ERS WAVE MISSION REPROCESSING- QC SUPPORT ENVISAT MISSION EXTENSION SUPPORT

Transcription

1 REPORT 8/2012 ISBN ISSN ERS WAVE MISSION REPROCESSING- QC SUPPORT ENVISAT MISSION EXTENSION SUPPORT - Annual Report 2011 Author (s): Harald Johnsen (Norut), Fabrice Collard (CLS)

2 Project Name: ASAR-QA Project No.: 650 Contractor(s): ESA/ESRIN Contractors Ref.: ESRIN Contract No.21334/08/I-OL, CCN.2 Document No.: 8/2012 Document Type: Report P5 Status: Open ISBN: ISSN: No. Pages: 16 Project Manager: Harald Johnsen Date: 29 April 2012 Author (s): Harald Johnsen (Norut), Fabrice Collard (CLS) Title: ERS Wave mission reprocessing QC support - Envisat mission extension support: Assessment of WV Product Quality after Orbit Change Summary: This report summarizes the activities and achievements within the project ERS Wave mission reprocessing- QC support Envisat Mission extension support for the period 1 st April 2011 until 31 st March Keywords: ASAR WM, Sentinel-1, Level 2, WVW, WSS Notes: Publisher: Norut Authorization: Kjell-Arild Høgda

3 Content 1.! Introduction... 4! 2.! Reference and applicable documents... 4! 2.1.! Reference documents... 4! 3.! Results... 5! 3.1.! ASAR Wave Product Quality Control & CAL/VAL Monitoring... 5! ! Routine WV L1 calibration and L2 product quality control... 5! ! L2 Product Validation... 5! 3.2.! ASAR Wave Algorithm Processing Baseline Maintenance... 5! 3.3.! Test Data Set For MTF Upgrade & Swell Tracking... 5! ! Test Data Set For MTF from WSS Data... 5! ! Wave Product and Swell Tracking from WSS Data... 9! ! Test Data Set from ASAR WM... 10! 3.4.! Definition of Calibration Method Using Wind Model... 12! 3.5.! New Algorithm Development... 13! ! Development of New Methodology Tailored to S-1 WV... 13! ! Prototype Algorithm Development and Testing... 16! 3.6.! QWG Participation... 16! ! Participation in QWG meetings... 16! 3

4 1. Introduction This is the annual report for the ESRIN/contract No as described in [R-1], [R-3] related to the work packages; WP 1000: ASAR Wave Product Quality Control & CAL/VAL Monitoring Wp 1100: Routine WV L1 calibration and L2 product quality control Wp 1200: L2 product validation WP 2000: ASAR Wave Algorithm Processing Baseline Maintenance Wp 2100: Algorithm Upgrade and Impact Assessment Wp 2200: Verification Using Prototype WP 3000: ASAR Leap Frog Data Exploitation Wp 3100: Prototype Processing of WVW Product From Leap Frog Data Set Wp 3200: Swell Tracking Using Leap Frog Data Set WP 4000: Definition of Calibration Method Using Wind Model Wp 4100: Description of Calibration Method and Expected Performance Wp 4200: Validation of Calibration Results Against Transponders WP 5000: New Algorithm Development Wp 5100: Development of New Methodology Tailored to S-1 WV Wp 5200: Prototype Algorithm Development and Testing WP 6000: QWG Participation Wp 6100: Participation in QWG meetings The activities have followed the work package plan, except for WP3000. It was possible to do the leap frog experiment with ASAR WM instrument for this period, so this activity was switched to using ASAR WSS data together with WW3 to generate the test data set for different swaths. The existing WM (S2,S4,VV,HH) data set collocated with WAM data has also been reprocessed to similar format. 2. Reference and applicable documents 2.1. Reference documents [R-1] Technical Support the Global Validation and long term quality controld of ASAR Wave Mode products Statement of Work, ENVI-CLVL-EOPG-SW X, Issue 0, Rev.9, 08/03/2011, Draft [R-2] Request for CCN work Quotation ESRIN/Contract No.21334/08/I-NB, CCN.2, ESA/ESRIN, [R-3] Johnsen H., Collard F., Global Validation and Long-Term Quality Assessment of ASAR Wave Mode Products - Description of Work, Norut, [R-4] ASAR WM Monthly Cycle Reports 4

