Native oak tree species dominate the deciduous forests of South Korea. Although the acorns of these oak trees represent the main food source for many wildlife species, information pertaining to their nutrient composition and associated seasonal changes is limited. Thus, the objective of this study was to describe the seasonal changes in the acorn nutrient composition of six oak species in terms of nitrogen (N), phosphorus (P), calcium (Ca), magnesium (Mg), and sodium (Na) concentrations, Quercus acutissima, Q. aliena, Q. mongolica, Q. variabilis, Q. dentata, and Q. serrata. The results indicated that N concentrations of Q. aliena acorns were constant, whereas those of Q. dentata changed over the seasons. Those of Q. acutissima acorns were higher in summer and autumn but Q. mongolica acorns were higher in spring and summer. Q. serrata acorns were highest in autumn but Q. variabilis acorns were found to be the lowest in N concentration. P concentrations of acorns of six species tended to decline in the summer but increased in the spring and autumn. Ca and Mg concentrations showed an obvious trend of decline over the seasons for all species except Q. mongolica. Na concentrations of Q. aliena, Q. dentata, and Q. serrata acorns were constant over the seasons whereas those of Q. dentata tended to increase. Q. variabilis acorns were highest in autumn but Q. acutissima acorns were lowest in Na concentration. Overall, these results showed that acorn nutrient composition varies by season, and that the nature of the variability is largely species dependent.
Kim, Min-Ji;Shin, Jin-Ho;Lee, Hyo-Shin;Kwon, Won-Tae
Atmosphere
/
v.18
no.4
/
pp.507-524
/
2008
In this paper, future climate changes over East Asia($20^{\circ}{\sim}50^{\circ}N$, $100^{\circ}{\sim}150^{\circ}E$) are projected by anthropogenic forcing of greenhouse gases and aerosols using coupled atmosphere-ocean general circulation model (AOGCM) simulations based on Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) B1, A1B and A2 scenarios. Before projection future climate, model performance is assessed by the $20^{th}$ Century (20C3M) experiment with bias, root Mean Square Error (RMSE), ratio of standard deviation, Taylor diagram analysis. The result of examination of the seasonal uncertainty of T2m and PCP shows that cold bias, lowered than that of observation, of T2m and wet bias, larger than that of observation, of PCP are found over East Asia. The largest wet bias is found in winter and the largest cold bias is found in summer. The RMSE of temperature in the annual mean increases and this trend happens in winter, too. That is, higher resolution model shows generally better performances in simulation T2m and PCP. Based on IPCC SRES scenarios, East Asia will experience warmer and wetter climate in the coming $21^{st}$ century. It is predict the T2m increase in East Asia is larger than global mean temperature. As the latitude goes high, the warming over the continents of East Asia showed much more increase than that over the ocean. An enhanced land-sea contrast is proposed as a possible mechanism of the intensified Asian summer monsoon. But, the inter-model variability in PCP changes is large.
Park, Jong Suk;Kang, KiRyong;Kang, Hyun-Suk;Kim, Young-Hwa
Journal of Korean Society of Coastal and Ocean Engineers
/
v.25
no.5
/
pp.267-275
/
2013
This study projected the future ocean wave climate changes based on global climate change scenario using the coupled climate model HadGEM2-AO according to the emission scenarios and using regional wave model. Annual mean significant wave height (SWH) is linked closely to annual mean wind speed during the forthcoming 21st Century. Because annual mean speed decreased in the western North Pacific, annual mean SWH is projected to decrease in the future. The annual mean SWH decreases for the last 30 years of the 21st century relative to the period 1971-2000 are 2~7% for RCP4.5 and 4~11% for RCP8.5, respectively. Also, extreme SWH and wind speed are projected to decrease in the future. In terms of seasonal mean, winter extreme SWH shows similar trend with annual extreme SWH; however, that of summer shows large increasing tendency compared with current climate in the western North Pacific. Therefore, typhoon intensity in the future might be more severe in the future climate.
