Sea State t Measurement using Synthetic Aperture Radar Data

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Sea State t Measurement using Synthetic Aperture Radar Data Lehner, Susanne Pleskachevsky, Andrey Li, Xioming Brusch, Stephan German Aerospace Center, Remote Sensing Technology Institute

Outline Satellites ENVISAT (ASAR) TerraSAR-X Algorithms for sea state t estimation sea state parameters global: ENVISAT ASAR CWAVE_ENV sea state parameters local: TerraSAR-X XWAVE Applications wave tracing: underwater topography by observation of long wave refraction in coastal areas and energy flux along the wave track implementation of SAR information into numerical modelling

1.1 CWAVE for Envisat ENVISAT CWAVE _ ENV (CWAVE for ENVISAT) for Advanced SAR (ASAR) wave mode data based on the CWAVE approach developed for ERS-2 SAR wave mode data non-linear geophysical model function from CWAVE applied and tuned Validation conducted by in situ buoy measurements, ECMWF reanalysis, WAM-wave model results Altimeter measurements without needing input of prior information ASAR images covering 6/10km 5km acquired along the orbit every 100 km. homogenous case makes SAR an independent instrument measuring integrated wave parameters like SWH and mean wave period to altimeter quality. Publication: Li, X.-M., Lehner, S., Bruns, Th. Ocean wave integral wave parameter Measurements using Envisat ASAR wave mode data IEEE TGRS, 2010. DOI:10.1109/TGRS.2010.2052364.

1.2 CWAVE for Envisat: comparisons New technique (CWAVE_ENV) developed for deriving significant wave height from ASAR wave mode data under severe weather situations. vs.buoy vs.ecmwf vs.dwd Vs. JASON Vs. GFO A global data set of 25 000 pairs of ASAR wave mode images and collocated reanalysis WAM results from the European Centre for Medium- Range Weather Forecasts (ECMWF) is used to tune CWAVE _ ENV model coefficients. Validation conducted by comparing the retrieved SWH to in situ buoy measurements shows a scatter index of 0.24 and 0.16 when compared to the ECMWF reanalysis WAM. collocated area with a radius of 100 km, +/-3h Publication: Li, X.-M., Lehner, S., Bruns, Th. Ocean wave integral wave parameter Measurements Lehner, Pleskachevsky, using Envisat Li, Brusch: ASAR Sea State wave Measurement mode data using Synthetic Aperture Radar Data IEEE TGRS, 2010. DOI:10.1109/TGRS.2010.2052364.

1.3 CWAVE for Envisat: validation of wave models An underestimation of wave height in wave-model forecasting especially during storms DWD RA SAR RA (altimeter) SAR Red DWD model Blue SAT two independent measurements show underestimation by wave model (DWD) Publication: Li, X.-M., Lehner, S., Bruns, Th. Ocean wave integral wave parameter Measurements Lehner, Pleskachevsky, using Envisat Li, Brusch: ASAR Sea State wave Measurement mode data using Synthetic Aperture Radar Data IEEE TGRS, 2010. DOI:10.1109/TGRS.2010.2052364.

2.1 TerraSAR-X satellite 514 km altitude, ground speed 7km/s, 15 orbits/day, repetition 11 days sensor: high frequency X-band SAR (Synthetic Aperture Radar) wavelength 31mm, frequency 9,6GHz Basic modes and resolution: TS-X launched on June 15, 2007 Spotlight, 10km x 10km, of 1-2m Stripmap, 30km wide strips at a resolution between 3,3 (azimuth) and 6m, ScanSAR 100km wide strips at a resolution of 18m Main application and algorithms Wind Field Generation Sea State Parameters Coastlines and Morphodynamics Ship Detection Underwater topography estimation

2.2 TerraSAR-X: effect of the achieved higher resolution (1) Acquired over the German island of Norderney, 2x7 km subscene. TerraSAR-X: lover altitude (514km against 800km by ENVISAT) and ground speed reduced Doppler-shift of facets, moving to sensor, reduced cut-off of azimuth travelling waves ERS April 4, 2004 ENVISAT TerraSAR-X Stripmap August 27, 2007 pixel size of 12 meters

2.2 TerraSAR-X: effect of the achieved higher resolution (2) Hamburg TerraSAR-X Spotlight over Hamburg, 29 12 2007 5:42 UTC