5 3. Results 3.1. ASAR Wave Product Quality Control & CAL/VAL Monitoring Routine WV L1 calibration and L2 product quality control The monthly cycle reports are produced regularly and made available on Internet ( In Figure 1 is shown an extract from the cycle reports from the period Jan 2007 until Apr Figure 1 shows the time evolution of the ASAR WM geophysical calibration constant, derived using CMOD in combination with global collocated ECMWF wind field. Figure 1 shows that the gain has been relatively constant (<0.5dB) since January The cycle reports show no anomaly for the parameters analyzed in the WVS and WVW products. Figure 1 Evolution of ASAR WM gain (i.e. absolute calibration constant) as function of time since January L2 Product Validation 3.2. ASAR Wave Algorithm Processing Baseline Maintenance There has been no algorithm upgrade within this reporting period Test Data Set For MTF Upgrade & Swell Tracking Test Data Set For MTF from WSS Data In preparation of Sentinel1 wave inversion from wide swath products, SAR wave MTF coherence throughout the whole range of incidence angles is still to be assessed. Since it was not possible to generate ASAR WM leap frog data set, we decided to use the ASAR WSS data in combination with WW3 to generate the test data set needed for evaluating the modulation transfer function at different swaths. The processing of WSS data into Level1b and running the WW3 is to be done (Spring 2012) at CLS and Ifremer, respectively. 5

6 About 500 WSS scenes in VV polarization (Figure 2) have been acquired and processed into SLC products at VIGISAT ground station in March The WSS SLC products have then been processed into cross spectra. Figure 2 : Coverage of ASAR WSS dataset acquired and processed in March 2012 at VIGISAT ground station in Brest. Over only a month, sufficient wind and wave conditions were observed to cover the range of dominant wavelength in all directions relative to azimuth in a variety of wind (Figure 3) and wave height (Figure 4) conditions. 6

7 Figure 3 : Range of wave dominant direction relative to azimuth and dominant wavelength in the WSS March 2012 and related wind speed in color. 7

8 Figure 4 : Range of wave dominant direction relative to azimuth and dominant wavelength in the WSS March 2012 dataset and related significant wave height in color. Once the WW3 collocated spectra will be available, an empirical MTF model will be derived and compared to the theoretical model used for wave mode Level2 wave spectra inversion. 12 additional months of data with the same coverage have been acquired at VIGISAT ground station but have not yet been processed into WSS products and cross spectra. If the WWS/WW3 comparison results in too few cases available for each set of incidence angle/wavelength/direction, these additional level0 wide swath products will be processed and collocated with WW3 the same way as for march

9 Norut Tromsø RAPPORT 8/ Wave Product and Swell Tracking from WSS Data The same dynamic validation scheme used for ASAR wave mode was attempted for ASAR wide swath mode. This consists in extracting wave spectra over sub-image tiles, partition each spectra to extract dominant wave parameters (i.e. significant wave height, dominant direction and wavelength as mapped on Figure 5) and propagate partitions to any given time (cf Figure 6) and assess the coherence of all partitions from all observations at a given location and time. The exercise was done using all ASAR wave spectra observations from wave and wide swath mode acquired and processed at VIGISAT ground station as part of the SAR wind/wave/current demonstration project SOPRANO. At a given location and time, propagated partitions from WSS products could then be collocated together with propagated partitions from wave mode to provide an internal consistency check. Further quantitative consistency assessment will be performed once the MTF is updated as a result of the WSS/WW3 analysis described in previous chapter. Figure 5 : Sample swell field extracted from ASAR WSS products in case of moderate wind (left) and low wind (right) where some artifacts are observed. 9

10 Figure 6 : Sample swell tracking outputs using a combination of wave mode and wide swath mode wave spectra Test Data Set from ASAR WM In parallel to the WSS test data set generation, the historical WM data set at VV-S2-S4 and HH- S2-S4 has been processed to similar form as the WSS test data set, using the WAM model instead of WW3 for assessment of MTF. Exploring the MTF using this data set is ongoing. In the following is shown some features of the MTF analysis. The ASAR WM data set has been inverted to Level 2 product using the baseline (theoretical) MTF model. The ratio of the significant waveheight resolved by the SAR and the corresponding WAM waveheight is analysed in terms of wind/wave field, polarization and swath. This ratio reflects the performance of the baseline MTF used in the Level 2 processing. 10