We monitored the current macrozoobenthic community structure after the Sea Prince oil spill around Keumo-do and Sori-do, Korea. Macrobenthic animals were collected seasonally around Sori-Keumo do using a van Veen grab ($0.1m^2$) from October 1999 to April 2000. In total, 196 species were identified at 46 sites around Keumho-do. The mean density was 1,460 individuals/$m^2$, and polychaetes comprised 80% of the total density of the macrozoobenthic. Dominant species were the polychaete Tharyx sp. (51%), the echinoderm Amphioplus megapomus (5%) and the polychaete Lumbrineris longifolia (3%). We identified 176 macrobenthic species at 36 sites around Sori-do. The mean density was 1,068 individuals/$m^2$, and polychaetes was the most abundant faunal group, comprising 41%, followed by mollusks (24%) and echinoderms (20%). Dominant species in Sori-do were the mollusk Potamocorbula amurensis (23%), the chinoderm Amphioplus megapomus (14%), and the polychaete Tharyx sp. (10%). The overall community structures in the study area showed few seasonal changes, although there was a gradual change in the species composition within each benthic community. Tharyx sp. was the most abundant species in the study area. Because this species has not been found in the other coastal areas except during recent investigations, it is considered to have increased during the course of community succession after the oil spill. The macrozoobenthic around Keumo-do showed little change in species richness, whereas around Sori-do, it showed a few increases in species richness after the summer of 1998. The overall density showed the same trend as species richness. Based on improved community indices, we suggest that the macrozoobenthic communities around Sori-Keumo Islands are gradually recovering from the oil-spill damagecaused by the oil spill.
Climate change, a result of increasing global warming, has been receiving more public attention due to its serious impact upon many industries. In this study we consider sustainable- (Green-) Growth and Green-Finance, and in particular temperature derivatives, as appropriately active responses to the world's significant climate change trends. We characterize the daily average temperatures in Seoul, South Korea with their seasonal properties and cycles of error terms. We form forecasting models and perform Monte Carlo simulations, and find that the risk-neutral values for CDD call-options and HDD put-options have risen since 1960s, which implies that the trend of temperature increase can be quantified in the financial markets. Contrary to the existing models, the Vasicek model with the explicit consideration of cycles in the error terms suggests that the significant option-values for the CDD call -options above certain exercise prices, implying that there is the possibility of explicit hedging against the considerable and stable increase in temperature.
An, Soon-Il;Ha, Kyung-Ja;Seo, Kyong-Hwan;Yeh, Sang-Wook;Min, Seung-Ki;Ho, Chang-Hoi
Journal of Climate Change Research
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v.2
no.4
/
pp.237-251
/
2011
This study presents a review on the recent climate change over the Korean peninsula, which has experienced a significant change due to the human-induced global warming more strongly than other regions. The recent measurement of carbon dioxide concentrations over the Korean peninsula shows a faster rise than the global average, and the increasing trend in surface temperature over this region is much larger than the global mean trend. Recent observational studies reporting the weakened cold extremes and intensified warm extremes over the region support consistently the increase of mean temperature. Surface vegetation greenness in spring has also progressed relatively more quickly. Summer precipitation over the Korean peninsula has increased by about 15% since 1990 compared to the previous period. This was mainly due to an increase in August. On the other hand, a slight decrease in the precipitation (about 5%) during Changma period (rainy season of the East Asian summer monsoon), was observed. The heavy rainfall amounts exhibit an increasing trend particularly since the late 1970s, and a consecutive dry-day has also increased primarily over the southern area. This indicates that the duration of precipitation events has shortened, while their intensity became stronger. During the past decades, there have been more stronger typhoons affecting the Korean peninsula with landing more preferentially over the southeastern area. Meanwhile, the urbanization effect is likely to contribute to the rapid warming, explaining about 28% of total temperature increase during the past 55 years. The impact of El Nino on seasonal climate over the Korean peninsula has been well established - winter [summer] temperatures was generally higher [lower] than normal, and summer rainfall tends to increase during El-Nino years. It is suggested that more frequent occurrence of the 'central-Pacific El-Nino' during recent decades may have induced warmer summer and fall over the Korean peninsula. In short, detection and attribution studies provided fundamental information that needed to construct more reliable projections of future climate changes, and therefore more comprehensive researches are required for better understanding of past climate variations.
