• Journal of the Korean Geographical Society
• /
• v.46 no.3
• /
• pp.257-276
• /
• 2011

This study aimed to analyze the changes of extreme temperature indices in order to investigate impacts of urbanization on changes of extreme temperature. It was analyzed 16 indices related to extreme temperature indices to 60 weather stations in South Korea. Extreme temperature indices-related summer mostly increased, and its related to winter decreased. Percentile-based indices were clearly increased more than fixed-based indices as a tropical night. Decreasing trend of extreme temperature indices related to winter had more clear than increasing trend of extreme temperature indices related to summer. It was similar to trend that urban temperature was more clearly increased in winter than summer. Decreasing trend of indices-related daily minimum temperature had more clear than increasing trend of indices-related daily maximum temperature. Also, it was similar to increasing trend of minimum temperature had more clear than maximum temperature.

• Journal of the Korean earth science society
• /
• v.39 no.4
• /
• pp.327-341
• /
• 2018

Extreme temperatures and precipitations are expected to be more frequently occurring due to the ongoing global warming over the Korean Peninsula. However, few studies have analyzed the synoptic weather patterns associated with extreme events in a warming world. Here, the atmospheric patterns related to future extreme events are first analyzed using the HadGEM3-RA regional climate model. Simulations showed that the variability of temperature and precipitation will increase in the future (2051-2100) compared to the present (1981-2005), accompanying the more frequent occurrence of extreme events. Warm advection from East China and lower latitudes, a stagnant anticyclone, and local foehn wind are responsible for the extreme temperature (daily T>$38^{\circ}C$) episodes in Korea. The extreme precipitation cases (>$500mm\;day^{-1}$) were mainly caused by mid-latitude cyclones approaching the Korean Peninsula, along with the enhanced Changma front by supplying water vapor into the East China Sea. These future synoptic-scale features are similar to those of present extreme events. Therefore, our results suggest that, in order to accurately understand future extreme events, we should consider not only the effects of anthropogenic greenhouse gases or aerosol increases, but also small-scale topographic conditions and the internal variations of climate systems.

• Journal of the Korean earth science society
• /
• v.44 no.4
• /
• pp.255-263
• /
• 2023

Western coastal area of Chungnam, including Cheonsu Bay and Garorim Bay, has suffered from hot and cold extremes. In this study, the extreme sea surface temperature on the western coast of Chungnam was analyzed using the quantile regression method, which extracts the linear regression values in all quantiles. The regional MOHID (MOdelo HIDrodinâmico) model, with a high resolution on a 1/60° grid, was constructed to reproduce the extreme sea surface temperature. For future prediction, the SSP5-8.5 scenario data of the CMIP6 model were used to simulate sea surface temperature variability. Results showed that the extreme sea surface temperature of Cheonsu Bay in August 2017 was successfully simulated, and this extreme sea surface temperature had a significant negative correlation with the Pacific decadal variability index. As a result of future climate prediction, it was found that an average of 2.9℃ increased during the simulation period of 86 years in the Chungnam west coast and there was a seasonal difference (3.2℃ in summer, 2.4℃ in winter). These seasonal differences indicate an increase in the annual temperature range, suggesting that extreme events may occur more frequently in the future.

• Atmosphere
• /
• v.26 no.4
• /
• pp.697-709
• /
• 2016

This study estimates and evaluates the extreme value of 30 m-resolution daily maximum and minimum temperatures over South Korea, using inverse distance weighting (IDW), parameter-elevation regression on independent slopes model (PRISM) and generalized extreme value (GEV) method. The three experiments are designed and performed to find the optimal estimation strategy to obtain extreme value. First experiment (EXP1) applies GEV firstly to automated surface observing system (ASOS) to estimate extreme value and then applies IDW to produce high-resolution extreme values. Second experiment (EXP2) is same as EXP1, but using PRISM to make the high-resolution extreme value instead of IDW. Third experiment (EXP3) firstly applies PRISM to ASOS to produce the high-resolution temperature field, and then applies GEV method to make high resolution extreme value data. By comparing these 3 experiments with extreme values obtained from observation data, we find that EXP3 shows the best performance to estimate extreme values of maximum and minimum temperatures, followed by EXP1 and EXP2. It is revealed that EXP1 and EXP2 have a limitation to estimate the extreme value at each grid point correctly because the extreme values of these experiments with 30 m-resolution are calculated from only 60 extreme values obtained from ASOS. On the other hand, the extreme value of EXP3 is similar to observation compared to others, since EXP3 produces 30m-resolution daily temperature through PRISM, and then applies GEV to that result at each grid point. This result indicates that the quality of statistically produced high-resolution extreme values which are estimated from observation data is different depending on the combination and procedure order of statistical methods.

• Journal of Climate Change Research
• /
• v.6 no.2
• /
• pp.87-94
• /
• 2015

To compare changes in winter temperature over South Korea, 30-year average climate data and climate data of recent 10 years (2014~2014) such as mean temperature, daily maximum temperature and daily minimum temperature were analyzed. Also, we set analysis extreme cold waves frequency related to winter such as freezing days, snow days, days with temperature of below -5, and days with temperature of below -10. This process enabled the comparative analysis of winter temperature changes and extreme cold waves frequency related to winter. This study estimated that winter temperature has gradually increased throughout the last five decades, however, the frequency of extreme weather, such as cold waves has also increased.

