• Korean Journal of Ecology and Environment
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• v.52 no.1
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• pp.40-49
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• 2019

Seasonal succession of zooplankton community and species composition was studied from 2003 to 2014 in a deep reservoir, Lake Soyang, in monsoon climate region, Korea. Annual precipitation was concentrated more than 70% between June and September and it showed remarkably that seasonal variation in water quality. Seasonal variation of water quality in Lake Soyang appeared to be more significant than annual variations, and the inflow of turbid water during the summer rainfall was the most important environmental factor. Zooplankton sepecies composition in Lake Soyang showed obvious tendency through two periods (May to June and August to October) every year. Small zooplankton (rotifer; Keratella cochlearis, Polyarthra vulgaris) dominated in spring and mesozooplankton such as copepods and crustaceans were dominant in summer and fall. Zooplankton biomass showed the maximum in September after monsoon rainfall, and chlorophyll showed a similar seasonal variation and it showed a high correlation (r=0.45). The increase of zooplankton biomass is considered to be a bottom-up effect due to the increase of primary producers and inflow of nutrients and organic matter from rainfall. In this study, we found that the variation of zooplankton community was affected by rainfall in monsoon climate region and inflow of turbid water was an important environmental factor, which influenced the water quality, zooplankton seasonal succession in Lake Soyang. It was also considered to be influenced by hydrological characteristics of lake and environment of watershed. In conclusion, seasonal succession of zooplankton species composition was the same as the PEG model. But seasonal succession of zooplankton biomass differed not only in the temperate lake but also in the monsoon region.

• Atmosphere
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• v.24 no.3
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• pp.403-417
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• 2014

Future changes in seasonal mean temperature and precipitation over East Asia under anthropogenic global warming are investigated by comparing the historical run for 1979~2005 and the Representative Concentration Pathway (RCP) 4.5 run for 2006~2100 with 20 coupled models which participated in the phase five of Coupled Model Inter-comparison Project (CMIP5). Although an increase in future temperature over the East Asian monsoon region has been commonly accepted, the prediction of future precipitation under global warming still has considerable uncertainties with a large inter-model spread. Thus, we select best five models, based on the evaluation of models' performance in present climate for boreal summer and winter seasons, to reduce uncertainties in future projection. Overall, the CMIP5 models better simulate climatological temperature and precipitation over East Asia than the phase 3 of CMIP and the five best models' multi-model ensemble (B5MME) has better performance than all 20 models' multi-model ensemble (MME). Under anthropogenic global warming, significant increases are expected in both temperature and land-ocean thermal contrast over the entire East Asia region during both seasons for near and long term future. The contrast of future precipitation in winter between land and ocean will decrease over East Asia whereas that in summer particularly over the Korean Peninsula, associated with the Changma, will increase. Taking into account model validation and uncertainty estimation, this study has made an effort on providing a more reliable range of future change for temperature and precipitation particularly over the Korean Peninsula than previous studies.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.299-303
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• 2008

In this study, an uncertainty assessment for surface air temperature(T2m) and precipitation(PCP) over East Asia is carried out. The data simulated by the intergovermental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) Atmosphere-Ocean coupled general circulation Model (AOGCM) are used to assess the uncertainty. Examination of the seasonal uncertainty of T2m and PCP variabilities shows that spring-summer cold bias and fall warm bias of T2m are found over both East Asia and the Korea peninsula. In contrast, distinctly summer dry bias and winter-spring wet bias of PCP over the Korea peninsula is found. To investigate the PCP seasonal variability over East Asia, the cyclostationary empirical orthogonal function(CSEOF) analysis is employed. The CSEOF analysis can extract physical modes (spatio-temporal patterns) and their undulation (PC time series) of PCP, showing the evolution of PCP. A comparison between spatio-temporal patterns of observed and modeled PCP anomalies shows that positive PCP anomalies located in northeastern China (north of Korea) of the multi-model ensemble(MME) cannot explain properly the contribution to summer monsoon rainfalls across Korea and Japan. The uncertainty of modeled PCP indicates that there is disagreement between observed and MME anomalies. The spatio-temporal deviation of the PCP is significantly associated with lower- and upper-level circulations. In particular, lower-level moisture transports from the warm pool of the western Pacific and corresponding moisture convergence significantly contribute to summer rainfalls. These lower- and upper-level circulations physically consistent with PCP give a insight of the reason why differences between modeled and observed PCP occur.

