• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.3B
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• pp.285-293
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• 2010

Soil moisture is a key factor to control the exchange of water and energy between the surface and the atmosphere. In recent, many researches for spatial and temporal variability analyses of soil moisture have been conducted. In this study, we analyzed the spatio-temporal variability of soil moisture in Walnut Gulch Experimental Watershed, Arizona, U.S. during the Soil Moisture Experiment 2004 (SMEX04). The spatio-temporal variability analyses were performed to understand sensitivity of five observation sites with precipitation and relationship between mean soil moisture, and its standard deviation and coefficient of variation at the sites, respectively. It was identified that log-normal distribution was superior to replicate soil moisture spatial patterns. In addition, precipitation was identified as a key physical factor to understand spatio-temporal variability of soil moisure based on the temporal stability analysis. Based on current results, higher spatial variability was also observed which was agreed with the results of previous studies. The results from this study should be essential for improvement of the remotely sensed soil moisture retrieval algorithm.

• Journal of the Economic Geographical Society of Korea
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• v.20 no.2
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• pp.158-172
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• 2017

This study analyzes the time-space variability for the weekly passenger flow of the Seoul Subway system based on the dynamic visualization methods. For the purpose, we utilize one-week T-card transaction databases. By applying data mining algorithms, we extract passenger data for edge flows, on/off passengers at each subway station per minute interval time. It is practically intractable to analyze such spatio-temporal passenger flows by general statistical techniques. We employ dynamic visualization methods to analyze intuitively and to grasp effectively characteristics of the diurnal passenger flows on the Seoul Metropolitan Subway system during one week. As the result, we found that substantial differences exist on the spatio-temporal distribution patterns among days as well as between weekdays and weekend. We also investigates the time-space variability among eight major centers, and we found wide differences in their spatio-temporal distribution patterns.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.26 no.2
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• pp.72-80
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• 2014

The approximately highest high water(AHHW), which has been used frequently as a basis of the design sea level, has not only ambiguous return period but also spatio-temporal problems induced by sea level rise and the spatial variability of tidal characteristics. The ratios of 4 major constituents with other constituents were investigated. In addition, tidal data were analyzed by probability density function. The temporal variability may be cured by using the latest tidal data. And the AHHW at summer was examined to lessen the spatial variability. The results show that the design sea levels need to increase by 10 cm or more at the Southern Coast and by 15~25 cm at the East Coast.

• Korean Journal of Remote Sensing
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• v.22 no.5
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• pp.313-323
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• 2006

Forest Canopy Density is a dynamic process mediated by various natural and anthropogenic factors. It can be changed over time and locations in the same forest type and landscape. However, human dimensions are considered as the primary force of landscape change and subsequent forest canopy loss in tropical regions of the world. Many studies have been indicated that roads have a far greater impact on forests than simply allowing access for human use. Similarly, rivers have been used as means of transportation, hence illegal logging and felling further deplete forest canopy density. The main objective of this study was to investigate the spatio-temporal dynamic alterations of Forest Canopy Density (FCD) across with site associated factors such as biophysical, physical and human interferences in tropical region of Nepal from 1988 to 2001. Landsat TM and ETM+ of 1988 and 2001 were used to assess the spatial and temporal dynamic alterations of FCD. This analysis revealed that distance to human settlements at P=<0.01, rivers, human interferences (path and fire) and species composition had a statistically significance at P=<0.05 level. However, other factors did not show any significant relation. So, we concluded that understanding of dynamic alterations of FCD with respect to factors was quite complex phenomena. Other surrounding environment could also playa significant role. A comprehensive analysis could be required to understand such complexities. Therefore, additional factors such as climatic, biophysical, social, and institutional with respect to spatio-temporal variability should be considered for the better understanding of canopy dynamic.

