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Analysis of AMSR-E C & X-band Tb data dependencies with wind & wave characteristics

Analysis of AMSR-E C & X-band Tb data dependencies with wind & wave characteristics. Questions ?. How is Roughness - induced sea surface emissivity in the low frequency microwave domain dependent with sea surface state & wave developement ?

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Analysis of AMSR-E C & X-band Tb data dependencies with wind & wave characteristics

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  1. Analysis of AMSR-E C & X-band Tb data dependencieswithwind & wavecharacteristics

  2. Questions ? • How isRoughness-inducedsea surface emissivity in the lowfrequencymicrowavedomaindependentwithsea surface state & wavedevelopement ? • Impacts of swell, pure windseas or mixed sea states on the emissivityat X, C & L -bands? • Needs to getsea state parametrization & active/passive roughnesseffectsconsistency in the aquarius L-band SSS retrievalalgorithm

  3. How ? • Collect one month (aug 2010) of global L2A AMSR-E Tbs & L2 oceanproducts (sst, wind, water vapor, …) • Evaluate surface emissivity e surfresidualsbased on Wentzalgorithm for atmospheric & external sources corrections • Co-locate AMSR-E data withwaveparameters (total significantwaveheightHs, significantwaveheight for windseaHsws ) from ECMWF-WAM model forecasts (3-hourlyat 0.25° res) and ECMWF U10 • Estimateroughness-inducedresidualsΔeroughusing in situ SSS & AMSRE.SST to evaluate flat sea contribution • Look @ statisticaldepedencies of Δeroughwithbins of Hs,U10 & Hsws

  4. SSS fieldfrom in situ data Déploiement, Collecte & Traitement des Données In situ de surface pour la Validation de SMOS Projet GLOSCAL

  5. Objectivelyanalyzedin situ SSS Exemple of the Data set over 1 month @ 25 km resolution ObjectivelyAnalyzed Standardized in situ data +climatology LPO LPO

  6. Estimating the Flat sea surface Tbs contributions Dielectric constant model (Klein & swift, 76)

  7. Estimatedmonthlymean-averagedFlat sea surface Tbs contributions for X & C, H-V AMSR-E channels

  8. Estimated surface Tbsfrom X & C, H-V AMSR-E data

  9. Wind & waveproducts

  10. Co-localisation AMSR-ECMWF: |Δ t|<1.5 Hour & | Δ x|<25 km

  11. Estimatedmonthly-averagedroughnessinducedemissivityresiduals

  12. Mean Roughnessinducedemissivityresiduals as function of surface wind speed

  13. Mean Roughnessinducedemissivityresiduals as function of surface wind speed & total significantwave-height

  14. Illustration of the Mean Large ScaleWave impact on Roughnessinducedemissivityresidualsat a fixed surface wind speed of ~5 m/s Selection of data for ECMWF winds 4.5<U10<5.5 m/s Histograms of Hs for all waves and windseaat U10~5m/s Wind sea~0.5m The Hs changes atU10~5m/s are dominated by swell impact swells~0.5-3 m Very distinct distributions

  15. Illustration of the Mean Large ScaleWave impact on Roughnessinducedemissivityresidualsat a fixed surface wind speed of ~5 m/s Selection of data for ECMWF winds 4.5<U10<5.5 m/s For wind speed ~5 m/s, swells affect surface emissivityat 55° incidence angle and H-pol, have a negligible impact in V-pol

  16. Illustration of the Mean Large ScaleWave impact on Roughnessinducedemissivityresidualsat a fixed surface wind speed of ~8 m/s

  17. Monthlyaverage signature of tropical freswaterpools in AMSR-E Tbs

  18. Monthlyaverage signature of Tropical Atlantic freshwaterpools in AMSR-E Tbs Niger River Senegal & Geba Rivers Congo River Orrinoco River Amazon River

  19. Mississipi Delta Freshwaterrunoffinto the Tehuantepec Gulf

  20. Ganges and Brahmaputra Rivers Irrawaddy Delta Indus Delta

  21. Yangtse River

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