• Journal of The Korean Society of Agricultural Engineers
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• v.66 no.4
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• pp.17-26
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• 2024

This study aimed to design and build a web-based decision support system for wheat cultivation management. The system is designed to collect and measure the weather environment at the growth stage on a daily basis and predict the soil moisture content. Based on this, APSIM, one of the process-based crop models, was used to predict the potential yield of wheat cultivation in real time by making decisions at each stage. The decision-making system for wheat crop management was designed to provide information through a web-based dashboard in consideration of user convenience and to comprehensively evaluate wheat yield potential according to past, present, and future weather conditions. Based on the APSIM model, the system estimates the current yield using past and present weather data and predicts future weather using the past 40 years of weather data to estimate the potential yield at harvest. This system is expected to be developed into a decision support system for farmers to prescribe irrigation and fertilizer in order to increase domestic wheat production and quality by enhancing the yield estimation model by adding influence factors that can contribute to improving wheat yield.

• Journal of Korean Society for Atmospheric Environment
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• v.28 no.3
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• pp.261-272
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• 2012

In this study, climate variability was predicted by the Weather Research and Forecasting (WRF) model under two different scenarios (current trends scenario; SC1 and managed scenario; SC2) for future urban growth over the Seoul metropolitan area (SMA). We used the urban growth model, SLEUTH (Slope, Land-use, Excluded, Urban, Transportation, Hill-Shade) to predict the future urban growth in SMA. As a result, the difference of urban ratio between two scenarios was the maximum up to 2.2% during 50 years (2000~2050). Also, the results of SLEUTH like this were adjusted in the Weather Research and Forecasting (WRF) model to analysis the difference of the future climate for the future urbanization effect. By scenarios of urban growth, we knew that the significant differences of surface temperature with a maximum of about 4 K and PBL height with a maximum of about 200 m appeared locally in newly urbanized area. However, wind speeds are not sensitive for the future urban growth in SMA. These results show that we need to consider the future land-use changes or future urban extension in the study for the prediction of future climate changes.

• Journal of the Korean Solar Energy Society
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• v.29 no.5
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• pp.81-87
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• 2009

Computer simulation of buildings and solar energy systems is being used increasingly in energy assessments and design.. Building designers often now predict the performance of buildings simulation programmes that require hourly weather data. However, not all weather stations provide hourly data. Climate prediction models such as HadCM3 also provide the daily average dry bulb temperature as well as the maximum and minimum. Hourly temperature values are available for building thermal simulations that accounts for future changes to climate. In order to make full use of these predicted future weather data in building simulation programmes, algorithms for downscaling daily values to hourly values are required. This paper describes a more accurate method for generating hourly temperature values in the South Korea that uses all three temperature parameters from climate model. All methods were evaluated for accuracy and stability in terms of coefficient of determination and cumulative error. They were compared with hourly data collected in Seoul and Ulsan, South Korea.

• 한국태양에너지학회:학술대회논문집
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• 2011.04a
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• pp.54-58
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• 2011

According to the Fourth Assessment Report of the Inter governmental Panel on Climate Change(IPCC), climate change is already in progress around the world, and it is necessary to start mitigation and adaptation strategies for buildings in order to minimize adverse impacts. It is likely that the South Korea will experience milder winters and hotter and more extreme summers. Those changes will impact on building performance, particularly with regard to cooling and ventilation, with implications for the quality of the indoor environment, energy consumption and carbon emissions. This study generate weather data for future climate change for use in impacts studies using PRECIS (Providing REgional Climate for Impacts Studies). These scenarios and RCM (Regional Climate Model) are provided high-resolution climate-change predictions for a region generally consistent with the continental-scale climate changes predicted in the GCM (Global Climate Model).

• Atmosphere
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• v.29 no.4
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• pp.451-461
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• 2019

Medium-range forecast is highly dependent on ensemble forecast data. However, operational weather forecasters have not enough time to digest all of detailed features revealed in ensemble forecast data. To utilize the ensemble data effectively in medium-range forecasting, representative weather patterns in East Asia in this study are defined. The k-means clustering analysis is applied for the objectivity of weather patterns. Input data used daily Mean Sea Level Pressure (MSLP) anomaly of the ECMWF ReAnalysis-Interim (ERA-Interim) during 1981~2010 (30 years) provided by the European Centre for Medium-Range Weather Forecasts (ECMWF). Using the Explained Variance (EV), the optimal study area is defined by 20~60°N, 100~150°E. The number of clusters defined by Explained Cluster Variance (ECV) is thirty (k = 30). 30 representative weather patterns with their frequencies are summarized. Weather pattern #1 occurred all seasons, but it was about 56% in summer (June~September). The relatively rare occurrence of weather pattern (#30) occurred mainly in winter. Additionally, we investigate the relationship between weather patterns and extreme weather events such as heat wave, cold wave, and heavy rainfall as well as snowfall. The weather patterns associated with heavy rainfall exceeding 110 mm day^-1 were #1, #4, and #9 with days (%) of more than 10%. Heavy snowfall events exceeding 24 cm day^-1 mainly occurred in weather pattern #28 (4%) and #29 (6%). High and low temperature events (> 34℃ and < -14℃) were associated with weather pattern #1~4 (14~18%) and #28~29 (27~29%), respectively. These results suggest that the classification of various weather patterns will be used as a reference for grouping all ensemble forecast data, which will be useful for the scenario-based medium-range ensemble forecast in the future.

