• 대기
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• 제18권4호
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• pp.267-277
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• 2008

The occurrence and strength of the Asian Dust over the Korea Peninsular have been increased by the expansion of the desert area. For the continuous monitoring of the Asian Dust event, the geostationary satellites provide useful information by detecting the outbreak of the event as well as the long-range transportation of dust. The Infrared Optical Depth Index (IODI) derived from the MTSAT-1R data, indicating a quantitative index of the dust intensity, has been produced in real-time at Korea Meteorological Administration (KMA) since spring of 2007 for the forecast of Asian dust. The data processing algorithm for IODI consists of mainly two steps. The first step is to detect dust area by using brightness temperature difference between two thermal window channels which are influenced with different extinction coefficients by dust. Here we use dynamic threshold values based on the change of surface temperature. In the second step, the IODI is calculated using the ratio between current IR1 brightness temperature and the maximum brightness temperature of the last 10 days which we assume the clear sky. Validation with AOD retrieved from MODIS shows a good agreement over the ocean. Comparison of IODI with the ground based PM10 observation network in Korea shows distinct characteristics depending on the altitude of dust layer estimated from the Lidar data. In the case that the altitude of dust layer is relatively high, the intensity of IODI is larger than that of PM10. On the other hand, when the altitude of dust layer is lower, IODI seems to be relatively small comparing with PM10 measurement.

• 대기
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• 제22권2호
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• pp.163-174
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• 2012

Brightness temperature (BT) difference between sea fog and sea surface is small, because the top height of fog is low. Therefore, it is very difficult to detect sea fog with infrared (IR) channels in the nighttime. To overcome this difficulty, we have developed a new algorithm for detection of sea fog that consists in three tests. Firstly, both stratus and sea fog were discriminated from the other clouds by using the difference between BTs $3.7{\mu}m$ and $11{\mu}m$. Secondly, stratus occurring at a level higher than sea fog was removed when the difference between cloud top temperature and sea surface temperature (SST) is smaller than 3 K. In this process, we used daily SST data from AMSR-E microwave measurements that is available even in the presence of cloud. Then, the SST was converted to $11{\mu}m$ BT based on the regressed relationship between AMSR-E SST and MTSAT-1R $11{\mu}m$ BT at 1733 UTC over clear sky regions. Finally, stratus was further removed by using the homogeneity test based on the difference in cloud top texture between sea fog and stratus. Comparison between the retrievals from our algorithm and that from Korea Meteorological Administration (KMA) algorithm, shows that the KMA algorithm often misconceived sea fog as stratus, resulting in underestimating the occurrence of sea fog. Monthly distribution of sea fog over northeast Asia in 2008 was derived from the proposed algorithm. The frequency of sea fog is lowest in winter, and highest in summer especially in June. The seasonality of the sea fog occurrence between East and West Sea was comparable, while it is not clearly identified over South Sea. These results would serve to prevent the possible occurrence of marine accidents associated with sea fog.

• 대기
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• 제29권1호
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• pp.21-39
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• 2019

The conventional observations of the Korea Meteorological Administration (KMA) and National Centers for Environmental Prediction (NCEP) are compared in the numerical weather forecast system at the Korea Institute of Atmospheric Prediction Systems (KIAPS). The weather forecasting system used in this study is consists of Korea Integrated Model (KIM) as a global numerical weather prediction model, three-dimensional variational method as a data assimilation system, and KIAPS Package for Observation Processing (KPOP) as an observation pre-processing system. As a result, the forecast performance of NCEP observation was better while the number of observation is similar to the KMA observation. In addition, the sensitivity of forecast performance was investigated for each SONDE, SURFACE and AIRCRAFT observations. The differences in AIRCRAFT observation were not sensitive to forecast, but the use of NCEP SONDE and SURFACE observations have shown better forecast performance. It is found that the NCEP observations have more wind observations of the SONDE in the upper atmosphere and more surface pressure observations of the SURFACE in the ocean. The results suggest that evenly distributed observations can lead to improved forecast performance.

