• Journal of Climate Change Research
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• v.3 no.4
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• pp.281-291
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• 2012

Forests act as carbon sinks and also improve water resources and biodiversity to climate change. Secure funding, administrative support, and sustainable management systems are essential to conserve forests and to implement international forestry related projects to climate change. Public private partnership (PPP) could be an effective way for forestry sector in developing countries. Awareness analysis should be preceded in order to encourage participation of enterprises for the diversification of funding and the enhancing quality of projects. We conducted a survey targeting more than 129 private enterprises for awareness analysis. As a result, lack of information, complexity of processes and low profit resulted in low interest on forest projects from private enterprises. Improving awareness of recipient countries on forest resources, financial and institutional supports from the public sector, information sharing, performance management and equal partnership between sectors were suggested to encourage PPP in international forestry related projects to climate change.

• Atmosphere
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• v.34 no.2
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• pp.123-138
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• 2024

Using 18 multi-model-based a Shared Socioeconomic Pathway (SSP) and Representative Concentration Pathways (RCP) climate change scenarios, future changes in temperature and warmth index on the Korean Peninsula in the 21st century (2011~2100) were analyzed. In the analysis of the current climate (1981~2010), the ensemble averaged model results were found to reproduce the observed average values and spatial patterns of temperature and warmth index similarly well. In the future climate projections, temperature and warmth index are expected to rise in the 21st century compared to the current climate. They go further into the future and the higher carbon scenario (SSP5-8.5), the larger the increase. In the 21st century, in the low-carbon scenario (SSP1-2.6), temperature and warmth index are expected to rise by about 2.5℃ and 24.6%, respectively, compared to the present, while in the high-carbon scenario, they are expected to rise by about 6.2℃ and 63.9%, respectively. It was analyzed that reducing carbon emissions could contribute to reducing the increase in temperature and warmth index. The increase in the warmth index due to climate change can be positively analyzed to indicate that the effective heat required for plant growth on the Korean Peninsula will be stably secured. However, it is necessary to comprehensively consider negative aspects such as changes in growth conditions during the plant growth period, increase in extreme weather such as abnormally high temperatures, and decrease in plant diversity. This study can be used as basic scientific information for adapting to climate change and preparing response measures.

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.3
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• pp.170-178
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• 2016

It is not clear how to apply the climate scenario to assess the impact of climate change in the agricultural sector. Even if you apply the same scenario, the result can vary depending on the temporal-spatial downscaling, the post-treatment to adjust the bias of a model, and the prediction model selection (used for an impact assessment). The end user, who uses the scenario climate data, should select climate factors, a spatial extend, and a temporal range appropriate for the objectives of an analysis. It is important to draw the impact assessment results with minimum uncertainty by evaluating the suitability of the data including the reproducibility of the past climate and calculating the optimum future climate change scenario. This study introduced data processing methods for reducing the uncertainties in the process of applying the future climate change scenario to users in the agricultural sector and tried to provide basic information for appropriately using the scenario data in accordance with the study objectives.

• Journal of Korean Society on Water Environment
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• v.26 no.5
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• pp.822-833
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• 2010

Temperature increase due to climate changes causes change of water temperature in rivers which results in change of water quality etc. and the change of river ecosystem has a great impact on human life. Analyzing the impact of current climate changes on air and water temperature is an important thing in adapting to the climate changes. This study examined the effect of climate changes through analyzing air temperature trend for Nakdong river basin and analyzed the elasticity of air-water temperature to understand the effect of climate changes on water temperature. For analysis air temperature trend, collecting air temperature data from the National Weather Service on main points in Nakdong river basin, and resampling them at the units of year, season and month, used as data for air temperature trend analysis. Analyzing for elasticity of air-water temperature, the data were collected by the Water Environment Information system for water temperature, while air temperature data were collected at the National Weather Service point nearest in the water temperature point. And using the results of trend analysis and elasticity analysis, the effect of climate changes on water temperature was examined estimating future water temperature in 20 years and 50 years after. It is judged that analysis on mutual impact between factors such as heat budget, precipitation and evapotranspiration on river water temperature affected by climate changes and river water temperature is necessary.

