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Indirect Validation of Ocean Remote Sensing Data via Numerical Model: An Example of Wave Heights from Altimeter

Haoyu Jiang

2020Remote Sensing26 citationsDOIOpen Access PDF

Abstract

Using numerical model outputs as a bridge, an indirect validation method for remote sensing data was developed to increase the number of effective collocations between remote sensing data to be validated and reference data. The underlying idea for this method is that the local spatial-temporal variability of specific parameters provided by numerical models can compensate for the representativeness error induced by differences of spatial-temporal locations of the collocated data pair. Using this method, the spatial-temporal window for collocation can be enlarged for a given error tolerance. To test the effectiveness of this indirect validation approach, significant wave height (SWH) data from Envisat were indirectly compared against buoy and Jason-2 SWHs, using the SWH gradient information from a numerical wave hindcast as a bridge. The results indicated that this simple indirect validation method is superior to “direct” validation.

Topics & Concepts

HindcastRemote sensingAltimeterWave modelSignificant wave heightBuoyCollocation (remote sensing)Computer scienceEnvironmental scienceMeteorologyGeologyWind waveMachine learningGeographyOceanographyOcean Waves and Remote SensingOceanographic and Atmospheric ProcessesCoastal and Marine Dynamics