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Introduction

Road-mapping the Way Forward for Sentinel-3 Topography Mission SAR-Mode waveform Re-tracking over water surfaces. J Benveniste, P Cipollini, C Gommenginger, C Martin-Puig, D Cotton, S Dinardo, NOC (UK), Starlab (Spain), SatOC (UK), ESA/ESRIN (Italy). Introduction.

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Introduction

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  1. Road-mapping the Way Forward for Sentinel-3 Topography Mission SAR-Mode waveform Re-tracking over water surfaces J Benveniste, P Cipollini, C Gommenginger, C Martin-Puig, D Cotton, S Dinardo, NOC (UK), Starlab (Spain), SatOC (UK), ESA/ESRIN (Italy)

  2. Introduction • This talk deals with findings and challenges relevant to the Sentinel-3 Radar Altimeter over ocean • We will see: • What is special about the Sentinel-3 Altimeter • What are the challenges • Validation Exercise: height inter-calibration with Jason-2 and SWH calibration w.r.t. wave buoys • Conclusions

  3. ) ) ) ) ) ) ) Conventional Low Resolution Mode (LRM) Vs/c PRF: ~2 kHz In LRM, the pulse-limited footprint moves across the surface pulse by pulse as the satellite passes overhead 3-7 km depending on sea state Courtesy: K. Raney, APL/JHU

  4. ) ) ) ) ) ) ) SAR altimeter (Cryosat-2, Sentinel-3): fundamentally different! Vs/c PRF: ~20 kHz SAR altimeter uses Doppler frequency effect to spotlight a small area along-track (250-300 m) resolved by each burst as the satellite passes overhead Courtesy: K. Raney, APL/JHU 250-300 meters

  5. At t=0, the SAR footprint is no longer circular but rectangular !! At t=0, the Across Track Resolution is the same as Pulse-Limited Altimetry (Pulse-Limited Diameter) but the footprint size reduces with the time delay REDLRM GREENSAR t<0 t=0 t>0 The footprint area is no longer constant with time delay

  6. Multi-looking 1D multi-looked 20Hz waveform • Doppler-beam selection/weighting & incoherent integration of beams from multiple bursts starting at the same ground cell (to reduce the speckle noise) i.e. multilooking • Note the peaky waveform shape and the long decaying tail due to varying footprint area in SAR Mode 128 gates

  7. Predicted advantages of SAR over LRM • More independent looks  improved retrieval precision • Two-fold improvement according to numerical studies by Jensen & Raney (1998) • Finer spatial resolution along track • ~300 meters along-track • Higher SNR • ~10 db more • Better performance close to land • especially for track ~90° to coastline • Less sensitivity to sea state

  8. THE FUTURE: Sentinel-3 Surface Topography Mission • LRM: open ocean • SAR: global coastal ocean + sea ice • SAR open loop: ice sheet margins • SAR open/closed loop: land & inland waters THE PRESENT: Cryosat-2 LRM: most of open ocean + most of land SAR: some oceanic & coastal regions + sea ice SARIN: few pilot regions (ocean & land) + land ice

  9. The ESA SAMOSA Project: • Study funded by ESA STSE, led by David Cotton (SatOC) • Starlab, NOC, De Montfort University, DTU Space & expert support from Keith Raney (JHU/APL) • Objectives & Methodology • Quantify range retrieval accuracy in pulse-limited and SAR mode as a function of significant wave height • Develop physically-based models for SAR altimeter ocean waveforms • Apply physically-based models to SAR ocean waveforms • Done for both simulated and real Cryosat SAR waveforms over ocean • Investigate method to reduce SAR mode data to pseudo-LRM • Applications to airborne SAR altimeter data, SAR waveforms over inland water (DMU), coastal regions, sea floor mapping (DTU Space),… • Development and Validation of SAMOSA SAR re-tracker with Cryosat-2 SAR mode data over ocean

  10. Next-generation SAMOSA models • SAMOSA1 gives acceptable fit to Cryosat-2 SAR waveforms BUT… • Circular antenna beam, no across-track mispointing • Non-physical behaviour for large mispointing angles • Over-estimates significant wave height (Hs) • Next generation model: SAMOSA2 • entirely new physically-based formulation developed by Starlab • Accounts for asymmetric antenna beam, ellipticity of the Earth, along- AND across-track mispointing, non-linear ocean wave effects • Physically correct response to mispointing • Improved fit to Cryosat-2 SAR waveforms • BUT… not fully-analytical & computational expensive

  11. SAMOSA3 model Simplification of SAMOSA2 while keeping its advanced features fully-analytical, robust and computationally fast !!

  12. Comparing SAM1, SAM2 and SAM3 • With SYMMETRIC antenna beam and no Earth ellipticity effects: • SAM3 and SAM1 are equivalent !! • These two entirely independent theoretical models converge !

