• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.618-620
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• 2003

Harmonics of sea surface temperature (SST) in the East Sea and their possible causes are examined by analyzing NOAA/AVHRR data, SSM/I wind speeds, NSCAT wind vectors, and NCEP heat flux data. Detailed spatial structures of amplitudes and phases of the seasonal cycles and their contributions to the total variance of SST have quantitatively. The Subpolar front serves as a boundary between regions of high annual amplitudes (${\geq}$10$^{\circ}$C) in the cold continental region and low amplitudes (${\leq}$10$^{\circ}$C) in the Tsushima Warm Current region. The low phase center of annual cycle is located over a seamount at 132.2$^{\circ}$E, 41.7$^{\circ}$N south of Vladivostok. Semi-annual amplitudes are significantly large leaching over 20% of the annual amplitudes in the Tatarskiy Strait and along the continental shelf off Russian coast in fall and spring, but its forcings are substantially annual. We have shown that fall cooling is attributed by direct and local wind forcing, while spring cooling is remotely forced by cold waters from sea ices in the Tatarskiy Strait.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
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• pp.306-309
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• 2007

Japanese Ocean Flux Data Sets with Use of Remote Sensing Observations (J-OFURO) includes global ocean surface heat flux data derived from satellite data and are used in many studies related to air-sea interaction. Recently latent heat flux data version 2 was constructed in J-OFURO. In version 2 many points are improved compared with version 1. A bulk algorithm used for estimation of latent heat flux is changed from Kondo (1975) to COASRE 3.0(Fairall et al., 2005). In version 1 we used NCEP reanalysis data (Reynolds and Smith, 1994) as SST data. However, the temporal resolution of the data is weekly and considerably low. Recently there are many kinds of global SST data because we can obtain SST data using a microwave radiometer sensor such as TRMM/MI and Aqua/AMSR-E. Therefore, we compared many SST products and determined to use Merged satellite and in situ data Global Daily (MGD) SST provided by Japan Meteorological Agency. Since we use wind speed and specific humidity data derived from one DMSP/SSMI sensor in J-OFURO, we obtain two data at most one day. Therefore, there may be large sampling errors for the daily-mean value. In order to escape this problem, multi-satellite data are used in version 2. As a result we could improve temporal resolution from 3-days mean value in version 1 to daily-mean value in version 2. Also we used an Optimum Interpolation method to estimate wind speed and specific humidity data instead of a simple mean method. Finally the data period is extended to 1989-2004. In this presentation we will introduce latent heat flux data version 2 in J-OFURO and comparison results with other surface latent heat flux data such as GSSTF2 and HOAPS etc. Moreover, we will present validation results by using buoy data.

• 대기
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• 제28권1호
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• pp.15-24
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• 2018

Sea ice plays an important role in modulating surface conditions at high and mid-latitudes. It reacts rapidly to climate change, therefore, it is a good indicator for capturing these changes from the Arctic climate. While many models have been used to study the predictability of climate variables, their performance in predicting sea ice was not well assessed. This study examines the predictability of the Arctic sea ice extent from ensemble prediction systems. The analysis is focused on verification of predictability in each model compared to the observation and prediction in particular, on lead time in Sub-seasonal to Seasonal (S2S) scales. The S2S database now provides quasi-real time ensemble forecasts and hindcasts up to about 60 days from 11 centers: BoM, CMA, ECCC, ECMWF, HMCR, ISAC-CNR, JMA, KMA, Meteo France, NCEP and UKMO. For multi model comparison, only models coupled with sea ice model were selected. Predictability is quantified by the climatology, bias, trends and correlation skill score computed from hindcasts over the period 1999 to 2009. Most of models are able to reproduce characteristics of the sea ice, but they have bias with seasonal dependence and lead time. All models show decreasing sea ice extent trends with a maximum magnitude in warm season. The Arctic sea ice extent can be skillfully predicted up 6 weeks ahead in S2S scales. But trend-independent skill is small and statistically significant for lead time over 6 weeks only in summer.

