• Atmosphere
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• v.26 no.4
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• pp.665-672
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• 2016

In this study, we examine future changes in the Hadley cell (HC) strength using CMIP5 climate change simulations. The current study is an extension of a previous study by Seo et al. that used all 30 available models. Here, we select 18-23 well-performing models based on their significant internal sensitivity of the interannual HC strength variation to the latitudinal temperature gradient variation. The model projections along with simple scaling analysis show that the inter-model variability in the HC strength change is a result of the inter-model spread in the meridional temperature gradient across the subtropics for both DJF and JJA, not by the tropopause height or gross static stability change. The HC strength is expected to weaken significantly during DJF, while little change is expected in the JJA HC strength. Compared to the calculations with all model members, selected model statistics increase the linear correlation between the changes in HC strength and meridional temperature gradient by 13~23%, confirming the robust sensitivity of the HC strength to the meridional temperature gradient. Two scaling equations for the selected models predict changes in HC strength better than all-member predictions. In particular, the prediction improvement in DJF is as high as 30%. The simple scaling relations successfully predict both the ensemble-mean changes and model-to-model variations in the HC strength for both seasons.

• The Plant Pathology Journal
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• v.36 no.5
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• pp.406-417
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• 2020

Early warning services for crop diseases are valuable when they provide timely forecasts that farmers can utilize to inform their disease management decisions. In South Korea, collaborative disease controls that utilize unmanned aerial vehicles are commonly performed for most rice paddies. However, such controls could benefit from seasonal disease early warnings with a lead time of a few months. As a first step to establish a seasonal disease early warning service using seasonal climate forecasts, we developed the EPIRICE Daily Risk Model for rice blast by extracting and modifying the core infection algorithms of the EPIRICE model. The daily risk scores generated by the EPIRICE Daily Risk Model were successfully converted into a realistic and measurable disease value through statistical analyses with 13 rice blast incidence datasets, and subsequently validated using the data from another rice blast experiment conducted in Icheon, South Korea, from 1974 to 2000. The sensitivity of the model to air temperature, relative humidity, and precipitation input variables was examined, and the relative humidity resulted in the most sensitive response from the model. Overall, our results indicate that the EPIRICE Daily Risk Model can be used to produce potential disease risk predictions for the seasonal disease early warning service.

• Environmental and Resource Economics Review
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• v.17 no.2
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• pp.287-311
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• 2008

This paper is designed to examine how the global timber market impacted by climate change would affect global warming through the carbon flux of forests. For this purpose, we integrated the modified TSM 2000 and the extended TCM in order to simulate the projection of net carbon release of forests from 1995 to 2085. On the basis of the simulation results under normal demand growth scenario, we identified that the global timber market impacted by climate change ameliorates the atmospheric carbon about 3.60% of carbon dioxide concentration in 1990 over 90 years. This implies that the global timber market impacted by climate change has a negative feedback effect on global warming over 90 years. For sensitivity analysis, we performed these simulation procedure under high demand growth scenario and very high demand growth scenario.

• Journal of the Korean association of regional geographers
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• v.19 no.4
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• pp.615-626
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• 2013

In this study, spatial patterns of the urban flood vulnerability index in Seoul are examined by considering climate exposure, sensitivity, and adaptability associated with floodings for recent 5 year (2006~2010) period by the smallest administrative unit called Dong. According to the results of correlation analyses based on the IPCC(Intergovernmental Panel on Climate Change)'s vulnerability model, among many variables associated with urban flooding, rainwater tank capacity, 1-day maximum precipitation and flood pumping station capacity have statistically-significant, and relatively-high correlations with the number of flood damage in Seoul. The flood vulnerability map demonstrates that the extensive areas along Anyang and Joongnang streams show relatively high flood vulnerability in Seoul due to high sensitivity. Especially in case of Joongnang stream areas, climatic factors also contribute to the increase of flood vulnerability. At local scales, several Dong areas in Gangdong-gu and Songpa-gu also show high flood vulnerability due to low adaptability, while those in Gangnam-gu do due to high sensibility and climate factor such as extreme rainfall events. These results derived from the flood vulnerability map by Dong unit can be utilized as primary data in establishing the adaptation, management and proactive policies for flooding prevention within the urban areas in more detail.

• Journal of Environmental Impact Assessment
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• v.24 no.2
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• pp.190-203
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• 2015

VRI(Vulnerability-Resilience Index), which is defined as a function of 3 variables: climate exposure, sensitivity, and adaptive capacity, has been quantified for the case of Typhoon which is one of the extreme weathers that will become more serious as climate change proceeds. Because VRI is only indicating the relative importance of vulnerability between regions, the VRI quantification is prerequisite for the effective adaptation policy for climate in Korea. For this purpose, damage statistics such as amount of damage, occurrence frequency, and major damaged districts caused by Typhoon over the past 20 years, has been employed. According to the VRI definition, we first calculated VRI over every district in the case of both with and without weighting factors of climate exposure proxy variables. For the quantitative estimation of weighting factors, we calculated correlation coefficients (R) for each of the proxy variables against damage statistics of Typhoon, and then used R as weighting factors of proxy variables. The results without applying weighting factors indicates some biases between VRI and damage statistics in some regions, but most of biases has been improved by applying weighting factors. Finally, due to the relations between VRI and damage statistics, we are able to quantify VRI expressed as a unit of KRW, showing that VRI=1 is approximately corresponding to 500 hundred million KRW. This methodology of VRI quantification employed in this study, can be also practically applied to the number of future climate scenario studies over Korea.

