• Ecology and Resilient Infrastructure
• /
• v.9 no.4
• /
• pp.269-281
• /
• 2022

The prediction of changes regarding the distribution of vegetation and plant species according to climate changes is important for ecosystem management. In this study, we attempted to develop an assessment method to evaluate the possibility of the potential distribution of warm-temperate woody plant species of East Asia in Korea. To begin with, a list of warm-temperate woody plants distributed in China and Japan, but not in Korea, was prepared, and a database consisting their global distribution and bioclimatic variables was constructed. In addition, the warm-temperate vegetation zone in Korea was delineated using the coldness index and relevant bioclimatic data were collected. After the exclusion of multicollinearity among bioclimatic variables using correlation analysis, mean temperature of the coldest quarter, mean temperature diurnal range, and annual precipitation were selected as the major variables that influence the distribution of warm-temperate plants. A multivariate environment similarity surfaces (MESS) analysis was conducted to calculate the similarity scores between the distribution of these three bioclimatic variables in the global distribution sites of the East Asian warm-temperate woody plants and the Korean warm-temperate vegetation zone. Finally, using stepwise variable-selection regression, the mean temperature of the coldest quarter and annual precipitation were selected as the main bioclimatic variables that affect the MESS similarity index. The mean temperature of the coldest quarter accounted for 88% of the total variance. For a total of 319 East Asian warm-temperate woody plant species, the possibility of their potential distribution in Korea was evaluated by applying the constructed multivariate regression model that calculates the MESS similarity index.

• Korean Journal of Fisheries and Aquatic Sciences
• /
• v.18 no.6
• /
• pp.497-505
• /
• 1985

We studied the annual and interannual fluctuations of sea surface temperature (SST) for 30 years ($1941{\sim}1970$) at 9 coastal stations in the Tsushima Current and the Kuroshio regions by means of harmonic analysis, correlation analysis, and spectral analysis. The fluctuations of annual mean and amplitude are 0.3 to $0.7^{\circ}C$, and those of annual phase are 3 to 4 days. The SST anomalies are about $1^{\circ}C$, and they are relatively large in summer and winter than in spring and fall. The SST anomalies in the Tsushima Current and the Kuroshio regions are related with each other. The predominant periods of SST anomalies differ slightly from station to station. The quasi-biennial (26 months) and pole tide (14 months) oscillations are found in the spectra of SST anomalies.

• Fisheries and Aquatic Sciences
• /
• v.24 no.1
• /
• pp.41-52
• /
• 2021

Data for fish species composition and the catch of fish species were obtained from the daily trading records for the period between April and December 2016 to 2018 at the set net fishing grounds in Yeosu Bay, Korea. The annual mean total catch was 195.8 tons, and the dominant species was the Spanish mackerel (Scomberomorus niphonius), which accounts for about 55 percent of the total catch. The catch increased in spring and autumn. Increase in spring is caused by not Spanish mackerel but other fish while the increase in autumn by Spanish mackerel. The distinct increase of the catch in summer, 2017 was due to the new recruitment of small-sized Spanish mackerel, which was probably to be from the fish population hatched in spring in the East China Sea. Our results showed a strong correlation between water temperature and catch fluctuation. The catch increases with the increase in water temperatures, and the periodic pattern of the water temperature and catch fluctuation is more consistent in the offshore waters, in which warm current flows, than in the coast waters.

• Journal of Ecology and Environment
• /
• v.33 no.1
• /
• pp.37-45
• /
• 2010

I conducted extensive analyses of daily weather data of precipitation and temperature monitored from the Surface Synoptic Meteorological Station in Seoul from 1 October 1907 to 31 December 2009 to understand how the climate is changing and the ecological implications for Seoul, Korea. Statistical analyses of the data, including the lengths of seasons and growing degree-days (GDD), showed a clear warming trend in the Seoul area over the study period. The mean daily temperature in Seoul increased by $2.40^{\circ}C$ over the period of one hundred years, which was about three times faster than the global trend and it was striking to notice that mean daily temperature in Seoul in recent 30 years was increasing with the rate of $5.50^{\circ}C$ per hundred years, which is an extremely fast rate of increase in temperature. In the last 100 years, an increase in the number of summer days was apparent, coupled with a reduction in the average number of winter days for about 27 to 28 days based on the analysis of mean daily temperature. Although the lengths of spring and autumn have not changed significantly over the century, early initiations of spring and late onsets of autumn were quite apparent. Total annual precipitation significantly increased at the rate of 2.67 mm/year over the last 100 years, a trend not apparent if the analysis is confined to periods of 30 to 40 years. The information has the potential to be used not only for better understanding of ecological processes and hydrology in the area, but also for the sustainable management of ecosystems and environment in the region.

