• Journal of Climate Change Research
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• v.5 no.3
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• pp.267-275
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• 2014

A key driver for climate change caused by global average temperature rise is greenhouse gas cumulative emissions that stay for long term in the atmosphere. Although at the moment there is no GHG emission, global warming will continue owing to GHG cumulative emission. In this study, scenarios are developed based on two types of optimistic and conservative diffusion goal. There were a total of 6 alternatives scenarios. The objective of this study are to compare scenarios in terms of GHG cumulative emissions and alternative fuels. An object of analysis is the residential buildings and time frame of scenarios is set up by 2030. And this study uses the LEAP model that is a bottom-up energy model. In conclusion, It is important to set specific diffusion pathway for mitigating climate change virtually.

• Journal of Climate Change Research
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• v.8 no.1
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• pp.1-10
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• 2017

Over the past centuries, industrialization in developed and developing countries has had a negative impact on global warming, releasing $CO_2$ emissions into the Earth's atmosphere. In recent years, the transportation sector, which emits one-third of total $CO_2$ emissions in the United States, has adapted by implementing a climate change action plan to reduce $CO_2$ emissions. Having an environmental policy might be an essential factor in mitigating the man-made global warming threats to protect public health and the coexistent needs of current and future generations; however, to my best knowledge, no research has been conducted in such a context with appropriate statistical validation process to evaluate the effects of climate change policy on $CO_2$ emission reduction in recent years in the U.S. transportation. The empirical findings using an entity fixed-effects model with valid statistical tests show the positive effects of climate change policy on $CO_2$ emission reduction in a state. With all the 49 states joining the climate change action plans, the U.S. transportation sector is expected to reduce its $CO_2$ emissions by 20.2 MMT per year, and for the next 10 years, the cumulated $CO_2$ emission reduction is projected to reach 202.3 MMT, which is almost equivalent to the $CO_2$ emissions from the transportation sector produced in 2012 by California, the largest $CO_2$ emission state in the nation.

• Atmosphere
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• v.29 no.2
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• pp.149-164
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• 2019

The purpose of this study is to introduce the improvement of current operational climate prediction system of KMA and to compare previous and improved that. Whereas the previous system is based on GloSea5GA3, the improved one is built on GloSea5GC2. GloSea5GC2 is a fully coupled global climate model with an atmosphere, ocean, sea-ice and land components through the coupler OASIS. This is comprised of component configurations Global Atmosphere 6.0 (GA6.0), Global Land 6.0 (GL6.0), Global Ocean 5.0 (GO5.0) and Global Sea Ice 6.0 (GSI6.0). The compositions have improved sea-ice parameters over the previous model. The model resolution is N216L85 (~60 km in mid-latitudes) in the atmosphere and ORCA0.25L75 ($0.25^{\circ}$ on a tri-polar grid) in the ocean. In this research, the predictability of each system is evaluated using by RMSE, Correlation and MSSS, and the variables are 500 hPa geopotential height (h500), 850 hPa temperature (t850) and Sea surface temperature (SST). A predictive performance shows that GloSea5GC2 is better than GloSea5GA3. For example, the RMSE of h500 of 1-month forecast is decreased from 23.89 gpm to 22.21 gpm in East Asia. For Nino3.4 area of SST, the improvements to GloSeaGC2 result in a decrease in RMSE, which become apparent over time. It can be concluded that GloSea5GC2 has a great performance for seasonal prediction.

• International Journal of Contents
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• v.17 no.1
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• pp.61-70
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• 2021

As the resolution of climate change scenario data applied with regional models increased, Earth System Grid Federation (ESGF) was established around major climate-related organizations to jointly operated and manage large-scale climate data. ESGF developed standard software to provide model output, observation data management, dissemination, and analysis using Peer to Peer (P2P) computing technology. Roles of each institution were divided into index and data nodes. Therefore, ESGF data node was established at APEC Climate Center in Korea on behalf of Asia to share data on climate change scenarios of CORDEX-East Asia (CORDEX-EA) to study climate changes in Eastern Asia. Climate researchers are expected to play a large role in researching causes of global warming and responding to climate change by providing CORDEX-EA regional model data to the world through ESGF data node.

• Atmosphere
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• v.32 no.3
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• pp.235-246
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• 2022

A large number of MJO skill metrics and process-oriented MJO simulation metrics have been developed by previous studies including the MJO Working Group and Task Force. To assess models' successes and shortcomings in the MJO simulation, a standardized set of diagnostics with the additional set of dynamics-oriented diagnostics are applied. The Global Coupled (GC) model developed for the operation of the climate prediction system is used with the comparison between the GC2 and GC3.1. Two GC models successfully capture three-dimensional dynamic and thermodynamic structure as well as coherent eastward propagation from the reference regions of the Indian Ocean and the western Pacific. The low-level moisture convergence (LLMC) ahead of the MJO deep convection, the low-level westerly and easterly associated with the coupled Rossby-Kelvin wave and the upper-level divergence are simulated successfully. The GC3.1 model simulates a better three-dimensional structure of MJO and thus reproduces more realistic eastward propagation. In GC2, the MJO convection following the LLMC near and east of the Maritime Continent is much weaker than observation and has an asymmetric distribution of both low and upper-level circulation anomalies. The common shortcomings of GC2 and GC3.1 are revealed in the shorter MJO periods and relatively weak LLMC as well as convective activity over the western Indian Ocean.

