• Journal of Korea Water Resources Association
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• v.57 no.1
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• pp.1-8
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• 2024

Persistent droughts due to climate change will intensify water shortage problems in Korea. According to the 1st National Water Management Plan, the shortage of domestic and industrial waters is projected to be 0.07 billion m³/year under a 50-year drought event. A long-term prediction of water demand is essential for effectively responding to water shortage problems. Unlike industrial water, which has a relatively constant monthly usage, domestic water is analyzed on monthly basis due to apparent monthly usage patterns. We analyzed monthly water usage patterns using water usage data from 2017 to 2021 in Chungcheong, South Korea. The monthly water usage rate was calculated by dividing monthly water usage by annual water usage. We also calculated the water distribution rate considering correlations between water usage rate and climate variables. The division method that divided the monthly water usage rate by monthly average temperature resulted in the smallest absolute error. Using the division method with average temperature, we calculated the water distribution rates for the Chungcheong region. Then we predicted future water usage rates in the Chungcheong region by multiplying the average temperature of the SSP5-8.5 scenario and the water distribution rate. As a result, the average of the maximum water usage rate increased from 1.16 to 1.29 and the average of the minimum water usage rate decreased from 0.86 to 0.84, and the first quartile decreased from 0.95 to 0.93 and the third quartile increased from 1.04 to 1.06. Therefore, it is expected that the variability in monthly water usage rates will increase in the future.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.13 no.1
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• pp.17-25
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• 1977

For four calender years (1971-1974), daily observations of weather conditions (air temperature, humidity, wind speed, wind direction, cloud amount, fog, precipitation etc.) at six stations in the north western Pacific Ocean are used to calculate mean monthly values and to check extra-conditions. At Petropavlosk and Miko'skoe, where indicate the characteristics of modified continental climate, the temperature and humidity are high in summer, and Iow in winter. At A Dak and She Mya, where indicate the characteristics of warm current type maritime climate, humidity is high in all season and annual range of air temperature is nearly negligible. At Simusir and Vasi!' eva, where indicate the characteristics of cold current type maritime climate, humidity is high in all season and annual range of air temperature is $15^{\circ}C.$ As dry cooling power is relatively high in winter, working condition on deck is bad. Most of fogs are advection fog in the area of cold current type climate in summer.

• The Korean Journal of Ecology
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• v.26 no.4
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• pp.199-202
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• 2003

According to the energy hypothesis, the energy input per unit area primarily determines species richness in regions of roughly equal area. Some energy-related ecological research included identification of major climatic variables to determine regional species richness. In this study, the local butterfly species richness was examined to find out whether weather variables affected the local distribution or abundance of butterfly populations. Butterfly monitoring data from May 2001 to April 2002 taken at Mt. Yudal, Mokpo, in the southwestern part of Korea, and six weather variables (monthly mean values of temperature, precipitation, evaporation, wind speed, air pressure, and sunlight) were analyzed. Multiple regression analysis showed that only temperature explained 80% and 70% of the variability of log-transformed number of species and individuals, respectively, indicating that temperature played an important role in local species richness. Furthermore, global warming could affect the abundance and distribution of butterflies regionally as well as locally.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.9
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• pp.1695-1699
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• 2009

This paper analyzed the characteristics of the demand of electric power in Jeju by year, day. For this analysis, this research used the correlation between the changes in the temperature and the demand of electric power in summer, and cleaned the data of the characteristics of the temperatures, using the coefficient of correlation as the standard. And it proposed the algorithm of forecasting the short-term electric power demand in Jeju, Therefore, in the case of summer, the data by each cleaned temperature section were used. Based on the data, this paper forecasted the short-term electric power demand in the exponential smoothing method. Through the forecast of the electric power demand, this paper verified the excellence of the proposed technique by comparing with the monthly report of Jeju power system operation result made by Korea Power Exchange-Jeju.

