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New kinetic equations and their modelling for wind wave forecasting.

风浪预报的新动力学方程及其建模。

基本信息

批准号：
NE/I01229X/1
负责人：
Victor Shrira
金额：
$ 38.01万
依托单位：
Keele University
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2011
资助国家：
英国
起止时间：
2011 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=NE%2FI01229X%2F1
关键词：
New kinetic equations their modelling

项目摘要

Wind waves are a key link in the feedback loop of ocean/atmosphere interaction. The quality of wind wave modelling directly affects the quality of weather forecasting and the accuracy of description of all processes at the air/water interface, since waves control fluxes of momentum, gas and heat exchange. Better wind wave modelling, especially of 'rogue' waves, is literally vital for reliability of growing shipping and offshore activities. At present all wave forecasting and modelling is based on numerical integration of the kinetic equation (KE), which is also referred to as the Hasselmann equation. The equation takes into account wind input, dissipation and interaction between waves of different scales and directions and describes the slow evolution of wind wave spectra in time and space. The interaction term, usually denoted as Snl, is dominant for energy carrying waves. The expression for Snl has not changed for half a century. Now the improved quality of observations and data input for wave modelling made it impossible to ignore the situations where the discrepancy between the KE based models and observations could not be bridged by any means. The following fundamental shortcomings of the modelling based upon the existing kinetic equation became apparent: (i) By construction, the KE cannot describe reaction of wave fields to rapid perturbations (e.g. abrupt changes of wind, wind gusts, sharp boundaries, etc). (ii) The KE based models can predict evolution of wave spectra only, while it is highly desirable to model the evolution of the wave height probability density function, or, more precisely, its departure from the Gaussian distribution. This, in particular, is badly needed for forecasting rogue waves, but also for assessing the validity of the KE based models. The KE itself 'does not know' when it ceases to be applicable. To address these shortcomings, the following radical ideas have been put forward very recently by the authors. New generalised kinetic equations have been derived from first principles by lifting two most restrictive assumptions: proximity of the wave field to equilibrium, and the oversimplification in taking into account the wave field departure from Gaussianity. Crucially, it was also discovered by the authors that for a typical wind waves it is possible to reconstruct evolution of probability density function once the spectrum is found. The proposal aims at creating a new numerical and conceptual framework for the study of wind wave evolution, by elaborating the above ideas and developing a new way of wind wave modelling based on the novel expression for Snl, derived from first principles. The purpose of this proposal is to create a numerical tool (robust parallel code) for solving the new kinetic equations and then to use this tool to address outstanding questions of wave field evolution. In developing the code, we will be greatly helped by the direct numerical simulation (DNS) algorithm developed by the authors for the simulation of long time evolution of wave field. The algorithm will be used for the validation of the new code. With the help of the new tool, we will delineate the situations where the standard KE is indeed valid and where it ceases to be applicable, and will investigate the regimes of wave evolution well beyond the limits of its applicability (e.g. gusty wind). We will model the evolution of wave field departure from Gaussianity, which, in particular, will make possible to assess probability of freak waves. We will formulate 'practical' parameterisations and recommendations for wave forecasting. This project aims to revolutionise wind wave modelling and forecasting. The new approach we propose is better suited to parallelisation of simulations and increase of power of computers, eventually it will replace the existing algorithms of calculating Snl. It will produce not only a more accurate description of reality, it has the potential to do it faster.

风波是海洋与大气相互作用反馈回路中的关键环节。风波模拟的质量直接影响天气预报的质量和对空气/水界面上所有过程描述的准确性，因为风波控制动量、气体和热交换的通量。更好的风浪建模，特别是“流氓”风浪的建模，对于日益增长的航运和海上活动的可靠性至关重要。目前，所有的波浪预报和建模都是基于动力学方程（KE）的数值积分，也称为哈塞曼方程。方程考虑了风的输入、耗散和不同尺度、不同方向波浪之间的相互作用，描述了风波谱在时间和空间上的缓慢演变。相互作用项，通常记为Snl，在带能波中占主导地位。半个世纪以来，Snl的表达一直没有改变。现在，观测质量的提高和波浪建模数据的输入使得不能忽视基于KE的模型与观测之间的差异无法通过任何手段弥合的情况。基于现有动力学方程的建模的以下基本缺陷变得明显：(i)通过构造，KE不能描述波场对快速扰动（例如风的突变、阵风、尖锐边界等）的反应。（ii）基于KE的模型只能预测波谱的演化，而波高概率密度函数的演化，或者更准确地说，波高概率密度函数偏离高斯分布的演化是非常理想的模型。特别是，这对于预测异常浪是非常需要的，而且对于评估基于KE模型的有效性也是非常需要的。KE本身“不知道”它何时不再适用。为了解决这些缺点，作者最近提出了以下激进的观点。新的广义动力学方程已经从第一性原理中推导出来，取消了两个最严格的假设：波场接近平衡，以及考虑波场偏离高斯性时的过度简化。至关重要的是，作者还发现，对于一个典型的风浪，一旦找到了频谱，就有可能重建概率密度函数的演变。该提案旨在通过阐述上述思想，并基于基于第一原理的新颖Snl表达式开发一种新的风波模拟方法，为研究风波演变建立一个新的数值和概念框架。本提案的目的是创建一个数值工具（鲁棒并行代码）来求解新的动力学方程，然后使用这个工具来解决波场演化的突出问题。在开发代码时，作者开发的用于模拟波场长时间演化的直接数值模拟（DNS）算法将对我们有很大的帮助。该算法将用于新代码的验证。在新工具的帮助下，我们将描述标准KE确实有效和不再适用的情况，并将研究远远超出其适用性限制的波浪演变机制（例如阵风）。我们将对波场偏离高斯性的演化进行建模，特别是，这将使评估异常波的概率成为可能。我们将为海浪预报制定“实用的”参数化和建议。这个项目旨在革新风浪建模和预报。我们提出的新方法更适合于模拟的并行化和计算机能力的提高，最终将取代现有的计算信噪比的算法。它不仅能更准确地描述现实，而且有可能更快地做到这一点。