A Specular Reflection Removal Method for Large Scale Ocean Surface Images

Author(s):  
Shengke Wang ◽  
Changyin Yu ◽  
Yujuan Sun ◽  
Junyu Dong
2021 ◽  
Author(s):  
Gregory Wagner ◽  
Andre Souza ◽  
Adeline Hillier ◽  
Ali Ramadhan ◽  
Raffaele Ferrari

<p>Parameterizations of turbulent mixing in the ocean surface boundary layer (OSBL) are key Earth System Model (ESM) components that modulate the communication of heat and carbon between the atmosphere and ocean interior. OSBL turbulence parameterizations are formulated in terms of unknown free parameters estimated from observational or synthetic data. In this work we describe the development and use of a synthetic dataset called the “LESbrary” generated by a large number of idealized, high-fidelity, limited-area large eddy simulations (LES) of OSBL turbulent mixing. We describe how the LESbrary design leverages a detailed understanding of OSBL conditions derived from observations and large scale models to span the range of realistically diverse physical scenarios. The result is a diverse library of well-characterized “synthetic observations” that can be readily assimilated for the calibration of realistic OSBL parameterizations in isolation from other ESM model components. We apply LESbrary data to calibrate free parameters, develop prior estimates of parameter uncertainty, and evaluate model errors in two OSBL parameterizations for use in predictive ESMs.</p>


As emphasized recently by Munk & Wunsch, the traditional methods of monitoring the ocean circulation give data too hopelessly aliased in space and time to permit a proper assessment of basin-wide dynamics and heat flux on climatic timescales. The prospect of nearly continuous recording of ocean-surface topography by satellite altimetry with suitable supporting measurements might make such assessments possible. The associated identification of the geocentric oceanic tidal signal in the data would be an additional bonus. The few weeks of altimetry recorded by Seasat gave a glimpse of the possibilities, but also clarified the areas where better precision and knowledge are needed. Further experience will be gained from currently projected multi-purpose satellites carrying altimeters, but serious knowledge of ocean circulation will result only from missions that are entirely dedicated to the precise measurement of ocean topography.


2016 ◽  
Vol 33 (12) ◽  
pp. 2769-2784 ◽  
Author(s):  
M.-H. Rio ◽  
R. Santoleri ◽  
R. Bourdalle-Badie ◽  
A. Griffa ◽  
L. Piterbarg ◽  
...  

AbstractAccurate knowledge of ocean surface currents at high spatial and temporal resolutions is crucial for a gamut of applications. The altimeter observing system, by providing repeated global measurements of the sea surface height, has been by far the most exploited system to estimate ocean surface currents over the past 20 years. However, it neither permits the observation of currents moving away from the geostrophic balance nor is it capable of resolving the shortest spatial and temporal scales of the currents. Therefore, to overcome these limitations, in this study the ways in which the high-spatial-resolution and high-temporal-resolution information from sea surface temperature (SST) images can improve the altimeter current estimates are investigated. The method involves inverting the SST evolution equation for the velocity by prescribing the source and sink terms and employing the altimeter currents as the large-scale background flow. The method feasibility is tested using modeled data from the Mercator Ocean system. This study shows that the methodology may improve the altimeter velocities at spatial scales not resolved by the altimeter system (i.e., below 150 km) but also at larger scales, where the geostrophic equilibrium might not be the unique or dominant process of the ocean circulation. In particular, the major improvements (more than 30% on the meridional component) are obtained in the equatorial band, where the geostrophic assumption is not valid. Finally, the main issues anticipated when this method is applied using real datasets are investigated and discussed.


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