• 대기
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• 제30권4호
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• pp.439-454
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• 2020

This study investigates the change in the fine particulate matter (PM2.5) concentration and World Health Organization (WHO) air quality index (AQI) in East Asia (EA) under Shared Socioeconomic Pathways (SSPs). AQI is an indicator of increasing levels about health concern, divided into six categories based on PM2.5 annual concentrations. Here, we utilized the ensemble results of UKESM1, the climate model operated in Met Office, UK, for the analysis of long-term variation during the historical (1950~2014) and future (2015~2100) period. The results show that the spatial distributions of simulated PM2.5 concentrations in present-day (1995~2014) are comparable to observations. It is found that most regions in EA exceeded the WHO air quality guideline except for Japan, Mongolia regions, and the far seas during the historical period. In future scenarios containing strong air quality (SSP1-2.6, SSP5-8.5) and medium air quality (SSP2-4.5) controls, PM2.5 concentrations are substantially reduced, resulting in significant improvement in AQI until the mid-21st century. On the other hand, the mild air pollution controls in SSP3-7.0 tend to lead poor AQI in China and Korea. This study also examines impact of increased in PM2.5 concentrations on downward shortwave energy at the surface. As a result, strong air pollution controls can improve air quality through reduced PM2.5 concentrations, but lead to an additional warming in both the near and mid-term future climate over EA.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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• pp.415-418
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• 2004

The Studying is on developing precision of the moisture information on a soil. We used the data of AQUA AMSR-E which were obtained by Direct Receiving System in Korea Meteorological Administration(KMA). Although we know the Soil Moisture Information(SMI) helps the numerical weather model to produce the realistic results, we couldn't do it for the problem on a spatial resolution of the data is too low to apply. So we've tried to develop in a spatial resolution by using the AMSR-E data with a Digital Elevation Model(DEM) and Normal Difference Vegetation Index(NDVI) from AQUA MODIS and compared the difference between their information in statics. The result is more precise than the simple algorithm by a polarization ratio, and we could get the better result to use in forecast practically, if it's apply to get more detail in the vegetation temperature.

• 대기
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• 제16권3호
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• pp.225-234
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• 2006

Convective systems propagate eastward with a persistent pattern in the longitude-time space. The characteristic structure and fluctuation of convective system is helpful in determining its predictability. In this study, convective index (CI) was defined as a difference between GOES-9 window and water vapor channel brightness temperatures following Mosher (2001). Then the temporal-spatial scales and variational characteristics of the summer convective systems in the East Asia were analyzed. It is found that the average moving speed of the convective system is about 14 m/s which is much faster than the low pressure system in the summer. Their average duration is about 12 hours and the average length of the cloud streak is about 750km. These characteristics are consistent with results from other studies. Although the convective systems are forced by the synoptic system and are mostly developed in the eastern edge of the Tibetan Plateau, they have a persistent pattern, i.e., appearance of the maximum intensity of convective systems, as they approach the Korean Peninsula. The consistency of the convective systems, i.e., the eastward propagation, suggests that there exists an intrinsic predictability.

• 한국지리정보학회지
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• 제1권1호
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• pp.99-108
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• 1998

국지 기상 모형의 지표 특성을 표현하기 위해 토양 구분, 식생 구분, 지표 거칠기 길이, 지표 알베도와 엽면지수가 지면 과정 모수화 내에서 처방되어야 한다. 이 연구에서는 인공위성 관측값으로부터 계절함수로 얻어진 경,위도 1도 및 1도의 엽면지수, 지표거칠기 길이, 눈이 없을 때의 지표 알베도와 상세 격자 NDVI를 지면 과정 모형에 적용하였다. 생물권과 대기권 사이, 지면과 대기 사이의 상호작용에서 이러한 인공위성 자료를 사용한 것과 사용하지 않은 것을 비교함으로써, 열, 에너지 및 수증기 속들, 지면 기온, 바람, 식생 물함유량, 비습, 강수장의 민감도가 조사되었다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2019년도 학술발표회
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• pp.150-150
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• 2019

The development of prolong and severe drought can directly impact on the environment, agriculture, economics and society of country. A lot of efforts have been made across worldwide in the planning, monitoring and mitigation of drought. Currently, different drought indices such as the Palmer Drought Severity Index (PDSI), Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI) are developed and most commonly used to monitor drought characteristics quantitatively. However, it will be very meaningful and essential to develop a more effective technique for assessment and monitoring of onset and end of drought. Therefore, in this study, the hidden Markov Bayesian classifier (MBC) was employed for the assessment of onset and end of meteorological drought classes. The results showed that the probabilities of different classes based on the MBC were quite suitable and can be employed to estimate onset and end of each class for meteorological droughts. The classification results of MBC were compared with SPI and with past studies which proved that the MBC was able to account accuracy in determining the accurate drought classes. For more performance evaluation of classification results confusion matrix was used to find accuracy and precision in predicting the classes and their results are also appropriate. The overall results indicate that the MBC was effective in predicating the onset and end of drought events and can utilized for monitoring and management of short-term drought risk.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2008년도 International Symposium on Remote Sensing
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• pp.80-83
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• 2008

Diverse researches using vegetation index have been carried out to monitor spring droughts that have frequently occurred since 2000. The strength of the drought monitoring using vegetation index lies in that it can reflect characteristics of satellite images: large area coverage, cyclicity, and promptness. However, vegetation index involve uncertainly caused by diverse factors that affect vegetation stress. In this study, multi-temporal vegetation index is compared with the most representative meteorological drought indices like PSDI, SPI. Based on the results from analyses, usability of vegetation index as a tool of drought analysis is proposed.

