• 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.

• Atmosphere
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• v.31 no.5
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• pp.525-537
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• 2021

Black ices on road surfaces in winter tend to cause severe and terrible accidents. It is very difficult to detect black ice events in advance due to their localities as well as sensitivities to surface and upper meteorological variables. This study develops a methodology to detect the road sections vulnerable to black ice with the use of road surface temperature data obtained from a mobile road weather observation vehicle. The 7 experiments were conducted on the route from Nam-Wonju IC to Nam-Andong IC (132.5 km) on the Jungang Expressway during the period from December 2020 to February 2021. Firstly, temporal road surface temperature data were converted to the spatial data with a 50 m resolution. Then, the spatial road surface temperature was normalized with zero mean and one standard deviation using a simple normalization, a linear de-trend and normalization, and a low-pass filter and normalization. The resulting road thermal map was calculated in terms of road surface temperature differences. A road ice index was suggested using the normalized road temperatures and their horizontal differences. Road sections vulnerable to black ice were derived from road ice indices and verified with respect to road geometry and sky view, etc. It was found that black ice could occur not only over bridges, but also roads with a low sky view factor. These results are expected to be applicable to the alarm service for black ice to drivers.

• Journal of Digital Contents Society
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• v.19 no.9
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• pp.1739-1749
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• 2018

We propose a marine observation system using existing light buoys to observe various marine information of marine locations. Our proposed ocean observation system is composed of the existing standard light buoy type and can be easily connected to the light buoy. The proposed marine observation system measures the mean wave height, maximum wave height, mean wave height and water temperature measured in the ocean. Besides, it can measure the air pressure, temperature, wind speed and wind speed in real time. In order to measure important peaks in marine observations, 2200 peak data are collected for 10 minutes, and the collected data are subjected to spectral analysis to extract significant wave and wave period data. The developed system removes the noise by using the filter because the marine observation system attaches to the light buoy. We compare and analyze the measurement data of the existing proven floating marine observation system and the standard equivalent system developed. Also, it is proved that the data of the standard type backbone ocean observation system developed through the comparative experiment is similar to that of the existing ocean observation system.

• Journal of the Korean association of regional geographers
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• v.2 no.2
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• pp.49-73
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• 1996

This study produces quantitatively weather entropy and information ratio using information theory about frequency in the appearance of precipitation phenomenon and monthly change, and then applies them to observation of the change of their space scale by time. As a result of these, this study defines Pusan, Chongju and Kwangju's weather representativeness and then establishes the range of weather representativeness. Based on weather entropy (statistical parameter)-the amount of average weather information-and information ratio, we can define each area's weather representativeness, which can show us more constant form included topographical, geographical factors and season change. The data used for this study are the daily precipitotion and cloudiness during the recent five years($1990{\sim}1994$) at the 69 stations in Korea. It is divided into class of no precipitation, that of precipitation. The results of this study can be summarized as follows: (1) The four season's mean value of information ratio is the highest value. as 0.641, on the basis of Chongju. It is the lowest as 0.572, on the basis of Pusan. On a seasonal basis, the highest mean value of information rate is April's (spring) in Chongju, and the lowest is October's(fall) in Pusan. Accordingly weather representativeness has the highest in Chongju and the lowest in Pusan. (2) To synthesize information ratio of decaying tendancy and half-decay distance, Chonju's weather representativeness has the highest in April, July and October. And kwangju has the highest value in January and the lowest in April and July. Pusan's weather representativeness is not high, that of Pusan's October is the lowest in the year. (3) If we establish the weather representative character on the basis of Chongju-Pusan, the domain of Chongju area is larger than that of Pusan area in October, July and April in order. But Pusan's is larger than Chongju's in January. In the case of Chongju and Kwangju, the domain of Chongju area is larger than that of Kwangju in October, July and April in order, but it is less than that of Kwangju area in January. In the case of Kwangju-Pusan, the domain of Kwangju is larger than that of Pusan in October, July in order. But in April it is less than Pusan's.

• Journal of the Korean earth science society
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• v.35 no.4
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• pp.215-224
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• 2014

Data assimilation effect of mobile rawinsonde observation was evaluated using Unified Model (UM) with a Three-Dimensional Variational (3DVAR) data assimilation system during the intensive observation program of 2013 summer season (rainy season: 20 June-7 July 2013, heavy rain period: 8 July-30 July 2013). The analysis was performed by two sets of simulation experiments: (1) ConTroL experiment (CTL) with observation data provided by Korea Meteorological Administration (KMA) and (2) Observing System Experiment (OSE) including both KMA and mobile rawinsonde observation data. In the model verification during the rainy season, there were no distinctive differences for 500 hPa geopotential height, 850 hPa air temperature, and 300 hPa wind speed between CTL and OSE simulation due to data limitation (0000 and 1200 UTC only) at stationary rawinsonde stations. In contrast, precipitation verification using the hourly accumulated precipitation data of Automatic Synoptic Observation System (ASOS) showed that Equivalent Threat Score (ETS) of the OSE was improved by about 2% compared with that of the CTL. For cases having a positive effect of the OSE simulation, ETS of the OSE showed a significantly higher improvement (up to 41%) than that of the CTL. This estimation thus suggests that the use of mobile rawinsonde observation data using UM 3DVAR could be reasonable enough to assess the improvement of prediction accuracy.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2004.11a
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• pp.61-70
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• 2004

