• Atmosphere
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• v.27 no.2
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• pp.163-175
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• 2017

The global terrestrial ecosystems have shown a large spatial variability in recent decades and represented a carbon sink pattern at mid-to-high latitude in Northern Hemisphere. However, there are many uncertainties in magnitude and spatial distribution of terrestrial carbon fluxes due to the effect of climate factors. So, it needs to accurately understand the spatio-temporal variations on carbon exchange flux with climate. This study focused on the effects of climate factors, .i.e. temperature, precipitation, and solar radiation, to terrestrial biosphere carbon flux. We used the terrestrial carbon flux that is simulated by a CarbonTracker, which performs data assimilation of global atmospheric $CO_2$ mole fraction measurements. We demonstrated significant interactions between Net Ecosystem Production (NEP) and climate factors by using the partial correlation analysis. NEP showed positive correlation with temperature at mid-to-high latitude in Northern Hemisphere but showed negative correlation pattern at $0-30^{\circ}N$. Also, NEP represented mostly negative correlation with precipitation at $60^{\circ}S-30^{\circ}N$. Solar radiation affected NEP positively at all latitudes and percentage of positive correlation at tropical regions was relatively lower than other latitudes. Spring and summer warming had potentially positive effect on NEP in Northern Hemisphere. On the other hand as increasing the temperature in autumn, NEP was largely reduced in most northern terrestrial ecosystems. The NEP variability that depends on climate factors also differently represented with the type of vegetation. Especially in crop regions, land carbon sinks had positive correlation with temperature but showed negative correlation with precipitation.

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• v.1 no.1
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• pp.58-67
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• 2020

Terrestrial ecosystems influence climate change via their climate regulation function, which is manifested within the carbon, water, and energy circulation between the atmosphere and surface. However, it has been challenging to quantify the climate regulation of terrestrial ecosystems and identify its regional distribution, which provides useful information for establishing regional climate-mitigation plans as well as facilitates better understanding of the interactions between the climate and land processes. In this study, a land surface model (LSM) that represents the land-atmosphere interactions and plant phenological variations was introduced to assess the contributions of terrestrial ecosystems to atmospheric warming or cooling effects over East Asia over the last half century. Three main climate-regulating components were simulated: net radiation flux, carbon exchange, and moisture flux at the surface. Then, the contribution of each component to the atmospheric warming or cooling (negative or positive feedback to the atmosphere, respectively) was investigated. The results showed that the terrestrial ecosystem over the Siberian region has shown a relatively large increase in positive feedback due to the enhancement of biogeochemical processes, indicating an offset effect to delay global warming. Meanwhile, the Gobi Desert shows different regional variations: increase in positive feedback in its southern part but increase in negative one in its eastern part, which implies the eastward movements of desert areas. As such, even though the LSM has limitations, this model approach to quantify the climate regulation is useful to extract the relevant characteristics in its spatio-temporal variations.

• Atmosphere
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• v.26 no.4
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• pp.553-563
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• 2016

Land evaporation contribution to precipitation over East Asia is studied to understand terrestrial moisture source of continental precipitation. Moisture recycling of precipitation relying on terrestrial evaporation is estimated based on the analysis method of Van der Ent et al. (2010). We utilize HadGEM2-AO simulations for the period of 1970~1999 and 2070~2099 from RCP8.5. Globally, 46% of terrestrial precipitation is depending from continental evaporation. 58% of terrestrial evaporation returns as continental precipitation. Over East Asia, precipitation has been affected by local evaporation and transported moisture. The advection of upwind continental evaporation results from the prevailing westerlies from the midwestern of Eurasian continent. For the present-day period, about 66% of the precipitation over the land of East Asia originates from land evaporation. Regionally, the ratios change and the ratios of precipitation terrestrial origin over the Northern inland and Southern coast of East Asia are 82% and 48%, respectively. Seasonally, the continental moisture recycling ratio is larger during summer (JJA) than winter (DJF). According to RCP8.5, moisture recycling ratio is expected to change. At the end of the 21st century, the impact of continental moisture sources for precipitation over East Asia is projected to be reduced by about 5% compared to at the end of 20th century. To understand the future changes, moisture residence time change is investigated using depletion and replenishment time.

