• Atmosphere
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• v.31 no.3
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• pp.311-326
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• 2021

To improve the predictability of high-impact weather phenomena around Seoul, where a larger number of people are densely populated, KMA conducted the intensive observation from 22 June to 20 September in 2020 over the Seoul area. During the intensive observation period (IOP), the dropsonde from NIMS Atmospheric Research Aircraft (NARA) and the radiosonde from KMA research vessel Gisang1 were observed in the Yellow Sea, while, in the land, the radiosonde observation data were collected from Icheon and Incheon. Therefore, in this study, the effects of radiosonde and dropsonde data during the IOP were investigated by Observing System Experiment (OSE) based on Korean Integrated Model (KIM). We conducted two experiments: CTL assimilated the operational fifteen kinds of observations, and EXP assimilated not only operational observation data but also intensive observation data. Verifications over the Korean Peninsula area of two experiments were performed against analysis and observation data. The results showed that the predictability of short-range forecast (1~2 day) was improved for geopotential height at middle level and temperature at lower level. In three precipitation cases, EXP improved the distribution of precipitation against CTL. In typhoon cases, the predictability of EXP for typhoon track was better than CTL, although both experiments simulated weaker intensity as compared with the observed data.

• Journal of Environmental Science International
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• v.32 no.11
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• pp.841-852
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• 2023

In this study, the significant wave height and wave period of a specially designed observation system that connected two drifting buoys to an ocean data buoy was observed for 23 days from February 7 to 29, 2020, and the results were compared and analyzed. The results indicated that, in comparison to the ocean data buoy, the drifting buoy exhibited greater variability in significant wave height over shorter time intervals. The wave period of the ocean data buoy also appeared longer than that of the drifting buoy. The greater the observed significant wave height and wave period from both the ocean data and drifting buoys, the more pronounced the differences between the two observation instruments become. Moreover, the study revealed that the disparity in observation methods between the ocean data and drifting buoys did not significantly affect the significant wave height characteristics, as long as the period remained unchanged for up to half of the observation time.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.349-352
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• 2007

The Fourth Assessment Report of IPCC predicted that global warming is already happening and it should be caused from the increase of greenhouse gases by the extension of human activities. These global changes will give a serious influence for human society. Global environment can be monitored by the earth observation using satellite. For the observation of global climate change and resolving the global warming process, satellite should be useful equipment and its detecting data contribute to social benefits effectively. JAXA (former NASDA) has made a new plan of the Global Change Observation Mission (GCOM) for monitoring of global environmental change. SGLI (Second Generation GLI) onboard GCOM-C (Climate) satellite, which is one of this mission, provides an optical sensor from Near-DV to TIR. Characteristic specifications of SGLI are as follows; 1) 250 m resolutions over land and area along the shore, 2) Three directional polarization observation (red and NIR), and 3) 500 m resolutions temperature over land and area along shore. These characteristics are useful in many fields of social benefits. For example, multi-angular observation and 250 m high frequency observation give new knowledge in monitoring of land vegetation. It is expected that land products with land aerosol information by polarization observation are improved remarkably. We are studying these possibilities by ground data and satellite data.

• Atmosphere
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• v.18 no.4
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• pp.299-316
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• 2008

The intensive upper-air observation network was organized over southwestern region of the Korean Peninsula during the Korea Enhanced Observing Program in 2005 (KEOP-2005). In order to examine the effect of additional upper-air observation on the numerical weather forecasting, three Observing System Experiments (OSEs) using Korea Local Analysis and Prediction System (KLAPS) and Weather Research and Forecasting (WRF) model with KEOP-2005 data are conducted. Cold start case with KEOP-2005 data presents a remarkable predictability difference with only conventional observation data in the downstream and along the Changma front area. The sensitivity of the predictability tends to decrease under the stable atmosphere. Our results indicates that the effect of intensive observation plays a role in the forecasting of the sensitive area in the numerical model, especially under the unstable atmospheric conditions. When the intensive upper-air observation data (KEOP-2005 data) are included in the OSEs, the predictability of precipitation is partially improved. Especially, when KEOP-2005 data are assimilated at 6-hour interval, the predictability on the heavy rainfall showing higher Critical Success Index (CSI) is highly improved. Therefore it is found that KEOP-2005 data play an important role in improving the position and intensity of the simulated precipitation system.

