• Korean Journal of Agricultural and Forest Meteorology
• /
• v.23 no.1
• /
• pp.1-14
• /
• 2021

Onions are a representative produce that requires supply-demand control measures due to large fluctuations in production and price by growing season. Accurate forecasts of crop production can improve the effectiveness of such measures. However, it is challenging to obtain accurate estimates of crop productivity for onions because they are mainly grown on the open fields. The objective of this study was to perform the empirical analysis of the relationship between factors for crop growth and meteorological conditions, which can support the development of models to predict crop growth and production. The growth survey data were collected from open fields. The survey data included the weight of above ground organs as well as that of the bulbs. The estimates of meteorological data were also compiled for the given fields. Correlation analysis between these factors was performed. The random forest was also used to compare the importance of the meteorological factors by the growth stage. Our results indicated that insolation in early March had a positive effect on the growth of the above-ground. There was a negative correlation between precipitation and the growth of the above-ground at the end of March although it has been suggested that drought can deter the growth of onion. The negative effects of precipitation and daylight hours on the growth of the above-ground and under-ground were significant during the harvest period. These meteorological factors identified by growth stage can be used to develop models for onion growth and production forecast.

• Journal of Convergence for Information Technology
• /
• v.9 no.11
• /
• pp.103-109
• /
• 2019

The purpose of this study is to examine various existing models that analyze the economic value of meteorological information, to present a new analysis model, a market model, and to quantitatively analyze the economic value of meteorological information in the Korean service industry using the market model. The research method of this paper will basically use empirical analysis along with the theoretical approach to critically examine the existing analytical model of economic value of meteorological information and to suggest a new analytical model. The analysis results are as follows. Theoretically, the marginal cost of firms is reduced by providing the amount of weather information, and social welfare is increased by the increase of consumer and producer surplus. In this paper, the marginal cost of 1% increase in the amount of weather information decreases by 0.101% and the increase in social welfare increases by 1,247billion Won in 2017. On the other hand, in the accommodation and restaurant sectors, the marginal cost due to a 1% increase in weather information decreased by 0.218%, and the social welfare increase increased by 308billion Won in 2017.

• Journal of the Korean earth science society
• /
• v.41 no.6
• /
• pp.575-587
• /
• 2020

Meteorological phenomena are observed by the Korea Meteorological Administration in a variety of ways (e.g., surface, upper-air, marine, ocean, and aviation). However, there are limits to the meteorological observation of the planetary boundary layer (PBL) that greatly affects human life. In particular, observations using a sonde or aircraft require significant observational costs in economic terms. Therefore, the goal of this study was to measure and analyze the meteorological factors of the vertical distribution of the see-land breeze among local meteorological phenomena using meteorological drones. To investigate the spatial distribution of the see-land breeze, a same integrated meteorological sensor was mounted on each drone at three different points (seaside, bottom of mountain, and mountainside), including the Boseong tall tower (BTT) at the Boseong Standard Weather Observatory (BSWO) in the Boseong region. Vertical profile observations for air temperature, relative humidity, wind direction, wind speed, and air pressure were conducted up to 400 m every 30 minutes from 1100 LST to 1800 LST on August 4, 2018. The spatial characteristics of meteorological phenomena for temperature, relative humidity, and atmospheric pressure were not shown at the four points. Strong winds (~8 m s-1) were observed from the midpoint (~100 m) at strong solar radiation hour, and in the afternoon the wind direction changed from the upper layer at the inland area to the west wind. It is expected that the analysis results of the lower atmospheric layer observed using the meteorological drone may help to improve the weather forecast more accurately.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.30 no.2
• /
• pp.89-98
• /
• 2007

In this paper the economic value of weather forecasts is valuated for profit-oriented enterprise decision-making situations. Value is estimated in terms of monetary profits (or benefits) resulted from the forecast user's decision under the specific payoff structure, which is represented by a profit/loss ratio model combined with a decision function and a value score (VS). The forecast user determines a business-related decision based on the probabilistic forecast, the user's subjective reliability of the forecasts, and the payoff structure specific to the user's business environment. The VS curve for a meteorological forecast is specified by a function of the various profit/loss ratios, providing the scaled economic value relative to the value of a perfect forecast. The proposed valuation method based on the profit/loss ratio model and the VS is adapted for hypothetical sets of forecasts and verified for site-specific probability of precipitation forecast of 12 hour and 24 hour-lead time, which is generated from Korea meteorological administration (KMA). The application results show that forecast information with shorter lead time can provide the decision-makers with great benefits and there are ranges of profit/loss ratios in which high subjective reliability of the given forecast is preferred.

• Journal of the Korean Society for Aviation and Aeronautics
• /
• v.19 no.1
• /
• pp.29-37
• /
• 2011

Last April, Europe was severly damaged as all social and economic activities came to a halt prompted by the cancellation of all flights resulting from volcanic ash. This exemplifies that the meteorology conditions have significant influence on the flights of airplanes. Hence, in this research the influence that the meteorology has on the domestic flights and its characteristics will be examined, and the core meteorological factors that influence flights in each airport will be drawn. In order to do this, statistical analysis on the influence that the meteorology has on flights was carried out in order to analyze the data about flight cancelation and delay and also its cause, primarily based on the Gimpo, Gimhae, and the Jeju airports. As a result, first, the meteorological factors which impact flight cancellation and delay were different among the domestic airports, and second, it was analyzed that fog was the main meteorological factor in the Gimpo airport, strong wind in the Jeju airport, and fog in the Gimhae airport. Third, between the day the flights were cancelled and delayed occurred, and the day that weren't, the fact that there existed a difference among the actual meteorological factors was statistically drawn. With the result of such analysis, meteorological factors pertaining to the cancellation and delay of flights must be considered seperately by each airport and specialized meteorological information must be provided accordingly. Further, when selecting the position of an airport that is to be constructed in the future, implications that there is a definite need for the meteorology effect evaluation based on past meteorology data can be drawn.

