• 한국대기환경학회:학술대회논문집
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• 한국대기환경학회 2008년도 추계학술대회 논문집
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• pp.498-499
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• 2008

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.147-149
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• 2003

The wetness, a function of precipitation and temperature etc, and the warmth, a function of temperature, are the dominant factor for global vegetation distribution. This paper employs the normalized difference vegetation index (NDVI), warmth index (WAI), and wetness index (WEI), and focuses on an essential climate-vegetation relationship at global scale. The NDVI was acquired from ‘Twenty-year global 4-minute AVHRR NDVI dataset.’ The WEI is defined as the fraction of the precipitation to the potential evaporation. The WAI was calculated by accumulating the monthly mean temperature of the portion exceeded 5$^{\circ}C$ throughout the year. Meteorological data for the WEI and WAI calculation were obtained from the ISLSCP CD-ROM. All analyses were conducted for 1 ${\times}$ 1 degree grid box on the terrestrial area of the Earth, and on annual value basis averaged in 1987 and 1988. The result of analyses demonstrated that there are two regimes in their relations, that is, a regime in which NDVIs vary depending on the WEI, and a regime in which NDVIs vary depending on the WAI. These two regimes appeared to correspond to the wetness dominant and warmth dominant vegetation, respectively. The geographical distributions of two regimes were mapped. Most of the world vegetation is categorized into wetness dominant, while warmth dominant vegetation is seen in the high-latitude area mainly to the north of 60$^{\circ}$N in the Northern Hemisphere and high-altitude areas.

• Journal of the Korean Data and Information Science Society
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• 제23권6호
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• pp.1309-1317
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• 2012

Stochastic weather generators are commonly used to simulate time series of daily weather, especially precipitation amount. Recently, a generalized linear model (GLM) has been proposed as a convenient approach to fitting these weather generators. In this paper, a stochastic weather generator is considered to model the time series of daily precipitation at Seoul in South Korea. As a covariate, global temperature is introduced to relate long-term temporal scale predictor to short-term temporal predictands. One of the limitations of stochastic weather generators is a marked tendency to underestimate the observed interannual variance of monthly, seasonal, or annual total precipitation. To reduce this phenomenon, we incorporate time series of seasonal total precipitation in the GLM weather generator as covariates. It is veri ed that the addition of these covariates does not distort the performance of the weather generator in other respects.

• 국제학술발표논문집
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• The 6th International Conference on Construction Engineering and Project Management
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• pp.738-739
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• 2015

The main objective of this study, "Spatial Downscaling of Precipitation from GCMs for Assessing Climate Change over Han River and Imjin River Watersheds", is to carry out over Han River and Imjin River watersheds. To this end, a statistical regression method with MOS (Model Output Statistics) corrections at every downscaling step was developed and applied for downscaling the spatially-coarse Global Climate Model Projections (GCMPs) from CCSM3 and CSIRO with respect to precipitation into 0.1 degree (about 11 km) spatial grid over study regions. The spatially archived hydro-climate data sets such as Willmott, GsMap and APHRODITE datasets were used for MOS corrections by means of monthly climatology between observations and downscaled values. Precipitation values downscaled in this study were validated against ground observations and then future climate simulation results on precipitation were evaluated for the projections.

• 한국지구과학회지
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• 제39권4호
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• pp.327-341
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• 2018

Extreme temperatures and precipitations are expected to be more frequently occurring due to the ongoing global warming over the Korean Peninsula. However, few studies have analyzed the synoptic weather patterns associated with extreme events in a warming world. Here, the atmospheric patterns related to future extreme events are first analyzed using the HadGEM3-RA regional climate model. Simulations showed that the variability of temperature and precipitation will increase in the future (2051-2100) compared to the present (1981-2005), accompanying the more frequent occurrence of extreme events. Warm advection from East China and lower latitudes, a stagnant anticyclone, and local foehn wind are responsible for the extreme temperature (daily T>$38^{\circ}C$) episodes in Korea. The extreme precipitation cases (>$500mm\;day^{-1}$) were mainly caused by mid-latitude cyclones approaching the Korean Peninsula, along with the enhanced Changma front by supplying water vapor into the East China Sea. These future synoptic-scale features are similar to those of present extreme events. Therefore, our results suggest that, in order to accurately understand future extreme events, we should consider not only the effects of anthropogenic greenhouse gases or aerosol increases, but also small-scale topographic conditions and the internal variations of climate systems.

