Remote sensing of ocean color and aerosol properties: resolving the issue of aerosol absorption.
Remote sensing of ocean color and aerosol properties: resolving the issue of aerosol absorption.
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DOI：
10.1364/ao.36.008670
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发表时间：
1997-11
期刊：
影响因子：
1.9
通讯作者：
Howard R. Gordon;Tao Du;Tianming Zhang
中科院分区：
文献类型：
--
作者：
Howard R. Gordon;Tao Du;Tianming Zhang
目前的大气校正和气溶胶反演算法的海洋颜色传感器使用测量的近红外，其中来自海洋的贡献是已知的情况1沃茨的大气反射率的顶部，以评估气溶胶的光学特性。这种测量无法区分弱吸收和强吸收气溶胶，如果假设气溶胶的吸收特性不正确，则大气校正和气溶胶反演算法失败。我们提出了一种算法，似乎有希望在水中的生物物理特性和气溶胶光学特性的大气中含有弱吸收和强吸收气溶胶的检索。通过使用大多数海洋颜色仪器（412-865 nm）可用的整个光谱，我们同时恢复海洋的生物光学特性和一组最能描述气溶胶光学特性的气溶胶模型。该算法被应用到模拟的情况下，可能会发生在美国东海岸在夏季时，气溶胶可能是本地产生的弱吸收海洋型或污染产生的强吸收城市型运输的风在海洋上。模拟结果表明，该算法在弱吸收和强吸收气溶胶的大气中均表现良好。该算法成功地识别了吸收气溶胶，并提供了气溶胶光学厚度的接近值。它还提供了海洋生物光学特性的出色检索。该算法使用的生物光学模型的情况1沃茨和一组气溶胶模型的操作。海洋和大气的相关参数系统地变化，以找到最好的（在均方根意义上）适合测量的大气层顶的光谱反射率。提供的例子表明，算法的性能存在的错误，例如，白浪贡献的误差和辐射校准的误差。
Current atmospheric correction and aerosol retrieval algorithms for ocean color sensors use measurements of the top-of-the-atmosphere reflectance in the near infrared, where the contribution from the ocean is known for case 1 waters, to assess the aerosol optical properties. Such measurements are incapable of distinguishing between weakly and strongly absorbing aerosols, and the atmospheric correction and aerosol retrieval algorithms fail if the incorrect absorption properties of the aerosol are assumed. We present an algorithm that appears promising for the retrieval of in-water biophysical properties and aerosol optical properties in atmospheres containing both weakly and strongly absorbing aerosols. By using the entire spectrum available to most ocean color instruments (412-865 nm), we simultaneously recover the ocean's bio-optical properties and a set of aerosol models that best describes the aerosol optical properties. The algorithm is applied to simulated situations that are likely to occur off the U.S. East Coast in summer when the aerosols could be of the locally generated weakly absorbing Maritime type or of the pollution-generated strongly absorbing urban-type transported over the ocean by the winds. The simulations show that the algorithm behaves well in an atmosphere with either weakly or strongly absorbing aerosol. The algorithm successfully identifies absorbing aerosols and provides close values for the aerosol optical thickness. It also provides excellent retrievals of the ocean bio-optical properties. The algorithm uses a bio-optical model of case 1 waters and a set of aerosol models for its operation. The relevant parameters of both the ocean and atmosphere are systematically varied to find the best (in a rms sense) fit to the measured top-of-the-atmosphere spectral reflectance. Examples are provided that show the algorithm's performance in the presence of errors, e.g., error in the contribution from whitecaps and error in radiometric calibration.