• The Korean Journal of Applied Statistics
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• v.25 no.2
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• pp.351-362
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• 2012

Weather generators are statistical tools to produce synthetic sequences of daily weather variables. We propose the multisite weather generators with a spatio-temporal correlation based on hierarchical generalized linear models. We develop a computational algorithm to produce future weather variables that use three different types of green-house gases scenarios. We apply the proposed method to a daily time series of precipitation and average temperature for South Korea.

• Journal of Environmental Science International
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• v.14 no.10
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• pp.945-953
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• 2005

Daily time series of longshore sea surface temperature (SST) data at 3 stations, sea surface SST data at 58 stations in the eastern coast of the Korean Peninsular from 2001 to 2005 were used in order to study the temporal and spatial variations of the upwelling coastal cold water occurred in summer season. When the cold water occurred, SST has been decreased more than $-5^{\circ}C$ in a day. The cold water occurred frequently in the eastern coastal areas of Korea such as Ulgi, Kampo, Jukbyun. Daily variations of cold water temperature were quantified using remote control buoy system at Kijang in the southeastern coastal water from July to August in 2004. Hourly variations of SST occurred around $\pm3^{\circ}C$ when cold water disappeared at Kijang. There were close relationship between the strength of East Korean Warm Current, North Korean Cold Water and the scale of spatio-temporal cold water variations in summer season.

• Journal of Environmental Science International
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• v.29 no.7
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• pp.715-727
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• 2020

It is well known that atmospheric environments, including both meteorology and air quality, significantly affect public health, such as chronic lung disease and cancer, and respiratory infections. In this study, we have analyzed correlations between the number of daily respiratory outpatients and the atmospheric environments data for about ten years for the city of Busan, South Korea. The respiratory problem patients data have been categorized into two health-vulnerable groups by age over 65(DayPA_O65) and under 20(DayPA_U20), each of which shows relatively higher correlations with air quality and meteorology, respectively. However, time series analysis with factor separation results in that DayPA_O65 and DayPA_U20 show a higher relation with variance components and daily irregular factors of atmospheric concentrations, respectively.

• Current Photovoltaic Research
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• v.8 no.2
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• pp.54-59
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• 2020

Within the IEA (International Energy Agency) PVPS (Photovoltaic Power System) Programme Task 15, 'Enabling Framework for the Acceleration of BIPV,' a round-robin action focusing on the performance of vertical BIPV elements as a facade in different climatic environments was performed. The performance of identical (both, in construction and bill of materials (BOM)) glass-to-glass c-Si BIPV elements was monitored at seven outdoor test sites in 6 different countries in Europe and Asia. In this work, the comprehensive results of the electrical and corresponding meteorological data will be presented and discussed. The monitored data were merged, processed, and filtered for further analysis. The analysis includes the chracteristics of the module temperatures and the in-plane irradiation at the outdoor test locations, mean daily PR per test module, time series of mean daily performance ratio coefficients, and monthly yield.

• Journal of Environmental Science International
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• v.19 no.10
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• pp.1229-1235
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• 2010

Three meteor-statistical forecasting models - the transfer function model, the time-series autoregressive model and the neural networks model - were tested to develop a daily forecasting model for Jejudo, where the need and demand for wind power forecasting has increased. All the meteorological observation sites in Jejudo have been classified into 6 groups using a cluster analysis. Four pairs of observation sites among them, all having strong wind speed correlation within the same meteorological group, were chosen for a model test. In the development of the wind speed forecasting model for Jejudo, it was confirmed that not only the use a wind dataset at the objective site itself, but the introduction of another wind dataset at the nearest site having a strong wind speed correlation within the same group, would enhance the goodness to fit of the forecasting. A transfer function model and a neural network model were also confirmed to offer reliable predictions, with the similar goodness to fit level.

