• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1389-1399
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• 2023

KOMPSAT-3/3A (K3/K3A) absolute radiometric calibration study was conducted based on a Field Line of sight Automated Radiance Exposure (FLARE) system. FLARE is a system, which has been developed by Labsphere, Inc. adopted a SPecular Array Radiometric Calibration (SPARC) concept. The FLARE utilizes a specular mirror target resulting in a simplified radiometric calibration method by minimizing other sources of diffusive radiative energies. Several targeted measurements of K3/3A satellites over a FLARE site were acquired during a field campaign period (July 5-15, 2021). Due to bad weather situations, only two observations of K3 were identified as effective samples and they were employed for the study. Absolute radiometric calibration coefficients were computed using combined information from the FLARE and K3 satellite measurements. Comparison between the two FLARE measurements (taken on 7/7 and 7/13) showed very consistent results (less than 1% difference between them except the NIR channel). When additional data sets of K3/K3A taken on Aug 2021 were also analyzed and compared with gain coefficients from the metadata which are used by current K3/K3A, It showed a large discrepancy. It is assumed that more studies are needed to verify usefulness of the FLARE system for the K3/3A absolute radiometric calibration.

• Journal of the Korean association of regional geographers
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• v.19 no.3
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• pp.384-400
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• 2013

In this study, spatio-temporal patterns of extreme precipitation events caused by typhoons are examined based on observational daily precipitation data at approximately 340 weather stations of Korea Meterological Administration's ASOS (Automated Synoptic Observation System) and AWS (Automatic Weather System) networks for the recent 10 year period (2002~2011). Generally, extreme precipitation events by typhoons exceeding 80mm of daily precipitation commonly appear in Jeju Island, Gyeongsangnam-do, and the eastern coastal regions of the Korean Peninsula. However, the frequency, intensity and spatial extent of typhoon-driven extreme precipitation events can be modified depending on the topography of major mountain ridges as well as the pathway of and proximity to typhoons accompanying the anti-clockwise circulation of low-level moisture with hundreds of kilometers of radius. Yellow Sea-passing type of typhoons in July cause more frequent extreme precipitation events in the northern region of Gyeonggi-do, while East Sea-passing type or southern-region-landfall type of typhoons in August-early September do in the interior regions of Gyeongsangnam-do. These results suggest that when local governments develop optimal mitigation strategies against potential damages by typhoons, the pathway of and proximity to typhoons are key factors.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.1
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• pp.434-439
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• 2019

Recently, interest in urban temperature change and ground surface temperature change has been increasing due to weather phenomenon due to global warming, heat island phenomenon caused by urbanization in urban areas. In Korea, weather data such as temperature and precipitation have been collected since 1904. In recent years, there are 96 ASOS stations and 494 AWS weather observation stations. However, in the case of terrestrial networks, terrestrial meteorological data except measurement points are predicted through interpolation because they provide point data for each installation point. In this study, to improve the resolution of ground surface temperature measurement, the surface temperature using satellite image was calculated and its applicability was analyzed. For this purpose, the satellite images of Landsat 8 OLI TIRS were obtained for Seoul Metropolitan City by seasons and transformed to surface temperature by applying NASA equation to the thermal bands. The ground measurement data was based on the temperature data measured by AWS. Since the AWS temperature data is station based point data, interpolation is performed by Kriging interpolation method for comparison with Landsat image. As a result of comparing the satellite image base surface temperature with the AWS temperature data, the temperature difference according to the season was calculated as fall, winter, summer, based on the RMSE value, Spring, in order of applicability of Landsat satellite image. The use of that attribute and AWS support starts at $2.11^{\circ}C$ and RMSE ${\pm}3.84^{\circ}C$, which reflects information from the extended NASA.

• Korean Journal of Agricultural and Forest Meteorology
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• v.7 no.3
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• pp.185-191
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• 2005

An accurate prediction of dormancy release and bud burst in temperate zone fruit trees is indispensable for farmers to plan heating time under partially controlled environments as well as to reduce the risk of frost damage in open fields. A thermal time-based two-step phenological model that originated in Italy was applied to two important grapevine cultivars in Korea for predicting bud-burst dates. The model consists of two sequential periods: a rest period described by chilling requirement and a forcing period described by heating requirement. It requires daily maximum and minimum temperature as an input and calculates daily chill units (chill days in negative sign) until a pre-determined chilling requirement for rest release is met. After the projected rest release date, it adds daily heat units (anti-chill days in positive sign) to the chilling requirement. The date when the sum reaches zero isregarded as the bud-burst in the model. Controlled environment experiments using field sampled twigs of 'Campbell Early' and 'Kyoho' cultivars were carried out in the vineyard at the National Horticultural Research Institute (NHRI) in Suwon during 2004-2005 to derive the model parameters: threshold temperature for chilling and chilling requirement for breaking dormancy. The model adjusted with the selected parameters was applied to the 1994-2004 daily temperature data obtained from the automated weather station in the NHRI vineyard to estimate bud burst dates of two cultivars and the results were compared with the observed data. The model showed a consistently good performance in predicting the bud burst of 'Campbell Early' and 'Kyoho' cultivars with 2.6 and 2.5 days of root mean squared error, respectively.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.3
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• pp.29-39
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• 2017

