• East Asian Economic Review
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• v.27 no.4
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• pp.273-301
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• 2023

This study investigates the impacts of long-term climate variability on household consumption in Indonesia, a country highly vulnerable to climate change. The analysis combines household survey data from nearly 5,998 families with satellite-derived weather data from NASA POWER spanning 30 years. We use the long-term variability in temperature and precipitation as a proxy for climate change. This study examines the impact of climate change which proceeds over the long term, unlike previous studies concerning one-off or short-term climate events. In addition, using satellite data enhances the accuracy of households' exposure to climate variability. The analysis finds that households in a village with higher temperature and precipitation variability significantly consume less food. This implies that households more exposed to climate change are at higher risk of malnutrition in developing countries. This study has a limitation that it cannot rule out the potential endogeneity of choosing a climate-vulnerable residential location due to economic poorness.

• Journal of Korea Water Resources Association
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• v.57 no.4
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• pp.237-248
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• 2024

Watershed runoff that is an important component of the hydrological processes has been significantly altered by climate variability and human activities in many watersheds around the world. It is important to investigate the impacts of climate variability and human activities on watershed runoff change for water resource management. In this study, using watershed runoff data for 109 middle-sized watersheds in Korea, the impacts of climate variability and human activities on watershed runoff change were quantitatively evaluated. Using the Pittitt test, the analysis period was divided into two sub-periods, and the impacts of climate variability and human activities on the watershed runoff change were quantified using the Budyko hypothesis-based climate elasticity method. The overall results indicated that the relative contribution of climate variability and human activities to the watershed runoff change varied by middle-sized watersheds, and the dominant factors on the watershed runoff change were identified for each watershed among climate variability and human activities. The results of this study enable us to predict the watershed runoff change considering climate variability and watershed development plans, which provides useful information for establishing a water resource management plan to reduce the risk of hydrological disasters such as drought or flood.

• Ocean Systems Engineering
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• v.7 no.4
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• pp.319-328
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• 2017

Higher prediction efficacy is a very challenging task in any field of engineering. Due to global warming, there is a considerable increase in the global sea level. Through this work, an attempt has been made to find the sea level variability due to climate change impact at Haldia Port, India. Different statistical downscaling techniques are available and through this paper authors are intending to compare and illustrate the performances of three regression models. The models: Wavelet Neural Network (WNN), Minimax Probability Machine Regression (MPMR), Feed-Forward Neural Network (FFNN) are used for projecting the sea level variability due to climate change at Haldia Port, India. Model performance indices like PI, RMSE, NSE, MAPE, RSR etc were evaluated to get a clear picture on the model accuracy. All the indices are pointing towards the outperformance of WNN in projecting the sea level variability. The findings suggest a strong recommendation for ensembled models especially wavelet decomposed neural network to improve projecting efficiency in any time series modeling.

• Journal of Industrial Technology
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• v.35
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• pp.23-30
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• 2015

In recent, the various methods to predict the hydrological impacts due to climate change have been developed and applied. Especially, the variability of the meteorological factors such as rainfall, temperature, and evaporation can impact on the ecosystem in a basin. The variability caused by climate change on the meteorological factors can be divided by a gradual and abrupt change. Therefore, in this study, the gradual change is detected by simple linear regression and Mann-Kendall trend test. Also, the abrupt change is detected by Bayesian change point analysis. Finally, the result using these methods can identify the meteorological threats in the Cheongmicheon basin.

• Proceedings of the Korean Society of Crop Science Conference
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• 2000.11a
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• pp.12-27
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• 2000

During the recent decades, he problem of climate variability and change has been in the forefront of scientific problems. The objective of this study was to assess the impact of climate variability on crop growth and yield. The growth duration was the main impact of climate variability on crop yield. Phyllochronterval was shortened in the global worming situations. A simple model to describe developmental traits was provided from heading data of directly seeded rice cultivars and temperature data. Daily mean development rate could be explained by the average temperature during the growth stage. Simple regression equation between daily mean development rate(x) and the average temperature(y) during the growth period as y = ax + b. It can be simply modified as x = 1/a $\ast$ (y-b). The parameters of the model could depict the thermo sensitivity of the cultivars. On the base of this model, the three doubled CO2 GCM scenarios were assessed. The average of these would suggest a decline in rice production of about 11% if we maintained the current cultivars. Future cultivar's developmental traits could be suggested by the two model parameters.

• Journal of Climate Change Research
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• v.9 no.2
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• pp.171-179
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• 2018

The causal relationship between El Nino-Southern Oscillation (ENSO) and winter climate variability in Korea is tested by analyzing Korea Meteorological Administration Automatic Synoptic Observing System datasets for the past 59 years. Consistent with previous studies, positive phase of ENSO (El Nino) tends to cause warmer temperature and heavier precipitation in Korea in early winter with three-week lead time. This causality is quantified by performing Granger causality test. It turns out that ENSO explains an additional 9.25% of the variance of early-winter temperature anomalies in Korea, beyond that already provided by temperature itself. Likewise, 22.18% additional information is gained to explain early-winter precipitation variance by considering ENSO. This result, which differs from simple lead-lag correlation analysis, suggests that ENSO needs to be considered in predicting early-winter surface climate variability in Korea.