KSCE Journal of Civil and Environmental Engineering Research
/
v.28
no.1B
/
pp.41-53
/
2008
Unprecedented weather phenomena are occurring because of climate change: extreme heavy rains, heat waves, and severe rain storms after the rainy season. Recently, the frequency of these abnormal phenomena has increased. However, regular pattern or cycles cannot be found. Analysis of annual data or annual average data, which has been established a research method of climate change, should be applied to find frequency and tendencies of extreme climate events. In this paper, extreme indicators of precipitation and temperature marked by objectivity and consistency were established to analyze data collected by 66 observatories throughout Korea operated by the Meteorological Administration. To assess the statistical significance of the data, linear regression and Kendall-Tau method were applied for statistical diagnosis. The indicators were analyzed to find tendencies. The analysis revealed that an increase of precipitation along with a decrease of the number of rainy days. A seasonal trend was also found: precipitation rate and the heavy rainfall threshold increased to a greater extent in the summer(June-August) than in the winter (September-November). In the meanwhile, a tendency of temperature increase was more prominent in the winter (December-February) than in the summer (June-August). In general, this phenomenon was more widespread in inland areas than in coastal areas. Furthermore, the number of winter frost days diminished throughout Korea. As was mentioned in the literature, the progression of climate change has influenced the increase of temperature in the winter.
This paper examines characteristics of time series data related to the construction investment(stationarity and time series components such as secular trend, cyclical fluctuation, seasonal variation, and random change) and surveys predictibility, fitness, and explicability of independent variables of various models to build a short-term construction investment forecasting model suitable for current economic circumstances. Unit root test, autocorrelation coefficient and spectral density function analysis show that related time series data do not have unit roots, fluctuate cyclically, and are largely explicated by lagged variables. Moreover it is very important for the short-term construction investment forecasting to grasp time lag relation between construction investment series and leading indicators such as building construction permits and value of construction orders received. In chapter 3, we explicate 7 forecasting models; Univariate time series model (ARIMA and multiplicative linear trend model), multivariate time series model using leading indicators (1st order autoregressive model, vector autoregressive model and error correction model) and multivariate time series model using National Accounts data (simple reduced form model disconnected from simultaneous macroeconomic model and VAR model). These models are examined by 4 statistical tools that are average absolute error, root mean square error, adjusted coefficient of determination, and Durbin-Watson statistic. This analysis proves two facts. First, multivariate models are more suitable than univariate models in the point that forecasting error of multivariate models tend to decrease in contrast to the case of latter. Second, VAR model is superior than any other multivariate models; average absolute prediction error and root mean square error of VAR model are quitely low and adjusted coefficient of determination is higher. This conclusion is reasonable when we consider current construction investment has sustained overheating growth more than secular trend.
Land Surface Model (LSM) was developed for the Soyang river basin located in Korean Peninsula to clarify the spatio-temporal variability of hydrological weather parameters. Variable Infiltration Capacity (VIC) model was used as a LSM. The spatial resolution of the model was 10 km and the time resolution was 1 day. Based on the daily flow data from 2007 to 2010, the 7 parameters of the model were calibrated using the Isolated Particle Swarm Optimization algorithm and the model was verified using the daily flow data from 2011 to 2014. The model showed a Nash-Sutcliffe Coefficient of 0.90 and a correlation coefficient of 0.95 for both calibration and validation periods. The hydrometeorological variables estimated for the Soyang river basin reflected well the seasonal characteristics of summer rainfall concentration, the change of short and shortwave radiation due to temperature change, the change of surface temperature, the evaporation and vegetation increase in the cover layer, and the corresponding change in total evapotranspiration. The model soil moisture data was compared with in-situ soil moisture data. The slope of the trend line relating the two data was 1.087 and correlation coefficient was 0.723 for the Spring, Summer and Fall season. The result of this study suggests that the LSM can be used as a powerful tool in developing precise and efficient water resources plans by providing accurate understanding on the spatio-temporal variation of hydrometeorological variables.
Existing studies that analyze the causes and effects of water circulation use mostly rainfall - runoff models, which requires much effort in model development, calibration and verification. In this study, hydrological sensitivity analysis which can separate quantitatively the impacts by natural factors and anthropogenic factor was applied to the Hwacheon dam upper basin from 1967 to 2017. As a result of using various variable change point detection methods, 1999 was detected as a statistically significant change point. Especially, based on the hydrological sensitivity analysis using 5 Budyko based functions, it was estimated that the average inflow reduction amount by Imnam dam construction was $1.890\;billion\;m^3/year$. This results in this study was slightly larger than the those by existing researchers due to increase of rainfall and decrease of Hwacheon dam inflow. In future, it was suggested that effective water management measures were needed to resolve theses problems. Especially, it can be suggested that the monthly or seasonal analysis should be performed and also the prediction of discharge for future climate change should be considered to establish resonable measures.
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