• Journal of the Korean Geographical Society
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• v.42 no.1 s.118
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• pp.1-14
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• 2007

This study aimed to evaluate weather forecast accuracies of minimum temperature, maximum temperature, precipitation and sky cover by the localized land forecast areas over South Korea Average forecast accuracy score of precipitation was the lowest while that of sky cover was the highest during the study period Overall forecast accuracy scores for Gangwon-do was the lowest while those for Gyeongsangnam-do and Gyeongsangbuk-do were higher than other areas. The frequencies of perfect forecast(eight points) by seasons, were the highest during winter and the lowest during summer. pressure pattern analyses for days when forecast accuracy scores were poor, showed that precipitation forecast accuracy scores were lower due to the movement of the stationary fronts during summers. When continental polar air masses expanded, forecast accuracy of temperature became greatly lower during autumns and winters As the migratory anticyclone pattern rapidly moved, forecast accuracy became lower during springs and autumns. Forecast accuracies were compared by wind directions at 850hPa for the Young-dong region where forecast accuracy was the lowest. Forecast accuracy scores on minimum and maximum temperatures were low when winds were westerlies and forecast accuracy scores of precipitation were low when winds were easterlies.

• Journal of Korean Elementary Science Education
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• v.17 no.2
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• pp.123-136
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• 1998

In this study, it was purposed to investigate that the student's understading and usage of weather information for the students of elementary, middle and high school The questionaire of 20 questions of 5 categories which included how to get weather information, the understanding of reason for variation of weather elements, the abilities of reading weather map, understanding of weather forecast and the necessity and usefulness of weather map and clouds pictures of weather satellite were prepared and 2 classes of elementary school 5th grade each one class of 2nd and 3rd grade of middle school and 2 classes of high school were tested. followings were revealed in this study; 1) Students of all school are fond of TV watching to get weather information as they used to. 2) They think air temperatures is the most important weather elements and then rainfall. 5ut they seems to unknown the reason why weather elements are vary. 3) They seems to have poor ability of reading weather symbols in weather map and the distribution of air pressure systems. 4) They can read and understand about the reports of words on weather forecast, but most of them can't make weather forecast by the reading of weather map. 5) More than half of students think that the weather map is helpful and especially the cloud pictures from weather satellite is useful for usage of weather information.

• Atmosphere
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• v.26 no.1
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• pp.59-72
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• 2016

The comparison of prediction errors in geopotential height, temperature, and precipitation forecasts is made quantitatively to evaluate medium-range forecast skills between Global Seasonal Forecasting System version 5 (GloSea5) and Unified Model (UM) in operation by Korea Meteorological Administration during 2014. In addition, the performances in prediction of sea surface temperature anomaly in NINO3.4 region, Madden and Julian Oscillation (MJO) index, and tropical storms in western north Pacific are evaluated. The result of evaluations appears that the forecast skill of UM with lower values of root-mean square error is generally superior to GloSea5 during forecast periods (0 to 12 days). The forecast error tends to increase rapidly in GloSea5 during the first half of the forecast period, and then it shows down so that the skill difference between UM and GloSea5 becomes negligible as the forecast time increases. Precipitation forecast of GloSea5 is not as bad as expected and the skill is comparable to that of UM during 10-day forecasts. Especially, in predictions of sea surface temperature in NINO3.4 region, MJO index, and tropical storms in western Pacific, GloSea5 shows similar or better performance than UM. Throughout comparison of forecast skills for main meteorological elements and weather extremes during medium-range, the effects of initial and model errors in atmosphere-ocean coupled model are verified and it is suggested that GloSea5 is useful system for not only seasonal forecasts but also short- and medium-range forecasts.

• Communications for Statistical Applications and Methods
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• v.25 no.2
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• pp.199-215
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• 2018

Interest in $PM_{10}$ concentrations have increased greatly in Korea due to recent increases in air pollution levels. Therefore, we consider a forecasting model for next day $PM_{10}$ concentration based on the principal elements of air pollution, weather information and Beijing $PM_{2.5}$. If we can forecast the next day $PM_{10}$ concentration level accurately, we believe that this forecasting can be useful for policy makers and public. This paper is intended to help forecast a daily mean $PM_{10}$, a daily max $PM_{10}$ and four stages of $PM_{10}$ provided by the Ministry of Environment using various data mining techniques. We use seven models to forecast the daily $PM_{10}$, which include five regression models (linear regression, Randomforest, gradient boosting, support vector machine, neural network), and two time series models (ARIMA, ARFIMA). As a result, the linear regression model performs the best in the $PM_{10}$ concentration forecast and the linear regression and Randomforest model performs the best in the $PM_{10}$ class forecast. The results also indicate that the $PM_{10}$ in Seoul is influenced by Beijing $PM_{2.5}$ and air pollution from power stations in the west coast.

