• Journal of the Korean earth science society
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• v.27 no.2
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• pp.159-176
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• 2006

Geographic factors and mathmatical location of the Korean Peninsula have great influences on the variation patterns and appearances over a period of ten days of summer precipitation. In order to clarify the influence of several climate factors on precise climate classification in the middle part region of the Korea, weather entropy and the information ratio were calculated on the basis of information theory and of the data of 25 site observations. The data used for this study are the daily precipitation phenomenon over a period of ten days of summer during the recent thirteen years (1991-2003) at the 25 stations in the middle part region of the Korea. It is divided into four classes of no rain, $0.1{\sim}10.0mm/day,\;10.1{\sim}30.0mm/day$, 30.1mm over/day. Their temporal and spatial change were also analyzed. The results are as follows: the maximum and minimum value of calculated weather entropy are 1.870 bits at Chuncheon in the latter ten days of July and 0.960 bits at Ganghwa during mid September, respectively. And weather entropy in each observation sites tends to be larger in the beginning of August and smaller towards the end of September. The largest and smallest values of weather representative ness based on information ratio were observed at Chungju in the beginning of June and at Deagwallyeong towards the end of July. However, the largest values of weather representativeness came out during the middle or later part of September when 15 sites were adopted as the center of weather forecasting. The representative core region of weather forecasting and climate classification in the middle part region of the Korea are inside of the triangle region of the Buyeo, Incheon, and Gangneung.

• Journal of Korea Water Resources Association
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• v.36 no.3 s.134
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• pp.495-505
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• 2003

Convective weather systems such as organized mesoscale convective systems (Mesoscale Convective Complex, MCC and Convective Cloud Clusters, CCC) and much weaker Disorganized Short-lived Convection (DSC) in the region of India and Nepal were analyzed using the Meteosat-5 IR imagery. The diurnal march and propagation of patterns of convective activity in the Himalayas and Northern Indian subcontinent were examined. Results indicate that infrared satellite images of Northern India and along the southern flank of the Himalayas reveal a strong presence of convective weather systems during the 1999 and 2000 monsoons, especially in the afternoon and during the night. The typical MCCs have life-times of about 11 hours, and areal extent about $300,000km^2$. Although the core of MCC activity remains generally away from the Middle Himalayan range, the occurrence of heavy precipitation events in this region can be directly linked to MCCs that venture into the Lesser Himalayan region and remain within the region bounded by $25^{\circ}-30^{\circ}N$. One principal feature in the spatial organization of convection is the dichotomy between the Tibetan Plateau and the Northern Indian Plains: CCCs and DSCs begin in the Tibetan Plateau in the mid-afternoon into the evening; while they are most active in the mid-night and early morning in the Gangetic Plains and along the southern facing flanks of the Himalayas. Furthermore, these data are consistent with the daily cycle of rainfall documented for a network of 20 hydrometeorological stations in Central Nepal, which show strong nocturnal peaks of intense rainfall consistent with the close presence of Convective Weather Systems (CWSs) in the Gangetic Plains (Barros et al. 2000).

• Journal of the Korean earth science society
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• v.21 no.3
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• pp.258-275
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• 2000

The purpose of this study is to investigate diurnal variations of snowstorm occurred along the East Coast of the Korean Peninsula. The snowstorm which occurred on 5${\sim}$7 January 1997 have been analyzed. The pressure patterns were analyzed through surface and upper-air chart(850hPa). Diurnal variations of four areas, i. e. Youngdong, Mt. Taebaek, Youngseo and Kyungbuk regions were analyzed through wind direction and speed, cloud amounts, surface temperature, dewpoint temperature, relative humidity and sea level pressure. And snowfall amounts over four areas were analyzed through regional distribution, daily and temporal variations. The snowfall which occurred on January 5 was caused by the weak low pressure which is located in Kyusu region of Japan. The snowfall of January 6 occurred due to the Siberian high's expansion and instability. And northeasterly wind is one factor of the snowstorm which occurred in Mt. Taebaek region on 7 January. Heavy snowfall was caused by westerly wind but easterly wind occurred weak snowfall in Youngdong area. The precipitation of Kyungbuk region(eapecially, Pohang) was less than that of Youngdong region because the air mass which was not modified had influence on Kyungbuk region on 6${\sim}$7 January, 1997.