• Advances in environmental research
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• v.9 no.2
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• pp.97-107
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• 2020

The indiscriminate growth in global population poses a threat to the world in handling and disposal of Municipal solid waste. Rapid urban growth increases the production, consumption and generation of Municipal solid waste which leads to a drastic change in the environment. The methane produced from the Municipal Solid waste accounts for up to 11% global anthropogenic emissions, which is a major cause for global warming. This study reports the methane emission estimation using IPCC default, TNO, LandGEM, EPER and close flux chamber from open dump yards at Perungudi and Kodungaiyur in Chennai, India. The result reveals that the methane emission using close flux chamber was in the range of 8.8 Gg/yr-11.3 Gg/yr and 6.1Gg/yr to 9.1 Gg/yr at Kodungaiyur and Perungudi dump yard respectively. The per capita waste generation was estimated based on waste generation and population. The waste generation potential was projected using linear regression model for the period 2017-2050. The trend of CH₄ emission in the actual field measurement were increased every year, similarly the emission trend also increased in IPCC default method (mass balance approach), EPER Germany (zero order decay model) where as TNO and Land GEM (first order decay model) were decreased. The present study reveals that Kodungaiyur dump yard is more vulnerable to methane emission compared to Perungudi dump yard and has more potential in waste to energy conversion mechanisms than compare to Perungudi dump yard.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.343-346
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• 2002

Toward more accurate determination of the water cycle in association with climate variability and change as well as baseline data on the impacts of this variability on water resources, the Coordinated Enhanced Observing Period (CEOP) was launched on July 1,2001. The preliminary data period, EOP-1, was implemented from July to September in 2001. The first annual enhanced observing period, EOP-3, is going to start on October 1,2002. CEOP is seeking to achieve a database of common measurements from both in situ and satellite remote sensing, model output, and four-dimensional data analyses (4DDA; including global and regional reanalyses) for a specified period. In this context a number of carefully selected reference stations are linked closely with the existing network of observing sites involved in the GEWEX Continental Scale Experiments, which are distributed across the world. The initial step of CEOP is to develop a pilot global hydro-climatological dataset with global consistency under the climate variability that can be used to help validate satellite hydrology products and evaluate, develop and eventually predict water and energy cycle processes in global and regional models. Based on the dataset, we will address the studies on the inter-comparison and inter-connectivity of the monsoon systems and regional water and energy budget, and a path to down-scaling from the global climate to local water resources, as the second step.

• Atmosphere
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• v.23 no.2
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• pp.131-141
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• 2013

Many studies have related the recent variations of wildfire regime such as the increasing number of occurrances, their patterns and timing changes, and the severity of their extreme cases with global warming. However, there are only a few numbers of wildfire studies to assess how the future wildfire regime will change in the interactions between land and atmosphere with climate change especially over East Asia. This study was performed to estimate the future changing aspect of wildfire danger with global warming, using Haines Index (HI). Calculated from atmospheric instability and dryness, HI is the potential of an existing fire to become a dangerous wildfire. Using the Weather Research and Forecasting (WRF) model, two separated 5-year simulations of current (1995~1999) and far future (2095~2099) were performed and analyzed. Community Climate System Model 3 (CCSM3) model outputs were utilized for the model inputs for the past and future over East Asia; future prediction was driven under the IPCC A1B scenario. The results indicate changes of the wildfire danger regime, showing overall decreasing the wildfire danger in the future but intensified regional deviations between north and south. The overall changes of the wildfire regime seems to stem from atmospheric dryness which is sensitive to soil moisture variation. In some locations, the future wildfire danger overall decreases in summer but increases in winter or fall when the actual fire occurrence are generally peaked especially in South China.

• Journal of Environmental Science International
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• v.12 no.5
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• pp.529-539
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• 2003

We developed a numerical model that considered the influences on the thermal environment of vegetation, water surfaces and buildings to predict micro climatic changes in a few $\textrm{km}^2$ scales; and applied this model to the Mino residential development region in Osaka Prefecture by using a nested technique. The calculated temperatures and winds in the residential development region reasonably agreed with the observed ones. We then investigated the influences on the thermal environment of the construction of a dam, the change of the green coverage rate. The results obtained from the numerical simulations were qualitatively reasonable.

• The Korean Journal of Quaternary Research
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• v.23 no.1
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• pp.42-53
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• 2009

In response to the abrupt climate change in recent years, atmosphere, ocean and cryosphere are reported to be altered. In addition to these changes, the land surface is also gradually changing and its impact on the global climate may not be negligible. The land surface change impacts the global climate via two ways, the biogeochemical and biophysical feedbacks. The biogeochemcial change in the land surface modifies the atmospheric trace-gas concentrations through a change in photo synthesis, while biophycal changes of the land surface alters the surface albedo, which influences the amount of the short wave radiative heat fluxes. There are many examples in the past that the change in land surface greatly influences the global climate change. The recent IPCC report has suggested that the climate change will occur rather abrubtly in the near future. In order to predict the future climate accurately, the impact of the land surface change is fully considered.