• Journal of the Korean Institute of Landscape Architecture
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• v.14 no.2
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• pp.81-90
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• 1986

The full grasp of recreation demand and factors affecting on recreation demand can be very important information for park planning and management. The object-tives of this study are to investigate factors affecting the fluctuation of urban park visitors and to analyze the relationship between these factors and the daily parti-cipations. The results were as follows; 1) The peak of monthly participations comes on May, April, August and October in order. And these months are specified as school picnic period and vacation of school children. 2) In correlation analysis, the variables such as ‘Day of a week(D)’, ‘Monthly mean temp.(T)’and ‘Monthly character(M)’have high correlations with ‘No. of visitors’in order. And it is better to categorize months by its charater(picnic period in school, vacation etc) than by seasons. 3) Candidate regression model were established, as for 1984 log U= 1.51 + 0.64D1 + 0.02T + 0.36W1 - 0.23M4 + 0.003SS + 0.24Ml($R^2$=0.5326) where, U=no. of daily visitors D1 = sunday.ho1iday(1), weekday(0) T=monthly mean temperature($^{\circ}C$) W1= weather (sunny.cloudy(1) , rainy (>5mm)(0)> M4=non vacations and non school picnic period(1) , if not (0) SS=monthly sunshining hours M1=summer vacation(1), if not(0) 4) The most important variable was ‘Day of a week’(sunday.holiday or not). And temperature, weather and monthly charcter(especially picnic period of school and vacation) were in turn, hence ‘Children's grand park’shows the use pattern of park.

• Korean Journal of Remote Sensing
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• v.40 no.1
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• pp.81-91
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• 2024

Electrical energy is a key source of energy for modern civilization, and changes in electricity generation and consumption are closely related to industry and life in general. In this study, we identified the correlation between electricity generation and nighttime light values in South Korea and used it to predict monthly electricity generation trends in North Korea. The results of the study showed a low Pearson correlation coefficient of 0.34 between nighttime light and electricity generation in Seoul, but a high Pearson correlation coefficient of 0.79 between weighting for Seoul case nighttime light values and electricity generation using monthly average temperature. Using nighttime light values weighting for Seoul case by the average monthly temperature in Pyongyang to predict the monthly power generation trend in North Korea, we found that the month-on-month power generation increase in December 2022 was about 60% higher than the month-on-month power generation increase in December 2020 and 2021. The results of this study are expected to help predict monthly electricity generation trends in regions where monthly electricity generation data does not exist, making it difficult to identify timely industry trends.

• Journal of the Korean Geographical Society
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• v.43 no.3
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• pp.312-323
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• 2008

The purpose of this paper is to analyze thermal sensation which is measured by human physioclimatic reactions in South Korea. Relationships between Temperature-Humidity Index(THI) and human thermal sensation scale are derived from a questionnaire, which investigates degree of volunteer's thermal sensation with respect to each biometeorological condition. Analyses of these empirical relationships make it possible to calculate thermal sensational indices and to classify bioclimatic types for individual weather stations based on long-term(1971-2000) averages of monthly temperature and humidity data. A generalized annual physioclimatic maps for each Annual Cumulative Thermal Sensation Index for the 68 stations are constructed to show men tend to feel in various areas. The Monthly thermal sensations are affected by latitude, altitude, orographic effects and systems of airmasses. The Annual Cumulative Thermal sensations are increasing towards northern areas and inland, and that the major factors are largely derived from cold stress in winter. The Annual Physioclimatic Types are grouped 8 climatic types(M, ES, M-ES, M-S, W-ES, C-ES, C-M, C-M-ES) according to climatic stress. Results of this study can be applied for evaluation of thermal environment in our daily activities, and for searching relevant sports training-sites, climatherapy etc.