• 대기
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• 제24권2호
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• pp.245-251
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• 2014

Statistical trajectory analysis has been widely used to identify potential source regions for chemically and radiatively important chemical species in the atmosphere. The most widely used method is a statistical source-receptor model developed by Stohl (1996), of which the underlying principle is that elevated concentrations at an observation site are proportionally related to both the average concentrations on a specific grid cell where the observed air mass has been passing over and the residence time staying over that grid cell. Thus, the method can compute a residence-time-weighted mean concentration for each grid cell by superimposing the back trajectory domain on the grid matrix. The concentration on a grid cell could be used as a proxy for potential source strength of corresponding species. This technical note describes the statistical trajectory approach and introduces its application to estimate potential source regions of $CO_2$ enhancements observed at Korean Global Atmosphere Watch Observatory in Anmyeon-do. Back trajectories are calculated using HYSPLIT 4 model based on wind fields provided by NCEP GDAS. The identified $CO_2$ potential source regions responsible for the pollution events observed at Anmyeon-do in 2010 were mainly Beijing area and the Northern China where Haerbin, Shenyang and Changchun mega cities are located. This is consistent with bottom-up emission information. In spite of inherent uncertainties of this method in estimating sharp spatial gradients within the vicinity of the emission hot spots, this study suggests that the statistical trajectory analysis can be a useful tool for identifying anthropogenic potential source regions for major GHGs.

• 한국직업건강간호학회지
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• 제18권1호
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• pp.44-54
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• 2009

Purpose: The aim of this study was to examine the effects of obesity on the physiological levels of adiponectin, leptin and components of metabolic syndrome (MS) in male workers, aged 30-40 years. Methods: Body mass index (BMI) was measured with Anthropometric equipment. Blood pressure and serum parameters were measured with an automatic digital sphygmomanometer and autochemical analyzer, respectively. Adiponectin and leptin were analysed by ELISA kits and MS was defined based on the NCEP-ATP III. Results: Body fat mass of waist and hip, systolic and diastolic blood pressure were significantly higher, as expected, in the BMI>25kg/$m^2$ in comparison with the $BMI{\leq}25kg/m^2$. While fasting glucose, insulin, HOMA-IR and leptin in the BMI>25kg/$m^2$ were also significantly higher compared with $BMI{\leq}25kg/m^2$, HDL-cholesterol and adiponectin were significantly higher in $BMI{\leq}25kg/m^2$. On multiple logistic regression analysis for the components of MS, exercise, adiponectin and leptin were an only independent factor for MS in non-obese male workers($BMI{\leq}25kg/m^2$) after adjustment for age, cigarette smoking and drinking habits. Conclusion: These results suggested that the obesity in men was associated with physiological levels of adiponectin and leptin contributing to feedback control of MS and that dysfunction and/or declination in feedback control system associated with changes in physiological levels of neurptrophics: adiponectin and leptin might ultimately induce MS.

• 대한한의학회지
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• 제39권4호
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• pp.51-61
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• 2018

Introduction: This study evaluated whether body mass index (BMI) and waist circumference (WC) cut-offs for predicting metabolic syndrome (MetS) were different according to Sasang constitutional type. Methods: Data were obtained from 3,117 South Koreans (20-90 years old), and MetS was defined according to the revised NCEP-ATPIII criteria. Age-adjusted BMI and WC cut-offs were calculated according to Sasang constitutional type (Soyangin [SY], Taeeumin [TE], and Soeumin [SE]), sex, and age (men: ${\geq}40$ vs. <40 years, women: ${\geq}50$ vs. <50 years). Results: The prevalences of MetS were 29.9% (<40-year-old men), 35.1% (${\geq}40$-year-old men), 14.8% (<50-year-old women), and 47.7% (${\geq}50$-year-old women). The BMI ($kg/m^2$) and WC (cm) cut-offs for <40-year-old men were 25.9 and 89.9 (SY), 25.5 and 90.5 (TE), and 21.8 and 86.2 (SE). The cut-offs for ${\geq}40$-year-old men were 23.1 and 88.9 (SY), 25.0 and 89.9 (TE), and 22.2 and 87.5 (SE). The BMI and WC cut-offs for <50-year-old women were 22.5 and 81.2 (SY), 25.1 and 83.0 (TE), and 21.5 and 79.8 (SE). The cut-offs for ${\geq}50$-year-old women were 22.2 and 80.5 (SY), and 25.2 and 89.1 (TE), and 21.9 and 80.3 (SE). Conclusions: The BMI and WC cut-offs for identifying MetS varied according to Sasang constitution type.

