igarss2011_lion.pptx

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  • Results similar using other standard deviations for the observation error distribution
  • igarss2011_lion.pptx

    1. 1. modeling and applications OF swot satellite data <br />C. Lion1, K.M. Andreadis2, R. Fjørtoft3,<br />F. Lyard4, N. Pourthie3, J.-F. Crétaux1<br />1LEGOS/CNES, 2Ohio State University/JPL<br />3CNES, 4LEGOS/CNRS<br />
    2. 2. SWOT mission<br />1<br />NASA and CNES, launch in 2019<br />970km orbit, 78°inclination, 22 days repeat<br />KaRIN: InSAR Ka band<br />Wide swath altimeter<br />Ocean: “Low resolution” <br />meso-scale and submeso-scale<br />phenomena (10km and greater)<br />Hydrology: “High resolution”<br />surface area above (250m)² <br />rivers above 100m<br />970 km<br />
    3. 3. 2<br />Preparing the mission for hydrology<br />Modelisation and simulation for technical use<br />2. SAR amplitude image:<br /> Rhone river, France<br /> CNES/ Altamira information simulator<br />1. Radar cross section<br /> CNES/ CAP Gemini simulator<br />
    4. 4. Goals<br />Need for a simulator for scientific users (hydrology)<br />“Fast”: 3 months  3min<br />Easy to use: no need for heavy preparation of input data<br />Portable<br />Relatively realistic errors<br />Targets: deltas, rivers, lakes…<br />Output: water elevation<br />3<br />Simulator output: water height<br />The Amazon river, Brazil<br />
    5. 5. Simulator principle<br />Based on works of:<br />S. Biancamaria and M. Durand: swath calculation, principle<br />V. Enjolras: residual error calculation<br />4<br />
    6. 6. Simulator principle<br />Based on works of:<br />S. Biancamaria and M. Durand: swath calculation, principle<br />V. Enjolras: residual error calculation<br />5<br />
    7. 7. Simulator principle<br />Based on works of:<br />S. Biancamaria and M. Durand: swath calculation, principle<br />V. Enjolras: residual error calculation<br />6<br />
    8. 8. Residual height errors<br />7<br />Taken into account<br />Roll<br />Baseline variation<br />Thermal noise<br />Geometric decorrelation<br />BAQ noise<br />Satellite position<br />Not taken into account yet<br />Troposphere<br />Layover<br />Shadow<br />Processing (classification…)<br />….<br />
    9. 9. Residual height errors: Roll<br />Roll<br />8<br />B<br />a<br />i<br />R<br />r1<br />r2<br />H<br />h<br />
    10. 10. Residual height errors<br />Baseline<br />9<br />E_b<br />B<br />i<br />R<br />r1<br />r2<br />H<br />h<br />
    11. 11. Residual height errors<br />Coherence loss<br />g = gSNR + gSQRN + gg<br />N number of looks<br />10<br />B<br />i<br />R<br />r1<br />r2<br />H<br />h<br />
    12. 12. Simulator principle<br />Based on works of:<br />S. Biancamaria and M. Durand: swath calculation, principle<br />V. Enjolras: residual error calculation<br />11<br />
    13. 13. Simulator principle<br />Based on works of:<br />S. Biancamaria and M. Durand: swath calculation, principle<br />V. Enjolras: residual error calculation<br />12<br />m<br />
    14. 14. Simulator principle<br />Based on works of:<br />S. Biancamaria and M. Durand: swath calculation, principle<br />V. Enjolras: residual error calculation<br />13<br />
    15. 15. Simulation: Ohio River<br />14<br />3 months modelizationcourtesy: K. Andreadis<br />40.5<br />40.5<br />40<br />40<br />Latitude<br />Latitude<br />39.5<br />39.5<br />39<br />39<br />38.5<br />38.5<br />275<br />276<br />277<br />278<br />279<br />275<br />276<br />277<br />278<br />279<br />Longitude<br />Longitude<br />Input: Model LisFLOOD<br />Reference water height (m)<br />Output: Water height observed<br /> by SWOT (m)<br />
    16. 16. Assimilation methodology<br />15<br />Assimilating SWOT observations in a identical twin synthetic experiment<br />Ohio River study domain (only main stem)<br />LISFLOOD hydraulic model<br />Ensemble Kalman filter<br />Errors introduced to boundary inflows, channel width, depth and roughness<br />Observation errors from a Gaussian distribution N(0,5cm)<br />courtesy: K. Andreadis<br />
    17. 17. 16<br />Assimilation results<br />Water surface elevation along the river channel at two SWOT overpass times<br />208 Hours<br />280 Hours<br />Information is not always propagated down/up stream<br />Small ensemble size could partly be the reason <br />courtesy: K. Andreadis<br />
    18. 18. Conclusions<br />Simulation of SWOT data with more representative errors<br />The simulator is more user friendly: output format as input format, GUI, can be used with several models<br />Can be used for assimilations studies (estimate indirect valuables)<br />Need to improve the simulator: layover, decorrelation due to vegetation, troposphere …<br />17<br />
    19. 19. Thank for your attention<br />

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