• Korean Journal of Agricultural and Forest Meteorology
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• v.4 no.4
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• pp.248-253
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• 2002

This study was to provide information about snow falling phenomenon in Korea for 1934 years from BC 6 to 1928 based on the records of old literatures, which are the true record of the Chosun dynasty, records of king Kojong and Soonjong, and some data including history of the Koryo in internet home page of Korea meteorological administration. Key words used in search procedure were totally 20 words such as snow, heavy snow, big snow, snow pellets, snowstorm, avalanche, etc. The searching contents consisted of the time of the first and the last snow, the amount of snow falling, snow damage, the thought about heavy snow phenomenon, and unusual weather conditions related to snow. The earliest record for the first snow was July of the rural calendar in 733 and the latest record for the last snow was June 11 of the lunar calendar. From these records, it could be estimated that there were some snow falling even in summer season. The amount of almost heavy snow ranged from 1.2 m to 1.5 m, but sometimes there were some records about the amount of snow falling higher than 3 meters. It was also found that there were three records about big heavy snow damages. In 1524 and 1525, approximately 100 and 140 peoples in Kyungsung, Hamgyung Province were dead due to heavy snowstorm. It was also recorded that 91 people in Jeiu island were dead in 1670 because of snow damage. Some singular records about snow were also found in old literatures. There was a congratulatory ceremony of new snow when the first snow was falling in the year. There was also a ritual praying for snow when there was no snow in the year. It was also found that there was snow falling with worms and red snow falling.

• Journal of Environmental Health Sciences
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• v.31 no.3
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• pp.215-220
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• 2005

The atmospheric transportation and dispersion processes of air pollutants are important issues in dealing with air pollution problems. Air pollutants originated from biological and anthropogenic activities are not only limited to the local emission sources, but could also be transported and dispersed to other regions by synoptic weather systems. Besides, the complexity of topography of central Taiwan helps accumulating air pollutants to promote high-concentration episodes. The techniques of tethersonding were applied to monitor the vertical profiles of winds, air temperatures and humidity, as well as to collect air samples, to be analyzed for pollutants $(O_3,\;NO_2,\;NO\;and\; NMHC)$ from the ground up to 1000m. A time period of about one week, 19-26 October 2002, was chosen as the sampling period due to the high frequency of episode occurrence in autumn based on the past records. Associating with the analysis of weather patterns, the atmospheric characteristics over high-concentration areas can be resolved in more detail. The result of the tethersonding studies showed that weak northerly sea breeze (with thickness about 300m) with low wind speed (about 1 to 2 m/sec) could help develop high ozone concentrations in the down-wind areas. It is also important to have a built-up aloft of precursors and ozone to develop high concentration on the previous day.

• Water for future
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• v.20 no.2
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• pp.127-138
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• 1987

For determination of the design wave, a method of estimating the design wind speed at sea from the wind records at the nearby weather stations on land is proposed. Along the West Coast, the design wind speed are shown to have two main directions; namely, N through W, and WSW through S. Through the analysis of weather maps, fetches for the main wind directions along the West Coast are determined. The wind speeds at sea are found to have 0.8~0.9 times the wind speed at the stations on land for U$\geq$20m/s. The West Coast may be divided into three regions for which fetches are determind uniquely. Design waves with return period of 100 years are determined by the revised S.M..B. method along the West Coast, and show the deep water significant wave heights of 4.4~8.3 meters with wave periods of 8.9~12.0 seconds.

• Proceedings of the Korean Environmental Health Society Conference
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• 2005.06a
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• pp.184-210
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• 2005

The atmospheric transportation and dispersion processes of air pollutants are important issues in dealing with air pollution problems. Air pollutants originated from biological and anthropogenic activities are not only limited to the local emission sources, but could also be transported and dispersed to other regions by synoptic weather systems. Besides, the complexity of topography of central Taiwan helps accumulating air pollutants to promote high-concentration episodes. The techniques of tethersonding were applied to monitor the vertical profiles of winds, air temperatures and humidity, as well as to collect air samples, to be analyzed for pollutants ($O_3,\;NO_2$, NO and NMHC) from the ground up to 1000 m. A time period of about one week, 19 -26 October 2002, was chosen as the sampling period due to the high frequency of episode occurrence in autumn based on the past records. Associating with the analysis of weather patterns, the atmospheric characteristics over high-concentration areas can be resolved in more detail. The result of the tethersonding studies showed that weak northerly sea breeze (with thickness about 300 m) with now wind speed (about 1 to 2 m/sec) could help develop high ozone concentrations in the down-wind areas. It is also important to have a built-up aloft of precursors and ozone to develop high concentration on the previous day.