In this study, the GPM (Global Precipitation Mission) IMERG (Integrated Multi-satellitE retrievals for GPM) rainfall data was verified and evaluated using ground AWS (Automated Weather Station) and radar in order to investigate the availability of GPM IMERG rainfall data. The SPI (Standardized Precipitation Index) was calculated based on the GPM IMERG data and also compared with the results obtained from the ground observation data for the Hoengseong Dam and Yongdam Dam areas. For the radar data, 1.5 km CAPPI rainfall data with a resolution of 10 km and 30 minutes was generated by applying the Z-R relationship ($Z=200R^{1.6}$) and used for accuracy verification. In order to calculate the SPI, PERSIANN_CDR and TRMM 3B42 were used for the period prior to the GPM IMERG data availability range. As a result of latency verification, it was confirmed that the performance is relatively higher than that of the early run mode in the late run mode. The GPM IMERG rainfall data has a high accuracy for 20 mm/h or more rainfall as a result of the comparison with the ground rainfall data. The analysis of the time scale of the SPI based on GPM IMERG and changes in normal annual precipitation adequately showed the effect of short term rainfall cases on local drought relief. In addition, the correlation coefficient and the determination coefficient were 0.83, 0.914, 0.689 and 0.835, respectively, between the SPI based GPM IMERG and the ground observation data. Therefore, it can be used as a predictive factor through the time series prediction model. We confirmed the hydrological utilization and the possibility of real time drought monitoring using SPI based on GPM IMERG rainfall, even though results presented in this study were limited to some rainfall cases.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.639-639
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• 2012

물 수요 및 공급 체계를 바탕으로 수급 상황에 대한 판단을 위해 일반적으로 물수지 분석을 이용하고 있다. 물 수급 체계를 기반으로 하는 물수지 분석은 분석 대상유역의 물 수요를 고려하여 공급 가능량을 판단한 후 두 가지 인자 간 상호 비교를 통해 물 부족 여부를 판단하는 과정이라 할 수 있으며, 가장 대표적인 사례는 수자원장기종합계획에서의 물 수급 전망 분석 과정이라 할 수 있다. 수자원장기종합계획의 물 수급 전망에서는 미래 우리나라에서 예상되는 물 수요를 예측하고 수문조건에 따른 공급 상황과의 비교 검토를 통해 시공간적 물 부족 현황을 제시하고 있다. 수자원장기종합계획에서는 공급량 조건을 검토하기 위한 방법으로 기상청, 국토해양부, 한국수자원공사 등 다양한 기관에서 관측된 강우자료를 강우-유출모형에 적용한 후 산정된 자연유출량을 기반으로 물수지 분석을 수행하고 있다. 수자원장기종합계획과 같이 미래 우리나라의 물 수급 상황을 분석하고 이를 바탕으로 제시된 시공간적 물 부족 정보의 신뢰성을 높이기 위해서는 기본적으로 지역 또는 유역별 강우 발생 특성에 대한 정확한 고려가 기반이 되어야 한다. 그러나 현재 수자원장기종합계획 수립 과정에서 이용하고 있는 강우 관측지점의 공간적 분포를 살펴보면, 도서 및 해안지역의 경우 관측소의 밀도가 상대적으로 매우 빈약한 한계를 포함하고 있으며, 대부분 내륙 지역에 관측소가 집중된 현상을 보이고 있다. 이와 같은 상황에서 강우 관측자료를 이용한 분석을 수행할 경우 도서 및 해안지역에 대한 강우 발생 특성의 정확한 반영이 어려울 수 있으며, 이는 물 부족 분석 결과의 정확도 측면에서도 문제점으로 지적될 수 있다. 이러한 한계를 극복하기 위한 방안으로 기상청에서 운영 중인 자동기상관측지점(Automated Weather Station, AWS)의 관측자료를 이용하는 방안을 검토해볼 수 있다. AWS 지점은 내륙 및 도서 해안지역에 관계없이 고른 관측소 분포를 보이고 있으므로 이를 고려할 경우 기존 관측지점에서 한계로 지적된 부분을 충분히 극복할 수 있을 것으로 판단된다. 따라서 본 연구에서는 기상청에서 생산되고 있는 AWS 관측자료를 수집한 후 이를 수자원장기종합계획의 물수지 분석과 동일한 분석 과정에 적용하였으며, 그 결과에 대한 검토를 통해 국가 수자원계획의 신뢰도를 높일 수 있는 방안을 제시하였다.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.9 no.10
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• pp.923-934
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• 2019

This study investigates correlations between the impacts of urban and building form and microclimate on the energy consumption of buildings. It applies microscopic elements such as urban form, building form and character, and microclimate as factors in the energy consumption of buildings. To this end, the energy consumption of selected buildings in Seoul in August of 2017 was analyzed. Based on microscopic elements within a radius of 500 meters of 23 Automated Weather Station (AWS) measurement points selected by the Meteorological Office of the City of Seoul. With the exception of a few elements, the urban form and character elements demonstrate a significant relation to the energy consumption of buildings. It is also found that microclimate elements such as wind speed and humidity are pertinent to the energy consumption of buildings. It is helpful in that it suggests results for establishing more effective policies and strategies for enhancing the sustainability and resilience of cities.