  13. SAMOSA 3 Project: • Study funded by ESA STSE, led by David Cotton (SatOC) • Starlab, NOC, • Objectives & Methodology • Develop and characterize SAM3 model (Trade-off TN) • Deliver to the Sentinel-3 STM PAD a Detailed Processing Model (DPM) of a SAR ocean waveform re-tracker based on the best SAMOSA model to operationally retrack Sentinel-3 SAR-Mode L1b waveforms • Validate Retracker using Cryosat Data in high and low sea conditions

  14. SAMOSA 3 DDM and Re-tracker: Physically-based model developed by Starlab from first principles Analytical ( by Bessel Functions) solutions to model the Delay Doppler Maps (DDM) for the full span of Doppler Frequencies Model depends on epoch, significant wave height, Pu, surface rms slope, and mispointing angle(s), The model independent variables are the Doppler Frequency and the Time Delay The waveforms are retracked by Least- Square Fitting Algorithm (Levenberg-Marquard)

  15. Model Behaviour: effect of Sea State (SWH) SAMOSA3 model: Dependence of waveform shape on SWH • SWH affects the width of lobe of the SAR waveforms

  16. Model Behaviour: effect of mispointing • Roll mispointing affect shape of the SAR waveforms • Model insensible to pitch mispointing • Effect significant only for mispointing greater than 0.1 deg

  17. Effect of along-track mispointing: negligible

  18. Effect of across-track (roll) mispointing: changes waveform tail 0.5° 0.3° 0.1° 0.0°

  19. Challenges of SAR altimetry

  20. Challenge 1: LRMSAR transitions LRM SAR

  21. LRMSAR transitions (cont.) • Methodology to reduce SAR mode data to pseudo LRM has been developed by Starlab (RDSAR method) • Tested and validated with simulated SAR waveforms: • Full Bit Rate (FBR) SAR can be successfully transformed into pseudo-LRM waveforms that can be re-tracked with Brown model • RDSAR anyway does not give the same range noise as LRM (less number of accumulated independent looks)

  22. Coastal Zone Challenge 2: Coastal Zones Waveforms at 20 Hz, one waveform each 300 meters – Optimal Conditions

  23. Effect of the Land -> LIMITS Track Orientation and bright targets can have effect on the level of the Land Contamination.. Even in SAR mode !!! The land contamination in SAR Mode is greatly reduced but still present in unfavourable cases; MisFit and Ground Track Orientation to the coastline can be parameters useful to quantify the contamination

  24. Challenge 3: Inland Water

  25. Validation Exercise over open sea

  26. CryoSat-2 and Jason-2: Range error in SAR and LRM as a function of sea state • Comparison of CryoSat2 SAR with Jason2 LRM • Focus on small area in Norwegian Sea • July 2010 – March 2011 • Wide range of sea states Lots of CryoSat-2 data in LRM and SAR mode since July 2010 but not collocated (SAR and LRM are exclusive modes)

  27. Variability in SSH (Norwegian Sea) SAM3 SSH Ksiyinput = 0.01 deg CryoSat-2 SAR (Hs < 2m) SSH std 20Hz: 4.907 cm 1Hz: 1.097 cm Jason-2 LRM (Hs < 2m) SSH std 20Hz: 7.012 cm 1Hz: 1.568 cm Factor of 1.43 reduction in SSH error with CryoSat-2 L1B SAR SAR perf will improve with reprocessed CryoSat-2 L1B data

  28. Variability in Hs (Norwegian Sea) SAM3 SSH Ksiyinput = 0.01 deg CryoSat-2 SAR (Hs < 2m) Hs std 20Hz: 0.425 m 1Hz: 0.095 m Jason-2 LRM (Hs < 2m) Hs std 20Hz: 0.536 m 1Hz: 0.120 m Slight bias in SAR Hs ? Factor of 1.26 reduction in SWH error with C2 L1B SAR

  29. Bias in SAR Hs ? Validation against buoys Buoy wave height data from UK Met Office CryoSat-2 SAR data and buoys collocated within 50km and 30 minutes Data for July 2010 - May 2011

  30. CryoSat-2 SAR Hs against buoys SAM3 SWH Ksiyinput = 0.01 deg • Linear relation between C2 SAR Hs and buoy Hs over full range of sea states • Small bias < 0.5 m; Std ~ 0.3 m • Hs bias is directly linked to roll mispointing used as input to the SAR retracker • use of platform mispointing data as input to the SAR retracker should reduce this bias • Need to account for known small systematic bias in roll mispointing for C2 (Scharroo, pers comm.)

  31. Conclusions SAR opens up a wide range of new scientific possibilities over ocean, coastal zone and inland water Ready for Sentinel-3! • Performance of CryoSat-2 SAR should improve with optimised SAR retracking that uses platform roll mispointing as input • Both variability and SWH bias • Same analyses to be repeated in a less dynamic region • Analyses of CryoSat-2 SAR performance against pseudo-LRM products • In summary: • CryoSat-2 SAR mode produces very good data over ocean • we have a fully-analytical, robust and computationally efficient model that successfully retracks CryoSat-2 SAR waveforms • SAR shows improved performance compared to LRM for both SSH and SWH

  32. www.altimery2012.org

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