• KSCE Journal of Civil and Environmental Engineering Research
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• 제28권1B호
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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 the Korea Academia-Industrial cooperation Society
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• 제18권8호
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• pp.34-40
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• 2017

In recent years, global warming has caused abnormal weather phenomena. Unusually cold climates have occurred all around the world, including cold waves in the Northeastern United States, Beijing, China, Southern India, and Pakistan, as well as floods in Chile, Kazakhstan, and Vietnam. China has been experiencing a nationwide heat wave annually since the year 2013, especially in the southern region. In this study, we used Landsat 8 OLI TIRS sensor images from four periods to analyze the characteristics of abnormal high temperature phenomena in Cixi-si, China. Land cover classification was performed using 10 bands of satellite imagery, and the surface temperature was extracted using the 10th thermal band. The results of the land cover classification of the fourth period show the changes of the time series quantitatively. The results of the surface temperature calculation provided both the average overall temperature and the average temperature of individual items. The temperature was found to be highest for buildings, followed by grassland, forest, agricultural land, water systems, and tidal flats in the same period.

• Journal of Environmental Science International
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• 제24권1호
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• pp.133-150
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• 2015

Wind profiler provides vertical profiles of three-dimensional wind vectors with high spatiotemporal resolution. The wind vectors is useful to analyze severe weather phenomena and to validate the various products from numerical weather prediction model. However, the wind measurements are not immune to ground clutter, bird, insect, and aircraft. Therefore, quality of wind vectors from wind profiler must be quantitatively evaluated prior to its application. In this study, wind vectors from UHF wind profiler at Ganwon Regional Meteorological Administration was quantitatively evaluated using 27 radiosonde measurements that were launched every two or three hours according to rainfall intensity during Intensive Observation Period (IOP) from June to July 2013. In comparison between two measurements, wind vectors from wind profiler was relatively underestimated. In addition, the accuracy and quality of wind vectors from wind profiler decrease with increasing beam height. The accuracy and quality of the wind vectors for rainy periods during IOP were higher than for the clear-air measurements. The moderate rainfall intensity lead to multi-peaks in Doppler spectrum. It results in overestimation of vertical air motion, whereas wind vectors from wind profilers shows good agreement with those from radiosonde measurements for light rainfall intensity.

• Atmosphere
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• 제26권1호
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• pp.193-201
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• 2016

An anomalous cold-weather period occurred during January 2011 in East Asia, and this study investigates the event by focusing on the blocking phenomena formed at Northeastern Asia. The area of cold weather is determined to represent the characteristic features of abnormal cold temperature. The 2010/11 winter is divided into three periods P1, P2 (cold period), and P3. For the cold area ($30-50^{\circ}N$, $115-135^{\circ}E$) the corresponding cold period P2 is determined to be 39 days from 23 December 2010 through 30 January 2011. During P1 and P3 temperature anomalies from the climatological mean are small with large standard deviation compared to those of P2, which has large negative anomaly and small standard deviation. The period P2 is dominated by blocking, which was determined by distributions of 500-hPa geopotential height and potential temperature on the 2 PVU surface. Correlation-coefficient analyses show that during P2 the temperature in the cold area is related with pressure of Northeastern Asia, while the temperature during P1 and P3 is related with pressure of Northwest of Korea. Also, during P1 and P3 the temperature pattern shows eastward propagation, but during P2, a stationary pattern. All the observations imply that, during the cold period P2, the temperature in the cold area is related with blocking in Northeastern Asia. During P1 and P3 temperature pattern is related with 500-hPa geopotential height in Siberia, and this relationship is also observed in the climatological mean state.

• Journal of the Institute of Electronics Engineers of Korea CI
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• 제49권2호
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• pp.1-6
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• 2012

In recent years global climate change of hurricanes and torrential rains are going to significantly, that increase damages to property and human life. The disasters have been several claimed in every field. In future, climate changes blowing are keen to strike released to the world like in several movies. Reducing the damage of long-term weather phenomena are emerging with predicting changes in weather. In this study, it is shown how to predict the red tide phenomenon with multiple linear regression analysis and artificial neural network techniques. The red tide phenomenon causing risk could be reduced by filtering sensor data which are transmitted and forecasted in real time. It could be ubiquitous driven custom marine information service system, and forecasting techniques to use throughout the meteorological disasters to minimize damage.