• Journal of Climate Change Research
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• v.1 no.3
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• pp.219-226
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• 2010

This study is analyzed the financial feasibility of biomass power plant in China in terms of fuel marginal price of biomass power plant. The range of fuel price is 150~300 RMB and IRR(Internal Rate of Return), NPV(Net Present Value), DSCR(Debt Service Coverage Ratio) and operation time are analyzed by 10 RMB from 150 RMB. The sensitivity of IRR went down by 1.35 on average. The sensibility of NPV showed big difference by 20% on 260 RMB and 270 RMB. In addition, DSCR of loan is at 1.0 at raw cost of 242 RMB and at lower than 1.0 when the raw cost over 242 RMB. It means that the pay-off of principal and interest of the loan is expected to be difficult in that case. The operation time of power plant should be 88% against standard operation time to maintain over 1.0 of DSCR. Therefore, the factors affecting the cost of raw material to build the power plant and to operate it should be prioritized.

• Journal of Korea Water Resources Association
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• v.39 no.11 s.172
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• pp.923-934
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• 2006

In this study, the effects of variability in climate, groundwater withdrawal, and landuse on dry-weather streamflows were investigated by input sensitivity analysis using SWAT (Soil and Water Assessment Tool). Since only dry-period precipitation and daily average solar radiation among climate variables have high correlation coefficients to total flow (TF), sensitivity analyses of those were conducted. Furthermore, an equation was derived from simulation results for 30 years by multiple regression analysis. It may be used to estimate effects of various climatic variations (precipitation during the dry period, precipitation during the previous wet period, solar radiation, and maximum temperature). If daily average maximum temperatures increase, TFs during the dry period will decrease. Sensitivities of groundwater withdrawal and landuse were also conducted. Similarly, groundwater withdrawals strongly affect streamflow during the dry period. However, landuse changes (increasing urbanization) within the forested watershed do not appear to significantly affect TF during the dry period. Finally, a combined equation was derived that describes the relationship between the total runoff during the dry period and the climate, groundwater withdrawal and urban area proportion. The proposed equation will be useful to predict the water availability during the dry period in the future since it is dependent upon changes of temperature, precipitation, solar radiation, urban area ratio, and groundwater withdrawal.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.413-413
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• 2023

Wetlands are a critical component of the global carbon cycle and are essential in mitigating climate change. Accurately quantifying wetland carbon emissions is crucial for understanding and predicting the impact of wetlands on the global carbon budget. The uncertainty quantifying carbon in wetlands may comes from the ecosystem's hydrological, biochemical, and microbiological variability. The Community Land Model is a sophisticated and flexible land surface model that offers several configuration options such as energy and water fluxes, vegetation dynamics, and biogeochemical cycling, necessitating careful consideration for the alternative configurations before model implementation to develop a practical model framework. We conducted a systematic literature review, analyzing the alternatives, focusing on the carbon stock pools configurations and the parameters with significant sensitivity for carbon quantification in wetlands. In addition, we evaluated the feasibility and availability of in situ observation data necessary for validating the different alternatives. This analysis identified the most suitable option for our study site, the Binbong Wetland, in Korea.

• Korean Journal of Remote Sensing
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• v.33 no.6_2
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• pp.1119-1137
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• 2017

This study assessed the water provisioning and climate mitigation ecosystem services of the urban forest in Seoul and Gyeonggi-do. The ecosystem service assessment is conducted based on natural function, natural function and population, and natural function and the beneficiary of the ecosystem service. Then, the impact of climate change on ecosystem services is analyzed to figure out the sensitivity of the impact on the beneficiary when the natural function of forest destroys under climate change. Gyeonggi-do has higher function-based water provisioning ecosystem service than Seoul. And population-based water provisioning ecosystem service appears to be higher in the densely populated area. On the other hand, beneficiary-based water provisioning ecosystem service by applying both natural water supply function and beneficiary distribution appears different with the result of population-based water provisioning service assessment. In other words, regions with high beneficiary population show higher ecosystem service than those with a low beneficiary population even though they have the same water storage function. In addition, climate change has a negative impact on the water provisioning ecosystem service. Under climate change, water provisioning service is expected to decrease by 26%. For climate mitigation service, regions close to the forest seem to have a low temperature, which indicates their high climate mitigation service. The center of the city with high beneficiary population shows high beneficiary-based ecosystem service. The climate change impacts the forest growth to decrease which affect the beneficiary-based climate mitigation ecosystem service to decrease by 33%. From this study, we conclude that beneficiary-based function and ecosystem service assessment is needed as well as the supply-based classification of forest function suggested by Korea Forest Service. In addition, we suggest that not only supply-based function classification and ecosystem service assessment but also beneficiary-based function classification and ecosystem service assessment is needed for managing the urban forest, which has been destroyed by climate change. This will contribute to revaluing cases where a forest with low natural function but high beneficiary-based ecosystem service, which is not considered under the current forest function-based assessment system. Moreover, this could assist in developing a suitable management plan for the urban forest.

• Korean Journal of Remote Sensing
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• v.29 no.6
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• pp.589-593
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• 2013

Sea Surface Temperature (SST) is the temperature close to the ocean's surface and affects the Earth's atmosphere as an important parameter for the climate circulation and change. The SST from satellite still has biases from the error in specifying retrieval coefficients from either forward modeling or instrumental biases. So in this paper, we performed sensitivity analysis using input parameter of the SST to notice that the SST is most affected among the input parameter. We used Infrared (IR) data from the Communication, Ocean, and Meteorological Satellite (COMS)/Meteorological Imager (MI) from April 2011 to March 2012. We also used the Global Space-based Inter-Calibration System (GSICS) correction to quality of the IR data from COMS. SST was calculated by substituting the input parameters; IR data with or without the GSICS correction. The results of this sensitivity analysis, the SST was sensitive from -0.0403 to 0.2743 K when the IR data were changed by the GSICS corrections.