• 대기
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• 제30권4호
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• pp.405-420
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• 2020

In this study, we investigate the predictability of intraseasonal monthly temperature and precipitation variations using hindcast datasets from eight global circulation models participating in the operational multi-model ensemble (MME) seasonal prediction system of the Asia-Pacific Economic Cooperation Climate Center for the 1983~2010 period. These intraseasonal monthly variations are defined by categorical deterministic analysis. The monthly temperature and precipitation are categorized into above normal (AN), near normal (NN), and below normal (BN) based on the σ-value ± 0.43 after standardization. The nine patterns of intraseasonal monthly variation are defined by considering the changing pattern of the monthly categories for the three consecutive months. A deterministic and a probabilistic analysis are used to define intraseasonal monthly variation for the multi-model consisting of numerous ensemble members. The results show that a pattern (pattern 7), which has the same monthly categories in three consecutive months, is the most frequently occurring pattern in observation regardless of the seasons and variables. Meanwhile, the patterns (e.g., patterns 8 and 9) that have consistently increasing or decreasing trends in three consecutive months, such as BN-NN-AN or AN-NN-BN, occur rarely in observation. The MME and eight individual models generally capture pattern 7 well but rarely capture patterns 8 and 9.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2022년도 학술발표회
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• pp.329-329
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• 2022

Accurate characterization of terrestrial precipitation variation from high spatial resolution satellite sensors is beneficial for urban hydrology and microscale agriculture modeling, as well as natural disasters (e.g., urban flooding) early warning. However, the widely-used top-down approach for precipitation retrieval from microwave satellites is limited in several hydrological and agricultural applications due to their coarse spatial resolution. In this research, we aim to apply a novel bottom-up method, the parameterized SM2RAIN, where precipitation can be estimated from soil moisture signals based on an inversion of water balance model, to generate high spatial resolution terrestrial precipitation estimates at 0.01º grid (roughly 1-km) from the C-band SAR Sentinel-1. This product was then tested against a common reanalysis-based precipitation data and a domestic rain gauge network from the Korean Meteorological Administration (KMA) over central South Korea, since a clear difference between climatic types (coasts and mainlands) and land covers (croplands and mixed forests) was reported in this area. The results showed that seasonal precipitation variability strongly affected the SM2RAIN performances, and the product derived from separated parameters (rainy and non-rainy seasons) outperformed that estimated considering the entire year. In addition, the product retrieved over the mainland mixed forest region showed slightly superior performance compared to that over the coastal cropland region, suggesting that the 6-day time resolution of S1 data is suitable for capturing the stable precipitation pattern in mainland mixed forests rather than the highly variable precipitation pattern in coastal croplands. Future studies suggest comparing this product to the traditional top-down products, as well as evaluating their integration for enhancing high spatial resolution precipitation over entire South Korea.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2009년도 학술발표회 초록집
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• pp.1260-1264
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• 2009

Precipitation time series is a mixture of complicate fluctuation and changes. The monthly precipitation data of 61 stations during 36 years (1973-2008) in Korea are comprehensively analyzed using the EOFs technique and CSEOFs technique respectively. The main motivation for employing this technique in the present study is to investigate the physical processes associated with the evolution of the precipitation from observation data. The twenty-five leading EOF modes account for 98.05% of the total monthly variance, and the first two modes account for 83.68% of total variation. The first mode exhibits traditional spatial pattern with annual cycle of corresponding PC time series and second mode shows strong North South gradient. In CSEOF analysis, the twenty-five leading CSEOF modes account for 98.58% of the total monthly variance, and the first two modes account for 78.69% of total variation, these first two patterns' spatial distribution show monthly spatial variation. The corresponding mode's PC time series reveals the annual cycle on a monthly time scale and long-term fluctuation and first mode's PC time series shows increasing linear trend which represents that spatial and temporal variability of first mode pattern has strengthened. Compared with the EOFs analysis, the CSEOFs analysis preferably exhibits the spatial distribution and temporal evolution characteristics and variability of Korean historical precipitation.