• The Korean Journal of Ecology
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• 제19권5호
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• pp.403-416
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• 1996

Global natural vegetation mapping (GNVM) system was developed for estimating potential forest area of the globe. With input of monthly mean temperature and monthly precipitation observed at weather stations, the system spherically interpolates them into 1°×1°grid points on a blobe, converts them into vegetation types, and produces a potential vegetation map and a potenital vegetation area. The spherical interpolation was based on negative exponential function fed from the constant radius stations with oval weighing method which is latitudinally elongated weighing in temperature and longitudinally elongated weighing in precipitation. The temperature values were corrected for altitude by applying a linear lapse-rate (0.65℃ / 100m) with reference to a built-in digital terrain map of the globe. The vegetation classification was based upon Koppen’s sKDICe. The potential forest area is estimated for 6.96 Gha (46.24％) of the global land area (15.05 Gha).

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2002년도 Proceedings of International Symposium on Remote Sensing
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• pp.685-689
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• 2002

This study focused the relationship between the Normalized Difference Vegetation Index (NDVI) and the evapotranspiration (ET) temporal changes. Especially, the interannual change of the NDVI and ET from 1982 to 2000 at regional to continental scales was highlighted mainly over Asia. Monthly global NDVI data were acquired from Pathfinder AVHRR Land (PAL) data (1$\times$1 degree resolution). The monthly ET was estimated from assimilated atmospheric data provided from National Centers for Environmental Prediction (NCEP) (2.5$\times$2.5 degree resolution), and gridded global precipitation data of CPC Merged Analysis of Precipitation (CMAP) (2.5$\times$2.5 degree resolution). Significant positive correlations were found between the NDVI and ET interannual changes in May and June over western Siberia. Moreover, it was revealed that the most of area in Asia has positive correlation coefficient in May and June. These results delineate that the vegetation activity significantly contributes to the ET interannual change over extensive areas.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2023년도 학술발표회
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• pp.174-174
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• 2023

The impact of global warming on the south Asian summer monsoon is of critical importance for the large population of this region. This study aims to investigate the future changes of the precipitation extremes during pre-monsoon and monsoon, across this region in a more organized regional structure. The study area is divided into six major divisions based on the Köppen-Geiger's climate structure and 10 sub-divisions considering the geographical locations. The future changes of extreme precipitation indices are analyzed for each zone separately using five indices from ETCCDI (Expert Team on Climate Change Detection and Indices); R10mm, Rx1day, Rx5day, R95pTOT and PRCPTOT. 10 global climate model (GCM) outputs from the latest CMIP6 under four combinations of SSP-RCP scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) are used. The GCMs are bias corrected using nonparametric quantile transformation based on the smoothing spline method. The future period is divided into near future (2031-2065) and far future (2066-2100) and then the changes are compared based on the historical period (1980-2014). The analysis is carried out separately for pre-monsoon (March, April, May) and monsoon (June, July, August, September). The methodology used to compare the changes is probability distribution functions (PDF). Kernel density estimation is used to plot the PDFs. For this study we did not use a multi-model ensemble output and the changes in each extreme precipitation index are analyzed GCM wise. From the results it can be observed that the performance of the GCMs vary depending on the sub-zone as well as on the precipitation index. Final conclusions are made by removing the poor performing GCMs and by analyzing the overall changes in the PDFs of the remaining GCMs.

• 대한토목학회논문집
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• 제28권2B호
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• pp.237-248
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• 2008

우리나라에서 발생하는 강수량의 특성은 지협적인 원인이기 보다는 해수면 온도와 같은 기상 현상에 많은 영향을 받고 있다. 따라서 본 연구에서는 우리나라의 기상청에서 관측하는 61개 강우관측소의 월강수량과 범지구적 해수면 온도와의 상관관계를 분석하였다. 우리나라 강우량과 범지구적 해수면 온도와의 상관성 분석을 위해 군집분석과 주성분 분석을 통해 월강우량의 주요 성분을 추출하였다. 추출된 월강우량의 주요 성분과 범지구적 해수면 온도와의 상관성 분석을 통해 우리나라의 월강수량은 태평양에서 관측되는 해수면 온도와 통계적으로 유의한 상관관계를 갖는 해수면 온도 구역을 확인할 수 있었다. 또한, 월강수량의 Wavelet Transform 분석을 통해 2년과 4년 사이의 주기에서 강한 주성분을 갖는 것으로 나타났으며, 월강수량의 저빈도 특성을 확인할 수 있었다. 월강수량의 저빈도 주기 성분과 해수면 온도와의 상관성 분석에서 큰 상관성을 갖는 것으로 나타났으며, 이를 통해 해수면 온도를 이용한 강우량의 예측 가능성을 제시하였다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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• pp.178-181
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• 2004

The Tropical Rainfall Measuring Mission (TRMM) is an US-Japan joint space mission to observe tropical and subtropical rainfall. This satellite is equipped with the world's first precipitation radar that operates at 13.8 GHz. We introduce the TRMM precipitation radar (PR) system, along with the PR data processing and analysis algorithms, and some observation results obtained by the TRMM PR. It is concluded that the TRMM PR can give quite useful rainfall data for the understanding of global climate changes, meteorology, climatology, atmospheric science, and also for the studies of satellite communication.