• Journal of Korea Water Resources Association
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• v.44 no.11
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• pp.889-902
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• 2011

In this study, frequency analysis using drought index had implemented for the derivation of drought severity-duration-frequency (SDF) curves to enable quantitative evaluations of past historical droughts having been occurred in Korean Peninsular. Seoul, Daejeon, Daegu, Gwangju, and Busan weather stations were selected and precipitation data during 1974~2010 (37 years) was used for the calculation of Standardized Precipitation Index (SPI) and frequency analysis. Based on the results of goodness of fit test on the probability distribution, Generalized Extreme Value (GEV) was selected as most suitable probability distribution for the drought frequency analysis using SPI. This study can suggest return periods for historical major drought events by using newrly derived SDF curves for each stations. In case of 1994~1995 droughts which had focused on southern part of Korea. SDF curves of Gwangju weather station showed 50~100 years of return period and Busan station showed 100~200 years of return period. Besides, in case of 1988~1989 droughts, SDF of Seoul weather station were appeared as having return periods of 300 years.

• The Plant Pathology Journal
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• v.31 no.3
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• pp.290-298
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• 2015

Starting in 2012, severe diebacks usually accompanied by abundant gum exudation have occurred on yuzu trees in Goheung-gun, Jeonnam Province, where severely affected trees were occasionally killed. On-farm surveys were conducted at 30 randomly-selected orchards located at Pungyang-myeon, Goheung-gun, and the resulting disease incidences were 18.5% and 39.6% for dieback and gumming symptoms, respectively. Black spots on branches and leaves also appeared on infected trees showing a typical dieback symptom. Morphological and molecular identifications of the isolated fungal organisms from lesions on the symptomatic leaves and branches revealed that they are identical to Phomopsis citri, known to cause gummosis. In order to find the reason for this sudden epidemic, we investigated the weather conditions that are exclusively distinct from previous years, hypothesizing that certain weather extremes might have caused the severe induction of pre-existing disease for yuzu. There were two extreme temperature drops beyond the yuzu's cold hardiness limit right after an abnormally-warm-temperature-rise during the winter of 2011-12, which could cause severe frost damage resulting in mechanical injuries and physiological weakness to the affected trees. Furthermore, there was an increased frequency of strong wind events, seven times in 2012 compared to only a few times in the previous years, that could also lead to extensive injuries on branches. In conclusion, we estimated that the possible damages by severe frost and frequent strong wind events during 2012 could cause the yuzu trees to be vulnerable to subsequent fungal infection by providing physical entries and increasing plant susceptibility to infections.

• Journal of Ocean Engineering and Technology
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• v.35 no.4
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• pp.273-286
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• 2021

In recent years, as human casualties and property damage caused by hazardous waves have increased in the East Sea, precise wave prediction skills have become necessary. In this study, the Simulating WAves Nearshore (SWAN) third-generation numerical wave model was calibrated and optimized to enhance the accuracy of winter storm wave prediction in the East Sea. We used Source Term 6 (ST6) and physical observations from a large-scale experiment conducted in Australia and compared its results to Komen's formula, a default in SWAN. As input wind data, we used Korean Meteorological Agency's (KMA's) operational meteorological model called Regional Data Assimilation and Prediction System (RDAPS), the European Centre for Medium Range Weather Forecasts' newest 5th generation re-analysis data (ERA5), and Japanese Meteorological Agency's (JMA's) meso-scale forecasting data. We analyzed the accuracy of each model's results by comparing them to observation data. For quantitative analysis and assessment, the observed wave data for 6 locations from KMA and Korea Hydrographic and Oceanographic Agency (KHOA) were used, and statistical analysis was conducted to assess model accuracy. As a result, ST6 models had a smaller root mean square error and higher correlation coefficient than the default model in significant wave height prediction. However, for peak wave period simulation, the results were incoherent among each model and location. In simulations with different wind data, the simulation using ERA5 for input wind datashowed the most accurate results overall but underestimated the wave height in predicting high wave events compared to the simulation using RDAPS and JMA meso-scale model. In addition, it showed that the spatial resolution of wind plays a more significant role in predicting high wave events. Nevertheless, the numerical model optimized in this study highlighted some limitations in predicting high waves that rise rapidly in time caused by meteorological events. This suggests that further research is necessary to enhance the accuracy of wave prediction in various climate conditions, such as extreme weather.

