1 / 27

MIRE Tests Based on LOCEAN and Cardioid Model

MIRE Tests Based on LOCEAN and Cardioid Model. Xiaobin Yin, Jacqueline Boutin LOCEAN May, 5, 2009. Outline. Introduction to MIRE data Tests for open ocean area 1 MIRE with reduced constant noise 2 MIRE with realistic noise Tests for iceberg and ice area 1 MIRE with realistic noise

nixie
Télécharger la présentation

MIRE Tests Based on LOCEAN and Cardioid Model

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. MIRE Tests Based on LOCEAN and Cardioid Model Xiaobin Yin, Jacqueline Boutin LOCEAN May, 5, 2009

  2. Outline • Introduction to MIRE data • Tests for open ocean area 1 MIRE with reduced constant noise 2 MIRE with realistic noise • Tests for iceberg and ice area 1MIRE with realistic noise • Academic retrieval with Cardioid model

  3. -Introduction to MIRE data- Simulated uniform area -50°~-40°, 11 icebergs (4x4km) -70°~-60°, Ice area (-10℃)

  4. -Snapshot of Th- MIRE data with reduced noise (the one in prototype) MIRE data with realistic noise (the one given by Ingo) 0° 10° 0° 10° -40° -40° -45° -45° -50° -50°

  5. -Snapshot of Th- MIRE data with reduced noise (the one in prototype) MIRE data with realistic noise (the one given by Ingo) -70° -70°

  6. -Radiometric Accuracy- MIRE data with reduced noise (the one in prototype) MIRE data with realistic noise (the one given by Ingo) 1734*50/216=1.32K, 4196*50/216=3.20K 197*50/216=0.15K

  7. -Introduction to MIRE data- The forward models used to compute brightness temperatures are: For the sea: Two scale model for roughness computation. No foam. Galactic noise model 0 (constant value for incident galactic noise contribution, 3.7K). Constant atmosphere contribution (sea surface pressure=1013 hPa, Tair- SST=0). TEC (10 TECu) For the ice: Dielectric constant = 3.17 + 0.j (imaginary part = 0) Apply Fresnel in order to obtain reflectivity coefficients rh and rv Use surface temperature (ST) 263K in order to compute TH and TV TH=(1-rh)*ST TV=(1-rv)*ST Same atmosphere and galactic noise reflection model than for ocean. Finally, reduced or realistic radiometric noises are added.

  8. -Tests for open ocean area-MIRE with reduced constant noise Retrieving model: Common parts Two scale model of LOCEAN, constant data for atmospheric contribution (sea surface pressure=1013 hPa, Tair-SST=0) Differences: Case 1 Tb_galactic=3.7K, no error in Tb model and prior parameter. • Case 2 Tb_galactic=0K, no error in Tb model and prior parameter. • Case 3 Tb_galactic=0K, ΔTbmodel is 0.5K, ΔSSSprior is 100, ΔSSTprior is 1K, ΔWSU and ΔWSV are 1.5m/s, and ΔTEC is 5 TecU.

  9. -Tests for open ocean area-MIRE with reduced constant noise-Case 1 (The methods used togenerate L1c Tb) Theoretical uncertainty computed for SSS1, outputs of L2pp (Level 2 Prototype Processor)

  10. -Tests for open ocean area-MIRE with reduced constant noise-Case 1 Theoretical uncertainty computed for Acard4, outputs of L2pp

  11. SSS4 Cardioid Model (Model 4) Model of ocean surface emission According to Waldteufel et al. (2004), Bcard=0.8 Acard4 + SST4 Outputs of L2pp LOCEAN Model (Model 1) SSS1 +SST1 Outputs of L2pp Acard1

  12. -Tests for open ocean area- MIRE with reduced constant noise-Case 2 (same as case 1 except that Tb_galactic=0K)

