Comparative evaluation of the operational red-tide models

DC Field Value Language
dc.contributor.author 조홍연 -
dc.date.accessioned 2020-07-15T21:53:13Z -
dc.date.available 2020-07-15T21:53:13Z -
dc.date.created 2020-02-11 -
dc.date.issued 2016-04-21 -
dc.identifier.uri https://sciwatch.kiost.ac.kr/handle/2020.kiost/24873 -
dc.description.abstract Operational red-tide model (a.k.a. algal bloom model) can be described as the forecasting system of the red-tide (phytoplankton, algal species) parameters, such as spatial and temporal chlorophyll-a concentration, phytoplankton cell numbers, organic carbon concentrations, and so on. The model should be fully supported by the operational oceanographic system, because it requires many kinds of input data sets to simulate the red-tide parameters. In this study, the operational forecast models are selected and compared in terms of the essential data sets. These models are characterized by the model application regions, such as the Gulf of Mexico, the Gulf of Maine, the Mediterranean Sea, the North Sea, and the Baltic Sea. These models are also closely related to the Regional Ocean Observing System., organic carbon concentrations, and so on. The model should be fully supported by the operational oceanographic system, because it requires many kinds of input data sets to simulate the red-tide parameters. In this study, the operational forecast models are selected and compared in terms of the essential data sets. These models are characterized by the model application regions, such as the Gulf of Mexico, the Gulf of Maine, the Mediterranean Sea, the North Sea, and the Baltic Sea. These models are also closely related to the Regional Ocean Observing System. -
dc.description.uri 1 -
dc.language English -
dc.publisher KIOST -
dc.relation.isPartOf 제7차 한중공동워크숍 -
dc.title Comparative evaluation of the operational red-tide models -
dc.type Conference -
dc.citation.conferencePlace KO -
dc.citation.endPage 54 -
dc.citation.startPage 53 -
dc.citation.title 제7차 한중공동워크숍 -
dc.contributor.alternativeName 조홍연 -
dc.identifier.bibliographicCitation 제7차 한중공동워크숍, pp.53 - 54 -
dc.description.journalClass 1 -
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Marine Digital Resources Department > Marine Bigdata & A.I. Center > 2. Conference Papers
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