• Quantitative Bio-Science
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• v.37 no.2
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• pp.91-101
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• 2018

This study has analyzed applicable characteristics on big data of the meteorology and climate depending on press releases in the media. As a result, more than half of them were conducted by governmental departments and institutions (26.9%) and meteorological administration (25.0%). Most articles were written by journalists, especially the highest portion stems from straight articles focusing on delivering simple information. For each field, the number of cases had listed in order of rank to be exposed to the media; information service, business management, farming, livestock, and fishing industries, and disaster management, but others did rank far behind; insurance, construction, hydrology and energy. Application of big data about meteorology and climate differed depending on the seasonal change, it was directly related to temperature information during spring, to weather phenomenon such as monsoon and heat wave during summer, to meteorology and climate information during fall, and to weather phenomenon such as cold wave and heavy snow during winter.

• Journal of Electrical Engineering and Technology
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• v.12 no.2
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• pp.969-980
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• 2017

Galloping is one of the most serious vibration problems in transmission lines. Power lines can be extensively damaged owing to aerodynamic instabilities caused by ice accretion. In this study, the accident probability induced by galloping phenomenon was analyzed using logistic regression analysis. As former studies have generally concluded, main factors considered were local weather factors and physical factors of power delivery systems. Since the number of transmission towers outnumbers the number of weather observatories, interpolation of weather factors, Kriging to be more specific, has been conducted in prior to forming galloping accident estimation model. Physical factors have been provided by Korea Electric Power Corporation, however because of the large number of explanatory variables, variable selection has been conducted, leaving total 11 variables. Before forming estimation model, with 84 provided galloping cases, 840 non-galloped cases were chosen out of 13 billion cases. Prediction model for accidents by galloping has been formed with logistic regression model and validated with 4-fold validation method, corresponding AUC value of ROC curve has been used to assess the discrimination level of estimation models. As the result, logistic regression analysis effectively discriminated the power lines that experienced galloping accidents from those that did not.

• Journal of the Korean earth science society
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• v.44 no.2
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• pp.105-118
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• 2023

In this study, we predicted the presence of fog with a one-hour delay using the XGBoost DART machine learning algorithm for Andong, which had the highest occurrence of fog among inland stations from 2016 to 2020. We used six datasets: meteorological data, agricultural observation data, additional derived data, and their expanded data. The weather phenomenon numbers obtained through naked-eye observations and the visibility distances measured by visibility meters were classified as fog [1] or no-fog [0]. We set up twelve machine learning modeling experiments and used data from 2021 for model validation. We mainly evaluated model performance using recall and AUC-ROC, considering the harmful effects of fog on society and local communities. The combination of oversampled meteorological data features and the target induced by weather phenomenon numbers showed the best performance. This result highlights the importance of naked-eye observations in predicting fog using machine learning algorithms.

• Journal of Korean Society for Atmospheric Environment
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• v.16 no.5
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• pp.487-497
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• 2000

Spring time is a favorable season to be easily observed the Yellow Sand phenomenon in East Asia. In particular most of the phenomenon tend to occur in April. However, Yellow Sand phenomenon was observed from almost the whole country of Korea in winter of 1966, 1977 and 1999. The features of the synoptic weather pattern in the source regions, air stream flow between the source region and Korea, the measurement of TSP concentration, aerosol size distribution, and chemical composition of snow samples associated with Yellow Sand phenomenon were investigated. The result showed the characteristic evolutionary feature of the synoptic system associated with Yellow Sand phenomena, that is, a strong low level wind mobilized the dust within 2 or 3 days before Yellow Sand phenomenon being observed in Seoul. The wind was remarkably intensified in the source region on January 24, 1999 under the strong pressure gradient, A trajectory analysis showed that the Yellow Sand particle could be reached to Korea within 2 days from the source region, Gobi desert, through Loess plateau and Loess deposition region. The TSP concentration at the top of Kwanak mountain during the Yellow Sand phenomenon is abruptly increasing than the monthly mean concentration. The size resolved number concentration of aerosols ranging from 0.3 to 25${\mu}{\textrm}{m}$ was analyzed during Yellow Sand episode. It was evident that aerosols were distinguished by particles in the range of 2-3 ${\mu}{\textrm}{m}$ to result in the abrupt increase in January 1999, After Yellow Sand phenomenon, there was heavy snow in Seoul. By the analysis of snow collected during that time, it was observed that both the Ca(sup)2+ concentration and pH were increased abnormally compared to those in the other winter season.

