• Title/Summary/Keyword: Weather sensitivity

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Identification of Impact Factors in Ship-to-Ship Mooring Through Sensitivity Analysis

  • Lee, Sang-Won;Lee, Hyeong-Tak;Kim, Dae-Gun;Cho, Ik-Soon
    • Journal of Navigation and Port Research
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    • v.43 no.5
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    • pp.310-319
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    • 2019
  • With the recent increase in the volume of liquid cargo transportation, there is a need for STS( Ship To Ship) globally. In the case of the STS mooring, the safety assessment should be conducted according to other criteria because mooring is different from the general mooring at the quay, but there is no separate standard in Korea. Thus in this study, STS mooring simulation and sensitivity analysis using OPTIMOOR program, the numerical analysis program, was conducted to identify the characteristics of the STS mooring. The target sea modeled the Yeosu port anchorage in Korea and the target ship was selected as the case of VLCC (Very Large Crude Oil Carrier)-VLCC. Through the numerical simulation and sensitivity analysis, the characteristics of STS mooring were identified. Also based on these results, we focused on establishing the standard for STS mooring safety assessment. Numerical simulation results show that the STS mooring safety can be changed according to a ship's cargo loading condition, pre-tension of mooring line, sea depth, encounter angle with the weather, and the weather condition. Additionally, the risk matrix is prepared to establish the safe external force range in the corresponding sea area. This result can be used to understand the mooring characteristics of STS and contribute to the revision of mooring safety assessment criteria.

Qualification for Impedance-based Rain Detectors

  • Lee, Sang-Wook;Choi, Byung Il;Kim, Jong Chul;Woo, Sang-Bong;Kim, Yong-Gyoo
    • Journal of Sensor Science and Technology
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    • v.26 no.3
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    • pp.149-154
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    • 2017
  • Detection of rain is one of the essential weather factors that are monitored by automatic weather stations in Korea. In this work, we studied the operation standards required for impedance-based rain detectors in terms of surface temperature and sensitivity, in an effort to establish a qualification procedure for rain detectors. The surface temperature of rain detectors was measured at varying air temperatures from $-30^{\circ}C$ to $20^{\circ}C$, considering the hypothetical presence and absence of rain/snow. In addition, the sensitivity of rain detectors was studied generating artificial raindrops of regular size. The sensitivity was evaluated in terms of the critical number of droplets that triggers the activation of the rain detector. We found that the sensitivity is affected by stationary, horizontal, and vertical droplet deposition methods. The critical number of droplets for the stationary deposition is higher than that for both horizontal and vertical depositions, which provides the maximum limit of droplets required to activate the detector. Based on our experiments considering surface temperature measurements and sensitivity tests, we suggest a revised version of surface temperature and sensitivity requirements for the qualification of impedance-based rain detectors.

A Scheme for Reducing Load Forecast Error During Weekends Near Typhoon Hit (태풍 발생 인접 주말의 수요예측 오차 감소 방안)

  • Park, Jeong-Do;Song, Kyung-Bin
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.58 no.9
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    • pp.1700-1705
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    • 2009
  • In general, short term load forecasting is based on the periodical load pattern during a day or a week. Therefore, the conventional methods do not expose stable performance to every day during a year. Especially for anomalous weather conditions such as typhoons, the methods have a tendency to show the conspicuous accuracy deterioration. Furthermore, the tendency raises the reliability and stability problems of the conventional load forecast. In this study, a new load forecasting method is proposed in order to increase the accuracy of the forecast result in case of anomalous weather conditions such as typhoons. For irregular weather conditions, the sensitivity between temperature and daily load is used to improve the accuracy of the load forecast. The proposed method was tested with the actual load profiles during 14 years, which shows that the suggested scheme considerably improves the accuracy of the load forecast results.

Improvement of a Detecting Algorithm for Geometric Center of Typhoon using Weather Radar Data (레이더 자료를 이용한 기하학적 태풍중심 탐지 기법 개선)

