• Proceedings of the Korean Society of Crop Science Conference
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• 2000.11a
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• pp.12-27
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• 2000

During the recent decades, he problem of climate variability and change has been in the forefront of scientific problems. The objective of this study was to assess the impact of climate variability on crop growth and yield. The growth duration was the main impact of climate variability on crop yield. Phyllochronterval was shortened in the global worming situations. A simple model to describe developmental traits was provided from heading data of directly seeded rice cultivars and temperature data. Daily mean development rate could be explained by the average temperature during the growth stage. Simple regression equation between daily mean development rate(x) and the average temperature(y) during the growth period as y = ax + b. It can be simply modified as x = 1/a $\ast$ (y-b). The parameters of the model could depict the thermo sensitivity of the cultivars. On the base of this model, the three doubled CO2 GCM scenarios were assessed. The average of these would suggest a decline in rice production of about 11% if we maintained the current cultivars. Future cultivar's developmental traits could be suggested by the two model parameters.

• Korean Journal of Agricultural and Forest Meteorology
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• v.20 no.3
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• pp.252-261
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• 2018

This study was conducted to develop a method to generate daily maximum and minimum temperatures using monthly data. We analyzed 30-year daily weather data of the 23 meteorological stations in South Korea and elucidated the parameters for predicting annual trend (center value ($\hat{U}$), amplitude (C), deviation (T)) and daily fluctuation (A, B) of daily maximum and minimum temperature. We use national average values for C, T, A and B parameters, but the center value is derived from the annual average data on each stations. First, daily weather data were generated according to the occurrence of rainfall, then calibrated using monthly data, and finally, daily maximum and minimum daily temperatures were generated. With this method, we could generate daily weather data with more than 95% similar distribution to recorded data for all 23 stations. In addition, this method was able to generate Growing Degree Day(GDD) similar to the past data, and it could be applied to areas not subject to survey. This method is useful for generating daily data in case of having monthly data such as climate change scenarios.

• Atmosphere
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• v.17 no.1
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• pp.45-53
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• 2007

In order to investigate the impacts of heat wave on human health, cluster analysis of meteorological elements (e.g., temperature, dewpoint, sea level pressure, visibility, cloud amount, and wind components) for identifying offensive synoptic air masses is employed. Meteorological data at Seoul during the past 30 years are used. The daily death data at Seoul are also employed. Occurrence frequency of heat waves which is defined by daily maximum temperature greater than the threshold temperature (i.e., $31.2^{\circ}C$) was analyzed. The result shows that the frequency and duration of heat waves at Seoul are increasing during the past 30 years. In addition, the increasing trend of the frequency and duration clearly appears in late spring and early autumn as well as summer. Factor analysis shows that 65.1% of the total variance can be explained by 4 components which are linearly independent. Eight clusters (or synoptic air masses) were classified and found to be optimal for representing the summertime air masses at Seoul, Korea. The results exhibit that cluster-mean values of meteorological variables of an offensive air mass (or cluster) are closely correlated with the observed and standardized deaths.

• Journal of Climate Change Research
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• v.7 no.2
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• pp.205-215
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• 2016

The relationship between the climate and the number of heat-related patients in South Korea was analysed in this study. The number of the patients was 1,612 during the summer 2011 to 2015 according to the Heat-related Illness (HRI) surveillance system. The coefficient of determination between the number of the patients and the daily maximum temperature was higher than that between the number of them and the other elements: the daily mean/minimum temperature and relative humidity. The thresholds of daily maximum and minimum temperature in metropolitan cities (MC) were higher than those in regions except for MC (RMC). The higher the maximum and minimum temperature became, the more frequently the heat-related illness rate was observed. The regional difference of this rate was that the rate in RMC was higher than that in MC. Prolonged heat wave and tropical night tended to cause more patients, which continued for 20 days and 31 days of maximum values, respectively. On the other hand, the relative humidity was not proportional to the number of the patients which was rather decreasing at over 70% of relative humidity.

• Korean Management Science Review
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• v.26 no.1
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• pp.77-91
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• 2009

It is the most important sucess factor for the electricity generation industry to minimize operations cost of surplus electricity generation through accurate demand forecasts. Temperature forecast is a significant input variable, because power demand is mainly linked to the air temperature. This study estimates the information value of the temperature forecast by analyzing the relationship between electricity load and daily air temperature in Korea. Firstly, several characteristics was analyzed by using a population-weighted temperature index, which was transformed from the daily data of the maximum, minimum and mean temperature for the year of 2005 to 2007. A neural network-based load forecaster was derived on the basis of the temperature index. The neural network then was used to evaluate the performance of load forecasts for various types of temperature forecasts (i.e., persistence forecast and perfect forecast) as well as the actual forecast provided by KMA(Korea Meteorological Administration). Finally, the result of the sensitivity analysis indicates that a $0.1^{\circ}C$ improvement in forecast accuracy is worth about $11 million per year.

