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海表皮肤层厚度模型与应用
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摘要
海表皮肤层是海气边界层的重要组成部分和上层海洋温盐气剖面的上边界,也是海表温度(SST)和海表盐度(SSS)卫星遥感数据的可能误差源之一。海表皮肤层研究是海气交互作用的重要课题,对于提高遥感数据精度具有重要意义。
     本文首先引入Batchelor微尺度概念,提出了一个对海表风场和热通量场响应、用以计算海表温度、盐度和气体浓度皮肤层厚度的模型。据此认为任意两个皮肤层厚度之比可用对应物理量分子扩散率之比的平方根表示。模型对冷温层和高盐层效应的量化在理论上更为合理并符合实测资料。根据本厚度模型,可计算低风速情况下、海表风速和散热通量共同作用下的海气界面气体交换速率。
     利用OAFlux项目及ISCCP遥感实测的全球海表风场及热通量场等资料,基于皮肤层统一厚度模型模拟了全球海表面高盐层和冷温层的厚度及其上下表面物理量差异。结果显示,夜间无太阳热辐射情况下,全球高盐层和冷温层平均厚度分别约为65μm和1mm。全球平均冷温层上下表面温差均值为0.2℃左右,高盐层上下表面盐度差均值约为0.09psu。由高盐层厚度和上下表面盐度差模拟结果认为,高盐层在全球范围内可能引起的遥感海表盐度误差仅可达0.02psu。
     全球皮肤层理查森数分布显示,在大部分海域,皮肤层演变是由海表风应力引起的受迫对流控制。由于冷温层相比于高盐层更厚且更早达到不稳定,皮肤层内的自由对流不稳定性基本被冷温层作用控制。本文还对比了冷温层和高盐层分别对应的热通量场,分析了两皮肤层全球分布形态的相似性及其原因。
     考虑到遥感测量海水表面温度及表面盐度时需用海表以下实测温盐资料加以校正,但长时间大范围进行海洋表层海水垂向温盐剖面野外观测非常困难,建立经有限资料验证的混合层数值模型,用于模拟受太阳热辐射影响的表层海水温盐剖面演变十分重要。因此文章利用美国加利福尼亚湾三组船载光学实验的气象及海温资料,基于皮肤层效应和太阳热辐射的共同作用,结合混合层动力模式,建立了一个整合数值模型,用于模拟海表以下20m深度范围内的温盐剖面演变。本模型通过实时计算冷温层厚度合理加密了表层网格,并通过冷温层和高盐层作用的定量计算使数值模型更准确地估计海表的热量交换和盐度变化。计算结果与野外实测海温资料对比表明,模型能准确描述海温剖面的演变趋势。在近海表20cm深度内,特别是与遥感SST相关的近海表1cm深度内,模拟结果优于无本皮肤层模型的计算结果。文章也进一步分析了误差及其产生原因。
Sea surface skin layer is an important component of the air-sea interface boundary layer and the upper boundary of the profiles of temperature, salinity, and gas concentration in the sea. It is also a possible error source for remote sensing of sea surface temperature (SST) and sea surface salinity (SSS). The research on sea surface skin layer is a crucial subject for the research on air-sea interaction and would be meaningful to enhance the accuracy of sea surface remote sensing.
     By introducing Batchelor micro-scale, a unified thickness model for skin layers is developed to determine the depths of various ocean skin layers with same model parameters. In this model, the thickness would response to the both sea surface wind speeds and heat fluxes. The thickness ratio of each skin layers is the square root of the ratio of their diffusion rates. The cool skin and haline skin layer effects can be quantified reasonably and more accord with observed data. Based on this unified thickness model, air-sea gas transfer velocity is a function of both wind speeds and heat flux under low winds.
     Global distributions of haline skin layer and cool skin layer are then simulated, using surface forcing data mainly from OAFlux project and ISCCP. It is shown that, without solar radiation at night, the global average thickness of temperature and haline skin layers are respectively65μm and lmm. Global average temperature difference through cool skin layer is approximately0.2℃, while salinity difference through salinity layer is approximately0.09psu. The microwave remote sensing error caused by the haline skin layer effect is estimated to be only0.02psu.
     It is shown that forced convections due to sea surface wind stress are dominant over free convections driven by surface cooling in most regions of oceans. The free convection instability is largely controlled by cool skin effect for the thermal microlayer is much thicker and becomes unstable much earlier than the haline microlayer. The similarity of the global distributions of temperature difference and salinity difference across cool and haline skin layers is investigated by comparing their forcing fields of heat fluxes.
     The vertical water temperature and salinity profiles in the upper few meters of the ocean are essential for calibrating the sea surface temperature (SST) and salinity (SSS) from remotely sensed surface radiation fields. A reliable way to predict the SST and SSS profiles is necessary for many oceanographic applications, since high temporal and spatial coverage of surface profile observations are impractical. Based on several full sets of meteorological data and observed near-surface ocean temperature, measured in the Gulf of California during the Marine Optical Characterization Experiment (MOCE-5), a numerical model is made to simulate the vertical temperature and salinity profiles for the upper20meters of the ocean, considering both the sun's radiation and the skin effects. The simulated cool skin thickness can refine meshes near sea surface, because of which, the model can better estimate the sea surface cooling effect, thus better simulate the temperature profile near sea surface. The computation results are in reasonable agreement with the observed vertical temperature profiles in the ocean. Possible causes for difference between model results and observations are also discussed.
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