• 유통과학연구
• /
• 제21권7호
• /
• pp.65-71
• /
• 2023

Purpose: This study attempted to analyze the impacts of the backward linkage and output multipliers, and investigate the price fluctuation and the price forecast amongst the manufacturing sectors associated with food processing industrial output of Thailand. Research design, data and methodology: The Thailand Input-Output table with a size of 180 x 180 sectors from 2005, 2010, and 2015 was utilized while the secondary data of the time series from January 2002 to December 2021 were processed via a multiplicative model and Box-Jenkins model. Results: The backward linkage analysis indicates that canning and preserving of the meat sector majorly utilized the factors of production from the slaughtering sector; canning and preservation of fish and other seafoods sector largely used those factors from the ocean and coastal fishing sector; and the sugar sector used those of the sugarcane sector. Notably, the output multiplier analysis indicated that output multipliers of those 3 manufacturing sectors were highly increased; meanwhile the price fluctuation continually existed in all forms. Besides, the price forecast suggested that prices of chicken and sugarcane tended to be higher; whereas, the price of shrimp was unstable. Conclusions: Food processing industry contains the favorable components to be one of the industries of the future of Thailand.

• 대기
• /
• 제30권3호
• /
• pp.209-220
• /
• 2020

Seasonal predictability and variability of tropical storms (TCs) simulated in the Global Seasonal Forecast System version 5 (GloSea5) of the Korea Meteorological Administration (KMA) is assessed in Northern Hemisphere in 1996~2009. In the KMA, the GloSea5-Global Atmosphere version 3.0 (GloSea5-GA3) that was previously operated was switched to the GloSea5-Global Coupled version 2.0 (GloSea5-GC2) with data assimilation system since May 2016. In this study, frequency, track, duration, and strength of the TCs in the North Indian Ocean, Western Pacific, Eastern Pacific, and North Atlantic regions derived from the GloSea5-GC2 and GloSea5-GA3 are examined against the best track data during the research period. In general, the GloSea5 shows a good skill for the prediction of seasonally averaged number of the TCs in the Eastern and Western Pacific regions, but underestimation of those in the North Atlantic region. Both the GloSea5-GA3 and GC2 are not able to predict the recurvature of the TCs in the North Western Pacific Ocean (NWPO), which implies that there is no skill for the prediction of landfalls in the Korean peninsula. The GloSea5-GC2 has higher skills for predictability and variability of the TCs than the GloSea5-GA3, although continuous improvements in the operational system for seasonal forecast are still necessary to simulate TCs more realistically in the future.

• 한국해안·해양공학회논문집
• /
• 제34권1호
• /
• pp.11-18
• /
• 2022

본 연구는 대한해협 인근 입자추적 예측 기법의 정확도 개선을 위해서 해수유동 수치모델 결과를 이용하여 만든 입자추적 모델과 현장 관측 자료를 이용한 기계학습 기반 입자 추적 모델을 비교 및 분석하였다. 세부 연구 방법으로는 대한해협에서 관측된 표층 뜰개 이동 궤적 자료, 3개 관측소(가거도, 거제도, 교본초 관측소)의 조위 및 바람자료를 학습시켜 만든 기계 학습(선형 회귀, 의사결정나무) 기반 예측자료, 수치모델 예측자료(ROMS, MOHID)를 3가지 오차평가방법(CC, RMSE, NCLS)을 통해 비교하였다. 최종 결과로서 CC와 RMSE에서는 의사결정나무 모델의 예측 정확도가 가장 우수하였고 NCLS에서는 MOHID 모델의 예측 결과가 가장 우수하였다.

• 한국해양공학회지
• /
• 제31권1호
• /
• pp.69-79
• /
• 2017

This paper presents the operations of a multi-beam echo sounder (MBES) installed on the deep-sea remotely operated vehicle (ROV) Hemire. Hemire explored hydrothermal vents in the Forecast volcano located near the Mariana Trench in March of in 2006. During these explorations, we acquired profiling points on the routes of the vehicle using the MBES. Information on the position, depth, and attitude of the ROV are essential to obtain higher accuracy for the profiling quality. However, the MBES installed on Hemire does not have its own position and depth sensors. Although it has attitude sensors for roll, pitch, and heading, the specifications of these sensors were not clear. Therefore, we had to merge the high-performance sensor data for the motion and position obtained from Hemire into the profiling data of the MBES. Then, we could properly convert the profiling points with respect to the Earth-fixed coordinates. This paper describes the integration of the MBES with Hemire, as well as the coordinate conversion between them. Bathymetric maps near the summit of the Forecast volcano were successfully collected through these processes. A comparison between the bathymetric maps from the MBES and those from the Onnuri Research Vessel, the mother ship of the ROV Hemire for these explorations, is also presented.