• Journal of Environmental Impact Assessment
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• v.22 no.6
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• pp.677-693
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• 2013

IPCC showed that calculation of climate vulnerability index requires standardization process of various proxy variables for the estimation of climate exposure, sensitivity, and adaptive capacity. In this study, four different methodologies of standardization methods: Z-score, Rescaling, Ranking, and Distance to the reference country, are employed to evaluate climate vulnerability-VRI (Vulnerability-Resilience Indicator) over Korean peninsula, and the error ranges of VRI, arising from employing the different standardization are estimated. All of proxy variables are provided by CCGIS (Climate Change adaptation toolkit based on GIS) which hosts information on both past and current socio-economic data and climate and environmental IPCC SRES (A2, B1, A1B, A1T, A1FI, and A1 scenarios) climate data for the decades of 2000s, 2020s, 2050s, and 2100s. The results showed that Z-score and Rescaling methods showed statistically undistinguishable results with minor differences of spatial distribution, while Ranking and Distance to the reference country methods showed some possibility to lead the different ranking of VRI among South Korean provinces, depending on the local characteristics and reference province. The resultant VRIs calculated from different standardization methods showed Cronbach's alpha of more than 0.84, indicating that all of different methodologies were overall consistent. Similar horizontal distributions were shown with the same trends: VRI increases as province is close to the coastal region and/or it close toward lower latitude, and decreases as it is close to urbanization area. Other characteristics of the four different standardization are discussed in this study.

• 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.34 no.20
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• pp.8257-8271
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• 2021

This study presents the ability of seasonal forecast models to represent the observed midlatitude teleconnection associated with El Niño-Southern Oscillation (ENSO) events over the North American region for the winter months of December, January, and February. Further, the impacts of the associated errors on regional forecast performance for winter temperatures are evaluated, with a focus on 1-month-lead-time forecasts. In most models, there exists a strong linear relationship of temperature anomalies with ENSO, and, thus, a clear anomaly sign separation between both ENSO phases persists throughout the winter, whereas linear relationships are weak in observations. This leads to a difference in the temperature forecast performance between the two ENSO phases. Forecast verification scores show that the winter-season warming events during El Niño in northern North America are more correctly forecast in the models than the cooling events during La Niña and that the winter-season cooling events during El Niño in southern North America are also more correctly forecast in the models than warming events during La Niña. One possible reason for this result is that the remote atmospheric teleconnection pattern in the models is almost linear or symmetric between the El Niño and La Niña phases. The strong linear atmospheric teleconnection appears to be associated with the models' failure in simulating the westward shift of the tropical Pacific Ocean rainfall response for the La Niña phase as compared with that for the El Niño phase, which is attributed to the warmer central tropical Pacific in the models. This study highlights that understanding how the predictive performance of climate models varies according to El Niño or La Niña phases is very important when utilizing predictive information from seasonal forecast models.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2013.11a
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• pp.60-66
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• 2013

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.1
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• pp.42-55
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• 2017

Since the phases and patterns of the climate adaptability of vegetation can greatly differ from region to region, an intensive pixel scale approach is required. In this study, Partial Least Squares (PLS) regression on satellite image-based vegetation index is conducted for to assess the effect of climate factors on vegetation productivity and to predict future productivity of forests vegetation in South Korea. The results indicate that the mean temperature of wettest quarter (Bio8), mean temperature of driest quarter (Bio9), and precipitation of driest month (Bio14) showed higher influence on vegetation productivity. The predicted 2050 EVI in future climate change scenario have declined on average, especially in high elevation zone. The results of this study can be used in productivity monitoring of climate-sensitive vegetation and estimation of changes in forest carbon storage under climate change.

• Journal of the Korean Data and Information Science Society
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• v.28 no.1
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• pp.67-74
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• 2017

This paper analyzes the causal relationship from climate to international grain prices. Although climate is an important factor affecting the grain markets, it has been restrictively considered in previous studies analyzing the causal relationship of international grain prices. In this paper, monthly data from May 1987 to 2013 is used for the causal analysis in which the sea surface temperature (SST), a representative global climate variable, and the international prices of wheat, corn, and soybean, the world's three major crops, are considered. The test method is the parametric version of the nonparametric test for causality in high-order moments suggested by Nishiyama et al. (2011). The results show that the climate causes in the first moment the prices of all the three grains and causes in the second moment the prices of corn and soybean, but does not cause in the third moment any of the three grain prices.