• Atmosphere
• /
• v.31 no.4
• /
• pp.461-472
• /
• 2021

Yeongdong has frequently suffered from severe snowstorms, which generally give rise to societal and economic damages to the region in winter. In order to understand its mechanism, there has been a long-term measurement campaign, based on the rawinsonde measurements for every snowfall event at Gangneung since 2014. The previous observations showed that a typical heavy snowfall is generally accompanied with northerly or northeasterly flow below the snow clouds, generated by cold air outbreak over the relatively warmer East Sea. An intensive and multi-institutional measurement campaign has been launched in 2019 mainly in collaboration with Gangwon Regional Office of Meteorology and National Institute of Meteorological Studies of Korean Meteorological Administration, with a special emphasis on winter snowfall and spring windstorm altogether. The experiment spanned largely from February to April with comprehensive measurements of frequent rawinsonde measurements at a super site (Gangneung) with continuous remote sensings of wind profiler, microwave radiometers and weather radar etc. Additional measurements were added to the campaign, such as aircraft dropsonde measurements and shipboard rawinsonde soundings. One of the fruitful outcomes is, so far, to identify a couple of cold air damming occurrences, featuring lowest temperature below 1 km, which hamper the convergence zone and snow clouds from penetrating inland, and eventually make it harder to forecast snowfall in terms of its location and timing. This kind of comprehensive observation campaign with continuous remote sensings and intensive additional measurement platforms should be conducted to understand various orographic precipitation in the complex terrain like Yeongdong.

• Journal of Satellite, Information and Communications
• /
• v.7 no.1
• /
• pp.13-20
• /
• 2012

Despite of growing concern for developing meteorological satellites, poor investment has been realized to acquire effective and efficient satellite image processing technologies. In this study, not only qualitative exploration on mapping each elementary technology into related industries but quantitative inter-industry analysis induced from Total Cost of Ownership (TCO) of the Korean satellite image processing system were performed. Furthermore, economic assessment has been made by estimating internal rate of return(IRR) for the benefits returned versus TCO of the system. The results showed that agriculture and fisheries industry, tourist and leisure industry, and transportation industry were highly related with the acquisition of the system, and that 9.1 billion won of production-induced effects, 3.3 billion won of value-added-induced effects, and 54 individuals of employment-induced effects were anticipated except for those of directly relevant industries. Even in the pessimistic scenario, 7% of IRR exceeding 5.5% assumed as current public rate was postulated, consequently, the investment was fairly justified.

• Atmosphere
• /
• v.29 no.4
• /
• pp.501-509
• /
• 2019

Asian Dust is a meteorological phenomenon that sand particles are raised from the arid and semi-arid regions-Taklamakan Desert, Gobi Desert and Inner Mongolia in China-and transported by westerlies and deposited on the surface. Asian dust results in a negative effect on human health as well as environmental, social and economic aspects. For monitoring of Asian Dust, Korea Meteorological Administration operates 29 stations using a continuous ambient particulate monitor. Kim et al. (2016) developed an automatic quality check (AQC) algorithm for objective and systematic quality check of observed PM₁₀ concentration and evaluated AQC with results of a manual quality check (MQC). The results showed the AQC algorithm could detect abnormal observations efficiently but it also presented a large number of false alarms which result from valid error check. To complement the deficiency of AQC and to develop an AQC system which can be applied in real-time, AQC has been modulated. Based on the analysis of instrument status codes, valid error check process was revised and 6 status codes were further considered as normal. Also, time continuity check and spike check were modified so that posterior data was not referred at inspection time. Two-year observed PM₁₀ concentration data and corresponding MQC results were used to evaluate the modulated AQC compared to the original AQC algorithm. The results showed a false alarm ratio decreased from 0.44 to 0.09 and the accuracy and the probability of detection were conserved well in spite of the exclusion of posterior data at inspection time.

• Journal of Environmental Science International
• /
• v.22 no.9
• /
• pp.1171-1180
• /
• 2013

Recent climate change has led to fluctuations in agricultural production, and as a result national food supply has become an important strategic factor in economic policy. As such, in this study, panel data was collected to analyze the effects of seven meteorological elements and using the Lagrange multipliers method, the fixed-effects model for the production of five types of food crop and the seven meteorological elements were analyzed. Results showed that the key factors effecting increases in production of rice grains were average temperature, average relative humidity and average ground surface temperature, while wheat and barley were found to have positive correlations with average temperature and average humidity. The implications of this study are as follow. First, it was confirmed that the meteorological elements have profound effects on the production of food crops. Second, when compared to existing studies, the study was not limited to one food crop but encompassed all five types, and went beyond other studies that were limited to temperature and rainfall to include various meterological elements.

• Atmosphere
• /
• v.30 no.3
• /
• pp.237-248
• /
• 2020

In order to effectively prepare for damage caused by weather events, it is important to proactively identify the possible impacts of weather phenomena on the domestic society and economy. Text mining and Network analysis are used in this paper to build a database of damage types and levels caused by heat wave. We collect news articles about heat wave from the SBS news website and determine the primary and secondary effects of that through network analysis. In addition to that, based on the frequency with which each impact keyword is mentioned, we estimate how much influence each factor has. As a result, the types of impacts caused by heat wave are efficiently derived. Among these types of impacts, we find that people in South Korea are mainly interested in algae and heat-related illness. Since this technique of analysis can be applied not only to news articles but also to social media contents, such as Twitter and Facebook, it is expected to be used as a useful tool for building weather impact databases.