11 Figure 7 : Waveheight ratio (SAR/WAM) versus wind speed (left) and wind direction relative to range (right) The left plot in Figure 7 indicates an underestimation of the baseline MTF amplitude at lower wind speed and an overestimation at higher wind speed. The same wind speed dependency is observed in both polarization and in both swaths. The right plot in Figure 7 shows a weak wind direction dependency, where an underestimation of MTF amplitude at cross winds is observed compared to up/down winds. The same trend is observed in both polarizations and swaths, except for a scaling with swath. Figure 8 : Swell waveheight ratio (SAR/WAM) versus swell waveheight waveheight (right). (left) and wind sea The wind sea waveheight dependency observed in Figure 8 (right plot) is consistent with the wind dependency shown in Figure 7. However, the swell waveheight dependency in Figure 8 (left plot) is stronger than expected, especially at low waveheights. Again, there is no significant difference in trends wrt to polarizations or swaths. 11

12 Figure 9 : Swell waveheight ratio (SAR/WAM) versus dominant wave direction relative to ranges Figure 9 shows that there is no significant dependency in the waveheight ratio with respect to dominant wave direction. The conclusion from these results is that there is a wind field dependency in the MTF that needs to be compensated for beyond the baseline MTF. However, the dependency on swath and polarization seems to be similar except for scaling with swath Definition of Calibration Method Using Wind Model The basic principle is to use a well-known and calibrated (C-band scatterometers) backscatter model for sea surface that provides expected NRCS to incidence angle and external model surface wind speed and direction. Comparison between expected and observed backscatter yields a calibration constant that is shown to be unbiased and highly accurate (less than 0.1dB) providing a sufficient number of data are used and a even selection of wind direction and wind speed is considered. Details of the method and sample results are the subject of a separate technical note. 12

13 3.5. New Algorithm Development Development of New Methodology Tailored to S-1 WV Detection of extreme long wavelengths is hampered by the existing ASAR Level 2 algorithm due to the low frequency removal procedure applied to the data. Figure 10 illustrate two cases where long (left) and very long (right) swells are imaged and well described in the cross spectra but absent from the wave spectra, for the longer one. Figure 10 : ASAR Wave mode observation of long swells of respectively 547m (left) and 750m (right) dominant wavelength. Upper raw are the SAR NRCS imagettes, middle raw are the crossspectra intensities and bottom raw, the Level2 wave spectra. 13

14 Some testing to overcome this limitation has been done on the Sentinel-1 OSW algorithm, but more investigation is needed to make a robust procedure. In Figure 11 is an example of such data processed with to different test versions of the Sentinel-1 OSW algorithm. Figure 11: Level 1b (upper left) and Level 2 spectra processed with the original version (upper right) and a test version (lower left) of the Sentinel-1 OSW algorithm. Figure 11 (upper right) shows that the ASAR and the baseline Sentinel-1 Level 2 algorithm do not detect properly the very long swell system observed in the Level 1b product (upper left). Modification of the filtering operation before inversion solves this problem for the current data set, as shown in the lower left plot. However, a robust procedure needs to be developed. The current Sentinel-1 Level 2 algorithm performs the partitioning on the ocean wave spectra after the inversion. A new version of the same algorithm is developed in which the partitioning is performed on the cross-spectra i.e. before the inversion. This has shown improvements in some bimodal cases. Concerning the very long swell extraction, besides the loss of some swell partitions due to the low pass filtering operation, additional bias low on the dominant wavelength or peak period is observed on the inverted swell spectra (Figure 12) when compared to corresponding buoy observations. Note that equivalent peak period estimated directly from cross spectra do not seem to have quite such a bias low and further investigation is needed to understand what caused this bias in the inversion process. 14

15 Figure 12 : Evolution of dominant swell frequency (upper plot) or peak period (lower plot) with time as a swell system is passing by a wave buoy location. On upper plot, dominant frequency extracted from both SAR WVS cross spectra (blue) is superimposed to dominant frequency extracted from the SAR L2 WVW wave spectra (red) and to buoy time/frequency map. On the lower plot, corresponding peak period is compared in a more synthetic way for the same swell event at the same period and same wave buoy. 15

16 Prototype Algorithm Development and Testing Updating the baseline look-up tables for S2/S4/HH/VV based on the results shown in Section is done, and testing currently undertaken. In the baseline Level 2 algorithm, the partitioning is done on the final wave spectra. Testing of a modified scheme is undertaken, in which the partitioning is performed on the cross-spectra (i.e. before inversion). If the impact is positive, the baseline processing will be updated with this scheme QWG Participation Participation in QWG meetings A meeting was held in June 2011 at ESRIN, where issues related to the S-1 processing was discussed. A second meeting was held in March 2012 at Ifremer, where the main issue was to discuss the new strategy for WP