• Journal of the Korean Institute of Telematics and Electronics
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• 제10권5호
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• pp.16-20
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• 1973

The most important thing in locating disturbances in optimal rapid traffic singnal control is to collect information cocerning toraffit flow by means of a detection method. In order to set up an optimal traffic singnal period, the analysis of a delay time phenomena in the signal period must also be considered. In fact, each of the distributed traffic quantities on the road are not similar factors in view of speeds and distances of succeeding cars. The causing factors are analyzed by the method of control engineering analysis, and they are coincident with disturbance. Thus distubances cause errors. Distubances are fuctions of time, and are classified into three conditions: Natural road state and weather are the first. The second is structures and function of vehicles, and the third is inducedbydrivers. This thesis deals with the last two cases except the first one for maximum utilization of the existing road state and weather conditions. The first condition remains constant, and then there exist some relations between vehicles and drivers. In the long run, it can be shown that the scheme for minimizing whole errors in the optimal traffic signal time setting is definitely presented.

• KOREAN JOURNAL OF CROP SCIENCE
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• 제64권3호
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• pp.213-224
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• 2019

There is an increasing frequency in the occurrence of abnormal weather phenomena such as sharp increases and decreases in temperature. Under these weather conditions, the heading time of rice changes unexpectedly, which poses problems in agriculture. Therefore, we investigated the effect of temperature on the heading response at different growth stages in rice. During the period from transplanting to heading, the plants were subjected to different temperature treatments, each for a 9-day period, to observe the heading response. For the heading date analysis, "heading date" was defined as the number of days from transplanting to the appearance of the first spikelet. We found that the influence of temperature increased in the order of rooting stage, followed by meiosis, early tillering, spikelet differentiation, and panicle initiation stage in all ecological types and cultivars. In particular, unlike the results reported previously, the effect of temperature on heading during the photo-sensitive period was very small. Meanwhile, the influence of temperature on vegetative growth response at different growth stages was not consistent with heading response. These results can be used as basic data for predicting the variation in heading date owing to temperature variation at each growth stage. In addition, we propose that the concept of day length should be included in determining the influence of temperature on the photo-sensitive period.

• KSCE Journal of Civil and Environmental Engineering Research
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• 제41권3호
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• pp.209-217
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• 2021

Although forest fires are more often triggered by artificial causes than by natural causes, the combustion conditions that spread forest fire damage over a large area are affected by natural phenomena. Therefore, using partial least squares structural equation modeling (PLS-SEM), which can analyze the dependent and causal relationships between various factors, this study evaluated the causal relationships and relative influences between forest fire, weather, and drought, taking Gangwon Province as our sample region. The results indicated that the impact of drought on forest fires was 27 % and that of the weather was 38 %. In addition, forest fires in spring accounted for about 60 % of total forest fires. This indicatesthat along with meteorological factors, the autumn and winter droughts in the previous year affected forest fires. In assessing the risk of forest fires, if severe meteorological droughts occur in autumn and winter, the probability of forest fires may increase in the spring of the following year.

• Journal of the Korea Institute of Military Science and Technology
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• 제27권1호
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• pp.1-7
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• 2024

Weather is one of the main causes of aircraft accidents, and among the phenomena caused by weather, icing is a phenomenon in which an ice layer is formed when an object exposed to an atmosphere below a freezing temperature collides with supercooled water droplets. If this phenomenon occurs in the rotor blades, it causes defects such as severe vibration in the airframe and eventually leads to loss of control and an accident. Therefore, it is necessary to foresee the icing situation so that it can ascend and descend at an altitude without a freezing point. In this study, vibration data in normal and faulty conditions was acquired, data features were extracted, and vibration was predicted through deep learning-based algorithms such as CNN, LSTM, CNN-LSTM, Transformer, and TCN, and performance was compared to evaluate blade icing. A method for minimizing operating loss is suggested.

• Korean journal of applied entomology
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• 제63권1호
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• pp.77-80
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• 2024

Aedes albopictus, a common species in the Republic of Korea, is internationally known as a major vector for various diseases, and it is well-adapted to urban environments. Recent insect outbreaks in urban areas, attributed to climate change and urban heat islands, have increased the necessity of researching the effects on mosquito populations. This study analyzed climate data from 25 Automatic Weather System (AWS) stations in Seoul, identifying urban areas with pronounced heat island effects and suburban areas with milder effects. Nine urban heat island conditions were established based on this analysis, under which the hatching rates of Ae. albopictus were examined. The results revealed an increase in hatching rates correlating with the intensity of the urban heat island effect. Regression analysis further indicated that this trend accelerates as the strength of the heat island effect increases. This study suggests that temperature variations resulting from urban heat island phenomena can significantly influence the hatching rates of Ae. albopictus.