• Ocean and Polar Research
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• v.30 no.3
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• pp.313-324
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• 2008

In order to understand the variation of ENSO-related oceanic environments in the tropical and North Pacific Ocean, spatio-temporal variations of sea surface temperature anomaly (SSTA) and sea surface height anomaly (SSHA) are analyzed from distributions of complex empirical orthogonal functions (CEOF). Correlations among warm pool variation, southern oscillation index, and ocean surface currents were also examined with respect to interannual variability of the warm pool in western tropical Pacific. Spatio-temporal distributions of the first CEOF modes for SSTA and SSHA indicate that their variabilities are associated with ENSO events, which have a variance over 30% in the North Pacific. The primary reasons for their variabilities are different; SST is predominantly influenced by the change of barrier layer thickness, while SSH fluctuates with the same phase as propagation of an ENSO episode in the zonal direction. Horizontal boundary of warm pool area, which normally centered around $149^{\circ}E$ in the tropics, seemed to be expanded to the middle and eastern tropical regions by strong zonal currents through the mature phase of an ENSO episode.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.134-134
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• 2021

Precipitation is a crucial component of water cycle and play a key role in hydrological processes. Traditionally, gauge-based precipitation is the main method to achieve high accuracy of rainfall estimation, but its distribution is sparsely in mountainous areas. Recently, satellite-based precipitation products (SPPs) provide grid-based precipitation with spatio-temporal variability, but SPPs contain a lot of uncertainty in estimated precipitation, and the spatial resolution quite coarse. To overcome these limitations, this study aims to generate new grid-based daily precipitation using Automatic weather system (AWS) in Korea and multiple SPPs(i.e. CHIRPSv2, CMORPH, GSMaP, TRMMv7) during the period of 2003-2017. And this study used a machine learning based Random Forest (RF) model for generating new merging precipitation. In addition, several statistical linear merging methods are used to compare with the results of the RF model. In order to investigate the efficiency of RF, observed data from 64 observed Automated Synoptic Observation System (ASOS) were collected to evaluate the accuracy of the products through Kling-Gupta efficiency (KGE), probability of detection (POD), false alarm rate (FAR), and critical success index (CSI). As a result, the new precipitation generated through the random forest model showed higher accuracy than each satellite rainfall product and spatio-temporal variability was better reflected than other statistical merging methods. Therefore, a random forest-based ensemble satellite precipitation product can be efficiently used for hydrological simulations in ungauged basins such as the Mekong River.

• Atmosphere
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• v.16 no.2
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• pp.85-96
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• 2006

The six-year (2000~2005) record of aerosol optical thickness (AOT or $\tau$) data from the Moderate Resolution Imaging Spectroradiometer (MODIS) was analyzed over the Northeast Asia. The MODIS AOT standard products (MOD04_L2) over both ocean and land were collected to evaluate the spatial and temporal variability of the atmospheric aerosols over the study region ($32^{\circ}N{\sim}42^{\circ}N$ and $115^{\circ}E{\sim}133^{\circ}E$). The monthly averaged AOT result revealed slight changes(${\pm}0.002{\tau}/month$), which was almost unchangeable, over Korea. In contrast, the large AOT values (> 0.6) and a significant AOT increase (> 0.004 ${\tau}/month$) over East China were observed. For the analysis of spatio-temporal variability of AOT values, study area was divided by six sectors (I: North-East China, II: East China, III: Yellow Sea, IV: Korea Peninsular, V: East Sea, and VI: South Sea and Western part of Japan). The considerable result showed that particularly high AOT contribution was observed over sector I (32.5%) and II (25.5%) where some major urban and industrialized areas and agricultural fields are located and other cases were observed 13.2%, 14.6%, 7.1%, 7.0% over sector III, IV, V, and VI, respectively. In addition, yearly AOT changes based on seasons are observed differently at each sector but increasing trends reveal in summer and fall over all sectors.

