Oregon State University, Corvallis, OR, USA.
Ann Rev Mar Sci. 2013;5:95-113. doi: 10.1146/annurev-marine-121211-172408. Epub 2012 Jul 23.
The shallow waters of the nearshore ocean are popular, dynamic, and often hostile. Prediction in this domain is usually limited less by our understanding of the physics or by the power of our models than by the availability of input data, such as bathymetry and wave conditions. It is a challenge for traditional in situ instruments to provide these inputs with the appropriate temporal or spatial density or at reasonable logistical or financial costs. Remote sensing provides an attractive alternative. We discuss the range of different sensors that are available and the differing physical manifestations of their interactions with the ocean surface. We then present existing algorithms by which the most important geophysical variables can be estimated from remote sensing measurements. Future directions and opportunities will depend on expected developments in sensors and platforms and on improving processing algorithms, including data assimilation formalisms.
近岸海域的浅水区域是人们所热衷的，这里充满活力，同时也常常充满挑战。通常情况下，在这个领域进行预测，其限制因素不是我们对物理原理的理解，也不是模型的能力，而是输入数据的可用性，例如水深数据和波浪条件。传统的现场仪器很难以适当的时间或空间密度，或以合理的后勤或财务成本来提供这些输入。遥感提供了一种有吸引力的替代方法。我们讨论了现有的各种传感器以及它们与海洋表面相互作用的不同物理表现。然后，我们介绍了现有的算法，通过这些算法可以从遥感测量中估计出最重要的地球物理变量。未来的方向和机会将取决于传感器和平台的预期发展以及处理算法的改进，包括数据同化形式。
