OSSE Calibration at ESRL

1. OSSE Calibration at ESRL Nikki Privé Yuanfu Xie Dec 17 2009

2. Calibration process • Data denial tests are run for synthetic obs subsets of similar data types • Analysis impact (global RMS difference in control and data denial analysis) is calculated for synthetic obs and compared to analysis impact for data denial with real archived data from July 2005 • Standard deviation of synthetic errors are adjusted, errors are regenerated • New data denial case is run and compared to real data, errors adjusted, etc • Repeat until analysis impact matches real data analysis impact, or until satisfied that calibration is not possible

3. Calibration Status • Synthetic obs dataset: - conventional, OSBUV, and GOES radiance from NCEP - HIRS, AIRS, AMSU, MSU from GMAO • Calibration of conventional data has begun - Each obs type calibrated separately - Short 2-week test runs • After all conventional and radiance types are adjusted, long (7-week) calibration periods will be run for five chosen obs types for more extensive testing (anomaly correlation, forecast impact, etc)

4. Synthetic Obs Errors • GMAO error-adding code used to generate errors which are added to the ‘perfect’ synthetic observations • Original “default” standard deviation of errors from GSI convinfo and satinfo tables - function of height for conventional data - function of channel for radiance data • Calibration accomplished by changing standard deviation of errors applied to synthetic observations while leaving GSI error tables unchanged - changing GSI errors to match calibrated obs errors resulted in undoing of the calibration

5. Effects of changing GSI Errors All analysis impacts are global rms difference between data denial and control run for denial of AIRCRAFT types Four cases: Real data (black line) Original low-error obs, original GSI errors (green) Calibrated high-error obs, original GSI errors (red) Calibrated high-error obs, matching high GSI errors (blue) Results: Changing the GSI errors to match the obs errors un-calibrates the analysis impact.

6. AIRCRAFT data denial

7. AIRCRAFT data denial

8. Non-linearity/cross-interference of obs errors Tests run with data denial experiments and different levels of error on conventional and AMSU-A types. • Changing the error on obs type A does not significantly effect the analysis impact of obs type B. • Each obs type can be calibrated individually with less worry about nonlinearities. • If some obs types are not well-calibrated, this may have little effect on the OSSE experiment. • New obs types in the OSSE may need to be tested at a range of errors to fully evaluate impact.

9. Effect of increasing error on data denial analysis impact. Orig: low error data denial case Masserr: conventional mass obs error increased by factor of 3 Winderr: conventional wind obs error increased by factor of 2 Amsuerr: AMSUA-A error increased by factor of 3 For each case, a new control is run with all obs types included, then data denial are run for amsu-a and raob.

10. AMSU-A data denial

11. AMSU-A data denial

12. AMSU-A data denial

13. RAOB data denial

14. RAOB data denial

15. RAOB data denial

16. Calibration examples using RAOB denial case All RAOB/sonde types (120, 132, 182, 220 232) simultaneously tested. Error standard deviation adjusted at individual height levels for each obs type (T, RH, wind). RH and Wind most successfully calibrated. T is reasonably but not ‘perfectly’ calibrated. Some levels were not able to be calibrated: T below 800 mb, above 150 mb Q above 250 mb Wind above 100 mb

17. Successful calibration RAOB data denial

18. Calibration not needed RAOB data denial

19. Calibration not possible RAOB data denial

20. Calibration worsens impact RAOB data denial

21. Sample results from calibration of other conventional obs AIRCRAFT types SURFACE types SSMI/SCATTEROMETER types

22. AIRCRAFT data denial

23. AIRCRAFT data denial

24. SURFACE data denial

25. SURFACE data denial

26. SSMI data denial