• Smart Structures and Systems
• /
• v.20 no.1
• /
• pp.11-22
• /
• 2017

The long-term effect of ambient temperature on bridge strain is an important and challenging problem. To investigate this issue, one year data of strain and ambient temperature of a long-span cable-stayed bridge is studied in this paper. The measured strain-time history is decomposed into two parts to obtain the strains due to vehicle load and temperature alone. A linear regression model between the temperature and the strain due to temperature is established. It is shown that for every $1^{\circ}C$ increase in temperature, the stress is increased by 0.148 MPa. Furthmore, the extreme value distributions of the strains due to vehicle load, temperature and the combination effect of them during the remaining service period are estimated by the average conditional exceedance rate approach. This approach avoids the problem of declustering of data to ensure independence. The estimated results demonstrate that the 95% quantile of the extreme strain distribution due to temperature is up to $1.488{\times}10^{-4}$ which is 2.38 times larger than that due to vehicle load. The study also indicates that the estimated extreme strain can reflect the long-term effect of temperature on bridge strain state, which has reference significance for the reliability estimation and safety assessment.

• Journal of Environmental Science International
• /
• v.17 no.6
• /
• pp.657-669
• /
• 2008

Lately extreme weather event is occurring because of the global warming. Especially disaster due to the extreme heat are increasing but the definition and the standard of the extreme heat is obscure until now. So this study established the extreme heat standard by using the number of daily deaths. As a result, considering the climate of the megalopolis using daily maximum heat index and daily maximum temperature was the best for the standard of the extreme heat. And it showed that extreme heat lasted for 2 days affects the death toll the most. The regional incidence of the extreme heat is highest at August and July, September and June is following.

• 한국방재학회:학술대회논문집
• /
• 2008.02a
• /
• pp.89-92
• /
• 2008

The extreme heat watch warning system(EHWWS) that Korea Meterological Administration carried out a preliminary from July 1, 2007, considered both daily maximum temperature and daily maximum heat index simultaneously. It was requested revision of the standard level of EHWWS to solve the difficulty of forecasting occurred when we were considering two parameters simultaneously and we did not considering heat index according to areas. For this, we established three type standard, such as type 1 that considered both daily maximum temperature and daily maximum heat index, Under the extreme heat day that daily minimum temperature was more than $25^{\circ}C$, type 2 that considered daily maximum temperature and type 3 that considered only daily maximum heat index and then analyzed whether these 3 types satisfies the excess mortality of the extreme heat warning or not. As a results, type 1 and 2 were more explain away excess mortality each warning step than type 3. type 2 could also apply case of not to consider heat index according to areas and had a merit for extreme heat forecasting easily because the standard was simple. Therefore we think type 2 is more suitable and reasonable standard for Korea extreme heat watch warning system(KEHWWS) than type 1. In addition, we need to develop model that exactly predicts the excess mortality will be take place during the extreme heat warning and construct KEHWWS.

• Atmosphere
• /
• v.25 no.2
• /
• pp.205-219
• /
• 2015

In this study, the simulation results of temperature by regional climate model (Reg- CM4) over South Korea were corrected by Hempel et al. (2013)'s method (Hempel method), and evaluated with the observation data of 50 stations from Korea Meteorological Administration. Among the 30 years (1981~2010) of simulation data, 20 years (1981~2000) of simulation data were used as a training data, and the remnant 10 years (2001~2010) data were used for the evaluation of correction. In general, the Hempel method and parametric quantile mapping show a reasonable correction both in mean and extreme climate of temperature. As the results, the systematic underestimation of mean temperature was greatly reduced after bias correction by Hempel method. And the overestimation of extreme climate, such as the number of TN5% and freezing day, was significantly recovered. In addition to that, the Hempel method better preserved the temporal trend of simulated temperature than other bias correction methods, such as the quantile mapping. However, the overcorrection of the extreme climate related to the upper quantile, such as TX5% and hot days, resulted in the exaggeration of the simulation errors. In general, the Hempel method can reduce the systematic biases embedded in the simulation results preserving the temporal trend but it tends to overcorrect the non-linear biases, in particular, extreme climate related to the upper percentile.

• Journal of Environmental Science International
• /
• v.23 no.5
• /
• pp.873-885
• /
• 2014

To identify the characteristics of extreme heat events and tropical nights in major cities, the correlations between automated synoptic observing station (ASOS), automatic weather station (AWS), and temperature in seven metropolitan areas were analyzed. Temperatures at ASOS were found to be useful sources of the reference temperature of each area. To set the standard for identifying dates of extreme heat events in relation to regional topography and the natural environment, the monthly and yearly frequency of extreme heat in each region was examined, based on the standards for extreme heat day (EHD), tropical night day (TND), and extreme heat and tropical night day (ETD). All three cases identified 1994 as the year with the most frequent heat waves. The frequency was low according to all three cases in 1993, 2003 and 2009. Meanwhile, the yearly rate of increase was the highest in 1994, followed by 2010 and 2004, indicating that the frequency of extreme heat changed significantly between 1993 and 1994, 2003 and 2004, and 2009 and 2010. Therefore all three indexes can be used as a standard for high temperature events. According to monthly frequency data for EHD, TND, and ETD, July and August accounted for 80% or more of the extreme heat of the entire year.