• Korean Journal of Occupational Health Nursing
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• v.9 no.1
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• pp.56-61
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• 2000

This study was done in an attempt to reveal those factors interfering with the observation study. Three trained research assistants collected data by observing the two occupational health nurses working in the small scale enterprises on the 3rd and 10th of February, 1999. The first observation was performed on the 3rd of February without observation guidance. Guidance was given during the second observation on the 10th of February. These data were compared between reporters in nursing services of 'Workplace visiting', 'Health counselling' and 'Blood pressure checking' according to nursing time and frequency. These areas were chosen because these activities were regarded as clearly identifiable by observers in contrast to the other performances. The data showed inconsistency between reporters. However, they were reduced when reporters observed nurses with guidance, although there were still minor differences between data in time and frequency. Discussions were carried out to find possible reasons for these differences. The causes were mainly attributed to the difficulty in workplace conditions to observe, the work specificity of nurses visiting each workplace and the delicate situation between nurses and observers when reporters were travelling in the nurse's car. Therefore, the results suggest that the observation method applied to the nursing service research at small-scale enterprises should be more concerned about the selection of appropriate workplace and operational definition of nursing activity in order to more precisely measure nurses' attitudes.

• The Korean Journal of Applied Statistics
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• v.25 no.6
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• pp.1019-1026
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• 2012

This paper presents a method for the identification of "edge observations" located on a boundary area constructed by a truncation variable as well as for the identification of outliers and the after fit of multivariate skew $t$-distribution(MST) to asymmetric data. The detection of edge observation is important in data analysis because it provides information on a certain critical area in observation space. The proposed method is applied to an Australian Institute of Sport(AIS) dataset that is well known for asymmetry in data space.

• Communications for Statistical Applications and Methods
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• v.20 no.4
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• pp.283-290
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• 2013

Subjects can experience two types of recurrent events in a longitudinal study. In addition, there may exist intermittent dropouts that results in repeated observation gaps during which no recurrent events are observed. Therefore, theses periods are regarded as non-risk status. In this paper, we consider a special case where information on the observation gap is incomplete, that is, the termination time of observation gap is not available while the starting time is known. For a statistical inference, incomplete termination time is incorporated in terms of interval-censored data and estimated with two approaches. A shared frailty effect is also employed for the association between two recurrent events. An EM algorithm is applied to recover unknown termination times as well as frailty effect. We apply the suggested method to young drivers' convictions data with several suspensions.

• Publications of The Korean Astronomical Society
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• v.19 no.1
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• pp.55-63
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• 2004

Observation environment of the Bohyunsan Optical Astronomy Observatory(BOAO) has been examined using various statistical data including real observation times versus allocated times and seeing statistics. The data have been collected from the observation logs of the 1.8m telescope in the period 1998 - 2004. New criteria have been set up to calculate a more realistic observation efficiency of the observatory. The new statistical analysis based on the new criteria gives the overall observation efficiency of BOAO as $38.6\%$, that is equivalent to 115.8 observable nights out of 300 allocatable nights. The seeing statistics shows that the mean seeing measured at the focal images is 2".3. The present study of the observation environment of BOAO suggests that differential photometry and spectroscopy should be preferred modes of observation to maximize the productivity of BOAO.

• Atmosphere
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• v.28 no.2
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• pp.113-121
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• 2018

In order to monitor greenhouse gases including $CO_2$, various types of surface-, aircraft-, and satellite-based measurement projects have been conducted. These data help understand the variations of greenhouse gases and are used in atmospheric inverse modeling systems to simulate surface fluxes for greenhouse gases. CarbonTracker is a system for estimating surface $CO_2$ flux, using an atmospheric inverse modeling method, based on only surface observation data. Because of the insufficient surface observation data available for accurate estimation of the surface $CO_2$ flux, additional observations would be required. In this study, a system that assimilates aircraft $CO_2$ measurement data in CarbonTracker (CT2013B) is developed, and the estimated results from this data assimilation system are evaluated. The aircraft $CO_2$ measurement data used are obtained from the Comprehensive Observation Network for Trace gases by the Airliner (CONTRAIL) project. The developed system includes the preprocessor of the raw observation data, the observation operator, and the ensemble Kalman filter (EnKF) data assimilation process. After preprocessing the raw data, the modeled value corresponding spatially and temporally to each observation is calculated using the observation operator. These modeled values and observations are then averaged in space and time, and used in the EnKF data assimilation process. The modeled values are much closer to the observations and show smaller biases and root-mean-square errors, after the assimilation of the aircraft $CO_2$ measurement data. This system could also be used to assimilate other aircraft $CO_2$ measurement data in CarbonTracker.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.582-585
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• 2005

The Geostationary Operational Environmental Satellite (GOES) 9, which is currently located at 155°E geostationary orbits, has transmitted earth observation data acquired by imager to CDA at NOAA. After the acquisition on ground, observation data are corrected on ground and re-transmitted to GOES-9 for the dissemination to users. In this paper, the procedure and result from raw data acquisition and pre-processing for earth observation imagery retrieval from GOES-9 Raw data acquired in Korea at May 2005 are introduced.