Assimilation of surface sensitive infrared channels over land at Environment Canada

1. Assimilation of surface sensitive infrared channels over land at Environment Canada L. Garand, S.K. Dutta, and S. Heilliette DAOS Meeting Montreal, Qc August 15-16, 2014

2. Outline • Context & motivation • Approach • Assimilation results ________________________ • Also: Update on PCW mission

3. Context & motivation Env. Can. moving to ensemble-variational 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 (15 km in 2015) • ~140 AIRS and IASI channels assimilated: many sensitive to low level T, q, and Ts. RTM is RTTOV-10. Favorable context to attempt assimilating surface-sensitive IR channels over land and sea-ice vs earlier work with GOES (Garand et al. JAM, 2004) with analysis grid at 150 km and no hyperspectral IR.

4. Ensemble spread of Ts (Feb-Mar 2011) 00 UTC 06 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, B is 0.5(BENKF+ BNMC) 12 UTC 18 UTC

5. Ensemble T(~964 hpa) spread (Jan-Feb 2011) 00 UTC 06 UTC Only minor variations with local time Values < 0.5 K in SH seem underestimated 12 UTC 18 UTC

6. Key factors to consider • Reliable cloud mask • Spectral emissivity definition (CERES, U-Wisconsin) • Highly variable topography • Radiance bias correction • Background and observation error definition

7. Approach guided by prudence Assimilate under these restrictive conditions over land and sea ice: • Estimate of cloud fraction < 0.01 • High surface emissivity (> 0.97) • Relatively flat terrain (local height STD < 100 m) • Diff between background Ts and retrieval based on inverting RTE limited to 4K Radiance bias correction approach: • For channels flagged as being surface sensitive, use only ocean data to update bias coefficients

8. Assigned observation error to radiances Assigned= f std(O-P) Desroziers = <(O-P)(O-A)> 15.0mm 4.13mm 15.3mm 4.50mm f typically in range 1.6-2.0

9. 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

10. 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.

11. Examples of emissivity from CERES 10.7 micron 3.9 micron water: 0.990 water: 0.977 A large portion of land masses have surface emissivity > 0.97

12. First attempt: negative impact in region 60-90 N/S 00 hr 72hr Possible cause: cloud contamination ?

13. Second attempt: added constraints • Cut latitudes > 60 deg • Local gradient of topography < 50 m (was 100 m) Strong impact on (O-B) stats for surface channels

14. T std error diff. (CNTL-EXP) NH-Extratropics 6 Feb to 31March 2011 vs ERA Interim vs own analysis Consistent positive impact vs ERA Interim and own

15. T std diff (CNTL-EXP) vs ERA-Interim Tropics SH Extratropics

16. Zonal T STD difference (CNTL-EXP)vs ERA-Interim 72-h 120-h

17. (a) (b) Time series of T std diff at 850 hPa CNTL EXP NH extratropics Tropics EXP superior to CNTL 54-66 % of cases at days 3-5

18. 850 hPa TT anomaly cor. CNTL EXP NH extratropics Tropics

19. 120-h N-Extr vs ERA-Interim CNTL EXP U HR GZ T

20. Validation vs raobs 120-hFeb-Mar 2011 (59 days) CNTL EXP SH-extratropics NH-extratropics U V U V GZ T GZ T

21. Validation vs raobs 120-hFEB-Mar 2011 (59 days) CNTL EXP North America Europe U V U V GZ T GZ T

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

23. Std/bias of (O-P) and (O-A), AIRS 787CNTLEXP O-P O-A No major impact on bias. Strong assimilation over land, with std (O-P) of ~1.7 K, std (O-A) of 0.40 K (not shown)

24. Conclusion • Very encouraging results, especially in NH where most of new data are assimilated Next steps: • Relax limitations on emissivity, use MODIS-derived atlas • Run a summer cycle • Seek operational implementation Longer term • Evaluate problems specific to high latitudes

25. Update on Polar Communications and Weather (PCW) mission Goal: Fill communication and meteorological observation gaps in the Arctic Most likely configuration: 2 satellites in highly elliptical orbits Status: Seeking approval from Government in early 2015. Could start operating in 2021. Meteorological instrument: Similar to ABI or FCI A possible 2-sat HEO system

26. Capabilities ‘GEO-like’ continuous imaging of Arctic circumpolar region ‘GEO-like’ spatial (1-3 km) and temporal (15 min) resolution ‘Next-generation’ meteorological imager (ABI, FCI, 16+ channels) Near-real time processing to L1c for delivery to Environment Canada Compatibility with GEO imagers as part of WMO Global Observing System. Weather:High-Level Requirements

27. Orbit Comparison(2-sat Constellation) Molniya (12-h) Apogee: 39,800 km TAP (16-h) Apogee: 43,500 km Tundra (24-h) Apogee: 48,300 km

28. Science Studies: Uniqueness of HEO System vs LEO 23 LEO satellites needed to get 15 min Imagery at 60 N, versus 2 HEO Trichchenko and Garand, Can. J. Remote Sensing, 2012 Also, capability to get image triplets for AMV vastly superior to LEO

29. Science Studies:Impact on NWP 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

30. Example of PCW Geometry Matching[16-hr TAP Orbit] for intercalibration VIIRS/SNPP GEO Trishchenko and Garand, GSICS Newsletter, 2012