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Mr. In-Gyum Kim
National Institute of Meteorological Sciences, Korea Meteorological Administration

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Journal article
Published: 21 June 2021 in Sustainability
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Meteorological information at an arrival airport is one of the primary variables used to determine refueling of discretionary fuel. This study evaluated the economic value of terminal aerodrome forecasts (TAF), which has not been previously quantitatively analyzed in Korea. The analysis data included 374,716 international flights that arrived at Incheon airport during 2017–2019. A cost–loss model was used for the analysis, which is a methodology to evaluate forecast value by considering the cost and loss that users can expect, considering the decision-making result based on forecast utilization. The value was divided in terms of improving fuel efficiency and reducing CO2 emissions. The results of the analysis indicate that the annual average TAF value for Incheon Airport was approximately 2.2 M–20.1 M USD under two hypothetical rules of refueling of discretionary fuel. This value is up to 26.2% higher than the total budget of 16.3 M USD set for the production of aviation meteorological forecasts by the Korea Meteorological Administration (KMA). Further, it is up to 10 times greater than the 2 M USD spent on aviation meteorological information fees collected by the KMA in 2018.

ACS Style

In-Gyum Kim; Hye-Min Kim; Dae-Geun Lee; Byunghwan Lim; Hee-Choon Lee. Economic Value of Terminal Aerodrome Forecasts at Incheon Airport, South Korea. Sustainability 2021, 13, 6965 .

AMA Style

In-Gyum Kim, Hye-Min Kim, Dae-Geun Lee, Byunghwan Lim, Hee-Choon Lee. Economic Value of Terminal Aerodrome Forecasts at Incheon Airport, South Korea. Sustainability. 2021; 13 (12):6965.

Chicago/Turabian Style

In-Gyum Kim; Hye-Min Kim; Dae-Geun Lee; Byunghwan Lim; Hee-Choon Lee. 2021. "Economic Value of Terminal Aerodrome Forecasts at Incheon Airport, South Korea." Sustainability 13, no. 12: 6965.

Journal article
Published: 15 October 2020 in Sustainability
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The weather forecast service industry needs to understand customers’ opinions of the weather forecast to enhance sustainable communication between forecast providers and recipients particularly influenced by inherent uncertainty in the forecast itself and cultural factors. This study aims to investigate the potential for using social media data to analyze users’ opinions of the wrong weather forecast. Twitter data from Korea in 2014 are analyzed using textual analysis and association rule mining to extract meaningful emotions or behaviors from weather forecast users. The results of textual analysis show that the frequency of negative opinions is considerably high compared to positive opinions. More than half of the tweets mention precipitation forecasts among the meteorological phenomena, implying that most Koreans are sensitive to rain events. Moreover, association rules extracted from the negative tweets reveal a pattern of user criticism according to the seasons and types of forecast errors such as a “false alarm” or “miss” error. This study shows that social media data can provide valuable information on the actual opinion of the forecast users in almost real time, enabling the weather forecast providers to communicate effectively with the public.

ACS Style

Ki-Kwang Lee; In-Gyum Kim. Social Media Data Analytics to Enhance Sustainable Communications between Public Users and Providers in Weather Forecast Service Industry. Sustainability 2020, 12, 8528 .

AMA Style

Ki-Kwang Lee, In-Gyum Kim. Social Media Data Analytics to Enhance Sustainable Communications between Public Users and Providers in Weather Forecast Service Industry. Sustainability. 2020; 12 (20):8528.

Chicago/Turabian Style

Ki-Kwang Lee; In-Gyum Kim. 2020. "Social Media Data Analytics to Enhance Sustainable Communications between Public Users and Providers in Weather Forecast Service Industry." Sustainability 12, no. 20: 8528.