• Journal of Korea Water Resources Association
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• v.50 no.1
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• pp.17-28
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• 2017

A recent increase in extreme weather events and flash floods associated with the enhanced climate variability results in an increase in climate-related disasters. For these reasons, various studies based on a high resolution weather radar system have been carried out. The weather radar can provide estimates of precipitation in real-time over a wide area, while ground-based rain gauges only provides a point estimate in space. Weather radar is thus capable of identifying changes in rainfall structure as it moves through an ungauged basin. However, the advantage of the weather radar rainfall estimates has been limited by a variety of sources of uncertainty in the radar reflectivity process, including systematic and random errors. In this study, we developed an ensemble radar rainfall estimation scheme using the multivariate copula method. The results presented in this study confirmed that the proposed ensemble technique can effectively reproduce the rainfall statistics such as mean, variance and skewness (more importantly the extremes) as well as the spatio-temporal structure of rainfall fields.

• Atmosphere
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• v.24 no.2
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• pp.159-171
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• 2014

This study investigated the temporal and spatial characteristics of summertime (June-August) precipitation over Korean peninsula, using Korea Meteorological Administration (KMA)is Automated Synoptic Observing System (ASOS) data for the period of 1973-2010 and Automatic Weather System (AWS) data for the period of 1998-2010.The authors looked through climatological features of the summertime precipitation, then examined the degree of locality of the precipitation, and probable precipitation amount and its return period of 100 years (i.e., an extreme precipitation event). The amount of monthly total precipitation showed increasing trends for all the summer months during the investigated 38-year period. In particular, the increasing trends were more significant for the months of July and August. The increasing trend of July was seen to be more attributable to the increase of precipitation intensity than that of frequency, while the increasing trend of August was seen to be played more importantly by the increase of the precipitation frequency. The e-folding distance, which is calculated using the correlation of the precipitation at the reference station with those at all other stations, revealed that it is August that has the highest locality of hourly precipitation, indicating higher potential of localized heavy rainfall in August compared to other summer months. More localized precipitation was observed over the western parts of the Korean peninsula where terrain is relatively smooth. Using the 38-years long series of maximum daily and hourly precipitation as input for FARD2006 (Frequency Analysis of Rainfall Data Program 2006), it was revealed that precipitation events with either 360 mm $day^{-1}$ or 80 mm $h^{-1}$ can occur with the return period of 100 years over the Korean Peninsula.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.20-25
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• 2012

New Zealand suffers from regular floods, these being the most common source of insurance claims for damage from natural hazard events in the country. This paper describes the origin and distribution of the largest floods in New Zealand, and describes the systems used to monitor and predict floods. In New Zealand, broad-scale heavy rainfall (and flooding), is the result of warm moist air flowing out from the tropics into the mid-latitudes. There is no monsoon in New Zealand. The terrain has a substantial influence on the distribution of rainfall, with the largest annual totals occurring near the South Island's Southern Alps, the highest mountains in the country. The orographic effect here is extreme, with 3km of elevation gained over a 20km distance from the coast. Across New Zealand, short duration high intensity rainfall from thunderstorms also causes flooding in urban areas and small catchments. Forecasts of severe weather are provided by the New Zealand MetService, a Government owned company. MetService uses global weather models and a number of limited-area weather models to provide warnings and data streams of predicted rainfall to local Councils. Flood monitoring, prediction and warning are carried out by 16 local Councils. All Councils collect their own rainfall and river flow data, and a variety of prediction methods are utilized. These range from experienced staff making intuitive decisions based on previous effects of heavy rain, to hydrological models linked to outputs from MetService weather prediction models. No operational hydrological models are linked to weather radar in New Zealand. Councils provide warnings to Civil Defence Emergency Management, and also directly to farmers and other occupiers of flood prone areas. Warnings are distributed by email, text message and automated voice systems. A nation-wide hydrological model is also operated by NIWA, a Government-owned research institute. It is linked to a single high resolution weather model which runs on a super computer. The NIWA model does not provide public forecasts. The rivers with the greatest flood flows are shown, and these are ranked in terms of peak specific discharge. It can be seen that of the largest floods occur on the West Coast of the South Island, and the greatest flows per unit area are also found in this location.