• Journal of the Korea Institute of Building Construction
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• v.12 no.3
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• pp.257-265
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• 2012

Many construction companies are simultaneously carrying out numerous projects in the housing construction industry. It is essential to accurately forecast the cash flow of a project through optimal process management and resource input in order to manage funds rationally and enhance the competitiveness of a company. Current cash flow forecasting methods offer lower accuracy due to a large gap between the revenue and expenditure element. Expenditure elements depends on the real-time changing actual cost for work performed. This research survey was conducted on the actual state of construction management of K company to investigate the problems of cash flow forecasting. To achieve this, the work process and construction management system were integrated to improve the cost management system of K company. To accurately forecast the cash flow of a project, revenue and expenditure elements were displayed in the total cash flow forecast window. This research is expected to assist in the implementation of a system of cash flow forecasting on housing construction by excluding negative elements of revenue and expenditure.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.8
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• pp.647-658
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• 2021

Analysts' forecasts are important for providing useful guidance to investors, especially individual or small investors, and therefore it becomes critical to identify the elements which can potentially increase errors in analysts' forecasts. This study investigates potential factors which can lead to errors in forecasting by analysts, specifically in terms of the level and attributes of corporate earnings. Utilizing a sample of firms listed on the Korean stock markets, this study provides evidence that firms with more volatile and unpredictable earnings feature less accurate analyst forecasts. This study fills a void in the literature by conducting empirical tests for earnings attributes in terms of volatility and unpredictability that could potentially undermine the forecast accuracy. The negative association between the quality of earnings and forecast accuracy is more pronounced for firms with negative net income values. Additional analysis demonstrates that forecast accuracy is significantly lower for the fourth quarter than for other fiscal quarters and that fourth quarter earnings tend to be more volatile and unpredictable. This study contributes to the literature by providing new empirical evidence regarding the comprehensive effects of earnings quality and level on analysts' forecasting accuracy and further suggests potential factors contributing to the fourth quarter anomaly in analyst forecasts in terms of earnings attributes.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.13 no.21
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• pp.11-18
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• 1990

Because of the descent trend of the recent oil price and the ascent elements of the manufacturing price of public coal. the future demand of public coal is very obscured. In this paper, forecast the public coal demand by the regression analysis method reflected the policy and economic index of alternative energies.

• Korean Journal of Agricultural and Forest Meteorology
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• v.14 no.1
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• pp.1-10
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• 2012

Digital Forecast of the Korea Meteorological Administration (KMA) represents 5 km gridded weather forecast over the Korean Peninsula and the surrounding oceanic regions in Korean territory. Digital Forecast provides 12 weather forecast elements such as three-hour interval temperature, sky condition, wind direction, wind speed, relative humidity, wave height, probability of precipitation, 12 hour accumulated rain and snow, as well as daily minimum and maximum temperatures. These forecast elements are updated every three-hour for the next 48 hours regularly. The objective of this study was to construct Forest Fire Danger Rating Systems on the Korean Peninsula (FFDRS_KORP) based on the daily weather index (DWI) and to improve the accuracy using the digital forecast data. We produced the thematic maps of temperature, humidity, and wind speed over the Korean Peninsula to analyze DWI. To calculate DWI of the Korean Peninsula it was applied forest fire occurrence probability model by logistic regression analysis, i.e. $[1+{\exp}\{-(2.494+(0.004{\times}T_{max})-(0.008{\times}EF))\}]^{-1}$. The result of verification test among the real-time observatory data, digital forecast and RDAPS data showed that predicting values of the digital forecast advanced more than those of RDAPS data. The results of the comparison with the average forest fire danger rating index (sampled at 233 administrative districts) and those with the digital weather showed higher relative accuracy than those with the RDAPS data. The coefficient of determination of forest fire danger rating was shown as $R^2$=0.854. There was a difference of 0.5 between the national mean fire danger rating index (70) with the application of the real-time observatory data and that with the digital forecast (70.5).

• Korean Business Review
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• v.22 no.2
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• pp.61-86
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• 2009

The purpose of this article is to investigate the effects of cash flow and accrual, which are the elements of earnings, and those of the elements of cash flow and accrual on the consistency of cash flow and firm's value. We analyzed 4 kinds of regression models, of which the independent variables are this period's cash flow, the elements of cash flow, accrual, and the elements of accrual, and the dependent variables are the next period's cash flow, and the stock price at the end of financial statements disclosure months, respectively. The sample firms were the manufacturing companies listed on the Stock Exchange 1980 through 2006, of which the fiscal year ended in December. And, the results of the analyses are as follows: Cash flow and accrual are shown to have significant relationships with cash flow consistency and the evaluations of firms' value. And, the elements of cash flow or accrual proved to have more influence than the total amount of them, on cash flow consistency and the evaluation of firms' value. Also, the results present that some of the elements of cash flow and accrual differently affect cash flow consistency and the evaluation of firms' value. Accordingly, this study indicates that each of the elements of cash flow and accrual needs to be considered respectively rather than the total amount of them, in the case that cash flow and accrual are used in the decision-making concerned with the forecast of cash flow and the evaluation of firms' value. This study also shows that each element of cash flow and accrual needs to be used differently for cash flow forecast and the evaluation of firms' value.

• Atmosphere
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• v.28 no.2
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• pp.187-200
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• 2018

The heavy snowfall phenomenon with thunder and lightning occurred in Yeongdong coastal region on 20 January 2017. Amount of snow on that day was a maximum of 47 cm and was concentrated in a short time (2 hours) at the Yeongdong coastal area. The mechanism of thundersnow was investigated to describe in detail using observational data and numerical simulation (Weather Research and Forecast, WRF) applied lightning option. The results show that a convective cloud occurred at the Yeongdong coastal area. The east wind flow was generated and the pressure gradient force was maximized by the rapidly developed cyclone. The cold and dry air in the upper atmosphere has descended (so called tropopause folding) atmospheric lower layer at precipitation peak time (1200 LST). In addition, latent heat in the lower atmosphere layer and warm sea surface temperature caused thermal instability. The convective cloud caused by the strong thermal instability was developed up to 6 km at that time. And the backdoor cold front was determined by the change characteristics of meteorological elements and shear line in the east sea. Instability indexes such as Total totals Index (TT) and Lightning Potential Index (LPI) are also confirmed as one of good predictability indicates for the explosive precipitation of convective rainfall.