• Journal of Korea Water Resources Association
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• v.57 no.5
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• pp.333-346
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• 2024

High-resolution medium-range streamflow prediction is crucial for sustainable water quality and aquatic ecosystem management. For reliable medium-range streamflow predictions, it is necessary to understand the characteristics of forcings and to effectively utilize weather forecast data with low spatio-temporal resolutions. In this study, we presented a comparative analysis of medium-range streamflow predictions using the distributed hydrological model, WRF-Hydro, and the numerical weather forecast Global Data Assimilation and Prediction System (GDAPS) in the Geumho River basin, Korea. Multiple forcings, ground observations (AWS&ASOS), numerical weather forecast (GDAPS), and Global Land Data Assimilation System (GLDAS), were ingested to investigate the performance of streamflow predictions with highresolution WRF-Hydro configuration. In terms of the mean areal accumulated rainfall, GDAPS was overestimated by 36% to 234%, and GLDAS reanalysis data were overestimated by 80% to 153% compared to AWS&ASOS. The performance of streamflow predictions using AWS&ASOS resulted in KGE and NSE values of 0.6 or higher at the Kangchang station. Meanwhile, GDAPS-based streamflow predictions showed high variability, with KGE values ranging from 0.871 to -0.131 depending on the rainfall events. Although the peak flow error of GDAPS was larger or similar to that of GLDAS, the peak flow timing error of GDAPS was smaller than that of GLDAS. The average timing errors of AWS&ASOS, GDAPS, and GLDAS were 3.7 hours, 8.4 hours, and 70.1 hours, respectively. Medium-range streamflow predictions using GDAPS and high-resolution WRF-Hydro may provide useful information for water resources management especially in terms of occurrence and timing of peak flow albeit high uncertainty in flood magnitude.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.3
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• pp.136-149
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• 2011

The aim of this study is to develop future climate scenario by downscaling the regional climate model (RCM) from global climate model (GCM) based on IPCC A1B scenario. To this end, the study first resampled the KMA-RCM(Korea meteorological administration-regional climate model) from spatial resolution of 27km to 1km. Second, observed climatic data of temperature and rainfall through 1971-2000 were processed to reflect the temperature lapse rate with respect to the altitude of each meteorological observation station. To optimize the downscaled results, Co-kriging was used to calculate temperature lapse-rate; and IDW was used to calculate rainfall lapse rate. Fourth, to verify results of the study we performed correlation analysis between future climate change projection data and observation data through the years 2001-2010. In this study the past climate data (1971-2000), future climate change scenarios(A1B), KMA-RCM(Korea meteorological administration-regional climate model) results and the 1km DEM were used. The research area is entire South Korea and the study period is from 1971 to 2100. Monthly mean temperatures and rainfall with spatial resolution of 1km * 1km were produced as a result of research. Annual average temperature and precipitation had increased by $1.39^{\circ}C$ and 271.23mm during 1971 to 2100. The development of downscaling method using GIS and verification with observed data could reduce the uncertainty of future climate change projection.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.4
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• pp.1-18
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• 2022

Currently, the Korea Meteorological Administration evaluates the meteorological drought by region using SPI6(standardized precipitation index 6), which is a 6-month cumulative precipitation standard. However, SPI is an index calculated only in consideration of precipitation at 69 weather stations, and the drought phenomenon that appears for complex reasons cannot be accurately determined. Therefore, the purpose of this study is to calculate and compare SPI considering only precipitation and SDCI (Scaled Drought Condition Index) considering precipitation, vegetation index, and temperature in Gyeonggi. In addition, the advantages and disadvantages of the station data-based drought index and the satellite image-based drought index were identified by using results calculated through the comparison of SPI and SDCI. MODIS(MODerate resolution Imaging Spectroradiometer) satellite image data, ASOS(Automated Synoptic Observing System) data, and kriging were used to calculate SDCI. For the duration of precipitation, SDCI1, SDCI3, and SDCI6 were calculated by applying 1-month, 3-month, and 6-month respectively to the 8 points in 2014. As a result of calculating the SDCI, unlike the SPI, drought patterns began to appear about 2-month ago, and drought by city and county in Gyeonggi was well revealed. Through this, it was found that the combination of satellite image data and station data increased efficiency in the pattern of drought index change, and increased the possibility of drought prediction in wet areas along with existing dry areas.