一种新的风浪谱模型及其在高度计风速反演中的应用
摘要
风浪谱模型被广泛应用于海洋研究的诸多领域,例如海-气相互作用、上层海洋动力学、海浪预报、海洋微波遥感和海洋工程等。在风浪出现的一个很宽的频率范围,风浪谱可被分为大尺度的长波风浪谱(重力波)以及小尺度的短波谱(毛细重力波谱)。在高度计、微波散射计和微波辐射计的遥感机理研究中,全波数范围内的风浪谱模型扮演了不可缺少的角色。本文给出了一种新的全波数范围内的风浪谱模型,并将其应用到高度计风速反演中去,取得了较好的效果。
Liu等(2003)提出的深水风浪谱模型包括“风速”、“逆波龄”和“逆谱宽度”三个参数。依据该模型以及海上和实验实观测数据,本文作者发现了海上和实验室条件下,风速、逆波龄(反映波浪成长状态)和逆谱宽度三参数之间分别存在着统计关系。三参数统计关系式表明,影响风浪能量分布的“逆谱宽度”不是一个独立参数,它是由风速和逆波龄这两个最基本参数确定的。这样,三参数统计关系式连同Liu等(2003)的公式构成了一个新的风浪谱模型。在这个新模型中,逆波龄和风速两个基本参数确定了风浪谱的总能量水平、风浪谱的最大能量位置(表现为谱峰位置)和风浪能量分布的宽窄特征(表现为峰右侧高频波段谱的陡度)。
本文研究同时表明,依据实验室水槽数据获得的三参数统计关系式不同于依据海上现场观测数据获得的三参数统计关系式,在相同的风速和波龄条件下,实验室风浪谱的陡度不同于海上风浪谱的陡度,这也是海上风浪谱与实验室风浪谱的根本区别。
比较证实,由于考虑了波龄因子的影响,Liu等(2003)提出的风浪谱模型连同三参数统计关系式组成的新模型能够很好地符合不同成长状态下的海上观测数据和实验室水槽测量数据。根据新的风浪谱模型计算得到的谱宽度与乌克兰国家科学院获得的测量数据非常符合。此外,新的风浪谱模型能够很好地模拟美国海军实验室使用微波雷达获得的波面高度谱现场测量数据和其它现场测量数据。新的风浪谱模型不但有益于全面理解风速和逆波龄对风浪能量分布的影响,而且对于海洋微波遥感研究特别是判断海洋环境要素反演的不确定性具有重要意义。
依据粗糙海面电磁波镜面散射理论,将根据全波数范围内的谱模型计算的标准化雷达后向散射截面与TOPEX/Poseidon(T/P)高度计测得的雷达后向散射截面(Ku波段)进行比较,可以反演高度计风速。将反演获得的高度计风速与同步的浮标风速进行比较发现,在所选浮标附近海域,波龄因子对高度计风速反演存在较大影响。与目前T/P高度计风速反演业务化算法相比,考虑波龄因子影响后,根据谱模型反演获得的风速与浮标风速之间均方根误差和平均偏差更小。与20个浮标测量结果相比,根据新风浪谱模型反演获得的风速与浮标风速之间的均方根误差较目前高度计业务化算法减小了11%,偏差减小了21%。
以墨西哥湾同步高度计、浮标资料为例,定量研究了海浪成长状态对高度计风速反演的影响。同步的高度计风速和浮标风速比较显示,在墨西哥湾地区,海浪成长状态对高度计风速反演有较大影响。在考虑海浪成长状态影响的条件下,利用谱模型反演高度计风速,取得了较好的效果。由于波龄因子可以根据高度计测得有效波高以及业务化算法获得的风速得到,因此根据新风浪谱模型反演获得的风速具有广泛的适用性。
The wind wave spectrum models are widely used in various fields of ocean investigations, for example, ocean-atmosphere interaction, upper layer ocean dynamics, wave forcasting, ocean remote sensing and ocean engineering. Within the full wavenumber range, the wind wave spectrum can be divided into long wave spectrum (gravity spectrum) and short wave spectrum (gravity-capillary spectrum). They in particular play an important role in the study of the remote sensing theory concerning microwave scatterometers, radiometers and altimeters. In this thesis, a new wind wave spectrum model for full wavenumber range is proposed. Based on the new model, more accurate altimeter wind speeds are obtained.