• Journal of Korea Water Resources Association
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• v.47 no.4
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• pp.371-384
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• 2014

This study developed a new algorithm of extreme rainfall extraction based on the Communication, Ocean and Meteorological Satellite (COMS) and the Tropical Rainfall Measurement Mission (TRMM) Satellite image data and evaluated its applicability for the heavy rainfall event in July-2011 in Seoul, South Korea. The power-series-regression-based Z-R relationship was employed for taking into account for empirical relationships between TRMM/PR, TRMM/VIRS, COMS, and Automatic Weather System(AWS) at each elevation. The estimated Z-R relationship ($Z=303R^{0.72}$) agreed well with observation from AWS (correlation coefficient=0.57). The estimated 10-minute rainfall intensities from the COMS satellite using the Z-R relationship generated underestimated rainfall intensities. For a small rainfall event the Z-R relationship tended to overestimated rainfall intensities. However, the overall patterns of estimated rainfall were very comparable with the observed data. The correlation coefficients and the Root Mean Square Error (RMSE) of 10-minute rainfall series from COMS and AWS gave 0.517, and 3.146, respectively. In addition, the averaged error value of the spatial correlation matrix ranged from -0.530 to -0.228, indicating negative correlation. To reduce the error by extreme rainfall estimation using satellite datasets it is required to take into more extreme factors and improve the algorithm through further study. This study showed the potential utility of multi-geostationary satellite data for building up sub-daily rainfall and establishing the real-time flood alert system in ungauged watersheds.

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.4
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• pp.199-207
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• 2016

This study was conducted to develop a forest fire occurrence model using meteorological characteristics for practical forecasting of forest fire danger rate by reflecting the climate change for the time period of 2000yrs. Forest fire in South Korea is highly influenced by humidity, wind speed, temperature, and precipitation. To effectively forecast forest fire occurrence, we developed a forest fire danger rating model using weather factors associated with forest fire in 2000yrs. Forest fire occurrence patterns were investigated statistically to develop a forest fire danger rating index using times series weather data sets collected from 76 meteorological observation centers. The data sets were used for 11 years from 2000 to 2010. Development of the national forest fire occurrence probability model used a logistic regression analysis with forest fire occurrence data and meteorological variables. Nine probability models for individual nine provinces including Jeju Island have been developed. The results of the statistical analysis show that the logistic models (p<0.05) strongly depends on the effective and relative humidity, temperature, wind speed, and rainfall. The results of verification showed that the probability of randomly selected fires ranges from 0.687 to 0.981, which represent a relatively high accuracy of the developed model. These findings may be beneficial to the policy makers in South Korea for the prevention of forest fires.

• Journal of Wetlands Research
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• v.25 no.4
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• pp.353-365
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• 2023

The effects of climate change on green infrastructure and environmental media remain uncertain and context-specific despite numerous climate projections globally. In this study, the extreme weather conditions in seven major cities in South Korea were characterized through statistical analysis of 20-year daily meteorological data extracted fro m the Korea Meteorological Administration (KMA). Additionally, the impacts of extreme weather on Nature-based Solutions (NbS) were determined through a comprehensive review. The results of the statistical analysis and comprehensive review revealed the studied cities are potentially vulnerable to varying extreme weather conditions, depending on geographic location, surface imperviousness, and local weather patterns. Temperature extremes were seen as potential threats to the resilience of NbS in Seoul, as both the highest maximum and lowest minimum temperatures were observed in the mentioned city. Moreover, extreme values for precipitation and maximum wind speed were observed in cities from the southern part of South Korea, particularly Busan, Ulsan, and Jeju. It was also found that extremely low temperatures induce the most impact on the resilience of NbS and environmental media. Extremely cold conditions were identified to reduce the pollutant removal efficiency of biochar, sand, gravel, and woodchip, as well as the nutrient uptake capabilities of constructed wetlands (CWs). In response to the negative impacts of extreme weather on the effectiveness of NbS, several adaptation strategies, such as the addition of shading and insulation systems, were also identified in this study. The results of this study are seen as beneficial to improving the resilience of NbS in South Korea and other locations with similar climate characteristics.