{"title":"近岸动态环境中光学变率的预测","authors":"Grace Chang , Craig Jones , Michael Twardowski","doi":"10.1016/j.mio.2013.12.002","DOIUrl":null,"url":null,"abstract":"<div><p>Forecasting Optics REaltime in Shallow Energetic Environments (FORESEE) was developed for predictions of underwater visibility in dynamic surf zone environments. FORESEE employs key measurements of physical forcing and beam attenuation coefficient (beam c) and numerical wave and hydrodynamic models to: (1) generate predictions of energy variation, (2) relate energy characteristics to the optical property of interest, beam c, and (3) produce 24-hr forecast maps of spatially resolved visibility conditions at a site of interest. FORESEE beam c prediction performance was very good using site-specific data collected in Waimanalo, Hawaii (average root mean squared error of 0.38 m<sup>−1</sup>). Predictions of probability of object detection (P<sub><em>d</em></sub>) were on average within 75% accuracy for 2-m diver visibility. Differences between modeled and measured P<sub><em>d</em></sub> may have been affected by a phytoplankton bloom that was observed during field data collection. The addition of a growth term and a bottom-type term to the model could account for biological processes and differing bottom types in nearshore regions. Further improvements could also be made with more accurate model boundary conditions.</p></div>","PeriodicalId":100922,"journal":{"name":"Methods in Oceanography","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2013-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.mio.2013.12.002","citationCount":"6","resultStr":"{\"title\":\"Prediction of optical variability in dynamic nearshore environments\",\"authors\":\"Grace Chang , Craig Jones , Michael Twardowski\",\"doi\":\"10.1016/j.mio.2013.12.002\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Forecasting Optics REaltime in Shallow Energetic Environments (FORESEE) was developed for predictions of underwater visibility in dynamic surf zone environments. FORESEE employs key measurements of physical forcing and beam attenuation coefficient (beam c) and numerical wave and hydrodynamic models to: (1) generate predictions of energy variation, (2) relate energy characteristics to the optical property of interest, beam c, and (3) produce 24-hr forecast maps of spatially resolved visibility conditions at a site of interest. FORESEE beam c prediction performance was very good using site-specific data collected in Waimanalo, Hawaii (average root mean squared error of 0.38 m<sup>−1</sup>). Predictions of probability of object detection (P<sub><em>d</em></sub>) were on average within 75% accuracy for 2-m diver visibility. Differences between modeled and measured P<sub><em>d</em></sub> may have been affected by a phytoplankton bloom that was observed during field data collection. The addition of a growth term and a bottom-type term to the model could account for biological processes and differing bottom types in nearshore regions. Further improvements could also be made with more accurate model boundary conditions.</p></div>\",\"PeriodicalId\":100922,\"journal\":{\"name\":\"Methods in Oceanography\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1016/j.mio.2013.12.002\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Methods in Oceanography\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2211122013000492\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Methods in Oceanography","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2211122013000492","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Prediction of optical variability in dynamic nearshore environments
Forecasting Optics REaltime in Shallow Energetic Environments (FORESEE) was developed for predictions of underwater visibility in dynamic surf zone environments. FORESEE employs key measurements of physical forcing and beam attenuation coefficient (beam c) and numerical wave and hydrodynamic models to: (1) generate predictions of energy variation, (2) relate energy characteristics to the optical property of interest, beam c, and (3) produce 24-hr forecast maps of spatially resolved visibility conditions at a site of interest. FORESEE beam c prediction performance was very good using site-specific data collected in Waimanalo, Hawaii (average root mean squared error of 0.38 m−1). Predictions of probability of object detection (Pd) were on average within 75% accuracy for 2-m diver visibility. Differences between modeled and measured Pd may have been affected by a phytoplankton bloom that was observed during field data collection. The addition of a growth term and a bottom-type term to the model could account for biological processes and differing bottom types in nearshore regions. Further improvements could also be made with more accurate model boundary conditions.