1. Simulation based METOP-A/AVHRR SST algorithms Sonia Péré, Hervé Roquet, Pierre LeBorgne Centre de Météorologie Spatiale, Météo-France, Lannion, France

2. SST from polar orbiters,OSI-SAF WORKSHOP,Lannion 5-6 March 2013 Outline  Objectives  Data  Nighttime algorithms –Residual errors –Validation errors  Daytime algorithms –Residual errors –Validation errors  Conclusion

3. SST from polar orbiters,OSI-SAF WORKSHOP,Lannion 5-6 March 2013 Objectives  SAFREE (Francois et al, 2002) has been extensively used for OSI- SAF algorithm determination.  Alternate (ECMWF) profile data bases can be used (Hervé’s talk) –« Chevallier_Ccmax »: Cloud Cover <0.4 –« Chevallier_RH »: RH< 95% (levels 54-91): « clear sky » only –ECMWF output sampling + cloudiness filtering (« CEPMMT ») To prepare the upgrade of polar orbiter SST chains: Our objective is a first testing of the impact of profile database on algorithm performances through:  Internal evaluation (on simulations)  MDB validation + comparison with « optimal » algorithm The formalisms considered are those used operationally for METOP-A processing.

4. SST from polar orbiters,OSI-SAF WORKSHOP,Lannion 5-6 March 2013 Data  SAFREE 402 profiles  Chevallier_CCmax 1499profiles  Chevallier_RHmax1183 profiles  CEPMMT 2108 profiles  METOP-A MDB period: 2011/12 to 2012/12 –Global area; qual 3-5; no sdi –Subset used for « optimal » algo determination: no sdi+ validation box cov. > 0.6

5. SST from polar orbiters,OSI-SAF WORKSHOP,Lannion 5-6 March 2013 Geographical distribution Chevallier_CCmax Chevallier_RHmax

6. SST from polar orbiters,OSI-SAF WORKSHOP,Lannion 5-6 March 2013 Tskin –T11 distribution vs T11-T12 at secant =1 Color scale: W water vapour content SAFREECEPMMTChevallier_CCmax Chevallier_RHmax Cloudiness induced excessive water vapour content

7. SST from polar orbiters,OSI-SAF WORKSHOP,Lannion 5-6 March 2013 Nighttime algorithms sst=((a+(b*(sec-1)))*bt37)+((c+(d*(sec-1)))*(bt108-bt120))+(e*(sec-1))+f algobiasstdnbcas SAFREE0.3065535 cepmmt0.30410205 Chev+RHmax0.3295440 Residual st dev algobiasstdnbcas SAFREE0.2560.3205535 cepmmt0.2760.30810205 Chev+RHmax0.1660.3345440 Operational applied to simulation Optimal (mdb) 0.385143456 Coefficients obtained by regression on simulated bTS + noise

8. SST from polar orbiters,OSI-SAF WORKSHOP,Lannion 5-6 March 2013 Residual errors vs lat SAFREE Chevallier Rhmax CEPMMT Nightime algorithm residual errors (tsalgo-tskin)

9. SST from polar orbiters,OSI-SAF WORKSHOP,Lannion 5-6 March 2013 Nighttime algorithm: MDB validation results 215 232 cases

10. SST from polar orbiters,OSI-SAF WORKSHOP,Lannion 5-6 March 2013 Nighttime algorithm: MDB validation results Validation map : Optimal

11. SST from polar orbiters,OSI-SAF WORKSHOP,Lannion 5-6 March 2013 Nighttime algorithm: MDB validation results Validation map : SAFREE

12. SST from polar orbiters,OSI-SAF WORKSHOP,Lannion 5-6 March 2013 Nighttime algorithm: MDB validation results Validation map : Chevallier_RH

13. SST from polar orbiters,OSI-SAF WORKSHOP,Lannion 5-6 March 2013 Nighttime algorithm: MDB validation results Validation map : CEPMMMT

14. SST from polar orbiters,OSI-SAF WORKSHOP,Lannion 5-6 March 2013 Err vs msr Err vs t11-t12 err vs satzen Err vs SatzenErr vs lat Algo optimal Chev_Rhmax SAFREE CEPMMT

15. SST from polar orbiters,OSI-SAF WORKSHOP,Lannion 5-6 March 2013 Daytime algorithms Sst_NLC=(a+b*(sec-1))*bt108+(c+d*clim+e*(sec-1))*(bt108-bt120)+f*(sec-1)+g Algo NLCbiasstdnbcas SAFREE0.8214635 CEPMMT0.61110025 Chev+rhmax0.8185440 Residual st.dev. Algo NLCbiasstdnbcas SAFREE0.0150.8534635 CEPMMT0.0400.65910025 Chev+RHmax-0.0510.8885440 Operational applied to simulation optimal0.539143456

16. SST from polar orbiters,OSI-SAF WORKSHOP,Lannion 5-6 March 2013 Daytime algorithm residual errors (tsalgo-tskin) Distribution map of residual errors : SAFREE

17. SST from polar orbiters,OSI-SAF WORKSHOP,Lannion 5-6 March 2013 Daytime algorithm residual errors (tsalgo-tskin) Distribution map of residual errors : Chevallier RH

18. SST from polar orbiters,OSI-SAF WORKSHOP,Lannion 5-6 March 2013 Daytime algorithm residual errors (tsalgo-tskin) Distribution map of residual errors : CEPMMT

19. SST from polar orbiters,OSI-SAF WORKSHOP,Lannion 5-6 March 2013 Residual errors vs lat SAFREE Chevallier Rhmax CEPMMT Daytime algorithm residual errors (tsalgo-tskin)

20. SST from polar orbiters,OSI-SAF WORKSHOP,Lannion 5-6 March 2013 Daytime algorithm: MDB validation results nbcas: 318528

21. SST from polar orbiters,OSI-SAF WORKSHOP,Lannion 5-6 March 2013 Daytime algorithm: MDB validation results Validation map : Optimal

22. SST from polar orbiters,OSI-SAF WORKSHOP,Lannion 5-6 March 2013 Daytime algorithm: MDB validation results Validation map : Safree

23. SST from polar orbiters,OSI-SAF WORKSHOP,Lannion 5-6 March 2013 Daytime algorithm: MDB validation results Validation map : Chevallier RH max

24. SST from polar orbiters,OSI-SAF WORKSHOP,Lannion 5-6 March 2013 Daytime algorithm: MDB validation results Validation map : CEPMMT

25. SST from polar orbiters,OSI-SAF WORKSHOP,Lannion 5-6 March 2013 Err vs msr Err vs t11-t12 Err vs SatzenErr vs lat Algo optimal Chev_Rhmax SAFREE CEPMMT

26. SST from polar orbiters,OSI-SAF WORKSHOP,Lannion 5-6 March 2013 Conclusions  CEPMMT («natural» sampling) produces a more robust algorithm than Chevallier («variability» driven)  CEPMMT derived algorithms shows standard deviations close to optimal  All algorithms show regional errors and need a bias correction when applied in the « true » world  Further work –Introduce simulation adjustment before regression –Analyze other formalisms?