  • Jung, Woomi;Suk, Mi-Kyung;Choi, Youn;Kim, Kwang-Ho
    • Atmosphere
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    • v.30 no.4
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    • pp.347-360
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    • 2020
  • The automatic algorithm optimized for the Korean Peninsula was developed to detect and track the center of typhoon based on a geometrical method using high-resolution retrieved WISSDOM (WInd Syntheses System using DOppler Measurements) wind and reflectivity data. This algorithm analyzes the center of typhoon by detecting the geometric circular structure of the typhoon's eye in radar reflectivity and vorticity 2D field data. For optimizing the algorithm, the main factors of the algorithm were selected and the optimal thresholds were determined through sensitivity experiments for each factor. The center of typhoon was detected for 5 typhoon cases that approached or landed on Korean Peninsula. The performance was verified by comparing and analyzing from the best track of Korea Meteorological Administration (KMA). The detection rate for vorticity use was 15% higher on average than that for reflectivity use. The detection rate for vorticity use was up to 90% for DIANMU case in 2010. The difference between the detected locations and best tracks of KMA was 0.2° on average when using reflectivity and vorticity. After the optimization, the detection rate was improved overall, especially the detection rate more increased when using reflectivity than using vorticity. And the difference of location was reduced to 0.18° on average, increasing the accuracy.

Analysis of Traffic Characteristics of General National Roads by Snowfall in Gangwon-do (강원도에서 적설에 의한 일반국도 교통 특성 분석)

  • Jo, Eun Su;Kwon, Tae-Yong;Kim, Hyunuk;Kim, Kyu Rang;Kim, Seung Bum
    • Atmosphere
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    • v.31 no.2
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    • pp.157-170
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    • 2021
  • To investigate the effect of snowfall on the traffic of general roads in Gangwon-do, case analysis was performed in Gangneung, Pyeongchang, and Chuncheon using ASOS (Automated Synoptic Observing System) snowfall data and VDS (Vehicle Detector System) traffic data. First, we analyzed how much the traffic volume and speed decrease in snowfall cases on regional roads compared to non-snow cases, and the characteristics of monthly reduction due to snowfall were investigated. In addition, Pearson correlation analysis and regression analysis were performed to quantitatively grasp the effect of snowfall on traffic volume and speed, and sensitivity tests for snowfall intensity and cumulative snowfall were performed. The results showed that the amount of snowfall caused decrease both in the traffic volume and speed from usual (non-snowfall) condition. However, the trend was different by region: The decrease rate in traffic volume was in the order of Gangneung (17~22%), Chuncheon (14~17%), and Pyeongchang (11~14%). The decrease rate in traffic speed was in the order of Chuncheon (9~10%), Gangneung (8~9%), Pyeongchang (5~6%). No significant results were found in the monthly decrease rate analysis. In all regions, traffic volume and speed showed a negative correlation with snowfall. It was confirmed that the greater the amount of traffic entering the road, the greater the slope of the trend line indicating the change in snowfall due to the traffic volume. As a result of the sensitivity test for snowfall intensity and cumulative snowfall, the snowfall information at intervals of 6-hours was the most significant.

Analyzing the Impact of Weather Conditions on Beer Sales: Insights for Market Strategy and Inventory Management

  • Sangwoo LEE;Sang Hyeon LEE
    • Asian Journal of Business Environment
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    • v.14 no.3
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    • pp.1-11
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    • 2024
  • Purpose: This study analyzes the impact of weather conditions, holidays, and sporting events on beer sales, providing insights for market strategy and inventory management in the beer industry. Research design, data and methodology: Beer types were classified into Lagers and Ales, with further subcategories. The study utilized weekly retail sales data from January 2018 to August 2020, provided by Nielsen Korea. An ARMAX model was employed for time-series analysis. Results: The analysis revealed that increasing temperatures positively influence sales of Pilsners and Pale Lagers. Conversely, higher precipitation levels negatively affect overall Lager sales. Among Ales, only Stout sales showed a significant decrease with increased rainfall. Sunshine duration did not significantly impact sales for any beer type. Humidity generally had little effect on beer sales, with the exception of Amber Lagers, which showed sensitivity to humidity changes. Holidays and sporting events were found to significantly boost sales across most beer types, although the specific impacts varied by beer category. Conclusions: This study offers a detailed analysis of how weather conditions and specific events influence different beer type sales. The findings provide valuable insights for breweries, beer processors, and retailers to optimize their market strategies and inventory management based on weather forecasts and seasonal events. By understanding the consumption patterns of each beer type in relation to environmental factors, businesses can better anticipate demand fluctuations and tailor their operations accordingly.