• Ocean and Polar Research
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• v.32 no.1
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• pp.73-84
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• 2010

A terrestrial LiDAR was used to acquire precise and high-resolution topographical information of Malipo beach, Korea. Terrestrial LiDAR and RTK-DGPS (VRS) were mounted on top of a survey vehicle and used to scan 20 times stop-and-go method with 250 m spacing intervals at ebb tides. In total, 7 measurements were made periodically from 2008 to 2009 and after each beach replenishment event. We carried out GIS-based 3D spatial analysis such as slope and volume calculations in order to assess topographical changes over time. In relation to beach replenishment, comparative analysis of each volume change revealed them to be similar. This result indicates that the terrestrial LiDAR measurements are accurate and can be used to analyze temporal topographical changes. In conclusion, the methodology employed in this study can be used efficiently to exercise coastal management through monitoring and analyzing beach process such as erosion and deposition.

• Atmosphere
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• v.27 no.3
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• pp.301-316
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• 2017

This study analyzes the spatio-temporal variability of terrestrial carbon flux and the response of land carbon sink with climate factors to improve of understanding of the variability of land-atmosphere carbon exchanges accurately. The coupled carbon-climate models of CMIP5 (the fifth phase of the Coupled Model Intercomparison Project) and CT (CarbonTracker) are used. The CMIP5 multi-model ensemble mean overestimated the NEP (Net Ecosystem Production) compares to CT and GCP (Global Carbon Project) estimates over the period 2001~2012. Variation of NEP in the CMIP5 ensemble mean is similar to CT, but a couple of models which have fire module without nitrogen cycle module strongly simulate carbon sink in the Africa, Southeast Asia, South America, and some areas of the United States. Result in comparison with climate factor, the NEP is highly affected by temperature and solar radiation in both of CT and CMIP5. Partial correlation between temperature and NEP indicates that the temperature is affecting NEP positively at higher than mid-latitudes in the Northern Hemisphere, but opposite correlation represents at other latitudes in CT and most CMIP5 models. The CMIP5 models except for few models show positive correlation with precipitation at $30^{\circ}N{\sim}90^{\circ}N$, but higher percentage of negative correlation represented at $60^{\circ}S{\sim}30^{\circ}N$ compare to CT. For each season, the correlation between temperature (solar radiation) and NEP in the CMIP5 ensemble mean is similar to that of CT, but overestimated.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.529-534
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• 2009

Climate models, both global and regional, have increased in sophistication and are being run at increasingly higher resolutions. The Land Surface Models (LSMs) coupled to these climate models have evolved from simple bucket models to sophisticated Soil-Vegetation-Atmosphere Transfer (SVAT) schemes needed to support complex linkages and processes. However, some underpinnings of terrestrial hydrologic parameterizations so crucial in the predictions of surface water and energy fluxes cause model errors that often manifest as non-linear drifts in the dynamic response of land surface processes. This requires the improved parameterizations of key processes for the terrestrial hydrologic scheme to improve the model predictability in surface water and energy fluxes. The Common Land Model (CLM), one of state-of-the-art LSMs, is the land component of the Community Climate System Model (CCSM). However, CLM also has energy and water biases resulting from deficiencies in some parameterizations related to hydrological processes. This research presents the implementation of a selected set of parameterizations and their effects on the runoff prediction. The modifications consist of new parameterizations for soil hydraulic conductivity, water table depth, frozen soil, soil water availability, and topographically controlled baseflow. The results from a set of offline simulations are compared with observed data to assess the performance of the new model. It is expected that the advanced terrestrial hydrologic scheme coupled to the current CLM can improve model predictability for better prediction of runoff that has a large impact on the surface water and energy balance crucial to climate variability and change studies.

• Journal of Species Research
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• v.12 no.1
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• pp.109-113
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• 2023

To build a distribution model for Haemadipsa rjukjuana, we collected current occurrences of the species on Heuksando with adjacent islands. Based on current locations and 19 climate variables with DEM (digital elevation model), we built the MaxEnt (maximum entropy) species distribution model for H. rjukjuana in the islands. Then, we applied the MaxEnt model to the mainland of Korea with the current climate condition and topology. In addition to the current distribution scenario, we predicted the future distribution scenarios in Korea by Coupled Model Intercomparison Project Phase 6 (CMIP6) global climate models. Shared Socioeconomic Pathway (SSP) 585 of two CMIP6 models(GISS-E2-1 and INM-CM4-8) from 2040 to 2100 were used for the future projection.