• 대기
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• 제18권4호
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• pp.397-416
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• 2008

This study investigates a long-term variation of the annual extreme value for the instantaneous wind speed and the daily precipitation during 56 years (1951-2006) in Korea. Results show that there is a uptrend for both wind and precipitation extreme records, although regional trends are different from overall pattern in some places, particularly for wind speed. The estimated linear trends are 230 mm/56 yr in the daily precipitation and $15ms^{-1}$/56 yr in the maximum instantaneous wind speed. For precipitation, other indexes such as total annual precipitation, the number of extreme precipitation event, and precipitation intensity have dramatically increased as well, while there has been a clear downtrend for the number of strong wind events (> $14ms^{-1}$). It is found that the minimum surface pressure recorded during typhoon attacks in Korea tends to be decreasing, about 10 hPa/56 yr. This partly explains why the extreme values in the precipitation are increasing in Korea.

• 대한지리학회지
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• 제33권
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• pp.26-36
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• 1986

이 글에서는 다음의 내용을 다루었다. 1. 자료와 분석방법 2. 강수량의 연변화유형과 강수지역, (1) 연강수량의 분포특성, (2) 강수량의 연변화유형과 공간분포, (3) 강수지역

• 대한토목학회논문집
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• 제31권1B호
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• pp.13-20
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• 2011

강수량은 시공간적으로 변화하는 수문변량으로서 강수량의 시간적인 특성 또한 강수량의 특성을 정의하는데 매우 중요한 요소이다. 본 연구에서는 극치강수량의 지역빈도해석을 위한 범주화 과정에서 기존의 강수량과 관측소 위치좌표만을 이용한 범주화를 통해 해결할 수 없는 강우 발생의 계절적 변화와 집중에 대한 고려를 반영하기 위하여, 기존의 양적 범주화 과정에 시간적인 영향을 고려할 수 있는 요소로서 극치강수량 발생 시기 통계치를 활용할 수 있는 범주화 과정을 제시하였다. 본 연구에서는 극치강수량의 발생 시기에 대한 정량적인 분석이 가능한 순환통계기법을 이용하여 관측 지점별 시간 통계량을 산정하고, 이를 극치강수량과 결합하여 시 공간적인 특성자료를 생성한 후 수정 K-means 방법을 이용하여 군집화 해석을 수행하였으며, 전국을 다섯 개의 군집으로 분류하였다. 기존의 양적 범주화 결과와의 비교를 통해 발생 시간 통계치를 결합한 범주화 결과가 지형 및 권역을 반영하는 결과를 보임을 확인하였다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2010년도 학술발표회
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• pp.273-277
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• 2010

