• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.51 no.4
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• pp.600-613
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• 2015

The Fishing gear loss has been repeated every year in the West Sea; however, there has been no solution. So fisher men have undergone economic loss every year. Thus it is required to reduce the loss of fishing gear. In this study to find out the reason that the fishing gear is lost in the Sea, 10 years data of wave and current for 6 locations in the West Sea were investigated and a numerical modelling were conducted into the behaviour of a gillnet in wave and current. The fishing gear was modelled with the mass spring model. As a result, it came out into the open that the location where fishing gear loss occurred most frequently was Choongnam province. The height of the maximum significant wave in this province was 6.7 m and the period of that was 4.4 second. The maximum current speed was 0.7 m/s. As a result of simulation with these data, it was revealed that the buoy is one of the reasons to decrease the holding power of the gillnet. For example, the tension of anchor rope was decreased to 50% while the drag coefficient or volume of buoy was decreased to 25%. So it is predicted that an improvement of the buoy contributes to the reduction of the gillnet loss.

• Journal of the Korean Data and Information Science Society
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• v.28 no.6
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• pp.1437-1445
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• 2017

This paper suggests a temperature guidance which must be addressed in the preparation of specifications for military equipment used in ocean/coastal environment of the Korean peninsula. It would often be costly to design materiel to operate under the most extreme environmental conditions ever recorded. Therefore, military planners usually accept equipments designed to operate under environmental stresses for all the time except a certain small percentage of the time. In this study, an 1-percent frequency of occurrence is recommended. Pohang and Shineiju are chosen to represent the hottest and coldest regions, respectively, based on surface weather observations among 28 costal regions from 1904 to 2015. The 1st and 99th percentile temperatures for Pohang and Shineiju are $37.7^{\circ}C$ and $-23.7^{\circ}C$, respectively. Diurnal cycles, including solar radiation, relative humidity and wind-speed are also provided.

• Atmosphere
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• v.24 no.4
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• pp.523-532
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• 2014

In this study, thermal tropopause height defined from WMO (World Meteorological Organization) using temperature profile derived from Advance Microwave Sounding Unit-A (AMSU-A; hereafter named AMSU) onboard EOS (Earth Observing System) Aqua satellite is retrieved. The temperature profile of AMSU was validated by comparison with the radiosonde data observed at Osan weather station. The validation in the upper atmosphere from 500 to 100 hPa pressure level showed that correlation coefficients were in the range of 0.85~0.97 and the bias was less than 1 K with Root Mean Square Error (RMSE) of ~3 K. Thermal tropopause height was retrieved by using AMSU temperature profile. The bias and RMSE were found to be -5~ -37 hPa and 45~67 hPa, respectively. Correlation coefficients were in the range of 0.5 to 0.7. We also analyzed the change of tropopause height and temperature in middle troposphere in the extreme heavy rain event (23 October, 2003) associated with tropopause folding. As a result, the distinct descent of tropopause height and temperature decrease of ~8 K at 500 hPa altitude were observed at the hour that maximum precipitation and maximum wind speed occurred. These results were consistent with ERA (ECMWF Reanalysis)-Interim data (potential vorticity, temperature) in time and space.

• Journal of Korean Society for Atmospheric Environment
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• v.26 no.4
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• pp.392-402
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• 2010

Black carbon (BC) concentrations were measured with an aethalometer (AE-16, 880 nm) at time interval of 5-min at an urban site of Gwangju over a year 2008. 24-hr filter-based integrated measurements of $PM_{2.5}$ particles were also made at the same site during the winter and summer intensive periods to test any optical loading bias in the raw BC data measured by aethalometer. BC concentration was higher in winter than in summer, possibly due to increase in emissions from energy consumption and poor dispersion with reduction of boundary layer in winter. Also temporal cycles of BC indicate that short-term transient spikes were common, occurring primarily during the rush-hour periods. A similar feature was also observed in diurnal concentration cycle of CO, mainly emitted from motor vehicles. When both low wind speed and weather patterns such as mist, haze and etc were combined, high BC concentrations frequently occurred. The amount of optical loading effect described by the "k" factor showed the seasonal variation, ranging from 0.0003 to 0.0036. This implies that optical loading effect is not seen at all times. From the comparison between the filter-based elemental carbon (EC) and aethalometer BC data, it was found that the loading compensated BC values were more reasonable than the raw BC ones reported from the aethalometer.

• Journal of Korea Water Resources Association
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• v.49 no.2
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• pp.165-175
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• 2016

In order to examine the applicability, the evaporation estimation approaches based on solar radiation are classified into 3 different model groups (Model groups A, B, and C) in this study. Each group is tested in the 6 study stations (Seoul, Daejeon, Jeonju, Busan, Mokpo, and Jeju). The model parameters of each model group are estimated and verified with measured pan evaporation data. The applicability of verified model groups are compared with results of Penman (1948) combination approach. Nash-Sutcliffe (N-S) efficiency coefficients greater than 0.663 in all study stations indicate satisfactory estimates of evaporation. On the other hand, in the model verification process, N-S efficiency coefficients greater than 0.526 in all study stations indicate also satisfactory estimates of evaporation. However, N-S efficiency coefficients in all study cases except Model groups B and C in Busan are less than those of Penman (1948) combination approach. Therefore, it is concluded in this study that the evaporation estimation approaches based on solar radiation have capability to replace Penman (1948) combination approach for the estimation of evaporation in case that some meteorological data (wind speed, relative humidity) are missing or not measured.

