• Atmosphere
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• v.22 no.2
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• pp.149-161
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• 2012

Going by the research results of the past, of all the uncertainties resulting from the research on climate change, the uncertainty caused by the climate change scenario has the highest degree of uncertainty. Therefore, depending upon what kind of climate change scenario one adopts, the projection of the water resources in the future will differ significantly. As a matter of principle, it is highly recommended to utilize all the GCM scenarios offered by the IPCC. However, this could be considered to be an impractical alternative if a decision has to be made at an action officer's level. Hence, as an alternative, it is deemed necessary to select several scenarios so as to express the possible number of cases to the maximum extent possible. The objective standards in selecting the climate change scenarios have not been properly established and the scenarios have been selected, either at random or subject to the researcher's discretion. In this research, a new scenario selection process, in which it is possible to have the effect of having utilized all the possible scenarios, with using only a few principal scenarios and maintaining some of the uncertainties, has been suggested. In this research, the use of cluster analysis and the selection of a representative scenario in each cluster have efficiently reduced the number of climate change scenarios. In the cluster analysis method, the K-means clustering method, which takes advantage of the statistical features of scenarios has been employed; in the selection of a representative scenario in each cluster, the selection method was analyzed and reviewed and the PDF method was used to select the best scenarios with the closest simulation accuracy and the principal scenarios that is suggested by this research. In the selection of the best scenarios, it has been shown that the GCM scenario which demonstrated high level of simulation accuracy in the past need not necessarily demonstrate the similarly high level of simulation accuracy in the future and various GCM scenarios were selected for the principal scenarios. Secondly, the "Maximum entropy" which can quantify the uncertainties of the climate change scenario has been used to both quantify and compare the uncertainties associated with all the scenarios, best scenarios and the principal scenarios. Comparison has shown that the principal scenarios do maintain and are able to better explain the uncertainties of all the scenarios than the best scenarios. Therefore, through the scenario selection process, it has been proven that the principal scenarios have the effect of having utilized all the scenarios and retaining the uncertainties associated with the climate change to the maximum extent possible, while reducing the number of scenarios at the same time. Lastly, the climate change scenario most suitable for the climate on the Korean peninsula has been suggested. Through the scenario selection process, of all the scenarios found in the 4th IPCC report, principal climate change scenarios, which are suitable for the Korean peninsula and maintain most of the uncertainties, have been suggested. Therefore, it is assessed that the use of the scenario most suitable for the future projection of water resources on the Korean peninsula will be able to provide the projection of the water resources management that maintains more than 70~80% level of uncertainties of all the scenarios.

• Atmosphere
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• v.28 no.4
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• pp.457-467
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• 2018

This study investigated the variability of spring (March-May) forest fire risk in Korea for the period 1991~2017 and analyzed its relationship with large-scale climate factors. The Forest Weather Index (FWI) representing the meteorological risk for forest fire occurrences calculated based on observational data and its relationship with large-scale climate factors were analyzed. We performed the empirical orthogonal function (EOF) analysis on the spring FWI. The leading EOF mode of FWI accounting for about 70% of total variability was found to be highly correlated with total number of forest fire occurrences in Korea. The high FWI, forest fire occurrence risk, in Korea, is associated with warmer atmosphere temperature in midwest Eurasia-China-Korea peninsula, cyclonic circulation anomaly in northeastern China-Korea peninsula-northwest pacific, westerly wind anomaly in central China-Korea peninsula, and low humidity in Korea. These are further related with warmer sea surface temperature and enhanced outgoing longwave radiation over Western Pacific, which represents a typical condition for a La $Ni\tilde{n}a$ episode. This suggests that large-scale climate factors over East Asia and ENSO could have a significant influence on the occurrence of spring forest fires in Korea.

• Journal of the Korean earth science society
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• v.38 no.5
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• pp.345-356
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• 2017

It is important to understand the variability of tropospheric ozone since it is both a major pollutant affecting human health and a greenhouse gas influencing global climate. We analyze the characteristics of East Asia tropospheric ozone simulated in a chemistry-climate model. We use a global chemical transport model, driven by the prescribed meteorological fields from an air-sea coupled climate model simulation. Compared with observed data, the ozone simulation shows differences in distribution and concentration levels; in the vicinity of the Korean Peninsula, a large error occurred in summer. Our analysis reveals that this bias is mainly due to the difference in atmospheric circulation, as the anomalous southerly winds lead to the decrease in tropospheric ozone in this region. In addition, observational data have shown that the western North Pacific subtropical high (WNPSH) reduces tropospheric ozone across the southern China/Korean Peninsula/Japan region. In the model, the ozone changes associated with WNPSH are shifted westward relative to the observations. Our findings suggest that the variations in WNPSH should be considered in predicting tropospheric ozone concentrations.