• 대한원격탐사학회지
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• 제37권5_2호
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• pp.1295-1305
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• 2021

연안 및 대양의 효과적인 모니터링을 위해 여러 연구 분야에서 고품질의 위성 기반 해색 산출물들이 요구 있으며 이를 위해서는 정확한 대기 효과의 보정이 필수적이다. 현재 Geostationary Ocean ColorImage (GOCI)-II 지상시스템에서는 수증기 및 오존 등에 의한 가스 흡광 보정을 수행하기 위해 European Centre for Medium-Range Weather Forecasts (ECMWF) 또는 National Centers for Environmental Prediction (NCEP) 기상장 자료를 사용하고 있다. 이 과정에서 기상장 자료의 낮은 시공간해상도로 인해 오차가 발생할 수 있다. 따라서 본 연구에서는 복사 전달 모델 모의를 통해 개발된 GOCI-II의 수증기 흡광 보정 모델 및 GeoKompsat (GK)-2A/Advanced Meteorological Imager (AMI)의 가강수량 자료를 이용하여 수증기 흡광 효과를 보정하고 이에 따른 영향력을 분석하였다. 개발된 수증기 흡광 보정 모델 적용 유무에 따른 오차는 수증기의 영향이 적은 620 nm와 680 nm의 대기 상한 반사도에서 최대 1.3%와 0.27%로 적은 오차를 보였다. 그러나 수증기 흡광의 경향이 큰 709 nm 채널의 경우 태양 천정각 및 가강수량에 따라 6~15%의 큰 오차를 나타냈다. 레일리 보정 반사도에서는 대기 상한 반사도에서 발생한 오차가 크게 증폭되어 태양 천정각에 따라 GOCI-II의 각 밴드(620~865 nm) 별로 1.46~4.98, 7.53~19.53, 0.25~0.64, 14.74~40.5, 8.2~18.56, 5.7~11.9%의 큰 오차를 보이고 있다. 이는 수증기 흡광 보정이 해색 산출물의 정확도와 안정성에 큰 영향을 미칠 수 있다는 것을 의미하며, 향후 시공간 해상도가 높은 GK-2A/AMI와의 융합을 통해 GOCI-II 해색 산출물의 정확도 향상이 가능함을 시사한다.

• 대한원격탐사학회지
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• 제38권4호
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• pp.343-353
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• 2022