• Atmosphere
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• v.15 no.3
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• pp.179-186
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• 2005

Due to several difficulties, a number of Automatic Weather Systems (AWS) operated by Korea Meteorological Administration (KMA) are located on the rooftop so that the forming of standard observation environment to obtain the accuracy is needed. Therefore, the air temperature of AWSs on the synthetic lawn and the concrete of the rooftop is compared with the standard observation temperature. The hourly mean temperature is obtained by monthly and hourly mean value and the difference of temperature is calculated according to the location, the weather phenomenon, and cloud amount. The maximum and the minimum temperatures are compared by the conditions, such as cloud amount, the existence of precipitation or not. Consequently, the temperature on the synthetic lawn is higher than it on the concrete so that it is difficult to obtain same effect from ASOS, on the contrary the installation of AWS on the synthetic lawn seem to be inadequate due to heat or cold source of the building.

• The Journal of the Korea Contents Association
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• v.18 no.11
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• pp.1-12
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• 2018

Heat waves during summer cause a qualitative degradation in urban environments and increases the number of patients who suffer from heat-related illnesses, and the urbanization deepens these problems. It is a prerequisite to analyze the current status accurately in order to assess the urban heat island phenomenon. Thus, this study aims to collect weather measurements information at the occurrence of a severe heat wave in Seoul, thereby allowing analysis of information, which will also consider the land use type. The weather measurement information used in the analysis had an advantage, as the gap between measured locations is considerably shorter than before due to the miniaturization of the automatic weather systems (AWS), which are connected through the communication network. Based on the above collected information, a temporal change in the data due to land use type was analyzed. As a result, the difference in temperature change in response to the land use type could be compared, as could the occurrence pattern of the tropical night phenomenon, and the effect on temperature reduction in green belt areas could be identified through the comparison of the intensity of heat island by time and land use. The methods and results derived in this study through the comparative analysis in terms of time and land use, weather information measurements, and mapping can be utilized as foundational data that can be referred to in urban planning to reduce the heat island phenomenon in the future.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.1B
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• pp.41-53
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• 2008

Unprecedented weather phenomena are occurring because of climate change: extreme heavy rains, heat waves, and severe rain storms after the rainy season. Recently, the frequency of these abnormal phenomena has increased. However, regular pattern or cycles cannot be found. Analysis of annual data or annual average data, which has been established a research method of climate change, should be applied to find frequency and tendencies of extreme climate events. In this paper, extreme indicators of precipitation and temperature marked by objectivity and consistency were established to analyze data collected by 66 observatories throughout Korea operated by the Meteorological Administration. To assess the statistical significance of the data, linear regression and Kendall-Tau method were applied for statistical diagnosis. The indicators were analyzed to find tendencies. The analysis revealed that an increase of precipitation along with a decrease of the number of rainy days. A seasonal trend was also found: precipitation rate and the heavy rainfall threshold increased to a greater extent in the summer(June-August) than in the winter (September-November). In the meanwhile, a tendency of temperature increase was more prominent in the winter (December-February) than in the summer (June-August). In general, this phenomenon was more widespread in inland areas than in coastal areas. Furthermore, the number of winter frost days diminished throughout Korea. As was mentioned in the literature, the progression of climate change has influenced the increase of temperature in the winter.