• The Journal of Korean Medical History
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• v.32 no.2
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• pp.91-104
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• 2019

In this paper, the clinical records of Queen Inmok has been studied and the impact of historical events on her life has been analyzed. This paper has extracted her medical records during King Seonjo's and King Injo's period from the Annals and the Daily Records of Royal Secretariat of Joseon Dynasty, and then contemplated their medical implications consulting Donguibogam as a primary reference. Queen Inmok had been yang deficiency after national mourning. But suffering a series of misfortunes, she was ill with fire-heat (火熱) syndrome and finally passed away suffering from high fever, frequent diarrhea and profuse sweating. At that time, practitioners abused cold therapy following Jin Yuan Sia Jia (金元四大家), so they missed Queen Inmok's yang deficiency.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.228-232
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• 2017

Extreme hydrological events can cause serious threats to the society. Hence, the selection of probability distributions for extreme rainfall is a fundamental issue. For this reason, this study was focused on understanding possible distributional changes in annual daily maximum rainfalls (AMRs) over time in Sri Lanka using quantile regression. A simplified nine-category distributional-change scheme based on comparing empirical probability density function of two years (i.e. the first year and the last year), was used to determine the distributional changes in AMRs. Daily rainfall series of 13 station over Sri Lanka were analyzed for the period of 1960-2015. 4 distributional change categories were identified for the AMRs. 5 stations showed an upward trend in all the quantiles (i.e. 9 quantiles: from 0.05 to 0.95 with an increment of 0.01 for the AMR) which could give high probability of extreme rainfall. On the other hand, 8 stations showed a downward trend in all the quantiles which could lead to high probability of the low rainfall. Further, we identified a considerable spatial diversity in distributional changes of AMRs over Sri Lanka.

• Journal of the Korean Dietetic Association
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• v.25 no.1
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• pp.44-58
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• 2019

Predicting the number of meals in a foodservice organization is an important decision-making process that is essential for successful food production, such as reducing the amount of residue, preventing menu quality deterioration, and preventing rising costs. Compared to other demand forecasts, the menu of dietary personnel includes diverse menus, and various dietary supplements include a range of side dishes. In addition to the menus, diverse subjects for prediction are very difficult problems. Therefore, the purpose of this study was to establish a method for predicting the number of meals including predictive modeling and considering various factors in addition to menus which are actually used in the field. For this purpose, 63 variables in eight categories such as the daily available number of people for the meals, the number of people in the time series, daily menu details, weekdays or seasons, days before or after holidays, weather and temperature, holidays or year-end, and events were identified as decision variables. An ensemble model using six prediction models was then constructed to predict the number of meals. As a result, the prediction error rate was reduced from 10%~11% to approximately 6~7%, which was expected to reduce the residual amount by approximately 40%.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.54 no.1
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• pp.90-100
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• 2021

In the north and northeast of Cheonsu Bay, short-term fluctuations of surface water temperature are large owing to shallow water depth, weak current, and freshwater runoff. However, in the south of the bay, water temperature fluctuations are small owing to the inflow of offshore water by tidal currents. The water temperature in the north of the bay is higher in spring and summer than in the south of the bay, but lower in autumn and winter. During spring season, the fluctuation in the northern surface water temperature is the highest. The temperature fluctuations owing to tides are in phase with the tide in autumn and winter, and in the reverse phase with the tide in spring and summer. The dominant periods of water temperature fluctuations are half a day, daily, 15 days, and 1 month owing to the tide and 7 to 10 days, which are estimated based on atmospheric factors. Half a day and daily water temperature fluctuations are also highly correlated with air temperature and wind fluctuations. The sea area where water temperature fluctuations are highly correlated is divided into the north and south of the bay. The fluctuation phase is faster in the north of the bay than in the south or in the center.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1301-1314
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• 2022

Normalized Difference Vegetation Index (NDVI) is utilized as an indicator to represent the vegetation condition on the land surface in various applications such as land cover, crop yield, agricultural drought, soil moisture, and forest disaster. However, satellite optical sensors for visible and infrared rays cannot see through the clouds, so the NDVI of the cloud pixel is not a valid value for the land surface. This study proposed a real-time correction of the underestimation noise for GEO-KOMPSAT-2A (GK2A) daily NDVI and made sure its feasibility through the quantitative comparisons with Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI and the qualitative interpretation of time-series changes. The underestimation noise was effectively corrected by the procedures such as the time-series correction considering vegetation phenology, the outlier removal using long-term climatology, and the gap filling using rigorous statistical methods. The correlation with MODIS NDVI was higher, and the difference was lower, showing a 32.7% improvement compared to the original NDVI product. The proposed method has an extensibility for use in other satellite products with some modification.