• The Plant Pathology Journal
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• 제36권1호
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• pp.54-66
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• 2020

This study was conducted to evaluate usefulness of numerical weather prediction data generated by the Unified Model (UM) for plant disease forecast. Using the UM06- and UM18-predicted weather data, which were released at 0600 and 1800 Universal Time Coordinated (UTC), respectively, by the Korea Meteorological Administration (KMA), disease forecast on bacterial grain rot (BGR) of rice was examined as compared with the model output based on the automated weather stations (AWS)-observed weather data. We analyzed performance of BGRcast based on the UM-predicted and the AWS-observed daily minimum temperature and average relative humidity in 2014 and 2015 from 29 locations representing major rice growing areas in Korea using regression analysis and two-way contingency table analysis. Temporal changes in weather conduciveness at two locations in 2014 were also analyzed with regard to daily weather conduciveness (C_i) and the 20-day and 7-day moving averages of C_i for the inoculum build-up phase (C_inc) prior to the panicle emergence of rice plants and the infection phase (C_inf) during the heading stage of rice plants, respectively. Based on C_inc and C_inf, we were able to obtain the same disease warnings at all locations regardless of the sources of weather data. In conclusion, the numerical weather prediction data from KMA could be reliable to apply as input data for plant disease forecast models. Weather prediction data would facilitate applications of weather-driven disease models for better disease management. Crop growers would have better options for disease control including both protective and curative measures when weather prediction data are used for disease warning.

• 대기
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• 제28권2호
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• pp.223-232
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• 2018

The Global-Korean aviation Turbulence Guidance (G-KTG) system is developed using the operational Global Data Assimilation and Prediction System of Korea Meteorological Administration with 17-km horizontal grid spacing. The G-KTG system provides an integrated solution of various clear-air turbulence (CAT) diagnostics and mountain-wave induced turbulence (MWT) diagnostics for low [below 10 kft (3.05 km)], middle [10 kft (3.05 km) - 20 kft (6.10 km)], and upper [20 kft (6.10 km) - 50 kft (15.24 km)] levels. Individual CAT and MWT diagnostics in the G-KTG are converted to a 1/3 power of energy dissipation rate (EDR). 12-h forecast of the G-KTG is evaluated using 6-month period (2016.06~2016.11) of in-situ EDR observation data. The forecast skill is calculated by area under curve (AUC) where the curve is drawn by pairs of probabilities of detection of "yes" for moderate-or-greater-level turbulence events and "no" for null-level turbulence events. The AUCs of G-KTG for the upper, middle, and lower levels are 0.79, 0.69, and 0.63, respectively. Comparison of the upper-level G-KTG with the regional-KTG in East Asia reveals that the forecast skill of the G-KTG (AUC = 0.77) is similar to that of the regional-KTG (AUC = 0.79) using the Regional Data Assimilation and Prediction System with 12-km horizontal grid spacing.

• 한국지리정보학회지
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• 제21권3호
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• pp.19-34
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• 2018

본 논문의 목적은 농업용 저수지 저수율 계측자료와 기상인자와의 다중선형회귀분석을 통해 저수율 예측 월단위 회귀식을 산정하는데 있다. 2002년부터 2016년까지의 한국농어촌공사 저수지 3,067개에 대한 저수율 관측자료와 기상청 63개 지점 관측자료를 수집하여 저수율 예측 다중선형 회귀식을 도출하였으며, 개발된 월별 회귀식에 대한 $R^2$는 0.51~0.95로 분석되었다. 또한 회귀식의 적용성 평가를 위해 9개 대표저수지에 대해 관측값과 비교한 $R^2$는 0.44~0.81로 나타났다. 회귀식을 이용하여 평년(1976-2005) 대비 저수지 가뭄지수(Reservoir Drought Index, RDI)를 산정하여 ROC 분석을 수행한 결과, 극심한 가뭄의 경우 2년(2015~2016) 평균 적중률은 0.64로 겨울의 적중률이 0.70으로 가장 높았고, 여름의 적중률이 0.58로 가장 낮게 나타났으며, 봄과 가을의 적중률은 각각 0.59, 0.68로 분석되었다. 본 연구에서 도출한 회귀식은 가용한 관측자료 및 1~3개월의 장기 기상전망자료 기반의 월단위 저수율 전망자료 생산이 가능하므로, 이를 기반으로 농업가뭄 전망정보의 생산이 가능할 것으로 판단된다.

