1. Research and development on satellite data assimilation at the Canadian Meteorological Center L. Garand, S. K. Dutta, S. Heilliette, M. Buehner, and S. MacPherson World Weather Open Science Conference 2014 Montreal, Qc August 16-21, 2014

2. DRAFT – Page 2 – November 10, 2015 Outline Current data assimilation context Progress on the assimilation of surface sensitive infrared radiances over land Progress on the use of inter-channel error correlations Observing System Simulation Experiments capability Conclusion

3. DRAFT – Page 3 – November 10, 2015 New data assimilation context EC moving to ensemble-variational (EnVar) system with: Flow-dependent background errors including surface skin temperature correlations with other variables Analysis grid at 50 km, increments interpolated to model 25 km grid, 80 levels ~140 AIRS and IASI channels assimilated: many sensitive to low level T, q, and Ts. Assimilation of North America ground-based GPS (impacts humidity analysis)

4. DRAFT – Page 4 – November 10, 2015 Ensemble spread of Ts (Jan-Feb 2011 ) 00 UTC 06 UTC 12 UTC 18 UTC Maximum ~15h local In SH (summer) Maximum at night Tibetan area (winter) Ts background error over land in 4Dvar is Constant: 3 K. In EnVar background Error is 50% ENKF, 50% static (NMC)

5. DRAFT – Page 5 – November 10, 2015 Assimilation of surface-sensitive IR radiances over land Key challenges: Reliable cloud mask Spectral emissivity definition Highly variable topography Radiance bias correction Background and observation error definition

6. DRAFT – Page 6 – November 10, 2015 Approach guided by prudence Assimilate surface sensitive radiances under restrictive conditions over land and sea ice: Estimate of cloud fraction < 0.01 High surface emissivity (> 0.97) Relatively flat terrain (std of height < 100 m at 50 km scale) Diff between background Ts and rough retrieval < 4 K Radiance bias correction approach: For channels flagged as being surface sensitive, use only ocean data to update bias coefficients.

7. DRAFT – Page 7 – November 10, 2015 Limitation linked to topography Criterion used: local STD of topography < 50 m (on 3X3 ~50 km areas) RED: accepted, white std > 100 m, blue 100>std>50 m

8. DRAFT – Page 8 – November 10, 2015 Limitation linked to surface emissivity Surface emissivity AIRS ch 787 Emissivity based on CERES land types (~15 km) + weighted average for water/ice/snow fraction. Accept only emissivity > 0.97 ; Bare soil, open shrub regions excluded.

9. DRAFT – Page 9 – November 10, 2015 Assigned observation error to radiances 15.0  m4.13  m15.3  m4.50  m Assigned = f std(O-P) Desroziers = f typically in range1.6-2.0

10. DRAFT – Page 10 – November 10, 2015 First attempt: negative impact in regions 60-90 N/S 00 hr 72hr Possible cause: cloud contamination Risk reduction: no assimilation at latitudes > 60 deg.

11. DRAFT – Page 11 – November 10, 2015 Second attempt with added constraints Exclude latitudes > 60 deg Limit gradient of topography to 50 m (previously 100m) Strong sensitivity of this parameter to std(O-B) of surface channels

12. DRAFT – Page 12 – November 10, 2015 Temp std difference vs lead time NH-Extra_trop vs ERA Interim vs own analysis Consistent positive impact vs ERA Interim and own

13. DRAFT – Page 13 – November 10, 2015 T std diff (CNTL-EXP) vs ERA-Interim Tropics SH Extratropics

14. DRAFT – Page 14 – November 10, 2015 Time series of T std diff at 925 hPa NH extratropics Tropics CNTL EXP EXP superior to CNTL 55-65% of cases at days 3-5

15. DRAFT – Page 15 – November 10, 2015 850 hPa Temp anomaly corr. NH extratropics Tropics CNTL EXP

16. DRAFT – Page 16 – November 10, 2015 120-h N-Extr vs ERA-Interim CNTL EXP

17. DRAFT – Page 17 – November 10, 2015 Validation vs raobs 120-h FEB-Mar 2011 (59 days) North America Europe CNTL EXP U V GZ T

18. DRAFT – Page 18 – November 10, 2015 Added yield: about 15% (for surface sensitive channels) Number of radiances assimilated for surface channel AIRS 787 CNTL: ~1400/6h EXP: ~1600/6h CNTL EXP Region: world, EXP excludes surface-sensitive channels at latitudes > 60 Radiance thinning is at 150 km

19. DRAFT – Page 19 – November 10, 2015 R&D on Inter-channel error correlations Approach based on Desroziers et al. 2005. It allows for a simple evaluation of the R matrix using assimilation by- products (O-A) and (O-B) for channels i,j : R = Bormann et al. demonstrated that this method gives similar results as other methods No adjustable parameter

20. DRAFT – Page 20 – November 10, 2015 Known limitations The approach makes use of several assumptions (as other methods such as Hollingsworth-Longberg): –Unbiased observations –Uncorrelated Background and Observation errors –Well specified B matrix

21. DRAFT – Page 21 – November 10, 2015 Implementing the approach Desroziers diagnostic was applied using 21 days of quality controlled and bias corrected radiances assimilated in a reference cycle. The resulting Desroziers matrix was symmetrized: Estimates done for all radiances: AIRS, IASI, AMSU-A, AMSU-B, and SSM/I. Variances on diagonal still inflated (1.6 std(O-P)) 2 Added modest 3% to analysis time Did not affect convergence of analysis cost function, using standard pre-conditioning

22. DRAFT – Page 22 – November 10, 2015 Sample diagnosed correlations Correlation structure of the symmetrized R for the 142 AIRS channels selected for assimilation High correlations for water vapor and surface channels

23. DRAFT – Page 23 – November 10, 2015 Forecast scores against ECMWF analyses (std difference CNTL – EXP) 24-h RELATIVE HUMIDITY

24. DRAFT – Page 24 – November 10, 2015 72-hr scores against ECMWF T U V GZ

25. DRAFT – Page 25 – November 10, 2015 Temp. anomaly correlation against ECMWF analyses (500 hPa, world) Control Experiment General conclusion: Overall positive impact, Worth implementing

26. DRAFT – Page 26 – November 10, 2015 Planned Polar Communication and Weather Mission (PCW) A possible 2-sat HEO system Goal: Fill communication and meteorological observation gaps in the Arctic. 15 min Imagery above 55N. Most likely configuration: 2 satellites in highly elliptical orbit Status: Awaiting approval from government Could operate by 2021 Meteo instrument: Similar to ABI or FCI

27. DRAFT – Page 27 – November 10, 2015 PCW would fill AMV gaps at high latitudes: what impact to expect? Example of current AMV coverage per 6-h from 10 sources

28. DRAFT – Page 28 – November 10, 2015 Impact on NWP based on OSSE (ECMWF Nature Run used as “truth”) OSSE showing significant impact of PCW AMVs filling gap in polar areas Garand et al., JAMC, 2013 Positive impact (blue) at 120-h In both polar regions from 4 satellites

29. DRAFT – Page 29 – November 10, 2015 Conclusion R&D assimilation now benefiting from En-Var system. Encouraging results on assimilation of surface sensitive IR radiances over land. Next step is to relax limitation on surface emissivity. Overall positive impact considering inter-channel error correlation for all radiances. Plan is to implement along with Cris and ATMS in 2015. OSSE capability developed at EC, and used to support PCW