This research was performed to examine changes in the timing of the growth of crops along with changes in temperatures due tochanges and to analyze the change of water-supply-reliability by adding an analysis of the change of agricultural water supply patterns in the basin area of Miryang dam in Korea. Had-CM3 model from U.K. was the tool adopted for the GCM model, a stochastic, daily-meteorology-generation-model called LARS-WG was alsoused for downscaling and for the climate change scenario (A1B) which represents Korea's circumstances best. First of all, to calculate changes in the timing of the growth of crops during this period, the theory of GDD was applied. Except for the period of transplanting and irrigation, there was no choice but to find the proper accumulated temperature by comparing actual temperature data and the supply pattern of agricultural use due to limited temperature data. As a result, proper temperatures were found for each period. $400^{\circ}C$ for the preparation period of a nursery bed, $704^{\circ}C$ for a nursery bed's period, $1,295^{\circ}C$ for the rice-transplanting period, $1,744^{\circ}C$ for starting irrigation, and $3,972^{\circ}C$ for finishing irrigation. To analyze future agricultural supply patter changes, the A1B scenario of Had-CM3 model was adopted, and then Downscaling was conducted adopting LARS-WG. To conduct a stochastical analysis of LARS-WG, climate scenarios were generated for the periods 2011~2030, 2046~2065, 2080~2099 using the data of precipitation andMax/Min temperatures collected from the Miryang gauging station. Upon reviewing the result of the analysis of accumulated temperatures from 2011~2030, the supply of agricultural water was 10 days earlier, and in the next periods-2046~2065, 2080~2099 it also was 10 days earlier. With these results, it is assumed that the supply of agricultural water should be about 1 month ahead of the existing schedule to meet the proper growth conditions of crops. From the results of the agricultural water supply patterns should be altered, but the reliability of water supply becomes more favorable, which is caused from the high precipitation change. Furthermore, since the unique characteristics of precipitation in Korea, which has high precipitation in the summer, water-supply-reliability has a pattern that the precipitation in September could significantly affect the chances of drought the following winter and spring. It could be more risky to make changes to the constant supply pattern under these conditions due to the high uncertainty of future precipitation. Although, several researches have been conducted concerning climate changes, in the field of water-industry, those researches have been solely dependent on precipitation. Even so, with the high uncertainty of precipitation, it is difficult for it to be reflected in government policy. Therefore, research in the field of water-supply-patterns or evapotranspiration according to the temperature or other diverse effects, which has higher reliability on anticipation, could obtain more reliable results in the future and that could result in water-resource maintenance to be safer and a more advantageous environment.

• Journal of Ecology and Environment
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• 제42권2호
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• pp.77-84
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• 2018

Background: For understanding and evaluating a more realistic and accurate assessment of ecosystem carbon balance related with environmental change or difference, it is necessary to analyze the various interrelationships between soil respiration and environmental factors. However, the soil temperature is mainly used for gap filling and estimation of soil respiration (Rs) under environmental change. Under the fact that changes in precipitation patterns due to climate change are expected, the effects of soil moisture content (SMC) on soil respiration have not been well studied relative to soil temperature. In this study, we attempt to analyze relationship between precipitation and soil respiration in temperate deciduous broad-leaved forest for 2 years in Gwangneung. Results: The average soil temperature (Ts) measured at a depth of 5 cm during the full study period was $12.0^{\circ}C$. The minimum value for monthly Ts was $-0.4^{\circ}C$ in February 2015 and $2.0^{\circ}C$ in January 2016. The maximum monthly Ts was $23.6^{\circ}C$ in August in both years. In 2015, annual precipitation was 823.4 mm and it was 1003.8 mm in 2016. The amount of precipitation increased by 21.9% in 2016 compared to 2015, but in 2015, it rained for 8 days more than in 2016. In 2015, the pattern of low precipitation was continuously shown, and there was a long dry period as well as a period of concentrated precipitation in 2016. 473.7 mm of precipitation, which accounted for about 51.8% of the precipitation during study period, was concentrated during summer (June to August) in 2016. The maximum values of daily Rs in both years were observed on the day when precipitation of 20 mm or more. From this, the maximum Rs value in 2015 was $784.3mg\;CO_2\;m^{-2}\;h^{-1}$ in July when 26.8 mm of daily precipitation was measured. The maximum was $913.6mg\;CO_2\;m^{-2}\;h^{-1}$ in August in 2016, when 23.8 mm of daily precipitation was measured. Rs on a rainy day was 1.5~1.6 times higher than it without precipitation. Consequently, the annual Rs in 2016 was about 12% higher than it was in 2015. It was shown a result of a 14% increase in summer precipitation from 2015. Conclusions: In this study, it was concluded that the precipitation pattern has a great effect on soil respiration. We confirmed that short-term but intense precipitation suppressed soil respiration due to a rapid increase in soil moisture, while sustained and adequate precipitation activated Rs. In especially, it is very important role on Rs in potential activating period such as summer high temperature season. Therefore, the accuracy of the calculated values by functional equation can be improved by considering the precipitation in addition to the soil temperature applied as the main factor for long-term prediction of soil respiration. In addition to this, we believe that the accuracy can be further improved by introducing an estimation equation based on seasonal temperature and soil moisture.