The spectrum model of the wind waves for deep water proposed by Liu et al. (2003) contains three parameters: the wind speed, the inverse wave age and the inverse spectral width. Based on the deep water wave model proposed by Liu et al. (2003), statistical relationships among the wind speed, inverse wave age and inverse spectral width are derived for field data and laboratory data, respectively. With the statistical relationships and equations given by Liu et al. (2003), a new wind wave spectrum model for deep water is proposed in this study. In the new model, the total spectral energy level, the location of the maximum spectral energy (represented by location of spectral peak), and the width character of energy distribution (represented by the spectral steepness) at high frequencies located to the right of spectral peak of wind waves are all determined by the two basic parameters, i.e., the wind speed and the inverse wave age.
The statistical relationships also show that with the same wind speed and wave age, the steepness of the wind wave spectrum at high frequencies located to the right of the spectral peak for field case is different from that for laboratory case. This is the main difference between field wind wave spectrum and laboratory spectrum.
With the inverse spectral width, the new model is more appropriate to describe the real wind wave status. Compared with measurements in the Black Sea, the model calculated zeroth spectral moment m0 and the spectral width are in both good agreements with measured data. Furthermore, the new model can match elevation spectrum data obtained by four-frequency microwave radar and other field measurements fairly well. The new model can not only better describe and explain the influence of the wind speed and wave age on the energy distribution of developing wind waves generated in open ocean, but also it plays a significant role in the study of oceanic microwave remote sensing, especially for understanding the uncertainty of retrieved ocean environment variables.
Based on the specular reflection theory of electromagnetic waves at rough sea surface and the spectral model of wind waves with a wave age factor, the sea surface wind speeds are retrieved from the normalized radar backscatter cross section measured by TOPEX/Poseidon Ku-band altimeter using the mean square slope calculated from the spectral models of the wind waves and the gravity-capillary waves. The study shows the wave age factor has a significant influence on retrieving altimeter wind speeds. Compared with the empirical algorithm in operational use for altimeter winds retrieval, after the effects of wind age factor is included in the analytical algorithm, the root mean square difference and bias between retrieved altimeter wind speed from the analytical algorithm and buoy observations are 11% and 21% lower, respectively.
Effects of the wave state on altimeter wind speed retrieval are also investigated based on the observations in the Gulf of Mexico. The comparison between measurements from the altimeter and buoys shows that the wave state has significant effects on the altimeter wind speed retrieval. After considering the effects of the wave state, the altimeter winds are retrieved more accurately with a new wind wave spectrum model. The wave age factor which denotes the wave state can be calculated from altimeter measured H s and U 10 (from algorithm in operational use for TOPEX/Poseidon altimeter). Thus, the analytical algorithm proposed in this study has a comprehensive applicability.
Liu等(2003)提出的深水风浪谱模型包括“风速”、“逆波龄”和“逆谱宽度”三个参数。依据该模型以及海上和实验实观测数据,本文作者发现了海上和实验室条件下,风速、逆波龄(反映波浪成长状态)和逆谱宽度三参数之间分别存在着统计关系。三参数统计关系式表明,影响风浪能量分布的“逆谱宽度”不是一个独立参数,它是由风速和逆波龄这两个最基本参数确定的。这样,三参数统计关系式连同Liu等(2003)的公式构成了一个新的风浪谱模型。在这个新模型中,逆波龄和风速两个基本参数确定了风浪谱的总能量水平、风浪谱的最大能量位置(表现为谱峰位置)和风浪能量分布的宽窄特征(表现为峰右侧高频波段谱的陡度)。
本文研究同时表明,依据实验室水槽数据获得的三参数统计关系式不同于依据海上现场观测数据获得的三参数统计关系式,在相同的风速和波龄条件下,实验室风浪谱的陡度不同于海上风浪谱的陡度,这也是海上风浪谱与实验室风浪谱的根本区别。
比较证实,由于考虑了波龄因子的影响,Liu等(2003)提出的风浪谱模型连同三参数统计关系式组成的新模型能够很好地符合不同成长状态下的海上观测数据和实验室水槽测量数据。根据新的风浪谱模型计算得到的谱宽度与乌克兰国家科学院获得的测量数据非常符合。此外,新的风浪谱模型能够很好地模拟美国海军实验室使用微波雷达获得的波面高度谱现场测量数据和其它现场测量数据。新的风浪谱模型不但有益于全面理解风速和逆波龄对风浪能量分布的影响,而且对于海洋微波遥感研究特别是判断海洋环境要素反演的不确定性具有重要意义。
依据粗糙海面电磁波镜面散射理论,将根据全波数范围内的谱模型计算的标准化雷达后向散射截面与TOPEX/Poseidon(T/P)高度计测得的雷达后向散射截面(Ku波段)进行比较,可以反演高度计风速。将反演获得的高度计风速与同步的浮标风速进行比较发现,在所选浮标附近海域,波龄因子对高度计风速反演存在较大影响。与目前T/P高度计风速反演业务化算法相比,考虑波龄因子影响后,根据谱模型反演获得的风速与浮标风速之间均方根误差和平均偏差更小。与20个浮标测量结果相比,根据新风浪谱模型反演获得的风速与浮标风速之间的均方根误差较目前高度计业务化算法减小了11%,偏差减小了21%。
