• Journal of the Korean earth science society
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• v.29 no.3
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• pp.280-289
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• 2008

An extensive set of both in-situ and satellite data regarding oceanic sea surface temperatures in Northeast Asian seas, collected over a 10-year period, was collocated and surveyed to assess the accuracy of satellite-observed sea surface temperatures (SST) and investigate the characteristics of satellite measured SST errors. This was done by subtracting insitu SST measurements from multi-channel SST (MCSST) measurements. 845 pieces of collocated data revealed that MCSST measurements had a root-mean-square error of about 0.89$^{\circ}C$ and a bias error of about 0.18$^{\circ}C$. The SST errors revealed a large latitudinal dependency with a range of $\pm3^{\circ}C$ around 40$^{\circ}N$, which was related to high spatial and temporal variability from smaller eddies, oceanic currents, and thermal fronts at higher latitudes. The MCSST measurements tended to be underestimated in winter and overestimated in summer when compared to in-situ measurements. This seasonal dependency was discovered from shipboard and moored buoy measurements, not satellite-tracked surface drifters, and revealed the existence of a strong vertical temperature gradient within a few meters of the upper ocean. This study emphasizes the need for an effort to consider and correct the significant skin-bulk SST difference which arises when calculating SST from satellite data.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.10
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• pp.1422-1432
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• 1993

Nonlinear mapping function of the HCNN( Hidden Control Neural Network ) can change over time to model the temporal variability of a speech signal by combining the nonlinear prediction of conventional neural networks with the segmentation capability of HMM. We have two things in this paper. first, we showed that the performance of the HCNN is better than that of HMM. Second, the HCNN with its prediction error measure given by weighted distance is proposed to use suitable distance measure for the HCNN, and then we showed that the superiority of the proposed system for speaker-independent speech recognition tasks. Weighted distance considers the differences between the variances of each component of the feature vector extraced from the speech data. Speaker-independent Korean digit recognition experiment showed that the recognition rate of 95%was obtained for the HCNN with Euclidean distance. This result is 1.28% higher than HMM, and shows that the HCNN which models the dynamical system is superior to HMM which is based on the statistical restrictions. And we obtained 97.35% for the HCNN with weighted distance, which is 2.35% better than the HCNN with Euclidean distance. The reason why the HCNN with weighted distance shows better performance is as follows : it reduces the variations of the recognition error rate over different speakers by increasing the recognition rate for the speakers who have many misclassified utterances. So we can conclude that the HCNN with weighted distance is more suit-able for speaker-independent speech recognition tasks.

• Korean Journal of Remote Sensing
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• v.13 no.1
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• pp.1-12
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• 1997

The western equatorial Pacific Ocean, where sea surface temperature is the warmest on the globe, is characterized by numerous convective systems and large annual precipitation. In this region, the cloudiness data with tops higher than 8km level obtained from the GMS-IR data are used to investigate the diurnal variation of cloudiness. The amplitude and phase of diurnal and semi-diurnal cycles are mainly investigated to examine details on the temporal and spatial structure of clouds. Cloudiness variation has typical cycles and each cycle is associated with the air-sea interactive phenomena. Spectral analysis on the cloudiness time series data indicates that 30-60 day, 17-20day, 7-8 day, diurnal and semi diurnal cycle are peaked. During Northern Winter and Southern Summer, the large cloudiness exsists over New Guinea, the adjacent seas of North Australia, and the open oceanic regions east of $160^{\circ}$E. Cloudiness diurnal variability over the lands and their adjacent seas is about 2.0 times larger than that over the open sea regions. That may be due to the difference of specific heat between the land and sea. The maximum and minimum cloudiness appeared at 18:00 and 09:00 hours over the land, and at noon and 21:00 hours over the sea, respectively. The amplitude of diurnal component over the land is 4,7 times larger than that of semi-diurnal component, and 1.5 times over the sea.