2.3 TerraSAR-X: X-WAVE to obtain integrated wave parameters preliminary results published: The algorithm to derive significant wave height from TS-X SAR data presented as equation: Using Satellite 0.5 H s = x1 ( θspectral ) ( E (1.0 + Wave cos( αdata )) + for x2( Wave θ ) Energy Resource Characterization Pontes,M. T., Bruck, M. Lehener, S. A. and Kabuth In: ICOE 2010: 3rd International Conference on Ocean Energy, 6 October, Bilbao α - the wave peak direction related to the azimuth direction (0 α 90 ). E - the integrated value of the directional image spectrum in wave number space. Extraction θ - incidence of wave angle field from TerraSAR-X data Bruck, X 1 and M., x 2, Li,X.-M., coefficients and fited Lehner,S using the DWD wave model results, collocated buoys and WaMoS-radar. In: SEA-SAR-2010, Advances in SAR Oceanography from ENVISAT, ERS and ESA third party missions wave height obtained by the buoy located at Ekofisk oil platform shows a correlation of 0.83. 1km TS-X Spotlight mode VV VV polarization image acquired (10km 10km) on May acquired 15, 2009 on at Nov. 17:1919 14, UTC 2009 over at Ekofisk 10:57 UTC oil platform over the in NDBC North buoy Sea normalized spectrums: 1D integrated TS-X (in red) normalized spectrums: 1D integrated TS-X (in red) and WaMoS and buoy y( (in blue) for the measurements done at (in blue) on May 15, 2009 at 17:19 19 UTC over Ekofisk k oil platform. the location of the NDBC 44066 buoy The vertical black lines correspond to the buoy peak frequency

3.1 TerraSAR-X applications:tracking and implementation into modelling Stripmap on September 23, 2009 at 10:53 UTC Spotlight on 20.10.2009 at 21:36 UTC Rottenest Island, Australia NRCS random surface simulation by using wave spectra from a numerical wave model

3.2 TerraSAR-X applications: wave tracing Andrey Pleskachevsky: Investigation of wave propagation rays in near shore zones refraction of swell in shallow water (depth < 70m, 80m<L<300m) 2/12 Changing of wavelength depending on water depths TerraSAR-X (TSX) θ 30 0 Data used: TerraSAR-X Spotlight mode, 10x10km scenes, 1pixel 0.75m

3/12 Underwater bank detection 3.3 TerraSAR-X applications: wave tracing underwater topography (1) Andrey Pleskachevsky: Investigation of wave propagation rays in near shore zones Rottenest Island Underwater bank detection 1km TerraSAR-X Spotligth acquired on 20-10-2009

3.3 TerraSAR-X applications: wave tracing underwater topography (2) SAR image: Spotlight 3-D dept field derived from TeraSAR-X DEEPVIEW project Bathymetry Estimation Using TerraSAR-X and RapidEye Satellite Data no data Wavelenght field uniform mesh resolution of 150m

3.3 TerraSAR-X applications: wave tracing underwater topography (3) SAR image Comparison with echo-sounding data (different measurements, no errors are known) Wavelenght field bathymetry

3.3 TerraSAR-X applications: wave tracing underwater topography (4) TerraSAR-X SAR Andrey Pleskachevsky: Investigation of wave propagation rays in near shore zones Synergy SAR (TerraSAR-X) and optical information (QuickBird) QuickBird optic Depth estimation in domain 70-15m Depth estimation in domain 0-25m 150m uniform mesh Publication: (in preparation) Synergy and Fusion of Optical and Synthetic Aperture Radar Satellite Data for Underwater Topography Estimation in Costal Areas Pleskachevsky, A., Lehner, S. Heege, T., and C. Mott

5/12 3.3 TerraSAR-X applications: wave tracing underwater topography (5) Publication: Port Phillip Underwater Bottom-Topography in coastal areas from TerraSAR-X data, Melbourne Brusch,S., Held,P., Lehner,S., Rosenthal,W., and A.Pleskachevsky Journal of Remote Sensing (in print) 1km Duck Research PierInternational TerraSAR-X acquiredon onmarch March17, 17,2008 2008 TerraSAR-XSpotlight Spotlight acquired and wave rays SAR retrieved underwater topography compared against depth isolines from Topography obtained from TerraSAR-X TerraSAR X data [m] nautical chart. A