• 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 Korea Water Resources Association
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• v.49 no.8
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• pp.719-729
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• 2016

Extreme events of rainfall has increased mainly from climate change, resulting in more severe floods intensified by land use development. Appropriate estimation of design floods gets more attention to ensuring the safety of life and property in flood-prone areas for hydraulic structures such as dams and levees. In the current study, we reestimated the design flood of the Nam River Dam to adopt the influence of climatic change of hydrometeorological variables including recent datasets of extreme rainfall events. The climate change scenarios of extreme rainfall events in hourly scale that has been downscaled was used in analyzing the annual maximum rainfall for the weather stations in the Nam River Dam basin. The estimates of 200-year and 10,000-year return periods were calculated to provide a design flood and a probable maximum flood case for the Nam River Dam. The results present that the new estimate employing the RCP4.5 and RCP8.5 downscaled data is much higher than the original design flood estimated at the dam construction stage using a 200-year return period. We can conclude that the current dam area might be highly vulnerable and need an enhancement of the dam safety regarding the reduction of damage in Sachen bay from the outflow of Nam River Dam.

• Journal of Korea Water Resources Association
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• v.45 no.3
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• pp.275-290
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• 2012

In this study, we have developed an optimal time distribution model through extraction of peaks over threshold (POT) series. The median values for annual maximum rainfall dataset, which are obtained from the magnetic recording (MMR) and the automatic weather system(AWS) data at Seoul meteorological observatory, were used as the POT criteria. We also suggested the improved methodology for the time distribution of extreme rainfall compared to Huff method, which is widely used for time distributions of design rainfall. The Huff method did not consider changing in the shape of time distribution for each rainfall durations and rainfall criteria as total amount of rainfall for each rainfall events. This study have suggested an extracting methodology for rainfall events in each quartile based on interquartile range (IQR) matrix and selection for the mode quartile storm to determine the ranking cosidering weighting factors on minutely observation data. Finally, the optimal time distribution model in each rainfall duration was derived considering both data size and characteristics of distribution using kernel density function in extracted dimensionless unit rainfall hyetograph.

• Journal of The Geomorphological Association of Korea
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• v.19 no.3
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• pp.71-82
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• 2012

This research was carried out to estimate annual erosion and retreat rates by using datum-point and to identify the characteristics and causes of seasonal variations of sea-cliff slope in Pado-ri, Taean-gun. In the result, the erosion and retreat rates of sea-cliff were increased from spring to summer. The rates were increased rapidly between August and October, caused by the effects of extreme weather events such as severe rainstorms and typhoons, etc. Since then, the erosion and retreat rates of sea-cliff were decreased gradually, but the rates were increased again in winter due to the storm surge and mechanical weathering resulting from the repeated freezing and thawing actions of bed rocks. The factors that affect erosion and retreat rates of sea-cliff include the number of days with antecedent participation and daily maximum wave height. In particular, it turned out that the erosion is accelerated by strong wave energy during storm surges and typhoons. The annual erosion and retreat rates of study area for the past two years(from May 2010 to May 2012) were approximately 44~60cm/yr in condition of differences in geomorphological and geological characteristics at each point. These erosion and retreat rates were found to be higher than results of previous researches. This is caused by coastal erosion forces strengthened by extreme weather events. The erosion and retreat process of sea-cliff in the study area is composed by denudation of onshore areas in addition to marine erosion(wave energy).