• Korean Journal of Agricultural and Forest Meteorology
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• v.15 no.4
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• pp.304-311
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• 2013

There have been increasing cases for farmers to install automated weather stations (AWS) at their farms and orchards in order to take countermeasures to more frequent weather disasters caused by climate variability and weather extremes. Although raw data are the same, the additive values as agrometeorological information may vary depending on data processing methods. User demands on appropriate information could also be different among crop species, cropping systems and even cultivars. We designed an internet based AWS data processing and display system to help diverse users (e.g., farmers), extension workers to access their weather data on specific demands. The system was implemented at a rural catchment with 52 $km^2$ land area where 14 automated weather stations are in operation. This note introduces the system and describes the major modules in detail. By linking regional AWS networks, a feasibility for this system as an early warning system is also discussed.

• Korean Journal of Remote Sensing
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• v.15 no.1
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• pp.9-20
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• 1999

The use of climatic information is essential in the industial society. More specialized weather servies are required to perform better industrial acivities including agriculture. Especially, crop models require daily weather data of crop growing area or cropping zones, where routine weather observations are rare. Estimates of the spatial distribution of daily climates might complement the low density of standard weather observation stations. This study was conducted to estimate the spatial distribution of daily minimum and maximum temperatures in Korean Peninsula. A topoclimatological technique was first applied to produce reasonable estimates of monthly climatic normals based on 1km $\times$ 1km grid cell over study area. Harmonic analysis method was then adopted to convert the monthly climatic normals into daily climatic normals. The daily temperatures for each grid cell were derived from a spatial interpolation procedure based on inverse-distance weighting of the observed deviation from the climatic normals at the nearest 4 standard weather stations. Data collected from more than 300 automatic weather systems were then used to validate the final estimates on several dates in 1997. Final step to confirm accuracy of the estimated temperature fields was comparing the distribution pattern with the brightness temperature fields derived from NOAA/AVHRR. Results show that differences between the estimated and the observed temperatures at 20 randomly selected automatic weather systems(AWS) range from -3.$0^{\circ}C$ to + 2.5$^{\circ}C$ in daily maximum, and from -1.8$^{\circ}C$ to + 2.2$^{\circ}C$ in daily minimum temperature. The estimation errors, RMSE, calculated from the data collected at about 300 AWS range from $1.5^{\circ}C$ to 2.5$^{\circ}C$ for daily maximum/minimum temperatures.

• Journal of Digital Contents Society
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• v.18 no.7
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• pp.1377-1386
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• 2017

We propose a smart ocean meteorological observation system which is capable of real-time measurement of vulnerable marine climate and oceanographic conditions. Besides, imported products have several disadvantages such that they can't be measured for a long time and can't transmit data in real time. In the proposed system, smart ocean observation digging system, it observes real-time ocean weather with data logger methods. Furthermore, we also use existing dataloggers functions with various sensors which are available in the ocean at the same time. Also, we applied the Kalman-filter algorithm to the ocean crest measurement to reduce the noise and increase the accuracy of the real-time wave height measurement. In the experiment, we experimented the proposed system with our proposed algorithms through calibration devices in the real ocean environment. Then we compared the proposed system with and without the algorithms. As a result, the system developed with a lithium iron phosphate battery that can be charged by a system used in the ocean and minimized power consumption by using an RTC based timer for optimal use. Besides, we obtained optimal battery usage and measured values through experiments based on the measurement cycle.

• Atmosphere
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• v.13 no.4
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• pp.57-70
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• 2003

The National Center for Intensive Observation of Severe Weathers (NCIO) as a part of METRI's principal project "Korea Enhanced Observing Period; KEOP" was established at Haenam Weather Observatory in order to effectively monitor and observe heavy rainfall in summer, which is essential for the identification of the structure and evolution mechanism of mesoscale severe weather system. The intensive field-based experiments in 2002 within southwestern Korea toward various meteorological phenomena ranging from heavy rainfall to snowfall were conducted in collaboration with KMA(Korea Meteorological Administration) and universities. In this study, preliminary analysis results using intensive observation data obtained from these experiments are presented together with the introduction of NCIO and its operational structure.

