ones (total 21 items) were used. In the field of climate, Korea was found to lag far behind the U.S. (96.5p) and Japan (90.5p) with 77.6 points out of 100, which is 18.9 and 12.9 points lower than them respectively. On the other hand, Korea showed the narrowest gap with Japan (95.3p) and the U.S. (94.2) in the forecasting field, recording 90.3 points. Particularly, in surface observation, infrastructure and forecast accuracy segment, Korea was on a par with the U.S. and Japan, boasting 100.5 percent compared to their counterparts. However, in advanced observation, data quality and climate change segment, Korea was only at the level of 81.5 percent compared to that of the U.S. and Japan. All in all, the technological prowess of Korea, scoring 84.6 points, stood at 89.7 percent of that of the U.S. (94.3p) and 91.9 percent of Japan (92.1p).

• 대기
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• 제30권2호
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• pp.141-154
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• 2020

Seasonal forecast is growing in demand, as it provides valuable information for decision making and potential to reduce impact on weather events. This study examines how operational climate prediction systems can be reliable, producing the probability forecast in seasonal scale. A reliability diagram was used, which is a tool for the reliability by comparing probabilities with the corresponding observed frequency. It is proposed for a method grading scales of 1-5 based on the reliability diagram to quantify the reliability. Probabilities are derived from ensemble members using hindcast data. The analysis is focused on skill for 2 m temperature and precipitation from climate prediction systems in KMA, UKMO, and ECMWF, NCEP and JMA. Five categorizations are found depending on variables, seasons and regions. The probability forecast for 2 m temperature can be relied on while that for precipitation is reliable only in few regions. The probabilistic skill in KMA and UKMO is comparable with ECMWF, and the reliabilities tend to increase as the ensemble size and hindcast period increasing.

• 대기
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• 제32권4호
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• pp.381-394
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• 2022

The Korea Meteorological Administration (KMA) National Typhoon Center has been officially releasing reanalyzed best tracks for the previous year's northwest Pacific typhoons since 2015. However, while most typhoon researchers are aware of the data released by other institutions, such as the Joint Typhoon Warning Center (JTWC) and the Regional Specialized Meteorological Center (RSMC) Tokyo, they are often unfamiliar with the KMA products. In this technical note, we describe the best track data released by KMA, and the algorithms that are used to generate it. We hope that this will increase the usefulness of the data to typhoon researchers, and help raise awareness of the product. The best track reanalysis process is initiated when the necessary database of observations-which includes satellite, synoptic, ocean, and radar observations-has become complete for the required year. Three categories of best track information-position (track), intensity (maximum sustained winds and central pressure), and size (radii of high-wind areas)-are estimated based on scientific processes. These estimates are then examined by typhoon forecasters and other internal and external experts, and issued as an official product when final approval has been given.

• 한국대기환경학회지
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• 제26권3호
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• pp.253-264
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• 2010

This study investigates the relationship between daily mortality and heat stress in Seoul, using perceived temperatures (PT) derived from a heat budget model. During the summer season, observed PT intensity showed the biggest magnitude of summer heat stress from the middle 10 days of July to the first 10 days of August. The elderly (65 and above) were found to be the most vulnerable to heat stress. The threshold PT, with a significant increase in excess mortality, was $38^{\circ}C$. No time lagged effect was observed with summer heat stress, while a high correlation was observed between anomalies in PT and relative deviation of mortality. A comparison of the heat index and the discomfort index with excess mortality revealed that the discomfort index underestimated excess mortality, whereas the heat index could not appropriately explain the increase in excess mortality correlated with the increase in excess heat. In contrast, PT was found to be the weather element that best represents excess mortality due to heat stress, and is thus expected to serve as a more reliable forecast index of human biometeorology.

• 한국항공운항학회지
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• 제19권1호
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• pp.29-37
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• 2011

Last April, Europe was severly damaged as all social and economic activities came to a halt prompted by the cancellation of all flights resulting from volcanic ash. This exemplifies that the meteorology conditions have significant influence on the flights of airplanes. Hence, in this research the influence that the meteorology has on the domestic flights and its characteristics will be examined, and the core meteorological factors that influence flights in each airport will be drawn. In order to do this, statistical analysis on the influence that the meteorology has on flights was carried out in order to analyze the data about flight cancelation and delay and also its cause, primarily based on the Gimpo, Gimhae, and the Jeju airports. As a result, first, the meteorological factors which impact flight cancellation and delay were different among the domestic airports, and second, it was analyzed that fog was the main meteorological factor in the Gimpo airport, strong wind in the Jeju airport, and fog in the Gimhae airport. Third, between the day the flights were cancelled and delayed occurred, and the day that weren't, the fact that there existed a difference among the actual meteorological factors was statistically drawn. With the result of such analysis, meteorological factors pertaining to the cancellation and delay of flights must be considered seperately by each airport and specialized meteorological information must be provided accordingly. Further, when selecting the position of an airport that is to be constructed in the future, implications that there is a definite need for the meteorology effect evaluation based on past meteorology data can be drawn.