• Korean Journal of Environment and Ecology
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• v.28 no.1
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• pp.24-32
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• 2014

Our study is purposed to understand effect on spatio-temporal variability of macroinvertebrate community 11 sampling times at 4 sites between two streams (Shinchon stream and Gongji stream in Chuncheun City) from May 2011 to October 2013. In this study, the possible physical factors on spatio-temporal variability of macroinvertebrate community were discussed. After stream improvement project, the effects of anthropogenic disturbance in study sites appeared as increased water temperature more than $30^{\circ}C$ and the difference of water temperature between Shinchon stream and Gongji stream was by maximum $9^{\circ}C$ on 2012. The monsoon rainfall decreased number of species, individuals and biodiversity index of macroinvertebrate community, particularly, in Shincheon stream compare to Gongji stream. Dominant species of macroinvertebrate taxa was caddisfly in Shincheon stream and Diptera in Gongji stream but on August 2013, it was dominated by Diptera, Chironomidae spp. in all study sites. The spatio-temporal variability of macroinvertebrate community in the streams may be useful as bio-indicator influencing anthropogenic factors such as soil erosion (landslide or cultivation) or monsoon rainfall.

• Journal of the Korean earth science society
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• v.44 no.1
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• pp.1-12
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• 2023

Oceanic wind waves have been recognized as one of the important indicators of global warming and climate change. It is necessary to study the spatial and temporal variability of significant wave height (SWH) and wave direction in the Yellow Sea and a part of the East China Sea, which is directly affected by the East Asian monsoon and climate change. In this study, the spatial and temporal variability including seasonal and interannual variability of SWH and wave direction in the Yellow Sea and East China Sea were analyzed using European Center for Medium-Range Weather Forecasts (ECMWF) Reanalysis 5 (ERA5) data. Prior to analyzing the variability of SWH and wave direction using the model reanalysis, the accuracy was verified through comparison with SWH and wave direction measurements from Ieodo Ocean Science Station (I-ORS). The mean SWH ranged from 0.3 to 1.6 m, and was higher in the south than in the north and higher in the center of the Yellow Sea than in the coast. The standard deviation of the SWH also showed a pattern similar to the mean. In the Yellow Sea, SWH and wave direction showed clear seasonal variability. SWH was generally highest in winter and lowest in late spring or early summer. Due to the influence of the monsoon, the wave direction propagated mainly to the south in winter and to the north in summer. The seasonal variability of SWH showed predominant interannual variability with strong variability of annual amplitudes due to the influence of typhoons in summer.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.299-303
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• 2008

In this study, an uncertainty assessment for surface air temperature(T2m) and precipitation(PCP) over East Asia is carried out. The data simulated by the intergovermental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) Atmosphere-Ocean coupled general circulation Model (AOGCM) are used to assess the uncertainty. Examination of the seasonal uncertainty of T2m and PCP variabilities shows that spring-summer cold bias and fall warm bias of T2m are found over both East Asia and the Korea peninsula. In contrast, distinctly summer dry bias and winter-spring wet bias of PCP over the Korea peninsula is found. To investigate the PCP seasonal variability over East Asia, the cyclostationary empirical orthogonal function(CSEOF) analysis is employed. The CSEOF analysis can extract physical modes (spatio-temporal patterns) and their undulation (PC time series) of PCP, showing the evolution of PCP. A comparison between spatio-temporal patterns of observed and modeled PCP anomalies shows that positive PCP anomalies located in northeastern China (north of Korea) of the multi-model ensemble(MME) cannot explain properly the contribution to summer monsoon rainfalls across Korea and Japan. The uncertainty of modeled PCP indicates that there is disagreement between observed and MME anomalies. The spatio-temporal deviation of the PCP is significantly associated with lower- and upper-level circulations. In particular, lower-level moisture transports from the warm pool of the western Pacific and corresponding moisture convergence significantly contribute to summer rainfalls. These lower- and upper-level circulations physically consistent with PCP give a insight of the reason why differences between modeled and observed PCP occur.