Sensitivity Analysis of Numerical Weather Prediction Model with Topographic Effect in the Radiative Transfer Process (복사전달과정에서 지형효과에 따른 기상수치모델의 민감도 분석)

  • Jee, Joon-Bum;Min, Jae-Sik;Jang, Min;Kim, Bu-Yo;Zo, Il-Sung;Lee, Kyu-Tae
    • Atmosphere
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    • v.27 no.4
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    • pp.385-398
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    • 2017
  • Numerical weather prediction experiments were carried out by applying topographic effects to reduce or enhance the solar radiation by terrain. In this study, x and ${\kappa}({\phi}_o,\;{\theta}_o)$ are precalculated for topographic effect on high resolution numerical weather prediction (NWP) with 1 km spatial resolution, and meteorological variables are analyzed through the numerical experiments. For the numerical simulations, cases were selected in winter (CASE 1) and summer (CASE 2). In the CASE 2, topographic effect was observed on the southward surface to enhance the solar energy reaching the surface, and enhance surface temperature and temperature at 2 m. Especially, the surface temperature is changed sensitively due to the change of the solar energy on the surface, but the change of the precipitation is difficult to match of topographic effect. As a result of the verification using Korea Meteorological Administration (KMA) Automated Weather System (AWS) data on Seoul metropolitan area, the topographic effect is very weak in the winter case. In the CASE 1, the improvement of accuracy was numerically confirmed by decreasing the bias and RMSE (Root mean square error) of temperature at 2 m, wind speed at 10 m and relative humidity. However, the accuracy of rainfall prediction (Threat score (TS), BIAS, equitable threat score (ETS)) with topographic effect is decreased compared to without topographic effect. It is analyzed that the topographic effect improves the solar radiation on surface and affect the enhancements of surface temperature, 2 meter temperature, wind speed, and PBL height.

Hangul Font Outline Vector Modification Algorithm According to Weather Information (날씨에 따른 한글 폰트 윤곽선 벡터 변형 알고리즘)

  • Park, Dong-Yeon;Jo, Se-Ran;Kim, Nam-Hee;Lim, Soon-Bum
    • Journal of Korea Multimedia Society
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    • v.25 no.9
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    • pp.1328-1337
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    • 2022
  • Recently, research on various font designs has been actively conducted to deliver effective emotional information in a digital environment. In this study, we propose a Hangul font outline vector modification algorithm that effectively conveys sensitivity according to weather information and can be transformed immediately. The algorithm performs a series of transformations: sets outlines according to design pattern templates, calculates the glyph's position to reflect physical rules, splits outline segments into smaller sizes and deforms the outlines. Through this, we could create several vector font designs such as humidity, cloud, wind, and snow. The usability evaluation was close to good, so it can be used in diverse ways if we improve readability and effective design expression.

Forecast Sensitivity to Observations for High-Impact Weather Events in the Korean Peninsula (한반도에 발생한 위험 기상 사례에 대한 관측 민감도 분석)

  • Kim, SeHyun;Kim, Hyun Mee;Kim, Eun-Jung;Shin, Hyun-Cheol
    • Atmosphere
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    • v.23 no.2
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    • pp.171-186
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    • 2013
  • Recently, the number of observations used in a data assimilation system is increasing due to the enormous amount of observations, including satellite data. However, it is not clear that all of these observations are always beneficial to the performance of the numerical weather prediction (NWP). Therefore, it is important to evaluate the effect of observations on these forecasts so that the observations can be used more usefully in NWP process. In this study, the adjoint-based Forecast Sensitivity to Observation (FSO) method with the KMA Unified Model (UM) is applied to two high-impact weather events which occurred in summer and winter in Korea in an effort to investigate the effects of observations on the forecasts of these events. The total dry energy norm is used as a response function to calculate the adjoint sensitivity. For the summer case, TEMP observations have the greatest total impact while BOGUS shows the greatest impact per observation for all of the 24-, 36-, and 48-hour forecasts. For the winter case, aircraft, ATOVS, and ESA have the greatest total impact for the 24-, 36-, and 48-hour forecasts respectively, while ESA has the greatest impact per observation. Most of the observation effects are horizontally located upwind or in the vicinity of the Korean peninsula. The fraction of beneficial observations is less than 50%, which is less than the results in previous studies. As an additional experiment, the total moist energy norm is used as a response function to measure the sensitivity of 24-hour forecast error to observations. The characteristics of the observation impact with the moist energy response function are generally similar to those with the dry energy response function. However, the ATOVS observations were found to be sensitive to the response function, showing a positive (a negative) effect on the forecast when using the dry (moist) norm for the summer case. For the winter case, the dry and moist energy norm experiments show very similar results because the adjoint of KMA UM does not calculate the specific humidity of ice properly such that the dry and moist energy norms are very similar except for the humidity in air that is very low in winter.