• Ocean and Polar Research
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• v.41 no.3
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• pp.159-168
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• 2019

Understanding the interaction between climate and the water cycle is critical especially in a drought sensitive region such as California. This study explored hydrologic changes in central and southern California in relation to the glacial-interglacial climate cycles over the last 30 thousand years. To do this, we reconstructed paleovegetation using plant wax carbon isotopic compositions (${\delta}^{13}C$) preserved in marine sediment cores retrieved from the central California continental shelf (ODP Site 1018) and Santa Barbara Basin (ODP Site 893A). The results were then compared to the existing sea surface temperature (SST) and pollen records from the same cores to understand terrestrial hydrology in relation to oceanographic processes. The Last Glacial was generally dry both in central and southern California, indicated by grassland expansion, confirming the previously suggested notion that the westerly storm track that supplies the majority of the precipitation in California may not have moved southward during the glacial period. Southern California was drier than central California during the Last Glacial Maximum (LGM). This drying trend may have been associated with the weakening of the California Current and northerly winds leading to the early increase in SST in southern California and decline in both offshore and coastal upwelling. The climate was wetter during the Holocene in both regions compared to the glacial period and forest coverage increased accordingly. We attribute this wetter condition to the precipitation contribution increase from the tropics. Overall, we found a clear synchronicity between the terrestrial and marine environment which showed that the terrestrial vegetation composition in California is greatly affected by not only the global climate states but also regional oceanographic and atmospheric conditions that regulate the timing and amount of precipitation over California.

• Journal of the Korean earth science society
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• v.42 no.4
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• pp.445-458
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• 2021

Gravity Recovery and Climate Experiment (GRACE) gravimeter satellites observed the Earth gravity field with unprecedented accuracy since 2002. After the termination of GRACE mission, GRACE Follow-on (GFO) satellites successively observe global gravity field, but there is missing period between GRACE and GFO about one year. Many previous studies estimated terrestrial water storage (TWS) changes using hydrological models, vertical displacements from global navigation satellite system observations, altimetry, and satellite laser ranging for a continuity of GRACE and GFO data. Recently, in order to predict TWS changes, various machine learning methods are developed such as artificial neural network and multi-linear regression. Previous studies used hydrological and climate data simultaneously as input data of the learning process. Further, they excluded linear trends in input data and GRACE/GFO data because the trend components obtained from GRACE/GFO data were assumed to be the same for other periods. However, hydrological models include high uncertainties, and observational period of GRACE/GFO is not long enough to estimate reliable TWS trends. In this study, we used convolutional neural networks (CNN) method incorporating only climate data set (temperature, evaporation, and precipitation) to predict TWS variations in the missing period of GRACE/GFO. We also make CNN model learn the linear trend of GRACE/GFO data. In most river basins considered in this study, our CNN model successfully predicts seasonal and long-term variations of TWS change.

• Journal of Astronomy and Space Sciences
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• v.36 no.3
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• pp.149-157
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• 2019

In this study, we investigate the associations between the solar variability and teleconnection indices, which influence atmospheric circulation and subsequently, the spatial distribution of the global pressure system. A study of the link between the Sun and a large-scale mode of climate variability, which may indirectly affect the Earth's climate and weather, is crucial because the feedbacks of solar variability to an autogenic or internal process should be considered with due care. We have calculated the normalized cross-correlations of the total sunspot area, the total sunspot number, and the solar North-South asymmetry with teleconnection indices. We have found that the Southern Oscillation Index (SOI) index is anti-correlated with both solar activity and the solar North-South asymmetry, with a ~3-year lag. This finding not only agrees with the fact that El $Ni{\tilde{n}}o$ episodes are likely to occur around the solar maximum, but also explains why tropical cyclones occurring in the solar maximum periods and in El $Ni{\tilde{n}}o$ periods appear similar. Conversely, other teleconnection indices, such as the Arctic Oscillation (AO) index, the Antarctic Oscillation (AAO) index, and the Pacific-North American (PNA) index, are weakly or only slightly correlated with solar activity, which emphasizes that response of terrestrial climate and weather to solar variability are local in space. It is also found that correlations between teleconnection indices and solar activity are as good as correlations resulting from the teleconnection indices themselves.