• Atmosphere
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• v.31 no.5
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• pp.607-623
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• 2021

This study presents projections of future extreme climate over the Korean Peninsula (KP), using bias-corrected data from multiple regional climate model (RCM) simulations in CORDEX-EA Phase 2 project. In order to confirm difference according to degree of greenhouse gas (GHG) emission, high GHG path of SSP5-8.5 and low GHG path of SSP1-2.6 scenario are used. Under SSP5-8.5 scenario, mean temperature and precipitation over KP are projected to increase by 6.38℃ and 20.56%, respectively, in 2081~2100 years compared to 1995~2014 years. Projected changes in extreme climate suggest that intensity indices of extreme temperatures would increase by 6.41℃ to 8.18℃ and precipitation by 24.75% to 33.74%, being bigger increase than their mean values. Both of frequency indices of the extreme climate and consecutive indices of extreme precipitation are also projected to increase. But the projected changes in extreme indices vary regionally. Under SSP1-2.6 scenario, the extreme climate indices would increase less than SSP5-8.5 scenario. In other words, temperature (precipitation) intensity indices would increase 2.63℃ to 3.12℃ (14.09% to 16.07%). And there is expected to be relationship between mean precipitation and warming, which mean precipitation would increase as warming with bigger relationship in northern KP (4.08% ℃^-1) than southern KP (3.53% ℃^-1) under SSP5-8.5 scenario. The projected relationship, however, is not significant for extreme precipitation. It seems because of complex characteristics of extreme precipitation from summer monsoon and typhoon over KP.

• Ocean and Polar Research
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• v.30 no.4
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• pp.373-378
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• 2008

Long-term tide-gauge data from around the Korean Peninsula were reanalyzed. Both the coastal water and the open sea surrounding the Korean Peninsula appeared to have been influenced by global warming. The long-term change in relative sea levels obtained from tidal stations showed a general rising trend, especially near Jeju Island. It is proposed that global warming may have caused shifting of the path of the Kuroshio branch (Tsushima Warm Current) toward Jeju Island, causing a persistent increase in the water levels along the coast of the island over the last few decades.

• Journal of Korean Society for Atmospheric Environment
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• v.28 no.3
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• pp.249-260
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• 2012

Monitoring of climate change and atmospheric environment by satellite measurements has been increased in recent years. In this study, nitrogen dioxide ($NO_2$) measurements from Ozone Monitoring Instrument (OMI) were compared with surface measurements over the Korean peninsula. $NO_2$ from OMI measurements showed high values and also showed seasonal variations such as high concentration in winter and low in summer over metropolitan areas while $NO_2$ concentration at national background station was low and did not clearly show seasonal variations. Surface measurements showed similar temporal and spatial variations to those of satellite measurement. The comparison between satellite measurements and surface measurements showed that the correlation between them was higher in urban area (r=0.64 at Seoul and r=0.63 at Daegu) than in national background stations (r=0.37 at Jeju) because the concentration in urban area was relatively high so that the variation of $NO_2$ concentration could be detected better than at national background stations by satellite. Satellite can effectively measure the emission and transport of pollutants with no limitations in spatial coverage.

• Corrosion Science and Technology
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• v.10 no.4
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• pp.109-117
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• 2011

The Korean Peninsula is located in the middle latitude of the northern hemisphere and has a clear 4-seasons and shows the typical temperate climate. Because of seasonal winds, it is cold and dry by a northwestern wind in the winter and it is hot and humid by a southeast wind in the summer. Also, temperature difference between the winter and the summer is large and it shows a rainy season from June to July but recently this regular trend may be greatly changed by an unusual weather phenomena. Since the Peninsula is east high west low type, the climate is complicated too. Because these geographical and climate characteristics can affect the properties of corrosion of metals and alloys, a systematic research on atmospheric corrosion in the Peninsula is required to understand and control the corrosion behavior of the industrial facilities. This paper analyzed the atmospheric corrosion factors for several environments in the Korean Peninsula and categorized the corrosivity of atmospheric corrosion of metals and alloys on the base of the related ISO standards. Annual pH values of rain showed the range of 4.5~5.5 in Korean Peninsula from 1999 to 2009 and coastal area showed relatively the low pH's rain. Annual $SO_2$ concentrations is reduced with time and its concentrations of every major cities were below the air quality standard, but $NO_2$concentration revealed a steady state and its concentration of Seoul has been over air quality standard. In 2007, $SO_2$classes of each sites were in $P_0{\sim}P_1$, and chloride classes were in $S_0{\sim}S_1$, and TOW classes were in ${\tau}_3{\sim}{\tau}_4$.That is, $SO_2$ and chloride classes were low but TOW class was high in Korean Peninsula. On the base of these environmental classes, corrosivity of carbon steel, zinc, copper, aluminium can be calculated that carbon steel was in C2-C3 classes and it was classified as low-medium, and zinc, copper, and aluminium showed C3 class and it was classified as medium.