  13. -Inner and marginal region of swath- Marginal Marginal Inner -320km~320km

  14. -Tests for open ocean area-MIRE with reduced constant noise- Case 3 (same as case 1 except that Tb_galactic=0K, ΔTbmodel=0.5K, ΔSSSprior=100, ΔSSTprior=1K, ΔWSU=ΔWSV=1.5m/s, ΔTEC=5 TecU)

  15. -Tests for open ocean area- MIRE with reduced constant noise In some cases, mean error in inner region of smos swath (-320~320km) is different to that in marginal region of smos swath (-600~-320km and 320~600km). Bias plus noise in Tb measurement, Tb model or priors will lead to this difference between two regions.

  16. -Tests for open ocean area- MIRE with realistic noise- Case 1 (The methods used togenerate L1c Tb) Theoretical uncertainty computed for SSS1, outputs of L2pp

  17. -Tests for open ocean area- MIRE with realistic noise- Case 1 Mean=0.072 psu,rms=0.287psuSSS outputs of L2pp Mean=-0.051 psu, rms=0.343psu

  18. -Tests for open ocean area- MIRE with realistic noise- Case 1 Theoretical uncertainty computed for Acard4, outputs of L2pp

  19. -Tests for open ocean area- MIRE with realistic noise- Case 1 Mean=-0.045,Rms=0.300 Mean=0.063,Rms=0.250SSS outputs of L2pp

  20. -Tests for open ocean area- MIRE with realistic noise- Case 3 (same as case 1 except that Tb_galactic=0K, ΔTbmodel=0.5K, ΔSSSprior=100, ΔSSTprior=1K, ΔWSU=ΔWSV=1.5m/s, ΔTEC=5 TecU)

  21. -Tests for open ocean area- MIRE with realistic noise- Case 3

  22. -Tests for open ocean area- MIRE with realistic noise- Case 3 SSS1r – SSSp , mean=-3.28 , std=0.78 SSS4r – SSSp , mean=-4.18 , std=0.39 SST1r – SSTp , mean=-0.19 , std=0.16 SST1r – SSTp , mean=-0.64 , std=0.34 Acard1r – Acardt , mean=-2.90 , std=0.57 Acard4r – Acardt , mean=-3.84 , std=0.25

  23. -Tests for iceberg and ice area-MIRE with realistic noise- Case 1 (The methods used togenerate L1c Tb)

  24. -Tests for iceberg and ice area-MIRE with realistic noise - Case 1 - Case 3

  25. -Academic retrieval of Cardioid model- Tb=fr_ice x Tb_ice + (1-fr_ice) x Tb_ocean black, ε=5+0.5i; Ts(land)=263K; red, ε=3.17; Ts(ice)=263K; blue, ε=5+0.5i; Ts(ice)=275K; Slopes of SST and Acard are different with different sea fraction If SST and Acard or their slopes retrieved in Cardioid model could be used to account for sea fraction?

  26. Conclusion 1) As expected, case 1 gives almost no error in retrieved SSS and Acard for MIRE with reduced noise, which means prototype runs well. 2) A bias in Tb will cause biases in retrieved Acard and SST from Cardioid model. 3) In some cases, mean error in inner region of smos swath (-320~320km) is different to that in marginal region of SMOS swath (-600~-320km and 320~600km). Bias plus error in Tb measurement, Tb model or priors will lead to this difference between two regions.An indicator for bias in Tb measurements or Tb model? 3) Icebergs can be detected by retrieved SSS and Acard, even in case of Tb with bias. However, this can not be seen in SST. Maybe this is because of that iceberg is too small, being only 1% of SMOS ground resolution. 4) Retrieved SST in ice edge area from Model 1 (LOCEAN model) is quite different to that from Cardioid model. SST from Cardioid model is a function of sea fraction. Perspective 1) Test icebergs in different size 2) Using SST and Acard or their slopes retrieved in Cardioid model to account for sea fraction

  27. Thanks !

More Related