• Journal of the Korean earth science society
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• v.45 no.2
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• pp.111-120
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• 2024

Cloud coverage is a key factor in determining whether to proceed with observations. In the past, human judgment played an important role in weather evaluation for observations. However, the development of remote and robotic observation has diminished the role of human judgment. Moreover, it is not easy to evaluate weather conditions automatically because of the diverse cloud shapes and their rapid movement. In this paper, we present the development of a cloud monitoring program by applying a machine learning-based Python module "cloudynight" on all-sky camera images obtained at Miryang Arirang Astronomical Observatory (MAAO). The machine learning model was built by training 39,996 subregions divided from 1,212 images with altitude/azimuth angles and extracting 16 feature spaces. For our training model, the F1-score from the validation samples was 0.97, indicating good performance in identifying clouds in the all-sky image. As a result, this program calculates "Cloudiness" as the ratio of the number of total subregions to the number of subregions predicted to be covered by clouds. In the robotic observation, we set a policy that allows the telescope system to halt the observation when the "Cloudiness" exceeds 0.6 during the last 30 minutes. Following this policy, we found that there were no improper halts in the telescope system due to incorrect program decisions. We expect that robotic observation with the 0.7 m telescope at MAAO can be successfully operated using the cloud monitoring program.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2014.06a
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• pp.81-83
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• 2014

In recent years, owing to the irregular weather changes in the sailing vessels are needed for marine meteorological environmental counter measures. Marine meteorological monitoring system, information about these marine weather environments in real time around the coast by collecting a provides real time shipping and marine transportation safety is a system for. .. Long marine facilities marine observation sensors cover the routes developed by installing marine meteorological monitoring system, build management, and vessel safety is giving much help to navigate. The further development of the marine meteorological monitoring system analyzes the situation both at home and abroad, in order to study the safety of the vessel in navigable and marine accidents because the prevention and optimal marine meteorological monitoring system regarding the future development plan for discussion.

• Journal of the Korean Society of Systems Engineering
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• v.12 no.2
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• pp.59-67
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• 2016

Recently, the increased complexity of systems has made systems engineering necessary. It is very useful for system designers to understand the whole context of the concerned system based on systems engineering. A system model can be used to describe the outcome of a system design. A system model describes the system from the viewpoint of the stakeholder's needs using the mutually exclusive and collectively exhaustive principle. A system model can be used to smoothly design a large and complicated system based on the systems engineering development process. Many companies and countries are attempting to apply model-based systems engineering, and the significance of the system model quality is increasing as system models are referenced during system development. In this paper, we propose a quality assessment method for ontology which is one of system models by focusing on the system development process. First, in this process, a system developer should explicitly show the relationship between viewpoints. Then, the system developer should select dependent rather than independent viewpoints. With dependent viewpoints, each viewpoint used to describe the system has some logical relationship. The set of viewpoints makes it possible to show, not only tangible and physical system parts, but also conceptual system parts. In this paper, we develop an ontological system model of a Japanese weather observation system. By comparing some ontological system models, we verify the effectiveness of explicitly describing the relationships between viewpoints and select dependent viewpoints.

• Spatial Information Research
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• v.20 no.6
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• pp.13-21
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• 2012

In this study, homogeneous regions for regional frequency analysis were identified using rainfall data from 61 observation points in Korea. The used data were gathered from 1980 to 2010. Self organizing map and K-means clustering based on Davies-Bouldin Index were used to make clusters showing similar rainfall patterns and to decide the optimum number of the homogeneous regions. The results from this analysis showed that the 61 observation points can be optimally grouped into 6 geographical clusters. Finally, the 61 observations points grouped into 6 clusters were mapped regionally using Thiessen polygon method.

• Journal of Navigation and Port Research
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• v.26 no.4
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• pp.465-472
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• 2002

The waterfront has distinct climate characteristics different from urban or inland area. These may create not only the rise of energy and maintenance costs for facilities located at waterfront areas, but also the negative effects on the climate of the nearby inland area, unless these are treated with particular care. For the present study, the climate characteristics of waterfront were examined with climate data of 10 observation points carefully selected in Busan area. Each weather observation point was classified into either waterfront area of inland area, based on the distance from the coastal line. Special considerations were given to the climate data gathered at the Dae-Yeon weather station because it shows the climate characteristics similar to those of inland area, although it is located very near the waterfront area. Results indicates that this peculiar climate condition attributes, at least in part, to the reclamation of frontal coastal area.

• Journal of the Korean Data and Information Science Society
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• v.26 no.2
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• pp.289-299
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• 2015

The objective of the present study is to develop statistical quantitative forecast model for PM10 concentration over Seoul. We used three types of data (weather observation data in Korea, the China's weather observation data collected by GTS, and air quality numerical model forecasts). To apply the daily forecast system, hourly data are converted to daily data and then lagging was performed. The potential predictors were selected based on correlation analysis and multicollinearity check. Model validation has been performed for checking model stability. We applied two models (multiple regression model and threshold regression model) separately. The two models were compared based on the scatter plot of forecasts and observations, time series plots, RMSE, skill scores. As a result, a threshold regression model performs better than multiple regression model in high PM10 concentration cases.