• Journal of Plant Biotechnology
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• v.44 no.2
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• pp.142-148
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• 2017

Drought stress is one of the important factors that restrict the expansion of Hevea brasiliensis cultivation to non-traditional regions experiencing extreme weather conditions. Plants respond to drought stress by triggering expression of several drought responsive genes including transcription factors which in turn trigger expression of various downstream signalling pathways and adaptive networks. Expression of such drought responsive genes may revert back to their original level upon re-watering. However, no reports are available on such phenomenon in Hevea and hence, this study was initiated. For this purpose, NAC transcription factor (NAC tf) was chosen as candidate gene. Its expression levels were monitored under intermittent drought as well as irrigated conditions in two clones (RRII 105 and RRIM 600) of H. brasiliensis with contrasting tolerance level. Copy number of NAC tf was found similar in both the clones. Expression of NAC tf was found highly up-regulated in RRIM 600 (a relatively drought tolerant clone) than in RRII 105 (a relatively drought susceptible clone) throughout the drought incidences which upon re-watering, reached back to its original levels in both the clones. The study indicated the existence of an association between expression of NAC tf and drought tolerance trait exhibited by the tolerant clone RRIM 600. The study also proves the influence of drought and re-watering on the leaf photosynthesis and expression of NAC tf in H. brasiliensis.

• Journal of Environmental Science International
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• v.21 no.2
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• pp.153-163
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• 2012

The seasonal variations of ozone ($O_3$) concentrations were investigated with regard to the relationship between $O_3$ and wind distributions at two different sites (Jung Ang (JA): a semi-closed topography and Seo Chang (SC): a closed topography) within a valley city (Yangsan) and their comparison between these sites (JA and SC) and two non-valley sites (Dae Jeo (DJ) and Sang Nam (SN)) located downwind from coastal cities (Busan and Ulsan). This analysis was performed using the data sets of hourly $O_3$ concentrations, meteorological factors (especially, wind speed and direction), and those on high $O_3$ days exceeding the 8-h standard (60 ppb) during 2008-2009. In summer and fall (especially in June and October), the monthly mean values of the daily maximum $O_3$ concentrations and the number of high $O_3$ days at JA (and SC) were relatively higher than those at DJ (and SN). The increase in daytime $O_3$ concentrations at JA in June was likely to be primarily impacted by the transport of $O_3$ and its precursors from the coastal emission sources in Busan along the dominant southwesterly winds (about 5 m/s) under the penetration of sea breeze condition, compared to other months and sites. Such a phenomenon at SC in October was likely to be mainly caused by the accumulation of $O_3$ and its precursors due to the relatively weak winds under the localized stagnant weather condition rather than the contribution of regional transport from the emission sources in Busan and Ulsan.

• Journal of the Korean Geographical Society
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• v.50 no.1
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• pp.23-36
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• 2015

The temperature change patterns of climatic solar terms and their climatic fitness were analyzed. Harmonic analysis based on thirty-year(1981-2010) time-series data from sixty one weather stations across South Korea showed that the central peaks of the extreme heat had shifted toward start of autumn with increasing mean temperature. The overall climatic fitness of solar terms, such as major heat, frost descent, major snow, and major cold, was low, and it showed significant regional variations. The actual meteorological phenomenon representing each climatic solar term was observed much later than the day of the solar term at most weather stations. The number of observations, where an actual meteorological condition for each climatic solar term was recorded within ${\pm}1$ week from the day of that solar term, ranged only from 7.7% to 40.4% of the entire data. Study results also showed that the climatic fitness of major heat, frost descent, and major snow gradually changed in the east-west direction. Major cold, a solar term with higher climatic fitness, was influenced more strongly by latitude than longitude. Considering geographically uneven magnitude and trends in temperature changes, rearrangement and adjustment of time intervals between the solar terms may help us improve their applicability as realistic indicators of seasonal changes.