• 자원환경지질
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• 제54권1호
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• pp.77-89
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• 2021

본 연구에서는 Jeong et al. (2020)의 연구에서 수행된 지하수위 변동 패턴의 저차원 특징추출 과정의 문제점을 분석하고, 이에 대한 개선방안이 제안된다. 해당 연구에서는 Denoising autoencoder (DAE)를 이용해 전국의 연 단위 지하수위 변동 자료로부터 저차원 특징이 추출되며, 추출된 자료를 이용해 대수층의 수리 특성값을 예측하는 회귀 모델이 개발되었다. 그러나 특정 지역의 연도별 강수 패턴이 달라질 경우, 지하수위 변동 패턴 및 저차원 특징 또한 달라지며, 이에 따라 동일 지역임에도 불구하고 저차원 특징으로부터 추정되는 수리 특성값이 다양하게 나타날 수 있다. 이러한 문제를 해결하기 위해, 본 연구에서는 조건부 생성 모델인 Conditional variational autoencoder (CVAE)를 이용하였으며, 전국 71개 지역에서 10년 동안 획득된 지하수위 자료와 강수 자료 간 상관관계가 학습되었다. 학습된 모델을 통해 모든 지역에 대해 동일 강수 조건이 적용될 때의 지하수위 자료가 생성되었으며, 생성된 지하수위 자료로부터 저차원 특징이 추출되었다. CVAE를 이용해 동일 강수 조건으로 생성된 지하수위 자료의 저차원 특징과 기존 DAE를 통해 추출된 저차원 특징이 비교되었으며, 그 결과 CVAE를 이용해 추출된 저차원 특징 간 거리가 저차원 공간상에서 보다 가깝게 분포하는 것이 확인되었다. 따라서 제안된 방법을 이용할 경우 대수층 특성에만 영향을 받는 지역별 지하수위 자료 및 저차원 특징이 효과적으로 추출될 수 있으며, 이를 통해 기존 개발된 회귀 모델의 성능이 개선될 수 있을 것으로 판단된다.

• 한국대기환경학회지
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• 제15권4호
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• pp.393-402
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• 1999

Precipitation samples were collected by the wet-only sampling method in Iksan in the northwest of Chonbuk from March 1995 to February 1997. These samples were analyzed for the concentration of ion components, in addition to pH and electrical conductivity. The annual mean pH of precipitation was 4.8 and the seasonal trend of pH was shown to be low in Fall and Winter(4.5), middle-ranged in Spring(4.7) and high in Summer(5.0). The frequency of pH below 5.6 was about 71%. The seasonal pattern of pH frequency was found to be different in each season. In the case of the pH less than 5.0, the frequency was higher in Spring, Fall and Winter than in Summer, especially higher in Fall than in other seasons. The concentrations of analysed ions showed a pronounced seasonal pattern. However, major ion species for all seasons were $NH^+_4,;Ca^{2+};and;Na^+$ among cations and $SO^{2-}_4,;Cl^-;and;NO^-_3$ among anions. The major acidifying species appeared to be $nss-SO^{2-}_4;and;NO^-_3$, and the main bases responsible for the neutralization of precipitation acidity were $nss-Ca^{2+};and;NH^+_4$. The potential acidity of precipitation, pAi, was found to be between 3.0 and 5.0 for total samples, while the measured pH was approximately between 3.9 and 7.8. The seasonal trend of pAi showed a decreasing order: Summer (4.3), Winter(4.0), Spring and Fall(3.8). During the Fall, both pAi and pH were especially very low, which indicated that during this period the potential acidity of precipitation was high but the neutralizing capacity was low. For Spring, pAi was very low but pH was slightly high. This was likely due to the large amount of $CaCO_3$ in the soil particles transported over a long range from the Chinese continent that were incorporated into the precipitation, and then neutralized the acidifying species with its high concentraton.