• 한국지구과학회지
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• 제27권7호
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• pp.804-815
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• 2006

Meteorologists define a drought as a period of common dry weather. This may sound straightforward, but it is not so in reality. In this study, we attempted to identify meteorological drought conditions over South Korea. To evaluate the temporal and spatial variability of drought, we calculated two commonly used drought indices, the percent of normal precipitation (PNP) and the Palmer drought severity index (PDSI) calculated from fifty-eight meteorological stations below the Korean Meteorological Administration (KMA). The yearly precipitation has been growing gradually, and the amplitude between maximum and minimum also grow more explicitly from 1960's. According to the analysis of percentile anomaly of monthly precipitation, major drought duration was $1927{\sim}1929,\;1937{\sim}1939,\;1942{\sim}1944,\;1967{\sim}1968,\;1976{\sim}1977,\;1982{\sim}1983,\;1988,\;and\;1994{\sim}1995$. The severe drought occurred most frequently in Mokpo, Daegu, Jeonju, Busan, and Gangneung; it tended to occur more frequently in south sector than in mid sector of Korea and in south west sector than in south east sector. According to the analysis of seasonal distribution, extreme droughts occurred frequently in winter at Seoul, Gangneung, Jeonju, Daegu, and Busan. Severe droughts in summer were formed frequently at Seoul, Gangneung, and Mokpo, while that for spring at Jeonju, Daegu, and Busan. The results of PDSI distribution for the $1994{\sim}1995$ drought period were one of the most severe and widely spreaded droughts; it occurred most frequently in the south sector of South Korea. The comparison of time series between PDSI and Normal Percent showed that they exhibit a strong compatibility for the entire study period; it implies that both drought indices are useful method to indicate drought severity.

• 대기
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• 제24권2호
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• pp.173-188
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• 2014

The KMA has cooperated with the Oklahoma University in USA to develop a Polarimetric Radar Data (PRD) simulator to improve the microphysical processes in Korea Local Analysis and Prediction System (KLAPS), which is critical for the utilization of PRD into Numerical Weather Prediction (NWP) field. The simulator is like a tool to convert NWP data into PRD, so it enables us to compare NWP data with PRD directly. The simulator can simulate polarimetric radar variables such as reflectivity (Z), differential reflectivity ($Z_{DR}$), specific differential phase ($K_{DP}$), and cross-correlation coefficient (${\rho}_{hv}$) with input of the Drop Size Distribution (DSD) and scattering calculation of the hydrometeors. However, the simulator is being developed based on the foreign observation data, therefore the PRD simulator development reflecting rainfall characteristics of Korea is needed. This study analyzed a potential application of the 2-Dimension Video Disdrometer (2DVD) data by calculating the raindrop axis ratio according to the rain-types to reflect Korea's rainfall characteristics into scattering module in the simulator. The 2DVD instrument measures the precipitation DSD including the fall velocity and the shape of individual raindrops. We calculated raindrop axis ratio for stratiform, convective and mixed rainfall cases after checking the accuracy of 2DVD data, which usually represent the scattering characteristics of precipitation. The raindrop axis ratio obtained from 2DVD data are compared with those from foreign database in the simulator. The calculated the dual-polarimetric radar variables from the simulator using the obtained raindrop axis ratio are also compared with in situ dual-polarimetric observation data at Bislsan (BSL). 2DVD observation data show high accuracies in the range of 0.7~4.8% compared with in situ rain gauge data which represents 2DVD data are sufficient for the use to simulator. There are small differences of axis ratio in the diameter below 1~2 mm and above 4~5 mm, which are more obvious for bigger raindrops especially for a strong convective rainfall case. These differences of raindrop axis ratio between domestic and foreign rainfall data base suggest that the potential use of disdrometer observation can develop of a PRD simulated suitable to the Korea precipitation system.