以墨西哥湾同步高度计、浮标资料为例,定量研究了海浪成长状态对高度计风速反演的影响。同步的高度计风速和浮标风速比较显示,在墨西哥湾地区,海浪成长状态对高度计风速反演有较大影响。在考虑海浪成长状态影响的条件下,利用谱模型反演高度计风速,取得了较好的效果。由于波龄因子可以根据高度计测得有效波高以及业务化算法获得的风速得到,因此根据新风浪谱模型反演获得的风速具有广泛的适用性。
The wind wave spectrum models are widely used in various fields of ocean investigations, for example, ocean-atmosphere interaction, upper layer ocean dynamics, wave forcasting, ocean remote sensing and ocean engineering. Within the full wavenumber range, the wind wave spectrum can be divided into long wave spectrum (gravity spectrum) and short wave spectrum (gravity-capillary spectrum). They in particular play an important role in the study of the remote sensing theory concerning microwave scatterometers, radiometers and altimeters. In this thesis, a new wind wave spectrum model for full wavenumber range is proposed. Based on the new model, more accurate altimeter wind speeds are obtained.
The spectrum model of the wind waves for deep water proposed by Liu et al. (2003) contains three parameters: the wind speed, the inverse wave age and the inverse spectral width. Based on the deep water wave model proposed by Liu et al. (2003), statistical relationships among the wind speed, inverse wave age and inverse spectral width are derived for field data and laboratory data, respectively. With the statistical relationships and equations given by Liu et al. (2003), a new wind wave spectrum model for deep water is proposed in this study. In the new model, the total spectral energy level, the location of the maximum spectral energy (represented by location of spectral peak), and the width character of energy distribution (represented by the spectral steepness) at high frequencies located to the right of spectral peak of wind waves are all determined by the two basic parameters, i.e., the wind speed and the inverse wave age.
The statistical relationships also show that with the same wind speed and wave age, the steepness of the wind wave spectrum at high frequencies located to the right of the spectral peak for field case is different from that for laboratory case. This is the main difference between field wind wave spectrum and laboratory spectrum.
With the inverse spectral width, the new model is more appropriate to describe the real wind wave status. Compared with measurements in the Black Sea, the model calculated zeroth spectral moment m0 and the spectral width are in both good agreements with measured data. Furthermore, the new model can match elevation spectrum data obtained by four-frequency microwave radar and other field measurements fairly well. The new model can not only better describe and explain the influence of the wind speed and wave age on the energy distribution of developing wind waves generated in open ocean, but also it plays a significant role in the study of oceanic microwave remote sensing, especially for understanding the uncertainty of retrieved ocean environment variables.
Based on the specular reflection theory of electromagnetic waves at rough sea surface and the spectral model of wind waves with a wave age factor, the sea surface wind speeds are retrieved from the normalized radar backscatter cross section measured by TOPEX/Poseidon Ku-band altimeter using the mean square slope calculated from the spectral models of the wind waves and the gravity-capillary waves. The study shows the wave age factor has a significant influence on retrieving altimeter wind speeds. Compared with the empirical algorithm in operational use for altimeter winds retrieval, after the effects of wind age factor is included in the analytical algorithm, the root mean square difference and bias between retrieved altimeter wind speed from the analytical algorithm and buoy observations are 11% and 21% lower, respectively.
Effects of the wave state on altimeter wind speed retrieval are also investigated based on the observations in the Gulf of Mexico. The comparison between measurements from the altimeter and buoys shows that the wave state has significant effects on the altimeter wind speed retrieval. After considering the effects of the wave state, the altimeter winds are retrieved more accurately with a new wind wave spectrum model. The wave age factor which denotes the wave state can be calculated from altimeter measured H s and U 10 (from algorithm in operational use for TOPEX/Poseidon altimeter). Thus, the analytical algorithm proposed in this study has a comprehensive applicability.
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