This paper treats optimal route assessment system at seaway based on weather forecasting and wave measurement through observation. Since early times. captain & officer have been sailing to select the optimum route considering the weather ana ship status condition empirically. However. it is rare to find digitalized onboard route support system whereas weather fax or wave and swell chart are utilized for the officer. based on officer's experience. In this paper, optimal route assessment system which is composed of voyage efficiency and safety component is introduced. Optimum route minimized ETA (estimated time of arrival) ana fuel consumption is evaluated for efficient voyage considering speed loss and power increase based on wave added resistance of ship. In the view point of safety, seakeeping prediction is performed based on 3 dimensional panel method. Basically. the weather forecast is assumed to be prepared previously in order to operate this system.

• Journal of Navigation and Port Research
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• v.28 no.10 s.96
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• pp.833-841
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• 2004

This paper treats optimal route assessment system at seaway based on weather forecasting and wave measurement through observation Since early times, captain & officer have been sailing to select the optimum route considering the weather and ship status condition empirically. However, it is rare to find digitalized onboard route support system whereas weather fax or wave and swell chart are utilized for the officer, based on officer's experience. In this paper, optimal route assessment system which is composed of voyage efficiency and safety component is introduced. Optimum route minimized ETA(estimated time of arrival) and fuel consumption is evaluated for efficient voyage considering speed loss and power increase based on wave added resistance of ship. In the view point of safety, seakeeping prediction is performed based on 3 dimensional panel method. Basically, the weather forecast is assumed to be prepared previously in order to operate this system.

• Journal of the Korean earth science society
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• v.36 no.6
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• pp.553-566
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• 2015

The effects of vertical resolutions and planetary boundary layer (PBL) physics schemes in a numerical simulation with a very high resolution over the metropolitan area were investigated. The numerical experiments using the Weather Research and Forecast model were conducted from 0000 UTC 25 October to 0000 UTC 26 October 2013. We verified the numerical results against with six hourly observation data from the radiosonde at Seolleung, which was located in southern part of Seoul, and forty three auto weather systems in Seoul. In the experiments of vertical resolutions in low level atmosphere with 44, 50, and 60 layers, which are set to be subdivided particularly under 2 km height. The experiment in 60 layers, which has the highest vertical resolution in this study, showed relatively a clear diurnal variation of PBL heights. Especially, the difference of PBL heights and 10-meter wind fields were mainly seen in the area of high altitude lands for the experiments of vertical resolution. In the sensitivity experiment of PBL schemes such as asymmetric convective model-version 2 (ACM2), Yonsei University (YSU), and Mellow-Yamada-Janjic (MYJ) to the temperature, all three PBL schemes revealed lower temperature than observed profile from the radiosonde in the entire period. The experiments with YSU PBL and ACM2 PBL schemes show relatively less biased in comparison with the experiment of the MYJ PBL scheme.

• Korean Journal of Agricultural and Forest Meteorology
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• v.14 no.2
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• pp.53-62
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• 2012

Demand for high resolution weather data grows in the agriculture and forestry fields. Local Analysis and Prediction System (LAPS) can be used to analyze the local weather at high spatial and temporal resolution, utilizing the data from various sources including numerical weather prediction models, wind or temperature profilers, Automated Weather Station (AWS) networks, radars, and satellites. LAPS has been set to analyze weather elements such as air temperature, relative humidity, wind speed, and wind direction every hour at the spatial resolution of $100m{\times}100m$ for Gyeonggi-do on near real-time basis. The AWS data were revised by adding the agricultural field AWS data (33 stations) in addition to the KMA data. The analysis periods were from 1 to 31 August 2009 and from 15 to 21 February 2010. The comparison of the LAPS output showed the smaller errors when using the agricultural AWS observation data together with the KMA data as its input data than using only either the agricultural or KMA AWS data. The accuracy of the current system needs improvement by further optimization of analyzing options of the system. However, the system is highly applicable to various fields in agriculture and forestry because it can provide site specific data with reasonable time intervals.

• Korean Journal of Agricultural and Forest Meteorology
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• v.20 no.4
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• pp.337-347
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• 2018

Weather causes much of the risk of agricultural activity. For efficient farming, we need to use weather information. Modern agriculture has been developed to create high added value through convergence with state-of-the-art Information and Communication Technology (ICT). This study deals with the quality control algorithms of weather monitoring equipment through Ubiquitous Sensor Network (USN) observational equipment for efficient cultivation of cabbage. Accurate weather observations are important. To achieve this goal, the Korea Meteorological Administration, for example, developed various quality control algorithms to determine regularity of the observation. The research data of this study were obtained from five USN stations, which were installed in Anbandegi and Gwinemi from 2015 to 2017. Quality control algorithms were developed for flat line check, temporal outliers check, time series consistency check and spatial outliers check. Finally, the quality control algorithms proposed in this study can also identify potential abnormal observations taking into account the temporal and spatial characteristics of weather data. It is expected to be useful for efficient management of highland cabbage production by providing quality-controlled weather data.