• Title/Summary/Keyword: operational oceanographic

Search Result 16, Processing Time 0.018 seconds

Comparison of Multi-Satellite Sea Surface Temperatures and In-situ Temperatures from Ieodo Ocean Research Station (이어도 해양과학기지 관측 수온과 위성 해수면온도 합성장 자료와의 비교)

  • Woo, Hye-Jin;Park, Kyung-Ae;Choi, Do-Young;Byun, Do-Seung;Jeong, Kwang-Yeong;Lee, Eun-Il
    • Journal of the Korean earth science society
    • /
    • v.40 no.6
    • /
    • pp.613-623
    • /
    • 2019
  • Over the past decades, daily sea surface temperature (SST) composite data have been produced using periodically and extensively observed satellite SST data, and have been used for a variety of purposes, including climate change monitoring and oceanic and atmospheric forecasting. In this study, we evaluated the accuracy and analyzed the error characteristic of the SST composite data in the sea around the Korean Peninsula for optimal utilization in the regional seas. We evaluated the four types of multi-satellite SST composite data including OSTIA (Operational Sea Surface Temperature and Sea Ice Analysis), OISST (Optimum Interpolation Sea Surface Temperature), CMC (Canadian Meteorological Centre) SST, and MURSST (Multi-scale Ultra-high Resolution Sea Surface Temperature) collected from January 2016 to December 2016 by using in-situ temperature data measured from the Ieodo Ocean Research Station (IORS). Each SST composite data showed biases of the minimum of 0.12℃ (OISST) and the maximum of 0.55℃ (MURSST) and root mean square errors (RMSE) of the minimum of 0.77℃ (CMC SST) and the maximum of 0.96℃ (MURSST) for the in-situ temperature measurements from the IORS. Inter-comparison between the SST composite fields exhibited biases of -0.38-0.38℃ and RMSE of 0.55-0.82℃. The OSTIA and CMC SST data showed the smallest error while the OISST and MURSST data showed the most obvious error. The results of comparing time series by extracting the SST data at the closest point to the IORS showed that there was an apparent seasonal variation not only in the in-situ temperature from the IORS but also in all the SST composite data. In spring, however, SST composite data tended to be overestimated compared to the in-situ temperature observed from the IORS.

The Comparison of Thermal Infrared Satellite Observation for Plume Assessment of Thermal Discharge (온배수 확산 평가를 위한 열적외선 위성관측 비교)

  • Jeong, Jong-Chul
    • Journal of Environmental Impact Assessment
    • /
    • v.24 no.4
    • /
    • pp.367-374
    • /
    • 2015
  • To examine the effect of thermal discharge from nuclear power plants, Sea Surface Temperature (SST) is one of the most important variables measured by satellite remote sensing. However, the study was not much comparison of field data and satellite SST from operational Landsat 8 Thermal Infrared Sensor(TIRS) and Landsat 7 ETM+. The Landsat 8 TIRS have 2 spilt Thermal Infrared channels but ETM+ uses one channel for extracting of SST. In spite of that this research carried out that Landsat 7 ETM+ have more profitable for correction of SST than Landsat 8 TIRS. The used 15 Landsat 7 and 8 Thermal Infrared data of path/row 114-36 were processed by SST algorithm of ENVI and IDL. The in-situ SST data from KHOA(Korea Hydrographic and Oceanographic Administration) compared with satellite SST and the accuracy of extracted SST were assessed by each field sites in-situ point data with time series satellite SST.

Goal, Structure, and Recent Development of the GLOBEC Programme (GLOBEC 프로그램의 목적, 운영체계 및 최근의 동향에 대하여)

  • Kim, Su-Am
    • The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
    • /
    • v.5 no.1
    • /
    • pp.10-15
    • /
    • 2000
  • Goals, research direction, and operational structure of the Global Ocean Ecosystem Dynamics (GLOBEC), which is co-sponsored by the Scientific Committee on Oceanic Research (SCOR) and the Intergovemmental Oceanographic Commission (IOC), are described. Following the Joint Global Ocean Flux Study (JGOFS) activities on the lower trophic level in ecosystem during 1980s-90s, scientists have considered the responses of the mid and higher trophic levels to the environmental or climate change. The scientific steering committee of the GLOBEC published the implementation plan in 1999, and the IGBP will support the GLOBEC as one of its core projects for 10 years. The GLOBEC programme has four major components: the research foci, framework activities, regional programmes, and integrating activity. The core of GLOBEC research is the four research foci: retrospective analyses, process studies, predictive and modelling capabilities, and feedbacks. Currently, four regional programmes have been undergoing in the world ocean: Southern Ocean GLOBEC (SO-GLOBEC), Small Pelagic Fishes and Climate Changes (SPACC), Cod and Climate Change (CCC), and Climate Change and Carrying Capacity (CCCC). Also, national GLOBEC programmes were already established in 9 nations.

