• 한국환경과학회지
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• 제23권2호
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• pp.171-180
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• 2014

This study provides the empirical results of the customers' necessity and intentions of purchasing weather index insurance using survey of asking the customers' recognition about weather insurance. In this article, we discovered that not only the customers' past experience of loss but also the extent of damage and the effects that change in weather would have on their firm are positively related to an intention to purchase weather index insurance. In addition, the level of premiums was significantly higher for the highly-intended group of willing to purchase weather index insurance than the comparison group.

• 한국항공운항학회지
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• 제20권4호
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• pp.70-75
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• 2012

This paper is part of the research about the selection and justification of Jeju international airport as an aircraft category 'F' alternative airport, which is the results of an weather analysis based on meteorological statistics. As the results of the study, it has been only 1 day per year (58minutes) that weather conditions of Incheon and Jeju international airports, from January 2006 to June 2011, are below landing weather minimums of each airport at the same times. This means that these airports are not within the same meteorological region, which is against the current orthodoxy. In addition, it is very rare that weather conditions of Jeju international airports are below landing weather minimums when Incheon international airport is below landing weather minima. It shows that the meteorological characteristics of these regions differ widely and the designation of Jeju international airport as an alternative airport is scientifically reasonable.

• Water Engineering Research
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• 제4권3호
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• pp.111-126
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• 2003

Meteorological data are often needed to evaluate the long-term effects of proposed hydrologic changes. The evaluation is frequently undertaken using deterministic mathematical models that require daily weather data as input including precipitation amount, maximum and minimum temperature, relative humidity, solar radiation and wind speed. Stochastic generation of the required weather data offers alternative to the use of observed weather records. The precipitation is modeled by a Markov Chain-exponential model. The other variables are generated by multivariate model with means and standard deviations of the variables conditioned on the wet or dry status of the day as determined by the precipitation model. Ultimately, the objective of this paper is to compare Richardson's model and the improved weather generation model in their ability to provide daily weather data for the crop model to study potential impacts of climate change on the irrigation needs and crop yield. However this paper does not refer to the improved weather generation model and the crop model. The new weather generation model improved will be introduced in the Journal of KWRA.

• Journal of the Korean Data and Information Science Society
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• 제23권6호
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• pp.1309-1317
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• 2012

Stochastic weather generators are commonly used to simulate time series of daily weather, especially precipitation amount. Recently, a generalized linear model (GLM) has been proposed as a convenient approach to fitting these weather generators. In this paper, a stochastic weather generator is considered to model the time series of daily precipitation at Seoul in South Korea. As a covariate, global temperature is introduced to relate long-term temporal scale predictor to short-term temporal predictands. One of the limitations of stochastic weather generators is a marked tendency to underestimate the observed interannual variance of monthly, seasonal, or annual total precipitation. To reduce this phenomenon, we incorporate time series of seasonal total precipitation in the GLM weather generator as covariates. It is veri ed that the addition of these covariates does not distort the performance of the weather generator in other respects.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 추계학술대회 논문집 전력기술부문
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• pp.60-62
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• 2004

Transmission line outage is influenced by several weather factors: wind, rain snow, temperature, cloud and humidity. And most power system reliability studies assume a failure rate. It can be calculated by transmission line outage data and weather data. Also weather is divided into normal weather and adverse weather by failure rate analysis. The effect of failure rate is discussed with both normal weather and adverse weather. It can be used in effective information about system operation and planing.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2021년도 춘계학술대회
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• pp.67-69
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• 2021

기상레이더 영상은 시각적인 측면에서 가시성이 높아 다양한 활용이 가능하다. 즉 기상레이더 원시자료뿐 아니라 영상의 변화 특성만으로도 기상 현상의 흐름을 파악할 수 있는 장점을 가지고 있다. 특히 영상처리기법이 기상 연구 분야에서도 점차 확대되고 있고 기상레이더 영상과 같이 높은 해상도를 가지는 영상자료의 경우 영상처리기법이라는 새로운 접근을 통해 유용한 정보 생산을 기대할 수 있다. 본 연구에서는 영상처리기법 중 하나인 광학 흐름(Optical Flow) 기법으로 일정 시간 간격에 따른 기상레이더 이미지의 변화에서 기상 현상 흐름을 벡터로 산출하였다. 기상 현상 규모에 적합한 벡터 분석 해상도, 기상레이더 영상이 존재하지 않는 영역의 벡터보간, 특정 기상 현상의 흐름과 대기 전체 흐름 구분을 위한 상대 흐름 벡터 제거 등을 통해 분석하고자 하는 기상 현상의 특성을 도출하였다. 본 연구를 통해 기상레이더의 원시 자료 활용뿐 아니라 영상자료 고유의 특성 활용이라는 기상레이더 활용 영역 확대와 영상처리기법의 향후 기상학 분야에서의 활발한 활용을 기대해 본다.