• Journal of Climate Change Research
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• v.34 no.16
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• pp.6841-6853
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• 2021

The leading modes of the North Pacific jet (NPJ) variability include intensity changes and meridional shifts in jet position on low-frequency time scales. These leading modes of NPJ variability are closely associated with weather and climate conditions spanning from Asia to the United States. In this study, we investigated changes in the NPJ's role as a conduit for U.S. surface air temperature (SAT) anomalies during the boreal winter across the late 1990s. We found that the leading mode of NPJ variability changed from the NPJ intensity changes to meridional shifts in NPJ position across the late 1990s. It leads to the change in the role of the NPJ as a conduit for U.S. SAT anomalies. Before the late 1990s, the variability of NPJ intensity significantly impacted western U.S. SAT anomalies related to the anomalous surface cyclonic circulation over the North Pacific. After the late 1990s, however, the variability of the NPJ's meridional shift significantly influenced the eastern U.S. SAT anomalies in association with the anomalous surface cyclonic circulation over the northern North Pacific. Further analysis and model experiments revealed that the western to central North Pacific Ocean has been warming since the late 1990s and modulates atmospheric baroclinicity. This phenomenon mainly leads to a northward NPJ shift and implies that the eddy-driven mechanism on the NPJ's formation, which acts to enhance the meridional variability of NPJ position, becomes dominant. We conclude that this northward shift of NPJ could have contributed to enhancing the NPJ's meridional shift variability, significantly influencing the eastern U.S. SAT anomalies since the late 1990s.

• Ocean and Polar Research
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• v.34 no.1
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• pp.29-35
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• 2012

We investigated the interannual relationship between chlorophyll concentrations in the western North Pacific and tropical cyclones (TCs) in the western North Pacific by analyzing data collected for >12 years. Despite the short-term scale (2~3 weeks) in the contribution of tropical cyclones to phytoplankton, the current study revealed that the long-term chlorophyll variability in the western North Pacific is profoundly related to long-term variability in the frequency of TCs. It was also found that the Pacific decadal oscillation (PDO) tends to control such relationships between the 2 bio-physical systems. This result suggests a significant climatic relationship between TC activity and marine phytoplankton, and also suggests the possibility of more accurate estimations of primary production in the western North Pacific.

• Journal of Integrative Natural Science
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• v.13 no.1
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• pp.27-33
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• 2020

The unsustainable human activities like increased use of automobiles, heavy industrialization and the use of large volumes of fertilizers, chemicals and pesticides in the agricultural land cause climate change problems in one way or another. Under normal circumstances, the heat radiations from the sun will be reflected back. An excessive volume of GHGs in the atmosphere would prevent these radiations from reflecting back. East Asia is facing severe climate change issues in recent times. A lot of climate change problems such as hurricanes and floods have been reported from this region in the last couple of decades. The study aimed at investigating the climate change in East Asia with changing Sea Surface Temperature (SST). The study adopted a quantitative research method with a case study research design where a deliberate focus was made on the East Asia Region. Secondary data was gathered and analyzed to yield both descriptive and inferential statistics. The study concluded that the impact of East Asia Climate variability was significant mainly for some extreme events. Also, the study concluded that there was a significant link between the change of the East Asia climate variability and that of the sea surface temperature. Further, the study concluded that a linear relationship existed between the sea surface temperature and the climate of East Asia. Hence, a linear regression was a significant predictor of the East Asia Climate (EAC) based on changing sea surface temperature. The model revealed that 37.4% of the variations in the climate change index were explained by the changes in the sea surface temperature. The climate was expected to change with a value of 49.48 for a unit change in the sea surface temperature.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.154-154
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• 2022

The frequency of natural disasters, including floods and drought events, driven by climate change has increased in recent times. Investigating the climate regimes and the roles of climate variables are indispensable to forestall future climate change-related disasters. This study compares the variability of two popular and widely used climate indices i.e., the United Nations Environment Programme (UNEP) aridity index and the Modified De-Martonne (MDM) index to assess the trend of climate change in the Chungcheong provinces of South Korea. The trend of annual and monthly climate indices was conducted using a non-parametric Mann-Kendall test and Kolmogorov-Smirnov normality test with daily climate data of 48 years (1978-2020) from 10 synoptic stations. The findings indicate that UNEP and MDM indices had a wet climate regime for the annual trend, with the UNEP index indicating a relatively humid trend of 60% humid, 20% semi-arid, and 10% sub-humid for the 48-years study period. However, the MDM index showed a high frequency of a severe wet climatic condition followed by the semi-arid condition. The months of July and August had the highest occurring frequency of the wet climatic condition (90%) for both UNEP and MDM indices. Comparing the two provinces, Chungnam showed a relatively wetter climatic condition using the UNEP index, while the MDM index indicated no significant regional difference in climate regime between the two provinces. The Kolmogorov-Smirnov normality test showed that all the 10 stations are normally distributed for monthly climate conditions at a 5% significant level in the two provinces except five stations for UNEP index and four stations for MDM index in the month of January.