• Journal of Navigation and Port Research
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• v.34 no.2
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• pp.105-110
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• 2010

The studies on automatic ship collision avoidance system, which have been carried out in the last 10 years, are facing on new situation due to newly developed high technology such as computer and other information system. It was almost impossible to make it used in real navigation field 3-4 years ago because of the absence of any tool to give other ship's information, however recently developed technology suggests new possibility. This study is carried out to develop the automatic ship collision avoidance support system which considers ship's manoeuvrability into it's collision avoidance algorithm. One of the important part in ship collision avoidance system is collision decision module which can calculate collision risk with other ships and act properly to avoid the situation. Many of previous researches are using present ship's dynamic data such as present speed, position and course to calculate collision risk. However when a ship commences avoidance action, the real situation is quite different with one that has been estimated by the ship's initial data due to the ship's manoeuvring characteristic. Therefore it is better to take into account ship's manoeuvring characteristic from the stage of collision decision in ship collision avoidance system. In this study, these effects are included in the developed system. The proposed system are verified its usefulness in numerical simulation environments.

• Asian Journal of Atmospheric Environment
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• v.7 no.1
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• pp.17-24
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• 2013

Fog deposition onto the cool-temperate deciduous forest around Lake Mashu in northern Japan was estimated by the inferential method using the parameterizations of deposition velocity and liquid water content of fog (LWC). Two parameterizations of fog deposition velocity derived from field experiments in Europe and numerical simulations using a detailed multi-layer atmosphere-vegetation-soil model were tested. The empirical function between horizontal visibility (VIS) and LWC was applied to produce hourly LWC as an input data for the inferential method. Weekly mean LWC computed from VIS had a good correlation with LWC sampled by an active string-fog collector. By considering the enhancement of fog deposition due to the edge effect, fog deposition calculated by the inferential method using two parameterizations of deposition velocity agreed with that computed from throughfall data. The results indicated that the inferential method using the current parameterizations of deposition velocity and LWC can provide a rough estimation of water input due to fog deposition onto cool-temperature deciduous forests. Limitations of current parameterizations of deposition velocity related to wind speed, evaporation loss of rain and fog droplets intercepted by tree canopies, and leaf area index were discussed.

• Proceedings of KOSOMES biannual meeting
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• 2005.05a
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• pp.135-140
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• 2005

Currently, ECDIS and GPS plotters are much used as equipment providing operators with route information, but they do not have any function of automatic route creation and route explanation, so available for only experienced operators. Especially, the present situation is tint no study is made of the automatic route creation and route explanation using ENC for ECDIS, substitution system of paper chart. ENC is the electronic navigation chart that is produced using S-52, S-57 standard format required by IHQ. In this paper, an Vessel Operator Support System(VOSS) is proposed to generate an optimal route where ENC and GPS data is fusioned induding the wind direction and speed of an anemometer and tide data. The proposed system was testified by a simulation, and its effectiveness was verified.

• Journal of Environmental Science International
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• v.11 no.7
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• pp.687-696
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• 2002

Air quality monitoring data and meteorology data which had collected from 1995. 1. to 1999. 2. in six areas of Daegu, Manchondong, Bokhyundong, Deamyungdong, Samdukdong, Leehyundong and Nowondong, were investigated to determine the distribution and characteristic of ozone. A equation of multiple regression was suggested after time series analysis of contribution factor and meteorology factor were investigated during the day which had high concentration of ozone. The results show the following; First, 63.6% of high ozone concentration days, more than 60 ppb of ozone concentration, were in May, June and September. The percentage of each area showed that; Manchondong 14.4%, Bokhyundong 15.4%, Deamyungdong 15.6%, Samdukdong 15.6%, Leehyundong 17.3% and Nowondong 21.6%. Second, correlation coefficients of ozone, $SO_2$, TSP, $NO_2$ and CO showed negative relationship; the results were respectively -0.229, -0.074, -0.387, -0.190(p<0.01), and humidity were -0.677. but temperature, amount of radiation and wind speed had positive relationship; the results were respectively 0.515, 0.509, 0.400(p<0.01). Third, $R^2$ of equation of multiple regression at each area showed that; Nowondong 45.4%, Lee hyundong 77.9%, Samdukdong 69.9%, Daemyungdong 78.8%, Manchondong 88.6%, Bokhyundong 77.6%. Including 1 hour prior ozone concentration, $R^2$ of each area was significantly increased; Nowondong 75.2%, Leehyundong 89.3%, Samdukdong 86.4%, Daemyungdong 88.6%, Manchondong 88.6%, Bokhyundong 88.0%. Using equation of multiple regression, There were some different $R^2$ between predicted value and observed value; Nowondong 48%, Leehyundong 77.5%, Samdukdong 58%, Daemyungdong 73.4%, Manchondong 77.7%, Bokhyundong 75.1%. $R^2$ of model including 1 hour prior ozone concentration was higher than equation of current day; Nowondong 82.5%, Leehyundong 88.3%, Samdukdong 80.7%, Daemyungdong 82.4%, Manchondong 87.6%, Bokhyundong 88.5%.

• Journal of Advanced Navigation Technology
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• v.22 no.6
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• pp.491-499
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• 2018

Runway visual range (RVR), one of the important indicators of aircraft takeoff and landing, is affected by meteorological conditions such as temperature, humidity, etc. It is important to estimate the RVR at the time of arrival in advance. This study estimated the RVR of the local airport after 1 hour by upgrading the RVR estimation model using the proposed deep learning network. To this end, the advancement of the estimation model was carried out by changing the time interval of the meteorological data (temperature, humidity, wind speed, RVR) as input value and the linear conversion of the results. The proposed method generates estimation model based on the past measured meteorological data and estimates the RVR after 1 hour and confirms its validity by comparing with measured RVR after 1 hour. The proposed estimation model could be used for the RVR after 1 hour as reference in small airports in regions which do not forecast the RVR.