• Magazine of the Korean Society of Agricultural Engineers
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• v.17 no.2
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• pp.3772-3777
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• 1975

This paper reports on the analysis of the distributions of probable days being good for mechanical rice harvesting and the method of determining the capacity of rice harvesting machinery for the given harvesting duration. In the analysis of the probability distribution of days being good for rice harvesting, the daily rainfalls above which mechanical field work may be impracticable were specified and their frequency of occurances was analyzed by using the weather records during past twenty-one years measured at five different locations. The conclusions being drawn from the analysis are as follows: 1. The distributions of probable workable days in different region and harvesting duration are very distinct and are different to set a uniform trend (refer to Fig. 1-4). 2. The occurance of probable days being good for mechanical field work under 66% confidence level are quite variable by region and by ten-day period. The analysis indicates that the probable workable days may range from 7.5 to 8.5 days of 10-day span within optimum harvesting duration (refer to Table 1). 3. Based on the probability distributions analyzed, the optimun capacities of harvesting machinery required for different harvesting areas and harvesting start-date were estimated as a function of operating duration (refer to Fig. 5 and Table 2)

• Bulletin of the Korean Space Science Society
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• 2008.10a
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• pp.24.2-24.2
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• 2008

We have examined the relative contributions of representative space weather proxies (geomagnetic aa index) to global warming (Global temperature anomaly) and compared them with that of green house effect characterized CO2 content from 1868 to 2005. For this we used Hadcrut3 temperature anomaly (Ta) data, aa index taken at two anti-podal subauroral stations (Canberra Australia and hartland England), and the CO2 data come from historical ice core records. From the comparison between Ta and aa index, we found several interesting results: (1) the linear correlation coefficient between two parameters increases until 1990 and then decreases rapidly, and (2) the scattered plots between two parameters shows different patterns before and after 1990. A partial correlation of Ta and two quantities (aa, CO2) also shows that the geomagnetic effect (aa index) is dominant until about 1990 and the CO2 effect becomes much more important after then. These results imply that the green house effect become very important since at least 1990. For a further analysis, we simply assume that Ta (total) = Ta (aa) + Ta (CO2) and made a linear regression between Ta and aa index from 1868 to 1990. A linear model is then made from the linear regression between energy consumption (a proxy of CO2 effect) and Ta (total) - Ta (aa) since 1990. This linear model makes it possible to predict the temperature anomaly in 2030, about 1 degree higher than the present temperature, which is much larger than in the previous century.

• Korean Journal of Agricultural and Forest Meteorology
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• v.8 no.1
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• pp.22-27
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• 2006

Many aspects of climate have been observed to be increasingly volatile during the past several decades. Episodic climate change is not considered to be uncommon. However, there are substantial environmental, social, and economic impacts associated with climate variability that can be managed if the climate and its impacts are properly understood. Plants and natural communities exhibit several types of adaptive strategy to climate change. There is ample reason to relate increasingly erratic weather with a warming climate. Historic climate extremes, the adaptive mechanisms plants exhibit, and how people have (or have not) responded with strategically sound concepts and policy to facilitate a sustainable environmental ethic are reviewed with a vision of international needs and economic stability.

• Journal of Korea Multimedia Society
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• v.13 no.12
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• pp.1739-1747
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• 2010

The damage of natural disasters has occurred on huge scale more frequently than before. The damage caused by the disasters are summarized and are analyzed, and are managed as a very general type of documentation, not showing the position of previous damage records and related information such as weather, facilities of CCTV, hospitals, and gas station on the maps. Therefore, it needs to provide map-based searching systems considering damaged area as well as search key-words. This paper focuses on the development of a search system based on the map to manage previous disaster records and related information each disaster using spatial databases. This system consists of three modules, which are databases to store disaster data, the SQL procedure-based search module to extract needed information from the constructed databases, and the map module to express the search results on the map. This paper will contribute to provide framework of a system development for managing the disaster information according to each year and disaster based on the maps and to be utilized as the basic framework in developing damage prediction and prevention systems for disasters in future.

• Proceedings of the KSRS Conference
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• v.2
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• pp.627-630
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• 2006

Sequential Pattern Mining is the mining approach which addresses the problem of discovering the existent maximal frequent sequences in a given databases. In the daily and scientific life, sequential data are available and used everywhere based on their representative forms as text, weather data, satellite data streams, business transactions, telecommunications records, experimental runs, DNA sequences, histories of medical records, etc. Discovering sequential patterns can assist user or scientist on predicting coming activities, interpreting recurring phenomena or extracting similarities. For the sake of that purpose, the core of sequential pattern mining is finding the frequent sequence which is contained frequently in all data sequences. Beside the discovery of frequent itemsets, sequential pattern mining requires the arrangement of those itemsets in sequences and the discovery of which of those are frequent. So before mining sequences, the main task is checking if one sequence is a subsequence of another sequence in the database. In this paper, we implement the subsequence matching method as the preprocessing step for sequential pattern mining. Matched sequences in our implementation are the normalized sequences as the form of number chain. The result which is given by this method is the review of matching information between input mapped sequences.

• Korean Journal of Remote Sensing
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• v.22 no.5
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• pp.457-462
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• 2006

Sequential Pattern Mining is the mining approach which addresses the problem of discovering the existent maximal frequent sequences in a given databases. In the daily and scientific life, sequential data are available and used everywhere based on their representative forms as text, weather data, satellite data streams, business transactions, telecommunications records, experimental runs, DNA sequences, histories of medical records, etc. Discovering sequential patterns can assist user or scientist on predicting coming activities, interpreting recurring phenomena or extracting similarities. For the sake of that purpose, the core of sequential pattern mining is finding the frequent sequence which is contained frequently in all data sequences. Beside the discovery of frequent itemsets, sequential pattern mining requires the arrangement of those itemsets in sequences and the discovery of which of those are frequent. So before mining sequences, the main task is checking if one sequence is a subsequence of another sequence in the database. In this paper, we implement the subsequence matching method as the preprocessing step for sequential pattern mining. Matched sequences in our implementation are the normalized sequences as the form of number chain. The result which is given by this method is the review of matching information between input mapped sequences.