{"title":"Estimation of Significant Wave Heights Using Numerical and Neural Techniques and Comparison with Buoy and Satellite Observations","authors":"J. Vimala, G. Latha, R. Venkatesan","doi":"10.1260/1759-3131.5.4.223","DOIUrl":null,"url":null,"abstract":"Short term significant wave heights have been evaluated using the numerical WAM model and the results are compared with satellite (Jason-2) and moored buoy measurements. Additionally artificial neural network (ANN) is used to predict significant wave heights over a future time step and such predictions are also compared with corresponding satellite and buoy measurements. The observations from moored buoys monitored by India's National Institute of Ocean Technology for a period of about four and a half years at three locations in the Arabian Sea and three in Bay of Bengal covering the west as well as east coast of India are involved. The buoy recorded largest waves during the cyclonic condition, and this was confirmed at a location code named: BD11 by the satellite measurements as well as the WAM and ANN based evaluations. The evaluation accuracy reflected in the coefficient of correlation is found to be high in the Arabian Sea than the Bay of Bengal.","PeriodicalId":105024,"journal":{"name":"The International Journal of Ocean and Climate Systems","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The International Journal of Ocean and Climate Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1260/1759-3131.5.4.223","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
Short term significant wave heights have been evaluated using the numerical WAM model and the results are compared with satellite (Jason-2) and moored buoy measurements. Additionally artificial neural network (ANN) is used to predict significant wave heights over a future time step and such predictions are also compared with corresponding satellite and buoy measurements. The observations from moored buoys monitored by India's National Institute of Ocean Technology for a period of about four and a half years at three locations in the Arabian Sea and three in Bay of Bengal covering the west as well as east coast of India are involved. The buoy recorded largest waves during the cyclonic condition, and this was confirmed at a location code named: BD11 by the satellite measurements as well as the WAM and ANN based evaluations. The evaluation accuracy reflected in the coefficient of correlation is found to be high in the Arabian Sea than the Bay of Bengal.
使用数值WAM模型评估了短期有效浪高,并将结果与卫星(Jason-2)和系泊浮标测量结果进行了比较。此外,人工神经网络(ANN)用于预测未来时间步长的重要波高,并将这种预测与相应的卫星和浮标测量结果进行比较。印度国家海洋技术研究所(National Institute of Ocean Technology)在大约四年半的时间里,在阿拉伯海的三个地点和孟加拉湾的三个地点监测了系泊浮标的观测结果,覆盖了印度西海岸和东海岸。在气旋条件下,浮标记录了最大的波浪,这在一个代号为BD11的位置得到了卫星测量以及基于WAM和ANN的评估的证实。相关系数所反映的评价精度在阿拉伯海比孟加拉湾高。