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Modelling wind waves. What lies beyond the significant wave height?

模拟风浪。

基本信息

批准号：
NE/S011420/1
负责人：
Victor Shrira
金额：
$ 46.55万
依托单位：
Keele University
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2019
资助国家：
英国
起止时间：
2019 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=NE%2FS011420%2F1
关键词：
Modelling wind waves.What lies

项目摘要

Modelling random wind waves in the ocean is a fundamental problem with wide ranging applications of great significance. Proper wave modelling is crucial for navigation, fisheries, offshore industries, managing of coastal environments; on the other hand, being integrated into the weather and climate models it is fundamental for air-sea interaction. Crucially, all the ocean remote sensing in various bands of electromagnetic spectrum (including the satellite, airborne, on-shore and ship based devices) relies on knowledge of wind wave field characteristics. Improving this knowledge would increase remote sensing capabilities.Currently, all wave modelling is based on the Hasselmann kinetic equation, aka KE, and its modifications. Wind waves are random, and the KE describes evolution of ensemble averaged quantities caused by energy exchange between waves of different scales and directions owing to nonlinear resonant interactions, as well as energy input from wind and dissipation. The part concerned with the redistribution of energy between spectral components, S_nl, was considered to be firmly established for many decades, since it was derived from first principles in the same way as in other branches of physics.The overall situation in wave modelling cannot be considered satisfactory. Although the KE does capture the behaviour of bulk characteristics (peak frequency, significant wave height) there are unexplained major systematic discrepancies between the KE modelling and the high quality observations: the observed spectra are much wider and the magnitude of the spectral peak could be considerably smaller.The essence and main novelty of the project is in applying original direct numerical simulations algorithm (DNS-ZE) to analyse high quality data: unique observations off the Mexican coast by Romero & Melville (the Tehuantepec experiment) and data from observations by D.Hauser obtained using airborne and satellite scatterometers (KuROS and SWIM of CFOSAT). The DNS-ZE is an algorithm based on integration of a weakly nonlinear reduction of the Euler equations in nonlinear canonical variables. Currently it is the only DNS code able to perform simulations of wave evolution over several hundred kilometers. The simulations with the DNS-ZE showed excellent agreement with the observations and major discrepancies with the KE predictions.The proposal aims to utilise the unique opportunities opened by synergy of the DNS-ZE algorithm and new high quality datasets (revisited Tehuantepec observations and processed KuROS and SWIM data) and to address the following key problems:(i) To show that for various wave evolution scenarios supported by high quality data, the DNS-ZE indeed faithfully captures the evolution.(ii) To retrieve the source functions (wind input and dissipation) for various steady wind conditions.(iii) To quantify how wrong are the KE based predictions, to examine the specific implications sensitive to the shape of the spectra, e.g. for evolution of probability of freak waves, wave induced mixing in the upper ocean.(iv) To advance in finding the cause of the KE failure.The realisation of this project would change radically the present understanding of the accuracy of wave modelling and the serious limitations of the existing models. Advance in finding the cause of the KE failure would be a breakthrough in understanding of not only wind waves, but all kind of random nonlinear waves in fluids and plasmas.

海洋中随机风浪的模拟是一个具有广泛应用意义的基本问题。正确的波浪建模对于航海、渔业、近海工业、沿海环境管理至关重要;另一方面，将其纳入天气和气候模型对于海气相互作用至关重要。至关重要的是，所有的海洋遥感在电磁频谱的各个波段（包括卫星，机载，岸上和船舶为基础的设备）依赖于风浪场特性的知识。目前，所有的波浪建模都是基于Hasselmann动力学方程（也称为KE）及其修正。风浪是随机的，KE描述了由于非线性共振相互作用，以及风和耗散的能量输入，不同尺度和方向的波浪之间的能量交换所引起的系综平均量的演变。关于谱分量之间能量再分配的部分，S_nl，几十年来被认为是牢固地建立起来的，因为它和物理学的其他分支一样，是从第一性原理导出的，波动模拟的总体情况不能被认为是令人满意的。尽管KE确实捕捉到了本体特性的行为，（峰值频率、有效波高）KE模型与高质量观测之间存在无法解释的重大系统性差异：观测到的谱宽得多，谱峰的幅度可以小得多。该项目的本质和主要新奇在于应用了原始的直接数值模拟算法（DNS-ZE）。分析高质量的数据：Romero和梅尔维尔在墨西哥海岸进行的独特观测（特万特佩克实验）和D.豪瑟利用机载和卫星散射仪（KuROS和CFOSAT的SWIM）获得的观测数据。DNS-ZE是一种基于非线性正则变量的欧拉方程的弱非线性约化的积分算法。目前，它是唯一一个能够模拟数百公里以上波浪演变的DNS代码。DNS-ZE的模拟结果与观测结果非常吻合，但与KE的预测结果存在较大差异。该提案旨在利用DNS-ZE算法和新的高质量数据集（重新访问的特万特佩克观测数据和处理后的KuROS和SWIM数据）的协同作用所带来的独特机会，并解决以下关键问题：（i）为了表明，对于高质量数据支持的各种波浪演变情景，DNS-ZE确实忠实地捕捉了演变。(ii)在不同的稳定风况下，反演源函数（风输入和耗散）。(iii)为了量化基于KE的预测有多错误，为了检查对谱的形状敏感的具体含义，例如，对于反常波的概率的演变，在上层海洋中的波诱导混合。(iv)推进寻找KE故障的原因。该项目的实现将从根本上改变目前对波浪建模准确性的理解和现有模型的严重局限性。对KE失效原因的研究进展不仅是对风浪，而且是对流体和等离子体中各种随机非线性波认识的突破。