• Advances in environmental research
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• v.3 no.3
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• pp.253-281
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• 2014

The quest for enhanced thermal comfort for dwellings encompasses the holistic utilization of improved building fabric, impact of weather variation and amongst passive cooling design consideration the provision of appropriate ventilation and shading strategy. Whilst thermal comfort is prime to dwellings considerations, limited research has been done in this area with the attention focused mostly on non-dwellings. This paper examines the current and future thermal comfort implications of four different standard construction specifications which show a progressive increase in thermal mass and airtightness and is underpinned by the newly developed CIBSE adaptive thermal comfort method for assessing the risk of overheating in naturally ventilated dwellings. Interactive investigation on the impact of building fabric variation, natural ventilation scenarios, external shading and varying occupants' characteristics to analyse dwellings thermal comfort based on non-heating season of current and future weather patterns of London and Birmingham is conducted. The overheating analysis focus on the whole building and individual zones. The findings from the thermal analysis simulation are illustrated graphically coupled with statistical analysis of data collected from the simulation. The results indicate that, judicious integrated approach of improved design options could substantially reduce the operating temperatures in dwellings and enhance thermal comfort.

• Journal of Integrative Natural Science
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• v.10 no.4
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• pp.216-224
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• 2017

In the terrain of the Korean peninsula, mountainous and flat lands are complexly distributed in small areas. Therefore, local severe weather develops and disappears in a short time due to the influence of the terrain. Particularly in the case of local severe weather with heavy wind that has the greatest influence on aviation meteorology, the scale is very small, and it occurs and disappears in a short time, so it is impossible to predict with fragmentary data alone. So, we use weather radar to detect and predict local severe weather. However, due to the development of wireless communication services and the rapid increase of wireless devices, radio wave jamming and interference problems occur. In this research, we confirmed through the cases that when the radio interference echo which is one of the non-precipitation echoes that occur during the operation of the weather radar is displayed in the image, its form and shape are shown in a long bar shape, and have a strong dBZ. We also found the cause of the interference through the radio tracking process, and solved through the frequency channel negotiation and AP output minimizing. The more wireless devices increase as information communication technology develops in the future, the more emphasized the problem of radio wave interference will be, and we must make the radio interference eliminated through the development of the radio interference cancellation algorithm.

• Information Systems Review
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• v.26 no.2
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• pp.123-136
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• 2024

Weather significantly shapes daily life, impacting consumer behavior and psychology. Changes in weather influence ad receptivity, directly affecting corporate sales. Businesses strategically leverage weather in marketing efforts. Mobile devices have exponentially increased ad exposure, with real-time connectivity enhancing exposure time. Despite the need to empirically confirm weather's impact on mobile ad acceptance, research is lacking. This study explores weather's influence on mobile ad receptivity, considering environmental changes like air quality. Results aim to assist digital advertisers in refining targeted strategies with weather information.

• Journal of applied mathematics & informatics
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• v.9 no.2
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• pp.771-785
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• 2002

Many industries like energy, utilities, ice cream and leisure sports are closely related to the weather. In order to hedge weather related risks, they invest their assets with portfolios like option, coupons, future, and other weather derivatives. Among weather related derivatives, CDD and HDD index options are mainly transacted between companies. In this paper, the autocorrelation system of temperature will be checked for several cities in Korea and the parameter estimation will be carried based on the maximum likelihood estimation. Since the log likelihood increase as the number of parameters increases, we adopt the Schwarz information criterion .

• Journal of Environmental Science International
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• v.31 no.4
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• pp.357-363
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• 2022

In this study, we installed a weather observation tower tailored to the intertidal zone and established an intertidal weather observation system capable of real-time monitoring through a wireless network. This provided weather observation data representing the meteorological characteristics of the intertidal zone. To optimize this system in the future, we present practical directions for the development of observation equipment and for the data management and sharing, and we contribute to establishing the infrastructure.