• Journal of Environmental Science International
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• v.15 no.7
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• pp.653-657
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• 2006

Based on the monthly weather report of Korea Meteorological Administration (KMA) and daily sea surface temperature (SST) data from National Fisheries Research and Development Institute (NFRDI) (1995-2004), mean heat fluxes were estimated at the port of Yeosu. Net heat flux was transported from the air to the sea surface during February to September, and it amounts to $205 Wm^{-2}$ in daily average value in May. During October to January, the transfer of net heat flux was conversed from the sea surface to the air with $-70 Wm^{-2}$ in minimum of daily average value in December. Short wave radiation was ranged from $167 Wm^{-2}$ in December to $300 Wm^{-2}$ in April. Long wave radiation (Sensible heat) was ranged from $27 (-14) Wm^{-2}$ in July to $90 (79) Wm^{-2}$ in December. Latent heat showed $42 Wm^{-2}$ with its minimum in July and $104 Wm^{-2}$ with its maximum in October in daily average value.

• Magazine of the Korean Society of Agricultural Engineers
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• v.39 no.4
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• pp.114-121
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• 1997

In order to provide basic information for the estimation of evapotranspiration in the ponded direct seeding paddy field, both field lysimeter experiment and model prediction were performed to estimate daily ET. Various methods were used to predict daily reference crop ET and crop coefficients. Measure4 mean daily ET during the 1995 growing season varied from 5.9 to 6.1 mm depending on the species, while it varied from 5.1 to 5.5 mm in 1996. Model predicted mean daily ET during the 1995 growing season varied from 3.9 to 4.9 mm depending on the prediction model, while it varied from 3.5 to 4.7 mm in 1996. The smaller ET values both measured and predicted in 1996 were caused by the low values of temperature, sunshine hours, and solar radiation. Crop coefficients varied from 1.20 to 1.50 in 1995 depending on the prediction model, while it varied from 1.10 to 1.47 in 1996. Comparison of the seven reference crop ET prediction methods used in this study shows that the Penman-Monteith method and the FAO-Radiation method gave the lowest ET while the corrected Penman method and the Hargreaves method gave the largest ET. Since crop coefficients vary to a large extent based on the prediction methods, reference crop ET prediction method should be carefully selected in irrigation planning.

• The Korean Journal of Applied Statistics
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• v.27 no.5
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• pp.843-853
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• 2014

Accurate electricity demand forecasting for daily peak load is essential for management and planning at electrical facilities. In this paper, we rst, introduce the several time series models that forecast daily peak load and compare the forecasting performance of the models based on Mean Absolute Percentage Error(MAPE). The results show that the Reg-AR-GARCH model outperforms other competing models that consider Cooling Degree Day(CDD) and Heating Degree Day(HDD) as well as seasonal components.

• Journal of Ecology and Environment
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• v.47 no.2
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• pp.35-41
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• 2023

Background: Several species of amphibians in agricultural areas are often infected with ranaviruses; however, the biological or ecological factors that cause this infection are not well understood. In this study, we investigated whether local tadpole density, Gosner developmental stage, and weather conditions affected ranavirus infection in Dryophytes japonicus tadpoles in rice paddies over three months. Results: During the study, eight samplings were undertaken between June 6 and August 21, 2022. No die-off of tadpoles occurred, but 20 of 110 tadpoles (18.8%) were found to be infected with ranavirus. The tadpole density at the sampling site and Gosner stage of the sampled tadpoles were not related to the daily ranavirus infection rate. The mean daily highest temperature during the two weeks prior to the sampling date and the mean daily lowest and highest temperatures during the week prior to the sampling date were negatively related to the daily infection rate. Conclusions: Our results suggest that low and extreme temperatures caused by flooding and draining of paddy fields or climate change in summer could be a significant risk factor for ranavirus infection in summer-breeding frogs in agricultural areas.

• Atmosphere
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• v.24 no.1
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• pp.29-38
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• 2014

A characteristic of snowfall and minimum temperature variability in South Korea with respect to the variability of Arctic Oscillation (AO) was investigated. The climatic snowfall regions of South Korea based on daily new fresh snowfall data of 59 Korea Meteorological Administration (KMA) stations data corresponding to the sign of AO index during December to February 1979~2011 were classified. Especially, the differences between snowfalls of eastern regions and that of western regions in South Korea were seen by each mean 1000hPa geopotential height fields, which is one of physical structure, for the selected cases over the East Asia including the Korean Peninsula. Daily minimum temperature variability of 59 KMA station data and daily AO index during the same period were investigated using Cyclo-stationary empirical orthogonal function (CSEOF) analysis. The first CSEOF of wintertime daily AO index and that of minimum temperature of 59 KMA stations explain 33% and 66% of total variability, respectively. Correlation between principal component time series corresponding to the first CSEOF of AO index and that of temperature at the period of 1990s is over about -0.7 when that of AO index leads about 40 days.