• Journal of Climate Change Research
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• v.7 no.3
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• pp.325-334
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• 2016

We projected the distribution of Hedera rhombea, an evergreen broad-leaved climbing plant, under current climate conditions and predicted its future distributions under global warming. Inaddition, weexplained model uncertainty by employing 9 single Species Distribution model (SDM)s to model the distribution of Hedera rhombea. 9 single SDMs were constructed with 736 presence/absence data and 3 temperature and 3 precipitation data. Uncertainty of each SDM was assessed with TSS (Ture Skill Statistics) and AUC (the Area under the curve) value of ROC (receiver operating characteristic) analyses. To reduce model uncertainty, we combined 9 single SDMs weighted by TSS and resulted in an ensemble forecast, a TSS weighted ensemble. We predicted future distributions of Hedera rhombea under future climate conditions for the period of 2050 (2040~2060), which were estimated with HadGEM2-AO. RF (Random Forest), GBM (Generalized Boosted Model) and TSS weighted ensemble model showed higher prediction accuracies (AUC > 0.95, TSS > 0.80) than other SDMs. Based on the projections of TSS weighted ensemble, potential habitats under current climate conditions showed a discrepancy with actual habitats, especially in the northern distribution limit. The observed northern boundary of Hedera rhombea is Ulsan in the eastern Korean Peninsula, but the projected limit was eastern coast of Gangwon province. Geomorphological conditions and the dispersal limitations mediated by birds, the lack of bird habitats at eastern coast of Gangwon Province, account for such discrepancy. In general, potential habitats of Hedera rhombea expanded under future climate conditions, but the extent of expansions depend on RCP scenarios. Potential Habitat of Hedera rhombea expanded into Jeolla-inland area under RCP 4.5, and into Chungnam and Wonsan under RCP 8.5. Our results would be fundamental information for understanding the potential effects of climate change on the distribution of Hedera rhombea.

• Journal of Climate Change Research
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• v.9 no.1
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• pp.13-29
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• 2018

This study presented evaluation procedure for selecting appropriate GCMs and downscaling method by focusing on the climate extreme indices suitable for climate change adaptation. The procedure includes six stages of processes as follows: 1) exclusion of unsuitable GCM through raw GCM analysis before bias correction; 2) calculation of the climate extreme indices and selection of downscaling method by evaluating reproducibility for the past and distortion rate for the future period; 3) selection of downscaling method based on evaluation of reproducibility of spatial correlation among weather stations; and 4) MME calculation using weight factors and evaluation of uncertainty range depending on number of GCMs. The presented procedure was applied to 60 weather stations where there are observed data for the past 30 year period on Korea Peninsula. First, 22 GCMs were selected through the evaluation of the spatio-temporal reproducibility of 29 GCMs. Between Simple Quantile Mapping (SQM) and Spatial Disaggregation Quantile Delta Mapping (SDQDM) methods, SQM was selected based on the reproducibility of 27 climate extreme indices for the past and reproducibility evaluation of spatial correlation in precipitation and temperature. Total precipitation (prcptot) and annual 1-day maximum precipitation (rx1day), which is respectively related to water supply and floods, were selected and MME-based future projections were estimated for near-future (2010-2039), the mid-future (2040-2069), and the far-future (2070-2099) based on the weight factors by GCM. The prcptot and rx1day increased as time goes farther from the near-future to the far-future and RCP 8.5 showed a higher rate of increase in both indices compared to RCP 4.5 scenario. It was also found that use of 20 GCM out of 22 explains 80% of the overall variation in all combinations of RCP scenarios and future periods. The result of this study is an example of an application in Korea Peninsula and APCC Integrated Modeling Solution (AIMS) can be utilized in various areas and fields if users want to apply the proposed procedure directly to a target area.

• Proceedings of the Korean Society of Crop Science Conference
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• 2006.11a
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• pp.12-12
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• 2006