3.4 TerraSAR-X applications: wave tracing energy flux by swell waves Wave energy flux [J/m s] FLUX = E C g E = f(h s2 ) wave energy density per unit horizontal area C g = f(t,l) wave group velocity TerraSAR-X Spotlight: 25-02-2009 Heligoland Island North Sea

3.5 TerraSAR-X applications: SAR data into wave modelling (1) boundary and wind field derived from SAR numerical spectral wave model SAR Hs=1.2m Wave height derived from SAR Boundary spectra include swell part (from XWAVE) and wins-sea sea part (using JONSWAP by wind data) 1 km XWAVE - algorithm ago numerical spectral wave model K Mean value: ~ 1m DWD (WAM) model: ~ 1m Heligoland The Island K-model is a discrete spectral wave model adapted d to shallow waters and strong bottom gradients The K-model calculates the distribution of energy North Sea density E in the wave number domain (k,θ), θ is the wave direction TSX Spotlight acquired on 25.02.2009 Being an offspring of the WAM-Model, it contains some different source terms Wind field derived from TerraSAR-X XMOD - algorithm The wave breaking effect is implicitly Mean value: ~ considered 12m/s in the wind DWD: ~ 11m/s model via adequate energy loss due to non-linear dissipation (Kitaigorodski-scaling) Wind ~12m/s Topography 100x100m

3.5 TerraSAR-X applications: SAR data into wave modelling (2) boundary and wind field derived from SAR numerical spectral wave model random sea surface elevation Simulated using model spectrum Hs=1.2m shoaling shoaling shadowing 1 km refraction Heligoland Island refraction shadowing refraction shoaling wave height, m North Sea TSX Spotlight acquired on 25.02.2009 simulated wave height separated for swell and wind sea K-wave model on mesh 100x100m horizontal resolution

3.5 TerraSAR-X applications: SAR data into wave modelling (3) surface simulation by using wave spectra from numerical wave model Run: 10sec random sea surface elevation reproduced from model spectrum Hs=1.2m 1 km surface modeled for a short-crest wave propagation as train of individual mountains H=2m, L=50m Heligoland Island Pixel size 0.75m, SAR altitude 514km, North Sea SAR ground speed 7km/s TSX Spotlight acquired on 25.02.2009 Hs=1.5m, Tm2= 5sec Result: Integral-shaped structures visible as streaks sloped ~1 10 Θ ~ 1 10, L ~ 20 40m Modeled NRCS for a wave train traveling in direction 5 (up) and 45 (down) to range, incidence angle 52 (left) and 22 (right).

3.5 TerraSAR-X applications: SAR data into wave modelling (4) Slope and length of the structures in spectra height of the short-crest wind waves Hs=1.2m 1 km surface for short-crest wave as propagation of single mountain train shoaling 2 shoaling area 1 Wind ~13m/s

Sea State Measurement using Synthetic Aperture Radar Data Lehner, Susanne Pleskachevsky, Andrey Li, Xioming Brusch, Stephan 1. CWAVE_ENV sea state from ASAR ENVISAT underestimation of wave height in wave-model forecasting especially during storms 2. XWAVE sea state from TerraSAR-X high resolution data 3. Underwater topography banks, reefs detection and providing bathymetry maps 4. SAR data incorporation into wave modelling Thank you for your attention

Additional

Wind speed retrieved from HH polarizated Stripmap data of TerraSAR-X acquired over Sylt Island, North Sea on Mar. 26, 2008 (left, wind speed errors due to insufficient information are white masked, top right the location and quicklook are show). Wind from QuikSCAT scattorometer data (25km resolution) and DWD forecast model GSM (0.75 resolution) for the North Sea (bottom right). The retrieved wind fields show fine-scale turbulence effects which are not visible by coarser data.

Retrieved wind field (section 2.1 and fig.3) shows local variations (a), wave height simulated using TS-X derived wind ~10m s -1 at buoy position 54 46 2 N 8 22 8 E (c) corresponds with buoy measurement well (e). Varying the TS-X retrieved wind speed (increased and decreased at 3m s -1 ) results strong deviation about ~ 25% of modeled wave height (b, d).

Duck Research Pier Topography obtained from TerraSAR-X data [m] A TerraSAR-X Spotlight acquired on March 20, 2008 and wave rays