• 한국해양환경ㆍ에너지학회지
• /
• 제8권1호
• /
• pp.46-52
• /
• 2005

대양을 운항하는 선박의 최적 항로계획 수립에 중요한 해양환경정보를 실시간으로 예보하는 시스템(MEIS)을 개발하였다. 예보정보는 위성관측 대양환경 자료를 기반으로 유럽중기기후예보센터가 처리한 실시간 자료를 바탕으로 하며, 장기 관측자료 데이터베이스에 근거한 통계적 정보와 함께 제공된다. MEIS시스템은 육상 기지국에 설치되어 해양환경정보를 취득하고 처리하는 육상자료처리시스템(MEIS-Center)과 선박에 탑재되어 가공된 해양환경정보를 화상으로 구현하고 최적항로 선정을 돕는 선박탑재화상구현시스템(MEIS-Ship)으로 구성되며, 운항중인 선박과 육상기지국간의 정보 송수신을 위한 위성통신 시스템을 활용한다. 해양환경 요소는 바람, 파랑, 기압, 폭풍을 포함하며, 바람은 풍향과 풍속 정보를 제공하고, 파랑은 너울과 풍파로 구분하여 파고, 파향, 파주기 정보를 제공할 수 있다. 실시간 정보는 0.5°해상도로 5시간 간격의 10일 예보치가 매일 제공되며, 통계적 정보는 1.5° 해상도의 15년 관측자료를 이용하여 월평균 및 재현주기별 최대값이 산정된다. MEIS-Ship은 항로 시뮬레이션 기능을 제공하며, 설정된 항로에 대해 예보 및 통계적 해양환경정보를 그림 또는 표의 형태로 제공한다. MEIS는 예정 항로상의 정확한 실시간 해양환경 예보를 제공하므로 선박운항자가 항로의 위험도와 운항경제성을 고려하여 최적 항로를 선정하는 것이 가능하다.

• 한국수자원학회:학술대회논문집
• /
• 한국수자원학회 2009년도 학술발표회 초록집
• /
• pp.1142-1146
• /
• 2009

A rainfall simulation and forecasting technique that can generate daily rainfall sequences conditional on multi-model ensemble GCMs is developed and applied to data in Korea for the major rainy season. The GCM forecasts are provided by APEC climate center. A Weather State Based Downscaling Model (WSDM) is used to map teleconnections from ocean-atmosphere data or key state variables from numerical integrations of Ocean-Atmosphere General Circulation Models to simulate daily sequences at multiple rain gauges. The method presented is general and is applied to the wet season which is JJA(June-July-August) data in Korea. The sequences of weather states identified by the EM algorithm are shown to correspond to dominant synoptic-scale features of rainfall generating mechanisms. Application of the methodology to seasonal rainfall forecasts using empirical teleconnections and GCM derived climate forecast are discussed.

• 한국해양공학회지
• /
• 제33권5호
• /
• pp.427-434
• /
• 2019

Artificial intelligence (AI)-aided research currently enjoys active use in a wide array of fields thanks to the rapid development of computing capability and the use of Big Data. Until now, forecasting methods were primarily based on physics models and statistical studies. Today, AI is utilized in disaster prevention forecasts by studying the relationships between physical factors and their characteristics. Current studies also involve combining AI and physics models to supplement the strengths and weaknesses of each aspect. However, prior to these studies, an optimization algorithm for the AI model should be developed and its applicability should be studied. This study aimed to improve the forecast performance by constructing a model for neural network optimization. An artificial neural network (ANN) followed the ever-changing path of a typhoon to produce similar typhoon predictions, while the optimization achieved by the neural network algorithm was examined by evaluating the activation function, hidden layer composition, and dropouts. A learning and test dataset was constructed from the available digital data of one typhoon that affected Korea throughout the record period (1951-2018). As a result of neural network optimization, assessments showed a higher degree of forecast accuracy.