• Journal of Ecology and Environment
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• v.42 no.2
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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.

• Atmosphere
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• v.26 no.4
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• pp.711-716
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• 2016

The dynamical model forecasts using state-of-art general circulation models (GCMs) have some limitations to simulate the real climate system since they do not depend on the past history. One of the alternative methods to correct model errors is to use the canonical correlation analysis (CCA) correction method. CCA forecasts at the present time show better skill than dynamical model forecasts especially over the midlatitudes. Model outputs are adjusted based on the CCA modes between the model forecasts and the observations. This study builds a canonical correlation prediction model for subseasonal (June) precipitation. The predictors are circulation fields over western North Pacific from the Global Seasonal Forecasting System version 5 (GloSea5) and observed snow cover extent over Eurasia continent from Climate Data Record (CDR). The former is based on simultaneous teleconnection between the western North Pacific and the East Asia, and the latter on lagged teleconnection between the Eurasia continent and the East Asia. In addition, we suggest a technique for improving forecast skill by applying the ensemble canonical correlation (ECC) to individual canonical correlation predictions.

• Journal of Information Science Theory and Practice
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• v.10 no.spc
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• pp.135-142
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• 2022

Recently, with the development of data processing technology and the increase of computational power, methods to solving social problems using Artificial Intelligence (AI) are in the spotlight, and AI technologies are replacing and supplementing existing traditional methods in various fields. Meanwhile in Korea, heavy rain is one of the representative factors of natural disasters that cause enormous economic damage and casualties every year. Accurate prediction of heavy rainfall over the Korean peninsula is very difficult due to its geographical features, located between the Eurasian continent and the Pacific Ocean at mid-latitude, and the influence of the summer monsoon. In order to deal with such problems, the Korea Meteorological Administration operates various state-of-the-art observation equipment and a newly developed global atmospheric model system. Nevertheless, for precipitation nowcasting, the use of a separate system based on the extrapolation method is required due to the intrinsic characteristics associated with the operation of numerical weather prediction models. The predictability of existing precipitation nowcasting is reliable in the early stage of forecasting but decreases sharply as forecast lead time increases. At this point, AI technologies to deal with spatio-temporal features of data are expected to greatly contribute to overcoming the limitations of existing precipitation nowcasting systems. Thus, in this project the dataset required to develop, train, and verify deep learning-based precipitation nowcasting models has been constructed in a regularized form. The dataset not only provides various variables obtained from multiple sources, but also coincides with each other in spatio-temporal specifications.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.641-646
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• 2009

This study examines the effects of water shortage on agricultural wages in Northwest Bangladesh. For this study, meteorological data including information on the monthly temperature, precipitation, wind speed, hour of sunshine and humidity of six weather stations have been utilized during the monitoring period from 1985 to 2005. With the objective to analyze water surplus and water deficiency, a simple soil-water balance model and the modified Penman formula were applied to the Northwest Bangladesh. The seasonality of Mann-Kendell trend statistics has been used to identify the spatial variation of water surplus and deficiency throughout the region. For micro level verification of the result, a detailed field survey has been conducted within the study area. The results showed that the values of the potential evapotranspiration estimated by the modified Penmen equation were negative for certain periods. In this instance, the water deficiency of the district of Rajshahi was observed significantly in the period of pre-monsoon and post-monsoon. The field study also verified that because of such deficiency in water, the agricultural scenario of the area was widely influenced which lead to less agricultural production and less economic benefits.