• 한국농공학회논문집
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• 제49권4호
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• pp.3-12
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• 2007

The purpose of this paper is to analyze the relationship between meteorological factors and agricultural reservoir storage, and predict the reservoir storage by multiple regression equation selected by high correlated meteorological factors. Two agricultural reservoirs (Geumgwang and Gosam) located in the upsteam of Gongdo water level gauging station of Anseong-cheon watershed were selected. Monthly reservoir storage data and meteorological data in Suwon weather station of 21 years (1985-2005) were collected. Three cases of correlation (case 1: yearly mean, case 2: seasonal mean dividing a year into 3 periods, and case 3: lagging the reservoir storage from 1 month to 3 months under the condition of case 2) were examined using 8 meteorological factors (precipitation, mean/maximum/minimum temperature, relative humidity, sunshine hour, wind velocity and evaporation). From the correlation analysis, 4 high correlated meteorological factors were selected, and multiple regression was executed for each case. The determination coefficient ($R^{2}$) of predicted reservoir storage for case 1 showed 0.45 and 0.49 for Geumgwang and Gosam reservoir respectively. The predicted reservoir storage for case 2 showed the highest $R^{2}$ of 0.46 and 0.56 respectively in the period of April to June. The predicted reservoir storage for 1 month lag of case 3 showed the $R^{2}$ of 0.68 and 0.85 respectively for the period of April to June. The results showed that the status of agricultural reservoir storage could be expressed with couple of meteorological factors. The prediction enhanced when the storage data are divided into periods rather than yearly mean and especially from the beginning time of paddy irrigation (April) to high decrease of reservoir storage (June) before Jangma.

• 한국지구과학회지
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• 제43권2호
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• pp.239-252
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• 2022

국내에서 처음으로 도입한 기상 항공기에 탑재한 G-band 수증기 라디오미터(GVR) 관측으로 산출된 가강수량의 품질 관리 방법을 제안하였다. GVR 빔의 연직 최단 경로 자료만 사용하기 위해 기상 항공기의 자세 정보(pitch와 roll 각도)를 활용하였고, GVR 가강수량이 20 mm 이상의 자료를 제거하는 방법을 품질 관리에 적용하였다. GVR 가강수량이 20 mm 이상으로 증가할 때, 웜로드(Warm load) 평균 전력과 스카이로드(Sky load) 평균 전력의 차이가 0에 가까이 수렴하는 특성을 확인하였고, 이는 COMS (Communication, Ocean and Meteorological Satellite)의 운형, 운정고도, 운량자료와 구름통합관측기기(CCP), 강수입자 측정기(PIP)로 측정된 강수 및 구름 입자 크기로 확인한 하층운과 중층운에 의한 높은 밝기온도 때문으로 판단된다. 구름 많은 날의 품질 관리 적용 전후의 GVR 가강수량을 LDAPS (Local Data Assimilation and Prediction System) 가강수량과 정량적으로 비교하였는데 RMSD (Root Mean Square Difference)는 2.9 mm에서 1.8 mm로 감소하였고, KLAPS (Korea Local Analysis and Prediction System)와의 RMSD는 5.4 mm에서 4.3 mm로 감소하여 향상된 정확도를 보였다. 또한 품질 관리를 적용한 GVR 가강수량과 드롭존데 가강수량 관측 자료을 활용하여 COMS 가강수량과도 정량적으로 비교평가함으로써 본 연구에서 제안한 GVR 가강수량의 품질 관리 방법의 유효성을 확인하였다.

• 한국대기환경학회지
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• 제19권5호
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• pp.595-610
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• 2003

The statistical indexes such as RMSE (Root Mean Square Error), Mean Bias error, and IOA (Index of agreement) are used to evaluate 3 Dimensional wind and temperature fields predicted by operational meteorological model RAMS (Regional Atmospheric Meteorological System) implemented in CARIS (Chemical Accident Response Information System) for the dispersion forecast of hazardous chemicals in case of the chemical accidents in Korea. The operational atmospheric model, RAMS in CARIS are designed to use GDAPS, GTS, and AWS meteorological data obtained from KMA (Korean Meteorological Administration) for the generation of 3-dimensional initial meteorological fields. The predicted meteorological variables such as wind speed, wind direction, temperature, and precipitation amount, during 19 ∼ 23, August 2002, are extracted at the nearest grid point to the meteorological monitoring sites, and validated against the observations located over the Korean peninsula. The results show that Mean bias and Root Mean Square Error are 0.9 (m/s), 1.85 (m/s) for wind speed at 10 m above the ground, respectively, and 1.45 ($^{\circ}C$), 2.82 ($^{\circ}C$) for surface temperature. Of particular interest is the distribution of forecasting error predicted by RAMS with respect to the altitude; relatively smaller error is found in the near-surface atmosphere for wind and temperature fields, while it grows larger as the altitude increases. Overall, some of the overpredictions in comparisons with the observations are detected for wind and temperature fields, whereas relatively small errors are found in the near-surface atmosphere. This discrepancies are partly attributed to the oversimplified spacing of soil, soil contents and initial temperature fields, suggesting some improvement could probably be gained if the sub-grid scale nature of moisture and temperature fields was taken into account. However, IOA values for the wind field (0.62) as well as temperature field (0.78) is greater than the 'good' value criteria (> 0.5) implied by other studies. The good value of IOA along with relatively small wind field error in the near surface atmosphere implies that, on the basis of current meteorological data for initial fields, RAMS has good potentials to be used as a operational meteorological model in predicting the urban or local scale 3-dimensional wind fields for the dispersion forecast in association with hazardous chemical releases in Korea.

• 대기
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• 제13권3호
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• pp.31-39
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• 2003

• 대기
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• 제22권3호
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• pp.387-387
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• 2012