Decomposition of Submesoscale Ocean Wave and Current Derived from UAV-Based Observation
Round 1
Reviewer 1 Report
Comments and Suggestions for AuthorsThe sea surface waves and currents were observed by an unmanned aerial vehicle (UAV). The UAV images are decomposed by the Fast and Adaptive Multidimensional Empirical Mode Decomposition (FA-MEMD), and then the sea surface wave spectrum and current features were derived by 2D FFT and optical flow. The structure of the manuscript is well organized and the result were validated by in-situ measurement. However, more information should be given to better understand the method. The specific comments are as follows,
In Section 2.3, the methodology to process UAV images was briefly described, which should be more detailed. For example, as stated in the manuscript, GCPs are difficult to be got on sea surface, and the information on geometry, posture recorded by GPS/IMU and internal camera variables are used, how to use these information? Specific steps and mathematical equations should be given.
It is said that “BIMFs represent bidimensional components capturing spatial patterns or structures in both the horizontal and vertical dimensions of the data, with each BIMF corresponding to a different scale or frequency in the bidimensional signal”, and different BIMFs were used to estimate different frequencies of waves. However, the modes decomposed by the empirical orthogonal mode decomposition method may not necessarily correspond to the actual physical components, and the physical meanings of each mode need to be compared and determined with in-situ observations of waves.
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Reviewer 2 Report
Comments and Suggestions for AuthorsPlease see attached reviewer comments.
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Reviewer 3 Report
Comments and Suggestions for AuthorsThis paper describes measurements of coastal zone waves and currents from optical observations using an UAV. The work is interesting and should be published after some discussion and revisions.
The authors demonstrate that separating waves from currents in the images improves current estimates. But the processing used to separate waves from currents seems overly complicated. Why not just take a two dimensional FFT of an image and low pass the results?
I don’t see the point of showing the waves in three frequency bands. Would the complete wave spectrum result from adding the three wavenumber spectra together or is some energy lost in the processing.
A lot more might be done with the wave portion of the signal. The authors should look at published research on stereo optical observations of waves and X-band radar observations of waves.
Could you learn something about wave propagation and the dispersion relation by looking at sequences of images?
Discussing the waves in region 2 might be more interesting than those in region 1. The proximity of the islands might lead to refraction and diffraction patterns.
In section 2.1, the “bottom slope is generally flat”. That is contradicted by the statements about “interaction between currents and the seafloor” and “encounters a shallow seabed” as well as the bathymetry map. A better word for the drifter “resistor” is “drogue”.
In section 2.3, what is the third dimension in “a three-dimensional spatiotemporal dataset”. What use was made of the time dimension? “The time interval of the input data was set to 0.5 Hz” should be “…2 sec”.
In section 3.1, how was “time-series data” calculated from spatial images? Shouldn’t “waves with periods of 1-30 sec” be “…1-10 sec”?
In section 4.4, the computation time was about 18 hr. What kind of computer?
Comments on the Quality of English Language/
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Round 2
Reviewer 1 Report
Comments and Suggestions for AuthorsThe manuscript has been revised.