• Atmosphere
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• v.26 no.4
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• pp.687-696
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• 2016

The western North Pacific subtropical high (WNPSH) in boreal summer has interannual and interdecadal variability, which affects East Asian summer monsoon variability. In particular, it is well known that the intensity of WNPSH is reversely related to that of summer monsoon in North East Asia in association with Pacific Japan (PJ)-like pattern. Many coupled climate models weakly simulate this large-scale teleconnection pattern and also exhibit the diverse variability of WNPSH. This study discusses the inter-model differences of WNPSH simulated by different climate models, which participate in the Coupled Model Intercomparison Project phase 5 (CMIP5). In comparing with reanalysis observation, the 29 CMIP5 models could be assorted into two difference groups in terms of interannual variability of WNPSH. This study also discusses the dynamical or thermodynamics factors for the differences of two groups of the CMIP5 climate models. As results, the regressed precipitation in well-simulating group onto the Nino3.4 index ($5^{\circ}N-5^{\circ}S$, $170^{\circ}W-120^{\circ}W$) is stronger than that in poorly-simulating group. We suggest that this difference of two groups of the CMIP5 climate models would have an effect on simulating the interannual variability of WNPSH.

• Korean Journal of Environmental Biology
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• v.18 no.2
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• pp.215-226
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• 2000

We evaluated the aquatic ecosystem of Keum-Ho River through applications of the Index of Biological Integrity (IBI) using fish assemblages and Qualitative Habitat Evaluation Index (QHEI) during June-November 1999. Overall IBI values ranged from 13 to 37 with mean of 23 (n=25, Std. error= 1.16), indicating a "Poor" or "Very Poor" condition according to the criteria of Karr (1981) and U.S. EPA (1993). The values of mean IBI declined at the rate of $0.22km^{-1}$(($r^2$=0.91, p< 0.05) along the longitudinal distance from the headwaters to the down-river. Reduced IBI values at down-river (St. 4 and 5) were attributed to the decreases in riffle benthic species and the relative abundance of insectivore and increases in tolerant species, anormalies and exotic species. Spatial pattern in IBI agreed with QHEI values, which showed a linear relation ($r^2$=0.998, p< 0.001) with mean number of species. Field measurements of conductivity and pH, indicators for variation of conservative ions, showed that the river water was diluted up to 30% by summer precipitation and surface run-off from the watershed, resulting in physical and chemical instability during the monsoon. For these reasons, average IBI values during monsoon and postmonsoon decreased more than 20% compared to pre -monsoon. Before the perturbation of the system (i.e., pre-monsoon), values of QHEI were inversely correlated (r=-0.99, p< 0.0001) with realtive abundance of native omnivore and were positively correlated (r=0.87, p=0.05) with relative abundance of native carnivore. These results indicate that spatial degradation of habitat quality modified the species richness and trophic structure, producing decreased IBI values. (Biological integrity, IBI, Monsoon, Habitat, River, Korea)bitat, River, Korea)

• Magazine of the Korean Society of Agricultural Engineers
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• v.26 no.3
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• pp.35-45
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• 1984

Generally speaking, agriculture exist in a climatic environment of uncertainty. Namely, normal rainfall value, as given by the mean values, does not exist. Thought on exists, itl does not affect like extreme Precipitation value on the part of agriculture and of others. Therefore, it is important that we measure the duration and severity index of drought caused by extreme precipitation deficit. In this purpose, this study was dealt with the calculation of drought duration and severity indexs by the method of monthly weighting coefficient. There is no quantitive definition of drought that is universally acceptable. Most of the criteria was used to identify drought have been arbitrary because a drought is a 'non-event' as opposed to a distinct event such as a flood. Therefore, confusion arises when an attempt is made to define the drought phenomenon, the calculation of duration, drought index is based on the following four fundamental question, and this study was dealt with the answers of these four questions as they related to this analytical method, as follows. First, the primary interest in this study is to be the lack of precipitation as it relates to agricultural effective rainfall. Second, the time interval was used to be month in this analysis. Third, Drought event, distinguished analytically from other event, is noted by monthly weighting coefficient method based on monthly rainfall data. Fin-ally, the seven regions used in this study have continually affected by drought on account of their rainfall deficit. The result from this method was very similar to the previous papers studied by many workers. Therefore, I think that this method is very available in Korea to identify the duration of drought, the deficit of precipitation and severity index of drought, But according to the climate of Korea exist the Asia Monsoon zone. The monthly weighting coefficient is modify a little, Because get out of 0.1-0.4 occasionally.