• Journal of Environmental Science International
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• v.23 no.5
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• pp.873-885
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• 2014

To identify the characteristics of extreme heat events and tropical nights in major cities, the correlations between automated synoptic observing station (ASOS), automatic weather station (AWS), and temperature in seven metropolitan areas were analyzed. Temperatures at ASOS were found to be useful sources of the reference temperature of each area. To set the standard for identifying dates of extreme heat events in relation to regional topography and the natural environment, the monthly and yearly frequency of extreme heat in each region was examined, based on the standards for extreme heat day (EHD), tropical night day (TND), and extreme heat and tropical night day (ETD). All three cases identified 1994 as the year with the most frequent heat waves. The frequency was low according to all three cases in 1993, 2003 and 2009. Meanwhile, the yearly rate of increase was the highest in 1994, followed by 2010 and 2004, indicating that the frequency of extreme heat changed significantly between 1993 and 1994, 2003 and 2004, and 2009 and 2010. Therefore all three indexes can be used as a standard for high temperature events. According to monthly frequency data for EHD, TND, and ETD, July and August accounted for 80% or more of the extreme heat of the entire year.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.46 no.6
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• pp.868-877
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• 2013

To understand the effects of marine environmental and meteorological parameters on laver Porphyra yezoensis production at Nakdong River Estuary, we analyzed marine environmental (water temperature, salinity, nutrients, etc.) and meteorological properties (air temperature, wind speed, precipitation, sunshine hours) with yearly and monthly variations in laver production over 10 years (2003-2013). Air and water temperature, wind speed, sunshine hours and precipitation were major factors affecting yearly variability in laver production at the Nakdong River Estuary. Lower air and water temperatures together with higher levels of nutrients and sunshine and stronger wind speeds resulted in higher laver harvests. Salinity and nitrogen did not show clear correlations with laver production, mainly due to the plentiful supply of nitrogen from river discharge and the low frequency of environmental measurements, which resulted in low statistical confidence. However, environmental factors affecting monthly laver production were related to the life cycle (culturing stage) of Porphyra yezoensis and were somewhat different from factors affecting annual laver production. In November, a young laver needs lower water temperatures for rapid growth, while a mature laver needs much stronger winds and more sunshine, as well as lower temperatures for massive production and effective photosynthesis, mostly in December and January. However, in spring (March), more stable environments with fewer fluctuations in air temperature are needed to sustain the production of newly deployed culture-nets ($2^{nd}$ time culture). These results indicate that rapid changes in weather and marine environments caused by global climate change will negatively affect laver production and, thus, to sustain the yield of and predict future variability in laver production at the Nakdong River estuary, environmental variation around laver culturing farms needs to be monitored with high resolution in space and time.

• Atmosphere
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• v.16 no.4
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• pp.333-342
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• 2006

The long-term trends of global solar irradiance, air temperature, specific humidity and cloudiness measured at King Sejong station, Antarctica, during the period of 1988-2004, have been investigated. A statistically insignificant decrease, -0.21 $Wm^{-2}yr^{-1}$ (-0.26 %$yr^{-1}$, P<0.5) in global solar irradiance was found in an analysis from the time series of the monthly mean values, except for the increasing trends only in two months of January and June. The trends in irradiance are directly and inversely associated with the cloudiness trends in annual and monthly means. The trends in surface air temperature show a slight warming, $0.03^{\circ}Cyr^{-1}$ (1.88 %$yr^{-1}$, P<0.5) on the annual average, with cooling trend in the summer months and the warming in the winter. The exact relationship, if any, between the irradiance and temperature trends is not known. No significant tendency was found in specific humidity for the same periods. Recent (1996-2004) erythermal ultraviolet irradiance shows decreasing trend in annual mean, -0.15 $mWm^{-2}yr^{-1}$ (-1.18 %$yr^{-1}$, P<0.1) which is about five times the trends of global solar irradiance. The ratio of erythermal ultraviolet to global solar irradiance shows remarkable seasonal variations with annual mean value of 0.01 % and a peak in October and November, showing the increase of ultraviolet irradiance resulting from the Antarctic ozone hole. The sensitivity of global solar irradiance to the change in cloudiness is roughly $13%oktas^{-1}$ which is about twice of the value at the South Pole due to the difference in the average surface reflectance between the two stations. Much more sensitive values of $59%oktas^{-1}$ was found for erythermal UV irradiance than for the global solar irradiance.