• 한국지구과학회지
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• 제40권2호
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• pp.135-148
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• 2019

전세계적으로 일사계 비교관측 기술은 급격히 발전하고 있지만 국내의 경우 일사 비교관측 표준지침을 준비하고 있는 실정이다. 본 연구에서는 국내 기상 및 지리적 환경을 고려하여 전천일사계의 비교관측 절차를 정립하였다. 2017년 아시아 지역 복사센터에서는 국가표준 일사계들의 비교관측을 통해 일사계 보정이 이루어졌다. 이때 검교정된 기상청 기준기를 이용하여 기상청의 부기준기들과 강릉원주대의 전천일사계의 비교관측 및 검교정이 수행되었다. 비교관측 및 검교정은 2018년 10월 24일부터 10월 25일(2일)까지 수행되었으며 비교관측자료를 분석하여 오차분석 및 검교정을 수행하였다. 보정전 비교관측에 따르면, 전천일사계 부기준기들(B-J)은 기상청 전천일사계 기준기(A)를 기준으로 ${\pm}12.0W\;m^{-2}$2 이하의 편차가 나타났고 B와 I 전천일사계는 ${\pm}4.0W\;m^{-2}$ 미만의 작은 편차를 보였다. 태양 복사량이 $450W\;m^{-2}$ 이상인 자료들을 이용하여 감도정수의 보정값을 계산하였다. B와 I 일사계(오차 ${\pm}0.5W\;m^{-2}$ 이하)를 제외한 일사계들(오차 ${\pm}5W\;m^{-2}$ 이상)은 $0.08-0.16{\mu}V(W\;m^{-2})^{-1}$ 감도정수 변경이 적용되었다. C 일사계는 감도정수의 변화가 가장 컸으며 감도정수는 $-0.16{\mu}V(W\;m^{-2})^{-1}$으로 보정하였다. 비교관측에 참가한 9종의 기준기 및 부기준기들의 최종 관측오차는 $0.06W\;m^{-2}$ (0.08%) 이하였으며 허용범위인 ${\pm}1.00%$ (${\pm}4.50W\;m^{-2}$)로 검교정되었다.

• 한국농림기상학회지
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• 제22권3호
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• pp.128-134
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• 2020

국립농업과학원은 공동연구를 통해 기상청 소속 94개 종관기상관측소의 일별 기상자료를 기반으로 6가지 기상요소(최고·최저·평균 기온, 강수량, 일사량, 일조시간)에 대한 30m 및 270m 해상도의 격자형 일별 상세 기후 자료를 약 50년(1971-현재) 기간에 대해 생산하였고, 평년 기후값(1981-2010) 및 평년 대비 상세 기후 변화량 정보를 생산하였다. 이러한 일별 자료, 평년 자료 그리고 평년 대비 변화량 자료는 GeoTiff 형식으로 제공되며, 구글 크롬(Google Chrome) 에서 최적화된 https://agecoclim.agmet.kr 사이트에서 다운받을 수 있다. 본 연구 결과물은 현재 주식회사 에피넷과 국립농업과학원에서 공동으로 관리 중이며, 향후 기후·이상기상 변화량 분석 자동화 체계를 추가 보완을 통해 활용성을 제고하고, 기후 정보의 정확성을 향상시킬 예정이다.