  • PDF

Optimization of SWAN Wave Model to Improve the Accuracy of Winter Storm Wave Prediction in the East Sea

  • Son, Bongkyo;Do, Kideok
    • Journal of Ocean Engineering and Technology
    • /
    • v.35 no.4
    • /
    • pp.273-286
    • /
    • 2021
  • In recent years, as human casualties and property damage caused by hazardous waves have increased in the East Sea, precise wave prediction skills have become necessary. In this study, the Simulating WAves Nearshore (SWAN) third-generation numerical wave model was calibrated and optimized to enhance the accuracy of winter storm wave prediction in the East Sea. We used Source Term 6 (ST6) and physical observations from a large-scale experiment conducted in Australia and compared its results to Komen's formula, a default in SWAN. As input wind data, we used Korean Meteorological Agency's (KMA's) operational meteorological model called Regional Data Assimilation and Prediction System (RDAPS), the European Centre for Medium Range Weather Forecasts' newest 5th generation re-analysis data (ERA5), and Japanese Meteorological Agency's (JMA's) meso-scale forecasting data. We analyzed the accuracy of each model's results by comparing them to observation data. For quantitative analysis and assessment, the observed wave data for 6 locations from KMA and Korea Hydrographic and Oceanographic Agency (KHOA) were used, and statistical analysis was conducted to assess model accuracy. As a result, ST6 models had a smaller root mean square error and higher correlation coefficient than the default model in significant wave height prediction. However, for peak wave period simulation, the results were incoherent among each model and location. In simulations with different wind data, the simulation using ERA5 for input wind datashowed the most accurate results overall but underestimated the wave height in predicting high wave events compared to the simulation using RDAPS and JMA meso-scale model. In addition, it showed that the spatial resolution of wind plays a more significant role in predicting high wave events. Nevertheless, the numerical model optimized in this study highlighted some limitations in predicting high waves that rise rapidly in time caused by meteorological events. This suggests that further research is necessary to enhance the accuracy of wave prediction in various climate conditions, such as extreme weather.

Korean Ocean Forecasting System: Present and Future (한국의 해양예측, 오늘과 내일)

  • Kim, Young Ho;Choi, Byoung-Ju;Lee, Jun-Soo;Byun, Do-Seong;Kang, Kiryong;Kim, Young-Gyu;Cho, Yang-Ki
    • The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
    • /
    • v.18 no.2
    • /
    • pp.89-103
    • /
    • 2013
  • National demands for the ocean forecasting system have been increased to support economic activity and national safety including search and rescue, maritime defense, fisheries, port management, leisure activities and marine transportation. Further, the ocean forecasting has been regarded as one of the key components to improve the weather and climate forecasting. Due to the national demands as well as improvement of the technology, the ocean forecasting systems have been established among advanced countries since late 1990. Global Ocean Data Assimilation Experiment (GODAE) significantly contributed to the achievement and world-wide spreading of ocean forecasting systems. Four stages of GODAE were summarized. Goal, vision, development history and research on ocean forecasting system of the advanced countries such as USA, France, UK, Italy, Norway, Australia, Japan, China, who operationally use the systems, were examined and compared. Strategies of the successfully established ocean forecasting systems can be summarized as follows: First, concentration of the national ability is required to establish successful operational ocean forecasting system. Second, newly developed technologies were shared with other countries and they achieved mutual and cooperative development through the international program. Third, each participating organization has devoted to its own task according to its role. In Korean society, demands on the ocean forecasting system have been also extended. Present status on development of the ocean forecasting system and long-term plan of KMA (Korea Meteorological Administration), KHOA (Korea Hydrographic and Oceanographic Administration), NFRDI (National Fisheries Research & Development Institute), ADD (Agency for Defense Development) were surveyed. From the history of the pre-established systems in other countries, the cooperation among the relevant Korean organizations is essential to establish the accurate and successful ocean forecasting system, and they can form a consortium. Through the cooperation, we can (1) set up high-quality ocean forecasting models and systems, (2) efficiently invest and distribute financial resources without duplicate investment, (3) overcome lack of manpower for the development. At present stage, it is strongly requested to concentrate national resources on developing a large-scale operational Korea Ocean Forecasting System which can produce open boundary and initial conditions for local ocean and climate forecasting models. Once the system is established, each organization can modify the system for its own specialized purpose. In addition, we can contribute to the international ocean prediction community.

Development the Geostationary Ocean Color Imager (GOCI) Data Processing System (GDPS) (정지궤도 해색탑재체(GOCI) 해양자료처리시스템(GDPS)의 개발)

  • Han, Hee-Jeong;Ryu, Joo-Hyung;Ahn, Yu-Hwan
    • Korean Journal of Remote Sensing
    • /
    • v.26 no.2
    • /
    • pp.239-249
    • /
    • 2010
  • The Geostationary Ocean Color Imager (GOCI) data-processing system (GDPS), which is a software system for satellite data processing and analysis of the first geostationary ocean color observation satellite, has been developed concurrently with the development of th satellite. The GDPS has functions to generate level 2 and 3 oceanographic analytical data, from level 1B data that comprise the total radiance information, by programming a specialized atmospheric algorithm and oceanic analytical algorithms to the software module. The GDPS will be a multiversion system not only as a standard Korea Ocean Satellite Center(KOSC) operational system, but also as a basic GOCI data-processing system for researchers and other users. Additionally, the GDPS will be used to make the GOCI images available for distribution by satellite network, to calculate the lookup table for radiometric calibration coefficients, to divide/mosaic several region images, to analyze time-series satellite data. the developed GDPS system has satisfied the user requirement to complete data production within 30 minutes. This system is expected to be able to be an excellent tool for monitoring both long-term and short-term changes of ocean environmental characteristics.