Following graphics are showing the performances of Sentinel-1 C-band radar and algorithms of Level-2 in the detection of wave systems also called wave partitions.
In this page, analysis are performed with respect to wave mode beam (wv1 or wv2) and pass (Ascending or descending). Results are presented in 4 columns for WV1/Ascending, WV1/Descending, WV2/Ascending and WV2/descending - from left to right. Some sections have "Details" sub-sections. They are for advanced users, but access is not restricted.
Data Set Statistics
This section presents general information on the data set such as its geographical and temporal distributions.
Geographical Distribution of Waves Measurements
This section presents the geographical distribution of Waves measurements used in this page for our analysis. Indeed, it may be interested to know how homogeneous in space is the sampling. It also allow a posteriori monitoring of the data acquisition plan.
Temporal Distribution of Waves Measurements
This section presents the temporal distribution of Waves measurements used in this page for our analysis.
Cross assignments SAR - WW3
Cross assignments of wave systems per quality flag
In this section, the performances of the Sentinel-1 WV Level-2 wave systems with respect to WW3 colocated wave spectrum are separated over the values of the quality flag annotated in OCN products since IPF 3.1. The variables used is: oswQualityFlagPartition. This flag can take different values: - 'very_good' - 'good' - 'medium' - 'low' - 'poor' - 'NaN'
'NaN' means that the partition doesn't exists and therefore has no quality flag.
The flag is defined using a combination of different parameters: u10, Nv, partition contrast, SNR, HsNV.
To have details on this quality flag please refer to the Product Specification document.
In the figures below, the count of partitions per quality flag value is displayed.
The details of the repartition partition rank / partition quality flag (and vice et versa) can be found in the figures below:
Effective Hs for each partition
very good quality partitions (from OCN product quality flag)
good quality partitions (from OCN product quality flag)
medium quality good partitions
low quality partitions (from OCN product quality flag)
poor quality partitions (from OCN product quality flag)
Peak wavelength for each partition
very good quality partitions (from OCN product quality flag)
good quality partitions (from OCN product quality flag)
medium quality good partitions
low quality partitions (from OCN product quality flag)
poor quality partitions (from OCN product quality flag)
Dominant wave direction for each partition
very good quality partitions (from OCN product quality flag)
good quality partitions (from OCN product quality flag)
medium quality good partitions
low quality partitions (from OCN product quality flag)
poor quality partitions (from OCN product quality flag)
Cross assignments of wave systems per surface roughness class
In this section the partitions are divided by class of surface roughness.
This classification is based on the texture of the Level-1 sigma0 WV products.
A model coming from a supervised machine learning has been developed at IFREMER see Wang et al publication.
This semantic classification allows to separate WV images between 10 classes of met-oceans phenomena: * Rain cells * Pure Ocean Swell * Ocean front * Atmospheric front * biological slicks * Icebergs (or local target) * Sea ice * Low wind area * Wind streaks * Micro Convective Cell
The details of the repartition WV image classification / 1st partition quality flag (and vice et versa) can be found in the figures below:
Effective Hs for each partition
"Pure Ocean Swell" sigma0 Level-1 texture classification
"Atmospheric Front" sigma0 Level-1 texture classification
Peak wavelength for each partition
"Pure Ocean Swell" sigma0 Level-1 texture classification
"Atmospheric Front" sigma0 Level-1 texture classification
Dominant wave direction for each partition
"Pure Ocean Swell" sigma0 Level-1 texture classification
"Atmospheric Front" sigma0 Level-1 texture classification
Cross assignments of wave systems per order of energy
Summary of the different methods of cross assignment between the WW3 and S1 partitions For the significant wave height all winds
For the significant wave height at low wind speed ( wind speed < 3m/s)
For the wavelength (all wind speed consiedered)
Rate of matching (i.e. wave direction difference < 10deg and wave length difference <30m for the closest pair of partitions) cross assignment between Sentinel-1 and WW3 spectrum
This rate is supposed to be relatively constant in the time, any increase or decrease of this rate could be related to improvement of degradation in the partitioning algorithm applied to Sentinel-1 data (other things being equal). <\div>
wave partitions cross assignment SAR vs WW3 spectrum using only the most energetic SAR partition
The most energetic swell system in SAR OCN products is the one containing the highest total energy on the entire partition. It is not necessarily the first one in the order of ESA product labeled partitions.
Significant wave height computed using 2D ellipsoidal cut-off from the SAR on each partition.
Significant wave height computed using 2D ellipsoidal cut-off from the SAR on each partition. (version 2)
Wave direction (FROM convention) using 2D ellipsoidal cut-off from the SAR on each partition.
Wavelength using 2D ellipsoidal cut-off from the SAR on each partition.
Effective wavelength ( 2D ellipsoidal cut-off from the SAR on each partition) histogram .
Wave roses (FROM convention) using 2D ellipsoidal cut-off from the SAR on each partition.
wave partitions cross assignment SAR vs WW3 spectrum using the closest pair of partitions in the spectral domain (k,phi)
Closest pair of partitions between WW3 and SAR are associated using the effective peak wave number and effective direction of all the possible combination of partitions on the same spectral grid.
Significant wave height computed using 2D ellipsoidal cut-off from the SAR on each partition.
Significant wave height computed using 2D ellipsoidal cut-off from the SAR on each partition. (version 2)
Wave direction (FROM convention) using 2D ellipsoidal cut-off from the SAR on each partition.
Wave length using 2D ellipsoidal cut-off from the SAR on each partition.
Effective wavelength ( 2D ellipsoidal cut-off from the SAR on each partition) histogram .
Wave roses (FROM convention) using 2D ellipsoidal cut-off from the SAR on each partition.
wave partitions cross assignment SAR vs WW3 spectrum using only the 1st SAR partition
The primary swell system in SAR OCN products is the one containing the highest value of energy. It is not the most energetic one when integrating the energy on the whole partition.
Significant wave height computed using 2D ellipsoidal cut-off from the SAR on each partition.
Significant wave height computed using 2D ellipsoidal cut-off from the SAR on each partition. (version 2)
Wave direction (FROM convention) using 2D ellipsoidal cut-off from the SAR on each partition.
Barycentric Wavelength using 2D ellipsoidal cut-off from the SAR on each partition.
Peak Wavelength using 2D ellipsoidal cut-off from the SAR on each partition.
Effective wavelength ( 2D ellipsoidal cut-off from the SAR on each partition) histogram .
Wave roses (FROM convention) using 2D ellipsoidal cut-off from the SAR on each partition.
Effective Hs bias between the first SAR partition and closest WW3 partition (in the spectral domain) as function of wave direction.
