Real time wave forecasting using wind time history and numerical model |
| |
| Authors: | Pooja Jain MC Deo G Latha V Rajendran |
| |
| Institution: | 1. Department of Civil Engineering, Indian Institute of Technology Bombay, Powai, Mumbai 400 076, Maharashtra, India;2. National Institute of Ocean Technology, Chennai, India;1. College of Engineering, Ocean University of China, 238 Songling Road, Qingdao, 266100, China;2. Shandong Province Key Laboratory of Ocean Engineering, Ocean University of China, 238 Songling Road, Qingdao, 266100, China;1. Naval Physical and Oceanographic Laboratory, Thrikkakara P.O., Kochi 682 021, Kerala, India;2. Department of Ocean Engineering & Naval Architecture, Indian Institute of Technology Kharagpur, Kharagpur 721 302, West Bengal, India;3. Department of Physical Oceanography, Cochin University of Science and Technology, Kochi 682 016, Kerala, India;1. Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA;2. Glosten Associates, Seattle, WA 98101, USA;3. GE Renewable Energy, Richmond, VA 23237, USA;1. International Centre for Theoretical Sciences, Bengaluru, 560089, India;2. Department of Mathematics, Seattle University, Seattle, WA 98122, United States;3. Department of Mathematics, Pennsylvania State University, University Park, PA 16802, United States;4. Department of Applied Mathematics, University of Washington, Seattle, WA 98195, United States |
| |
| Abstract: | Operational activities in the ocean like planning for structural repairs or fishing expeditions require real time prediction of waves over typical time duration of say a few hours. Such predictions can be made by using a numerical model or a time series model employing continuously recorded waves. This paper presents another option to do so and it is based on a different time series approach in which the input is in the form of preceding wind speed and wind direction observations. This would be useful for those stations where the costly wave buoys are not deployed and instead only meteorological buoys measuring wind are moored. The technique employs alternative artificial intelligence approaches of an artificial neural network (ANN), genetic programming (GP) and model tree (MT) to carry out the time series modeling of wind to obtain waves. Wind observations at four offshore sites along the east coast of India were used. For calibration purpose the wave data was generated using a numerical model. The predicted waves obtained using the proposed time series models when compared with the numerically generated waves showed good resemblance in terms of the selected error criteria. Large differences across the chosen techniques of ANN, GP, MT were not noticed. Wave hindcasting at the same time step and the predictions over shorter lead times were better than the predictions over longer lead times. The proposed method is a cost effective and convenient option when a site-specific information is desired. |
| |
| Keywords: | |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