• Journal of Forest and Environmental Science
• /
• v.30 no.1
• /
• pp.36-44
• /
• 2014

We measured radial growth of Cryptomeria japonica and Chamaecyparis obtusa growing in Gangneung, Boseong, Yangsan and Ulleung-do, respectively and analyzed its relationship with temperature and precipitation. We found from the result of tree ring counting that forest stands of Cryptomeria japonica in Gangneung and Boseong was 40 to 50 years old and 50 to 70 years old in Yangsan and Ulleung-do. According to climate change, the mean temperature in Gangneung was found to be $12^{\circ}C$ to $13^{\circ}C$ which was similar to that of Boseong and Yangsan 40 to 50 years ago. While the result of the radial growth measured from Cryptomeria japonica in Gangneung showed a slightly decreasing tendency compared to the other areas, Chamaecyparis obtusa showed an increasing tendency. In the case of Cryptomeria japonica, a strong negative correlation between radial growth and climate related variables including both mean temperature and mean precipitation existed in Ulleung. There was a strong negative correlation between radial growth and mean temperature for Chamaecyparis obtusa in Yangsan, although there was a positive correlation in Gangneung and Yangsan.

• Journal of Korean Society on Water Environment
• /
• v.26 no.3
• /
• pp.482-490
• /
• 2010

In this study 17 GCMs' simulations of late 20th century climate in Korea are examined. A regionally averaged time series formed by averaging the temperature and precipitation values at all the Korean grid points. In order to compare general circulation models with observations, observed spatially averaged temperature and precipitation is calculated using 24 stations for 1971 to 2000. The annual mean difference between models and observed data are compared. For temperature, most models have a slight cold bias. The models with least bias in annual average temperature are NIES(MIROC3.2 hires), GISS(AOM) and INGV(SXG2005). For precipitation, almost all models have a dry bias, and for some the bias exceeds 50%. Models with lowest bias are NIES(MIROC3.2 hires), CCCma(CGCM3-T47) and MPI-M(ECHAM5-OM). The models' simulated seasonal cycles show that for temperature, CSIRO(Mk3.0) has the best followed by CCCma(CGCM3-T47) and CCCma(CGCM3-T63), and for precipitation, NIES(MIROC3.2 hires) has the best followed by CSIRO(Mk3.0) and CNRM(CM3). In the assessment using Taylor diagram, CCCma(CGCM3-T47) ranks the best for temperature, and NIES(MIROC3.2 hires) ranks the best for precipitation.

• Journal of Korean Society of Environmental Engineers
• /
• v.39 no.12
• /
• pp.685-688
• /
• 2017

Using ALOHA and PHAST Program, it was modeled assuming the leakage accident scenarios of chlorine which is designated as accident preparation chemical in chemical control act. End-point distances corresponding to ERPG-2 concentrations were calculated while varying annual mean temperature, wind speed, humidity, and atmospheric stability. The calculated endpoint distance values were compared and the correlation with each meteorological factor was analyzed. And we also investigated strengths and weaknesses of ALOHA and PHAST. The results show that ALOHA has little or no correlation with annual average temperature, humidity and it has a large correlation with wind speed and atmospheric stability. In the case of PHAST, the end-point distances were correlated with all the meteorological factors such as average annual temperature, wind speed, humidity, and atmospheric stability, Among them, the effect of atmospheric stability were the largest.