An attempt to derive the surface temperature from the Korea Multi-purpose Satellite (KOMPSAT)-3A mid-wave infrared (MWIR) data acquired over the southern California on Nov. 14, 2015 has been made using the MODerate resolution atmospheric TRANsmission (MODTRAN) radiative transfer model. Since after the successful launch on March 25, 2015, the KOMPSAT-3A spacecraft and its two payload instruments - the high-resolution multispectral optical sensor and the scanner infrared imaging system (SIIS) - continue to operate properly. SIIS uses the MWIR spectral band of 3.3-5.2 ㎛ for data acquisition. As input data for the realistic simulation of the KOMPSAT-3A SIIS imaging conditions in the MODTRAN model, we used the National Centers for Environmental Prediction (NCEP) atmospheric profiles, the KOMPSAT-3Asensor response function, the solar and line-of-sight geometry, and the University of Wisconsin emissivity database. The land cover type of the study area includes water,sand, and agricultural (vegetated) land located in the southern California. Results of surface temperature showed the reasonable geographical pattern over water, sand, and agricultural land. It is however worthwhile to note that the surface temperature pattern does not resemble the top-of-atmosphere (TOA) radiance counterpart. This is because MWIR TOA radiances consist of both shortwave (0.2-5 ㎛) and longwave (5-50 ㎛) components and the surface temperature depends solely upon the surface emitted radiance of longwave components. We found in our case that the shortwave surface reflection primarily causes the difference of geographical pattern between surface temperature and TOA radiance. Validation of the surface temperature for this study is practically difficult to perform due to the lack of ground truth data. We therefore made simple comparisons with two datasets over Salton Sea: National Aeronautics and Space Administration (NASA) Jet Propulsion Laboratory (JPL) field data and Salton Sea data. The current estimate differs with these datasets by 2.2 K and 1.4 K, respectively, though it seems not possible to quantify factors causing such differences.

• 대한원격탐사학회지
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• 제36권5_3호
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• pp.1037-1051
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• 2020

최근 기후변화로 인해 강도가 높은 태풍의 빈도가 높아짐에 따라 태풍 예측의 중요성이 강조되고 있는 데, 태풍경로예측에 비해 태풍강도예측에 대한 연구는 미비한 상황이다. 이에 본 연구에서는 딥러닝 모델인 Multi-task learning (MTL) 기법을 활용하여 정지궤도기상위성을 활용한 관측자료와 수치예보모델을 융합한 실시간 추정 및 6시간, 12시간 후의 태풍강도예측 모델을 제안하고자 한다. 본 연구에서는 2011년에서 2016년까지 북서태평양에서 발생한 총 142개의 태풍을 대상으로 강도 예측 연구를 시행하였다. 한국 최초의 기상위성인 Communication, Ocean and Meteorological Satellite (COMS) Meteorological Imager (MI)를 활용하여 태풍의 관측영상을 추출하였고, National Center of Environmental Prediction (NCEP)에서 제공하는 Climate Forecast System version 2 (CFSv2)를 활용하여 6시간, 12시간 후의 태풍 주변 대기 및 해양 예측변수를 추출하였다. 본 연구에서는 각 입력자료의 활용성을 정량화 하기 위하여, 위성 기반 태풍관측영상만을 활용한 MTL 모델(Scheme 1)과 수치예보모델을 융합적으로 활용한 MTL 모델(Scheme 2)을 구축하고, 각 모델의 훈련 및 검증 성능을 정량적으로 비교하였다. 실시간 강도 추정의 결과 scheme 1과 scheme 2에서 비슷한 성능을 보이는 반면, 6시간, 12시간 후 태풍강도예측의 경우 scheme 2에서 각각 13%, 16% 개선된 결과를 보였다. 태풍 단계별 예측성능에 대한 분석을 시행한 결과, 저강도 태풍일수록 낮은 평균제곱근오차를 보인 반면, 대부분의 강도 단계에서 평균제곱근편차비는 30% 미만의 값을 보이며 유의미한 검증 결과를 보였다. 이에 본 연구에서 제시한 두가지 모델을 기반으로 2014년 발생한 태풍 HALONG의 시계열검증을 시행하였다. 그 결과, scheme 1의 경우 태풍 초기발달단계에서 태풍의 강도를 약 20 kts가량 과대 추정하는 경향을 보이는데, 환경예측자료를 융합한 scheme 2에서는 오차가 약 5 kts가량으로 과대 추정 경향이 줄어들었다. 본 연구에서 제시하는 현재, 6시간, 12시간 후 강도를 동시에 추출하는 MTL 모델은 Single-tasking model 대비 약 300%의 시간 효율을 보이며, 향후 신속한 태풍 예보 정보 추출에 큰 기여를 할 수 있을 것으로 기대된다.

• 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.