• Journal of the Korean Society of Marine Environment & Safety
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• v.20 no.6
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• pp.627-639
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• 2014

In respect of the nutrients cycling in coastal environment, regeneration in bottom layer is one of major source of nutrients. We analyzed the bottom water quality at the 14 stations during 9 years from 2004 to 2012 to investigate the characteristics of nutrients at bottom layer in Jinhae Bay. Concentrations of DIN, DIP and DSi showed the large seasonal variation and were higher in summer. Especially, average concentrations of these nutrients were two times higher in hypoxic season than in normoxic season. In summer, high concentrations of DIN, DIP and DSi caused by regeneration were common feature, but spatial distribution of DSi differ from that of DIN and DIP. DIN and DIP were higher in Masan Bay, while DSi was higher in Masan Bay as well as in center of Jinhae Bay. In comparison with DIN and DIP, DSi was significantly affected by nutrients regeneration at bottom layer in whole season. According to time series analysis, DIN concentration was decreased from approximately $14{\mu}M$ to $6{\mu}M$. This result induce that Si:N ratio at bottom layer in Jinhae Bay changed from approximately 1 to 3.

• Journal of Wetlands Research
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• v.23 no.4
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• pp.296-306
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• 2021

Elasticity is a statistical technique that interprets the changing pattern of another variable according to a change in one variable as a quantitative numerical value and provides more information than correlation analysis and is widely used in climate change research. In this study the elasticity was calculated and sensitivity analysis was performed using air temperature and water quality data of the major tributaries of the Nakdong River. In addition the confidence interval for the elasticity was calculated using the T-Test and the validity of the elasticity was examined. The strength of elasticity shows high strength in the order of summer>fall>spring>winter and the direction shows regional characteristics with both negative and positive elasticity. After performing hierarchical cluster analysis on monthly observation data they were classified into 5 clusters and the characteristics of each cluster were visually analyzed using a parallel coordinate graph. The direction and intensity of the air temperature elasticity show regional characteristics due to the relatively high population density and complex influencing factors such as sewage treatment plants, small-scale livestock houses and agricultural activities. In the case of TP it shows great regional variability according to the circulation of nutrients in the ecosystem caused by algae growth and death according to temperature changes. Since the air temperature elasticity of the major tributaries of the Nakdong River is over weak and is valid at the significance level of 5%, it was analyzed that there is a change in water quality according to the air temperature change.

• Korean Journal of Remote Sensing
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• v.34 no.6_2
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• pp.1179-1192
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• 2018

In order to detect the Antarctic Polar Front (PF) among the main fronts in the Southern Ocean, this study is based on the combinations of satellite-based sea surface temperature (SST) and height (SSH) observations. For accurate PF detection, we classified the signals as front or non-front grids based on the Bayesian decision theory from daily SST and SSH datasets, and then spatio-temporal synthesis has been performed to remove primary noises and to supplement geographical connectivity of the front grids. In addition, sea ice and coastal masking were employed in order to remove the noise that still remains even after performing the processes and morphology operations. Finally, we selected only the southernmost grids, which can be considered as fronts and determined as the monthly PF by a linear smoothing spline optimization method. The mean positions of PF in this study are very similar to those of the PFs reported by the previous studies, and it is likely to be well represents PF formation along the bottom topography known as one of the major influences of the PF maintenance. The seasonal variation in the positions of PF is high in the Ross Sea sector (${\sim}180^{\circ}W$), and Australia sector ($120^{\circ}E-140^{\circ}E$), and these variations are quite similar to the previous studies. Therefore, it is expected that the detection approach for the PF position applied in this study and the final composite have a value that can be used in related research to be carried out on the long term time-scale.

• Journal of the Korean earth science society
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• v.41 no.6
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• pp.599-616
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• 2020

Sea-surface temperature (SST) is one of the most important oceanic variables for understanding air-sea interactions, heat flux variations, and oceanic circulation in the global ocean. Extremely low SSTs from 0℃ down to -2℃ should be more important than other normal temperatures because of their notable roles in inducing and regulating global climate and environmental changes. To understand the temporal and spatial variability of such extremely low SSTs in the global ocean, the long-term SST climatology was calculated using the daily SST database of satellites observed for the period from 1982 to 2018. In addition, the locations of regions with extremely low surface temperatures of less than 0℃ and monthly variations of isothermal lines of 0℃ were investigated using World Ocean Atlas (WOA) climatology based on in-situ oceanic measurements. As a result, extremely low temperatures occupied considerable areas in polar regions such as the Arctic Ocean and Antarctic Ocean, and marginal seas at high latitudes. Six earth science textbooks were analyzed to investigate how these extremely low temperatures were visualized. In most textbooks, illustrations of SSTs began not from extremely low temperatures below 0℃ but from a relatively high temperature of 0℃ or higher, which prevented students from understanding of concepts and roles of the low SSTs. As data visualization is one of the key elements of data literacy, illustrations of the textbooks should be improved to ensure that SST data are adequately visualized in the textbooks. This study emphasized that oceanic literacy and data literacy could be cultivated and strengthened simultaneously through visualizations of oceanic big data by using satellite SST data and oceanic in-situ measurements.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.391-404
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• 2021