• Journal of Environmental Health Sciences
• /
• v.42 no.1
• /
• pp.41-52
• /
• 2016

Objectives: Scrub typhus is one of the most prevalent vector-borne diseases. It is caused by Orientia tsutsugamushi, which is transmitted when people are bitten by infected chigger mites. This study aims at quantifying the association between the incidence of scrub typhus and meteorological factors in Jeollabuk-do Province over the period 2001-2015. Methods: Reported cases of scrub typhus were collected from the website of the Disease Web Statistical System supported by the Korea Centers for Disease Control and Prevention (KCDC). Simultaneous meteorological data, including temperature, rainfall, relative humidity, and sunshine duration were collected from the website of the National Climate Data Service System by the Korea Meteorological Administration. Correlation and regression analyses were applied to identify the association between the incidence of scrub typhus and meteorological factors. Results: The general epidemiological characteristics of scrub typhus in Jeollabuk-do Province were similar to those nationwide for sex, age, and geographical distribution. However, the annual incidence rate (i.e., cases per 100,000) of scrub typhus in Jeollabuk-do Province was approximately four times higher than all Korea's 0.9. The number of total cases was the highest proportion at 13.3% in Jeonbuk compared to other regions in Korea. The results of correlation analysis showed that there were significant correlations between annual cases of scrub typhus and monthly data for meteorological factors such as temperature and relative humidity in late spring and summer, especially in the case of temperature in May and June. The results of regression analysis showed that determining factors in the regression equation explaining the incidence of scrub typhus reached 46.2% and 43.5% in May and June. Using the regression equation, each 1oC rise in the monthly mean temperature in May or June may lead to an increase of 38 patients with scrub typhus compared to the annual mean of incidence cases in Jeollabuk-do Province. Conclusion: The result of our novel attempts provided rational evidence that meteorological factors are associated with the occurrence of scrub typhus in Jeollabuk-do. It should therefore be necessary to observe the trends and predict patterns of scrub typhus transmission in relation to global-scale climate change. Also, action is urgently needed in all areas, especially critical regions, toward taking steps to come up with preventive measures against scrub typhus transmission.

• Ocean and Polar Research
• /
• v.44 no.2
• /
• pp.127-137
• /
• 2022

This study examined the growth pattern and environmental factors affecting the growth of the halophyte, Suaeda japonica, which is prevalent on tidal flats in the west coast of Korea in order to calculate annual carbon production. Quantitative sampling was conducted every month for three years from 2018 to 2020 on salt marshes located on the southern coast of Ganghwa Island. In terms of annual density affected by the germination rate at first period, especially when air temperature for winter time was constantly below 0℃ for long periods of time, germination decreased and precipitation in summer also exerted an influence. In terms of annual growth with regard to length, the part below the ground grew rapidly in the beginning after budding, while the part above ground grew at a relatively steady rate at all times. With regard to biomass, the part below the ground also increased from April in a manner similar to length growth, but decreased drastically from September with leaves falling off and water loss occurring. The part above ground showed a rapid increase from the beginning of the rainy season. Size-frequency distribution revealed broader patterns after the rainy season as individual growth varied, but from September, it stopped at all year. High growth rates were recorded in the initial phase of growth after budding and growth was rapid, but growth declined in summer when biomass increased. The annual mean production based on growth rate was calculated at 352 gDWt/m²/yr, and the highest production was 519 gDWt/m²/yr in 2018, but it has decreased since 2019. Annual carbon production was at calculated 143.41 gC/m²/yr for Suaeda japonica in the vicinity of the southern coast of Ganghwa Island.

• 제어로봇시스템학회:학술대회논문집
• /
• 2004.08a
• /
• pp.1330-1333
• /
• 2004

The methodology for modeling building energy consumption is well established for energy saving calculation in the temperate zone both for performance-based energy retrofitting contracts and measurement and verification (M&V) projects. Mostly, statistical regression models based on utility bills and outdoor dry-bulb temperature have been applied to baseline monthly and annual whole building energy use. This paper presents the application of neural networks (NN) to model landlord energy consumption of commercial buildings in Singapore. Firstly, a brief background information on NN and its application on the building energy research is provided. Secondly, five commercial buildings with various characteristics were selected for case studies. Monthly mean outdoor dry-bulb temperature ($T_0$), Relative Humidity (RH) and Global Solar Radiation (GSR) are used as network inputs and the landlord monthly energy consumption of the same period is the output. Up to three years monthly data are taken as training data. A forecast has been made for another year for all the five buildings. The performance of the NN analysis was evaluated using coefficient of variance (CV). The results show that NNs is powerful at predicting annual landlord energy consumption with high accuracy.