• 생물환경조절학회지
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• 제23권3호
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• pp.192-198
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• 2014

To establish the design criteria for seasonal heating load calculation in greenhouses, standard weather data are required. However, they are being provided only at seven regions in Korea. So, instead of using standard weather data, in order to find the method to build design weather data for seasonal heating load calculation, heating degree-hour and heating degree-day were analyzed and compared by methods of fundamental equation, Mihara's equation and modified Mihara's equation using normal and thirty years from 1981 to 2010 hourly weather data provided by KMA and standard weather data provided by KSES. Average heating degree-hours calculated by fundamental equation using thirty years hourly weather data showed a good agreement with them using standard weather data. The 24 times of heating degree-day showed relatively big differences with heating degree-hour at the low setting temperature. Therefore, the heating degree-hour was considered more appropriate method to estimate the seasonal heating load. And to conclude, in regions which are not available standard weather data, we suggest that design weather data should be analyzed using thirty years hourly weather data. Average of heating degree-hours derived from every year hourly weather data during the whole period can be established as environmental design standards, and also minimum and maximum of them can be used as reference data for energy estimation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권8호
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• pp.3567-3582
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• 2020

Human activities are often affected by weather conditions. Automatic weather recognition is meaningful to traffic alerting, driving assistance, and intelligent traffic. With the boost of deep learning and AI, deep convolutional neural networks (CNN) are utilized to identify weather situations. In this paper, a three-channel convolutional neural network (3C-CNN) model is proposed on the basis of ResNet50.The model extracts global weather features from the whole image through the ResNet50 branch, and extracts the sky and ground features from the top and bottom regions by two CNN5 branches. Then the global features and the local features are merged by the Concat function. Finally, the weather image is classified by Softmax classifier and the identification result is output. In addition, a medium-scale dataset containing 6,185 outdoor weather images named WeatherDataset-6 is established. 3C-CNN is used to train and test both on the Two-class Weather Images and WeatherDataset-6. The experimental results show that 3C-CNN achieves best on both datasets, with the average recognition accuracy up to 94.35% and 95.81% respectively, which is superior to other classic convolutional neural networks such as AlexNet, VGG16, and ResNet50. It is prospected that our method can also work well for images taken at night with further improvement.

• 한국태양에너지학회 논문집
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• 제34권1호
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• pp.8-18
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• 2014

Building simulation is used in a variety of sectors. In its early years, building simulation was mainly used in the design phase of a building for basic functions. Recently, however, it has become increasingly important during the operating phase, for commissioning and facility management. Most building simulation tools are used to estimate the thermal environment and energy consumption performance, and hence, they require the inputting of hourly weather data. A building simulation used for prediction should take into account the use of standard weather data. Weather data, which is used as input for a building simulation, plays a crucial role in the prediction performance, and hence, the selection of appropriate weather data is considered highly important. The present study proposed a technique for generating real-time weather data files, as opposed to the standard weather data files, which are required for running the building simulation. The forecasted weather elements provided by the Korea Meteorological Administration (KMA), the elements produced by the calculations, those utilizing the built-in functions of Energy Plus, and those that use standard values are combined for hourly input. The real-time weather data files generated using the technique proposed in the present study have been validated to compare with measured data and simulated data via EnergyPlus. The results of the present study are expected to increase the prediction accuracy of building control simulation results in the future.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2015년도 학술발표회
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• pp.234-234
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• 2015

The global patterns of annual and extreme precipitation are projected to be altered by climate change. There are various weather systems which bring precipitation (e.g. tropical cyclone, extratropical cyclone, etc.). It is possible in some regions that multiple weather systems affect the changes of precipitation. However, previous studies have assessed only the changes of precipitation associated with individual weather systems. The relative contributions of the weather systems to the changes of precipitation have not been quantified yet. Also, the changes of the relative importance of weather systems have not been assessed. This study present the quantitative estimates of 1) the relative contributions of weather systems (tropical cyclone (TC), extratropical cyclone (ExC), and "others") to the future changes of annual and extreme precipitation and 2) the changes of the proportions of precipitation associated with each weather system in annual and extreme precipitation based on CMIP5 generation GCM outputs. Weather systems are objectively detected from twelve GCM outputs and six models are selected for further analysis considering the reproducibility of weather systems. In general, the weather system which is dominant in terms of producing precipitation in the present climate contributes the most to the changes of annual and extreme precipitation in each region. However, there are exceptions for the tendency. In East Asia, "others", which ranks the second in the proportion of annual precipitation in present climate, has the largest contribution to the increase of annual precipitation. It was found that the increase of the "others" annual precipitation in East Asia is mainly explained by the changes of that in summer season (JJA), most of which can be regarded as the summer monsoon precipitation. In Southeast Asia, "others" precipitation, the second dominant system in the present climate, has the largest contribution to the changes of very heavy precipitation (>99.9 percentile daily precipitation of historical period). Notable changes of the proportions of precipitation associated with each weather system are found mainly in subtropics, which can be regarded as the "hotspot" of the precipitation regime shift.