• 한국지구과학회지
• /
• 제39권1호
• /
• pp.1-22
• /
• 2018

Eight different data sets are examined in order to gain insight into the surface heat flux traits of the East Asian marginal seas. In the case of solar radiation of the East Sea (Japan Sea), Coordinated Ocean-ice Reference Experiments ver. 2 (CORE2) and the Objectively Analyzed Air-Sea Fluxes (OAFlux) are similar to the observed data at meteorological stations. A combination is sought by averaging these as well as the Climate Forecast System Reanalysis (CFSR) and the National Centers for Environmental Prediction (NCEP)-1 data to acquire more accurate surface heat flux for the East Asian marginal seas. According to the Combination Data, the annual averages of net heat flux of the East Sea, Yellow Sea, and East China Sea are -61.84, -22.42, and $-97.54Wm^{-2}$, respectively. The Kuroshio area to the south of Japan and the southern East Sea were found to have the largest upward annual mean net heat flux during winter, at -460- -300 and at $-370--300Wm^{-2}$, respectively. The long-term fluctuation (1984-2004) of the net heat flux shows a trend of increasing transport of heat from the ocean into the atmosphere throughout the study area.

• 한국해안·해양공학회논문집
• /
• 제32권6호
• /
• pp.587-601
• /
• 2020

지역해양수치모델(ROMS)을 이용하여 동해 및 울릉도-독도 해역의 해양순환을 모의하였다. 동해 3 km 격자 수치모델과 HYCOM 9 km 격자 자료를 사용하여 울릉도 1 km 격자 수치모델, 울릉도-독도 300 m 격자 수치모델들을 서로 단방향 둥지격자화 기법으로 구축하였다. 그 과정에서 상위모델과는 다른 수심 자료 및 내·외삽 방법에 의해 나타날 수 있는 개방 경계자료의 왜곡에 대한 보정방법을 제시하였다. 구축한 시스템을 이용하여, 2018년 울릉도-독도 지역에서 수평해상도가 300 m인 초고해상도 해양순환 모의 결과를 산출하였다. 초고해상도 수치모델은 같은 조건임에도 불구하고 초기장 및 개방 경계자료에 따라 서로 다른 특징이 나타났다. 따라서 수치모델 결과를 인공위성 고도계 자료로 추정한 유속 자료 및 국립수산과학원의 수온 관측자료를 사용하여 비교 검증하였다. 검증결과 HYCOM 자료를 경계장으로 사용한 둥지격자기법 결과는 1 km 격자모델 보다 300 m 격자모델 결과에서 RMSE, Mean Bias, Pattern Correlation, Vector Correlation이 전반적으로 향상되었다. 그러나 동해 3 km 수치모델을 사용한 결과에서는 1 km 모델의 결과가 300 m 결과보다 우수하게 나타났다. 수온 수직단면도에서는 수평해상도가 고해상도일수록, 등온선의 골과 마루의 수직구조가 뚜렷해지는 경향이 나타났다. 또한 울릉도-독도 300 m 모델은 상위모델에서 재현되지 않았던 섬의 지형 효과에 따른 카르만 와열이 나타났다.

• 대기
• /
• 제24권1호
• /
• pp.39-48
• /
• 2014

This study provides a comparative analysis of cloud top heights observed by a Ka-band cloud radar and the Communication, Ocean and Meteorological Satellite (COMS) at Boseong National Center for Intensive Observation of severe weather (NCIO) from May 25, 2013 (1600 UTC) to May 27. The rainfall duration is defined as the period of rainfall from start to finish, and the no rainfall duration is defined as the period other than the rainfall duration. As a result of the comparative analysis, the cloud top heights observed by the cloud radar have been estimated to be lower than that observed by the COMS for the rainfall duration due to the signal attenuation caused by raindrops. The stronger rainfall intensity gets, the more the difference grows. On the other hand, the cloud top heights observed by the cloud radar have been relatively similar to that observed by the COMS for the no rainfall duration. In this case, the cloud radar can effectively detect cloud top heights within the range of its observation. The COMS indicates the cloud top heights lower than the actual ones due to the upper thin clouds under the influence of ground surface temperature. As a result, the cloud radar can be useful in detecting cloud top heights when there are no precipitation events. The COMS data can be used to correct the cloud top heights when the radar gets beyond the valid range of observation or there are precipitation events.