This document discusses modeling and applications of SWOT satellite data. The SWOT mission, launching in 2019, will use Ka-band radar interferometry and a wide swath altimeter to measure ocean and inland water elevations. A simulator was developed to generate realistic SWOT observations for scientific users studying hydrology. The simulator works quickly, is easy to use, and incorporates errors from various sources like thermal noise and baseline variation. The simulator output has been used to assimilate simulated SWOT data into hydraulic models of rivers, like the Ohio River, to estimate water surface elevations. Further improvements to the simulator are still needed to account for additional error sources like layover and atmospheric delays.

1. modeling and applications OF swot satellite data C. Lion1, K.M. Andreadis2, R. Fjørtoft3,F. Lyard4, N. Pourthie3, J.-F. Crétaux11LEGOS/CNES, 2Ohio State University/JPL3CNES, 4LEGOS/CNRS

2. SWOT mission1NASA and CNES, launch in 2019970km orbit, 78°inclination, 22 days repeatKaRIN: InSAR Ka bandWide swath altimeterOcean: “Low resolution” meso-scale and submeso-scalephenomena (10km and greater)Hydrology: “High resolution”surface area above (250m)² rivers above 100m970 km

3. 2Preparing the mission for hydrologyModelisation and simulation for technical use2. SAR amplitude image: Rhone river, France CNES/ Altamira information simulator1. Radar cross section CNES/ CAP Gemini simulator

4. GoalsNeed for a simulator for scientific users (hydrology)“Fast”: 3 months  3minEasy to use: no need for heavy preparation of input dataPortableRelatively realistic errorsTargets: deltas, rivers, lakes…Output: water elevation3Simulator output: water heightThe Amazon river, Brazil

5. Simulator principleBased on works of:S. Biancamaria and M. Durand: swath calculation, principleV. Enjolras: residual error calculation4

6. Simulator principleBased on works of:S. Biancamaria and M. Durand: swath calculation, principleV. Enjolras: residual error calculation5

7. Simulator principleBased on works of:S. Biancamaria and M. Durand: swath calculation, principleV. Enjolras: residual error calculation6

8. Residual height errors7Taken into accountRollBaseline variationThermal noiseGeometric decorrelationBAQ noiseSatellite positionNot taken into account yetTroposphereLayoverShadowProcessing (classification…)….

9. Residual height errors: RollRoll8BaiRr1r2Hh

10. Residual height errorsBaseline9E_bBiRr1r2Hh

11. Residual height errorsCoherence lossg = gSNR + gSQRN + ggN number of looks10BiRr1r2Hh

12. Simulator principleBased on works of:S. Biancamaria and M. Durand: swath calculation, principleV. Enjolras: residual error calculation11

13. Simulator principleBased on works of:S. Biancamaria and M. Durand: swath calculation, principleV. Enjolras: residual error calculation12m

14. Simulator principleBased on works of:S. Biancamaria and M. Durand: swath calculation, principleV. Enjolras: residual error calculation13

15. Simulation: Ohio River143 months modelizationcourtesy: K. Andreadis40.540.54040LatitudeLatitude39.539.5393938.538.5275276277278279275276277278279LongitudeLongitudeInput: Model LisFLOODReference water height (m)Output: Water height observed by SWOT (m)

16. Assimilation methodology15Assimilating SWOT observations in a identical twin synthetic experimentOhio River study domain (only main stem)LISFLOOD hydraulic modelEnsemble Kalman filterErrors introduced to boundary inflows, channel width, depth and roughnessObservation errors from a Gaussian distribution N(0,5cm)courtesy: K. Andreadis

17. 16Assimilation resultsWater surface elevation along the river channel at two SWOT overpass times208 Hours280 HoursInformation is not always propagated down/up streamSmall ensemble size could partly be the reason courtesy: K. Andreadis

18. ConclusionsSimulation of SWOT data with more representative errorsThe simulator is more user friendly: output format as input format, GUI, can be used with several modelsCan be used for assimilations studies (estimate indirect valuables)Need to improve the simulator: layover, decorrelation due to vegetation, troposphere …17

19. Thank for your attention