• 대기
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• 제26권4호
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• pp.495-508
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• 2016

In order to determine the prediction possibility of heavy rainfall, a variety of analyses was conducted by using three-dimensional data obtained from Korea Local Analysis and Prediction System (KLAPS) re-analysis data. Strong moisture convergence occurring around the time of the heavy rainfall is consistent with the results of previous studies on such continuous production. Heavy rainfall occurred in the cloud system with a thick convective clouds. The moisture convergence, temperature and potential temperature advection showed increase into the heavy rainfall occurrence area. The distribution of integrated liquid water content tended to decrease as rainfall increased and was characterized by accelerated convective instability along with increased buoyant energy. In addition, changes were noted in the various characteristics of instability indices such as K-index (KI), Showalter Stability Index (SSI), and lifted index (LI). The meteorological variables used in the analysis showed clear increases or decreases according to the changes in rainfall amount. These rapid changes as well as the meteorological variables changes are attributed to the surrounding and meteorological conditions. Thus, we verified that heavy rainfall can be predicted according to such increase, decrease, or changes. This study focused on quantitative values and change characteristics of diagnostic variables calculated by using numerical models rather than by focusing on synoptic analysis at the time of the heavy rainfall occurrence, thereby utilizing them as prognostic variables in the study of the predictability of heavy rainfall. These results can contribute to the identification of production and development mechanisms of heavy rainfall and can be used in applied research for prediction of such precipitation. In the analysis of various case studies of heavy rainfall in the future, our study result can be utilized to show the development of the prediction of severe weather.

• 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.

• 한국수자원학회논문집
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• 제51권6호
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• pp.471-479
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• 2018

본 연구는 기상학적 및 수문학적 가뭄지수를 이용하여 가뭄사상의 첨두 심도 발생시점과 가뭄발생 기간에 대한 연구를 수행하였다. 연구를 수행하기 위해 사용한 가뭄지수로 기상학적 가뭄지수는 표준강수지수(Standardized Precipitation Index, SPI)를 사용하였으며, 수문학적 가뭄지수로는 하천가뭄지수(Streamflow Drought Index, SDI)와 표준하천유량지수(Standardized Streamflow Index, SSI)를 이용하였다. 연구 대상지역은 농촌과 도시가 공존하는 청미천 유역을 선택하였으며, 평가기간은 1985년 1월부터 2017년 6월까지 32.5년을 평가하였다 하천유량은 SWAT 모형을 이용하여 산정하였다. 수집한 데이터를 이용하여 가뭄지수를 산정한 후에 시계열을 토대로 가뭄의 특성을 분석하였다. 그 결과 수문학적 가뭄은 기상학적 가뭄이 발생한 후에 발생하는 것을 확인할 수 있다. SDI가 SSI보다 SPI와의 첨두 발생시점, 가뭄 시작일의 차이와 평균 가뭄기간이 더 크게 나지만, 가뭄지수의 심도를 비교해보면 일반적으로 SSI가 SDI 보다 심각한 심도를 나타내고 있다. 그러므로 가뭄의 특성을 확인하기 위해서는 기상학적, 수문학적 가뭄지수 등 다양한 가뭄지수를 검토해야 한다.

• Journal of Astronomy and Space Sciences
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• 제33권2호
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• pp.137-146
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• 2016

The correlation between meteorological data collected at the optical wide-field patrol network (OWL-Net) Station No. 1 and the seeing of satellite optical observation data was analyzed. Meteorological data and satellite optical observation data from June 2014 to November 2015 were analyzed. The analyzed meteorological data were the outdoor air temperature, relative humidity, wind speed, and cloud index data, and the analyzed satellite optical observation data were the seeing full-width at half-maximum (FWHM) data. The annual meteorological pattern for Mongolia was analyzed by collecting meteorological data over four seasons, with data collection beginning after the installation and initial set-up of the OWL-Net Station No. 1 in Mongolia. A comparison of the meteorological data and the seeing of the satellite optical observation data showed that the seeing degrades as the wind strength increases and as the cloud cover decreases. This finding is explained by the bias effect, which is caused by the fact that the number of images taken on the less cloudy days was relatively small. The seeing FWHM showed no clear correlation with either temperature or relative humidity.