• Environmental and Resource Economics Review
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• v.29 no.4
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• pp.419-442
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• 2020

The majority of the natural gas demand in South Korea is mainly determined by the heating demand. Accordingly, there is a distinct seasonality in which the gas demand increases in winter and decreases in summer. Moreover, the degree of sensitiveness to temperature on gas demand has changed over time. This study firstly introduces changing temperature response function (TRF) to capture effects of changing seasonality. The temperature effect (TE), estimated by integrating temperature response function with daily temperature density, represents for the amount of gas demand change due to variation of temperature distribution. Also, this study presents an innovative way in forecasting daily temperature density by employing functional principal component analysis based on daily max/min temperature forecasts for the five big cities in Korea. The forecast errors of the temperature density and gas demand are decreased by 50% and 80% respectively if we use the proposed forecasted density rather than the average daily temperature density.

• Journal of Environmental Science International
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• v.22 no.8
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• pp.965-977
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• 2013

Reliable long-term streamflow forecasting is invaluable for water resource planning and management which allocates water supply according to the demand of water users. It is necessary to get probabilistic forecasts to establish risk-based reservoir operation policies. Probabilistic forecasts may be useful for the users who assess and manage risks according to decision-making responding forecasting results. Probabilistic forecasting of seasonal inflow to Andong dam is performed and assessed using selected predictors from sea surface temperature and 500 hPa geopotential height data. Categorical probability forecast by Piechota's method and logistic regression analysis, and probability forecast by conditional probability density function are used to forecast seasonal inflow. Kernel density function is used in categorical probability forecast by Piechota's method and probability forecast by conditional probability density function. The results of categorical probability forecasts are assessed by Brier skill score. The assessment reveals that the categorical probability forecasts are better than the reference forecasts. The results of forecasts using conditional probability density function are assessed by qualitative approach and transformed categorical probability forecasts. The assessment of the forecasts which are transformed to categorical probability forecasts shows that the results of the forecasts by conditional probability density function are much better than those of the forecasts by Piechota's method and logistic regression analysis except for winter season data.

• Korean journal of applied entomology
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• v.38 no.3
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• pp.231-240
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• 1999

The long-term tend an pattern changes of Chilo suppressalis(Walker) occurrence in Suwon were analyzed and the forecasting models for spring emergence of C. suppressalis in Suwon were developed. From 1965 to 196, the population dynamics of C. suppressalis in Suwon shows a cyclic fluctuation with one large peak an one small peak, and its periodicity was ca. 36 generations(18 years). C. suppressalis population dynamics in Suwon was characterized as controlled by the endogenous dynamics dictated by the 1st order negative feedback mechanism (fast density dependence). The dynaics mechanism of C. suppressalis populations was not changed although its population density decreased drastically over the years. Using th dta of C. suppressalis spring occurrence in Suwon, forecasting models for spring emergence of C.supressalis were developed based on temperature-dependent development model or degree days. In general, these models well described the C. suppressalis spring emergence pattern in Suwon. Also, forecasting problems in spring moth emergence related with C. suppressalis population dynamics were discussed.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.35 no.1
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• pp.46-56
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• 2002

The low temperature, low salinity and low density sea water which was originated from the southern part of the Yellow Sea and distributed from the surface to 20 m depth was transported by the northwesterly wind during the period from the middle of March to the beginning of April, 1998 and had an influence on the northern coastal sea area of Cheju Island. Accordingly, this kind of accumulated data may supply the fundamental data for the realtime monitoring of oceanographic conditions and may improve degree of the forecasting accuracy of fishing and oceanographic conditions.

• The Plant Pathology Journal
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• v.15 no.4
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• pp.158-161
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• 1999

We determined threshold environmental factros to initiate infection of pepper plants by Botrytis cinerea, a fungal pathogen of pepper gray mold, in two greenhouse conditions. A new efficient spore-trapping method was developed to estimate population density of airborne conidia in the greenhouses, and spore release was measured using a Kerssies' selective medium. At a given day, spores were released greater during daytime (mostly from 7:30 am to 10:30 am and at 4:30 pm) than nighttime. Diurnal and nocturnal temperatures in the greenhouse-1 were about $25^{\circ}$ and $17^{\circ}$,and relative humidity was 100% for prolonged 24 h due to rain on December 17, 1997. Population density of air-borne conidia was 3.0$\times$103 conidia/ $0.5\textrm{m}^3$ after two days, and the initial infection occurred in ten days. During the same period of time in the greenhouse-2, diurnal temperature was about $25^{\circ}$ and nocturnal temperature was below $15^{\circ}$, and population density of air-borne conidia was 104 conidia/ $0.5\textrm{m}^3$. Under these conditions, the initial infection started in three days. This indicates that the early infection occurs under which diurnal temperature is approximately $25^{\circ}$, nocturnal temperature is maintained below $15^{\circ}$, and population density of air-borne conidia is 104 conidia/ $0.5\textrm{m}^3$ at saturated relative humidity condition.

• Journal of Environmental Science International
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• v.19 no.2
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• pp.171-184
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• 2010

Accurate simulation of the meteorological field is very important to assess the wind resources. Some researchers showed that sea surface temperature (SST) plays a leading role on the local meterological simulation. New Generation Sea Surface Temperature (NGSST), Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA), and Real-Time Global Sea Surface Temperature (RTG SST) have different spatial distribution near the coast and OSTIA shows the best accuracy compared with buoy data in the southeastern coast of the Korean Peninsula. Those SST products are used to initialize the Weather Research and Forecasting (WRF) Model for November 13-23 2008. The simulation of OSTIA shows better result in comparison with NGSST and RTG SST. NGSST shows a large difference with OSTIA in horizontal and vertical wind fields during the weak synoptic condition, but wind power density shows a large difference during strong synoptic condition. RTG SST shows the similar patterns but smaller the magnitude and the extent.

