1. Real time Arctic SST retrieval from satellite IR data issues and solutions(?) Pierre Le Borgne, Gérard Legendre, Anne Marsouin, Sonia Péré, Hervé Roquet Centre de Météorologie Spatiale, Météo-France, Lannion, France

2. Earthtemp Arctic SST workshop 18-19 December, Exeter Outline METOP-A/AVHRR derived daytime SST in September 2013 -Data -METOP-A (daytime) -Atmospheric profile data set -Validation results (5years) -Regional algorithms -Use of NWP outputs -Conclusions

3. Earthtemp Arctic SST workshop 18-19 December, Exeter Data : METOP-A SST  METOP-A:1km resolution SST, Global coverage since 2007  METOP SST (see http://www.osi-saf.org )http://www.osi-saf.org –Cloud mask (Maia, L. Lavanant, MF/CMS) –Ice mask (Ice probability, S. Eastwood, met.no) –Cloud/ice control –Daytime algorithm SST = a T 11 + (b T CLI + c S  ) (T 11 - T 12 ) + d S  + e  MDB: 5 year Matchups at full resolution; buoy location in central pixel within 3 hrs

4. Earthtemp Arctic SST workshop 18-19 December, Exeter DATA: ECMWF output derived BT simulations (CEP+)  ECMWF operational forecasts  RTTOV version 10.2 applied onto each profiles  BTs at 3.7, 10.8 and 12  m Training dataset 60N

5. Earthtemp Arctic SST workshop 18-19 December, Exeter Daytime « Arctic » validation results Error vs clear sky coverage: Clouds induce negative errors (no evidence of ice related errors) Error vs T11-T12 5 year MDB All cov n  QL 3-5 174050.050.66 Simulated Error vs T11-T12 Simul. CEP+ n  5340.220.34

6. Earthtemp Arctic SST workshop 18-19 December, Exeter Validation conclusions  Significant influence of cloud contamination –Improved cloud/ice detection effort: met.no  Errors determined by the shape of atmospheric profiles: (ex: summer temperature inversion cases lead to large positive errors)  Errors well reproduced by simulations

7. Earthtemp Arctic SST workshop 18-19 December, Exeter Solutions 1)Multisensor Bias corrections (Hoyer et al, 2013, RSE, in press) AATSR and NAVOCEANO GAC data as reference 2) Regional algorithms NLC SST = (a + b S  ) T 11 + (c + d T CLI + e S  ) (T 11 - T 12 ) + f +g S  CASSTA SST = (a + b S  ) T 11 +c +d S  3) NWP derived correction methods

8. Earthtemp Arctic SST workshop 18-19 December, Exeter Regional algorithms ? 5 Year MDB +Cloud filtering reinforced: cov> 0.8; QL 4-5 Three regimes?

9. Earthtemp Arctic SST workshop 18-19 December, Exeter Regional algorithms Regional algorithms applied on the 5 year MDB 6143 cases (cov>0.8) QL 4-5 Operational NLC Simulation derived regional NLC Optimal regional NLC Optimal CASSTA (T10.8)  0.280.250.  0.450.500.440.64 Simulation dataset (CEP+) not adequate to determine regional algorithms T10.8 based algo Not convincing

10. Earthtemp Arctic SST workshop 18-19 December, Exeter NLC vs CASSTA on MDB T108- T120 max 0.0.10.20.5 Optimal NLC 0.760.730.750.59 Optimal CASSTA 0.770.740.780.68 Residual standard deviation on MDB

11. Earthtemp Arctic SST workshop 18-19 December, Exeter NWP derived methods  Simulations must be « exact »: they should produce the same BTs as would be observed, given a surface temperature and atmospheric profiles: A BT simulation adjustment step is necessary We need to compare observations and simulations (in consistent conditions)

12. Earthtemp Arctic SST workshop 18-19 December, Exeter Simulations too cold

13. Earthtemp Arctic SST workshop 18-19 December, Exeter Low wind zones: DW!

14. Earthtemp Arctic SST workshop 18-19 December, Exeter OSTIA and DW in the Arctic? Filter: 7 ms-1? June 2012June 2013June 2011

15. Earthtemp Arctic SST workshop 18-19 December, Exeter Relative number of clear sky cases with wind > 7ms-1 July 2012

16. Earthtemp Arctic SST workshop 18-19 December, Exeter Daytime prototype results in 2012 summer Arctic June July August 2012, lat > 60°N 1070 casesOperational NLC Operational NLC + bias correction Optimal HL NLC OSTIA d-0.10-0.13-0.12-0.31 s0.600.550.520.37

17. Earthtemp Arctic SST workshop 18-19 December, Exeter Trends with latitude Operational NLC + bias correction Optimal HL NLCOSTIA

18. Earthtemp Arctic SST workshop 18-19 December, Exeter Operational SST retrieval methods in Arctic  Global daytime algorithm leads to SST overestimations by several tenths of K for T108-T120 below 0.5K  Regional algorithms may solve the problem, however simulation derived algorithms necessitate dedicated profile data sets  DW induced differences between OSTIA and observed SST make NWP derived simulation adjustments quite difficult in permanent daylight conditions  Drastic wind filtering (> 10ms-1) has lead to satisfactory results.

19. Earthtemp Arctic SST workshop 18-19 December, Exeter Further work  CMS to write a paper on 5 (7) years of METOP-A Arctic results  X(?) to build up a profile database adapted to Arctic studies  CMS to prepare regional HL algorithms as a backup to simulation derived BTs for METOP-B  CMS & DMI to compare METOP biases (NWP derived vs Jacob’s method)  …….

20. Earthtemp Arctic SST workshop 18-19 December, Exeter 10.8 micron simulation error on the 1st of June 2012

21. Earthtemp Arctic SST workshop 18-19 December, Exeter Summertime error origin (see also LeBorgne et al, EUMETSAT Oslo 2011) 0.5<T11-T12 <0.7 Air temp. dt/dq 0.5<T11-T12 <0.7 Normal case  =0.04,  =0.16 0.<T11-T12 <0.3 Air temp. dt/dq 0.<T11-T12 <0.3 Summer Arctic Case  =0.55,  =0.21

22. Earthtemp Arctic SST workshop 18-19 December, Exeter Trends with T108-T120 Operational NLC + bias correction Optimal HL NLC

23. Earthtemp Arctic SST workshop 18-19 December, Exeter

24. Anomalies in Sept 2013 METOP-A/AVHRR derived daytime SST in September 2013