This study developed a long-term prediction model for the potential yield of garlic based on a genetic algorithm (GA) by utilizing global climate reanalysis data. The GA is used for digging the inherent signals from global climate reanalysis data which are both directly and indirectly connected with the garlic yield potential. Our results indicate that both deterministic and probabilistic forecasts reasonably capture the inter-annual variability of crop yields with temporal correlation coefficients significant at 99% confidence level and superior categorical forecast skill with a hit rate of 93.3% for 2 × 2 and 73.3% for 3 × 3 contingency tables. Furthermore, the GA method, which considers linear and non-linear relationships between predictors and predictands, shows superiority of forecast skill in terms of both stability and skill scores compared with linear method. Since our result can predict the potential yield before the start of farming, it is expected to help establish a long-term plan to stabilize the demand and price of agricultural products and prepare countermeasures for possible problems in advance.

• Journal of Korean Society on Water Environment
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• v.38 no.5
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• pp.220-230
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• 2022

Seasonal variability of water quality in the upland headwater streams in ten forested catchments (37.0~209.0 ha) was examined from April to November 2021. Here, seven physicochemical parameters were analyzed including pH, electrical conductivity (EC), biochemical oxygen demand (BOD), chemical oxygen demand (COD), total nitrogen (T-N), total phosphorous (T-P), and BOD/TOC. The parameters were compared with those of lowerland rivers as middle and lower reaches within a watershed. The pH showed was low (6.4~6.9) during all the seasons, however, BOD and BOD/TOC in the fall season were 2-fold higher than in the spring and summer seasons. Based on environmental standards, the water quality level revealed that the upland headwater streams maintained the purity and cleanliness of water except for pH in the summer season. BOD/TOC of all the seasons and BOD of the fall season in the upland headwater streams were higher than that in the lowerland rivers, whereas the rest of the physicochemical parameters in the upland headwater streams were lower than that in the lowerland rivers. Additionally, the water quality level maintained the purity and cleanliness of water as "Good" in two reaches. The unique aspects of our study design enabled us to draw inferences about water quality characteristics with temporal and spatial analysis in upland headwater streams. This design will be useful for the long-term strategy of effective water quality management for integrated upland headwater streams and lowerland rivers within a watershed.

• Journal of Environmental Health Sciences
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• v.48 no.6
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• pp.298-305
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• 2022

Background: The concentration of air pollutants as measured by the Air Quality Monitoring System (AQMS) is not an accurate population exposure level since actual human activities and temporal and spatial variability need to be considered. Therefore, to increase the accuracy of exposure assessment, the population should be considered. However, it is difficult to obtain population data due to limitations such as personal information. Objectives: The existing population defined in this study is the number of people in each region's grid. The purpose is to provide a methodology for evaluating exposure to PM_2.5 through existing population data provided by the National Geographic Information Institute. Methods: The selected study period was from October 26 to October 28, 2021. Using PM_2.5 concentration data measured at the Sensor-based Air Monitoring Station (SAMS) installed in Guro-gu and Wonju-si, the concentration for each grid was estimated by applying inverse distance weights through QGIS version 3.22. Considering the existing population, population-weighted average concentration (PWAC) was calculated and the exposure level of the population was compared by region. Results: The outdoor PM_2.5 concentration as measured through the SAMS was high in Wonju-si on all three days. Wonju-si showed an average 22% higher PWAC than Guro-gu. As a result of comparing the PWAC and outdoor PM_2.5 concentration by region, the PWAC in Guro-gu was 1~2% higher than the observed value, but it was almost the same. Conversely, observations of Wonju-si were 10.1%, 11.3%, and 8.2% higher than PWAC. Conclusions: It is expected that the Geographic Information System (GIS) method and the existing population will be used to evaluate the exposure level of a population with a narrow activity radius in further research. In addition, based on this study, it is judged that research on exposure to environmental pollutants and risk assessment methods should be expanded.