• KIEAE Journal
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• v.16 no.6
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• pp.69-75
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• 2016

Climate change has resulted in the urban heat island (UHI) effect throughout the globe, contributing to heat-related illness and fatalities. In order to reduce such damage, it is necessary to improve the climate observation network for precise observation of the urban thermal environment and quick UHI forecasting system. Purpose: This study analyzed the effective range of the climate observation network and the distribution of the existing Automatic Weather Stations (AWS) in Seoul to propose optimal locations for additional installment of AWS. Method: First, we performed quality analysis to pinpoint missing values and outliers within the high-density temperature data measured. With the result from the analysis, a spatial autocorrelation structure in the temperature data was tested to draw the effective range and correlation distance for each major time period. Result: As a result, it turned out that the optimal effective range for the climate observation network in Seoul in July was a radius of 2.8 kilometers. Based on this result, population density, and temperature data, we selected the locations for additional installment of AWS. This study is expected to be used to generate urban temperature maps, select and move measurement locations since it is able to suggest valid, specific spatial ranges when the data measured in point is converted into surface data.

• Journal of Environmental Science International
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• v.29 no.1
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• pp.45-54
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• 2020

High-resolution meteorological simulations were conducted using a Weather Research and Forecasting (WRF) model with an Urban Canopy Model (UCM) in the Ulsan Metropolitan Region (UMR) where large-scale industrial facilities are located on the coast. We improved the land cover input data for the WRF-UCM by reclassifying the default urban category into four detailed areas (low and high-density residential areas, commercial areas, and industrial areas) using subdivided data (class 3) of the Environmental and Geographical Information System (EGIS). The urban area accounted for about 12% of the total UMR and the largest proportion (47.4%) was in the industrial area. Results from the WRF-UCM simulation in a summer episode with high temperatures showed that the modeled temperatures agreed greatly with the observations. Comparison with a standard WRF simulation (WRF-BASE) indicated that the temporal and spatial variations in surface air temperature in the UMR were properly captured. Specifically, the WRF-UCM reproduced daily maximum and nighttime variations in air temperature very well, indicating that our model can improve the accuracy of temperature simulation for a summer heatwave. However, the WRF-UCM somewhat overestimated wind speed in the UMR largely due to an increased air temperature gradient between land and sea.

• Korean journal of applied entomology
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• v.58 no.4
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• pp.347-354
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• 2019

Temperature-dependent traits of Laodelphax striatellus, rice stripe virus vector, were investigated at 10 constant temperatures (12.5, 15.0, 17.5, 20.0, 22.5, 25.0, 27.5, 30.0, 32.5, and 35.0 ± 1℃) under a fixed photoperiod (14/10-hr light/dark cycle). Unit functions for the oviposition model were estimated and implemented into a population dynamics model using DYMEX. The longevity of L. striatellus adults decreased with increasing temperature (56.0 days at 15.0℃ and 17.7 days at 35.0℃). The highest total fecundity (515.9 eggs/female) was observed at 22.5℃, while the lowest (18.6 eggs/female) was observed at 35.0℃. Adult developmental rates, temperature-dependent fecundity, age-specific mortality rates, and age-specific cumulative oviposition rates were estimated. All unit equations described adult performances of L. striatellus accurately (r² =0.94~0.97). After inoculating adults, the constructed model was tested under pot and field conditions using the rice-plant hopper system. The model output and observed data were similar up to 30 days after inoculation; however, there were large discrepancies between observed and estimated population density after 30 days, especially for 1^st and 2^nd instar nymph densities. Model estimates were one or two nymphal stages faster than was observed. Further refinement of the model created in this study could provide realistic forecasting of this important rice pest.

• Atmosphere
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• v.28 no.2
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• pp.211-222
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• 2018

Cloud droplet activation process is well described by $K{\ddot{o}}hler$ theory and several parameterizations based on $K{\ddot{o}}hler$ theory are used in a wide range of models to represent this process. Here, we test the two different method of calculating the solute effect in the $K{\ddot{o}}hler$ equation, i.e., osmotic coefficient method (OSM) and ${\kappa}-K{\ddot{o}}hler$ method (KK). To do that, each method is implemented in the cloud droplet activation parameterization module of WRF-CHEM (Weather Research and Forecasting model coupled with Chemistry) model. It is assumed that aerosols are composed of five major components (i.e., sulfate, organic matter, black carbon, mineral dust, and sea salt). Both methods calculate similar representative hygroscopicity parameter values of 0.2~0.3 over the land, and 0.6~0.7 over the ocean, which are close to estimated values in previous studies. Simulated precipitation, and meteorological variables (i.e., specific heat and temperature) show good agreement with reanalysis. Spatial patterns of precipitation and liquid water path from model results and satellite data show similarity in general, but on regional scale spatial patterns and intensity show some discrepancy. However, meteorological variables, precipitation, and liquid water path do not show significant differences between OSM and KK simulations. So we suggest that the relatively simple KK method can be a good alternative to the OSM method that requires various information of density, molecular weight and dissociation number of each individual species in calculating the solute effect.