1. GSI Hybrid EnKF-3DVAR Upgrade Components –GPS RO bending angle rather than refractivity –Inclusion of compressibility factors for atmosphere –Retune SBUV ob errors – fix bug at top –Update radiance usage flags –Prepare for monitoring NPP and Metop-B (Use of data?) –Add GOES-13 data –Add Severi CSBT radiance product –Satellite monitoring stats code included in Ops. –New Sat wind data and QC –EnKF hybrid system –Update to current version of trunk –New version of Forecast model Restructured to include options for Semi-Lagrangian & NSST Model Updated postprocessor CAPE, CIN, & Lifted Index calculated from virtual temperature Ability to output GRIB2 directly Ability to read GFS spectral coefficient file which will be exercised during this implementation to save post run time 4 new variables for Fire Wx, 8 for Wind Energy, 3 for severe weather Switch to use CRTM 2.0.2 lib and coefficient files

2. 2 Motivation from Var Current background error covariance (applied operationally) in VAR –Isotropic recursive filters –Poor handle on cross-variable covariance –Minimal flow-dependence added Implicit flow-dependence through linearization in normal mode constraint (Kleist et al. 2009) Flow-dependent variances (only for wind, temperature, and pressure) based on background tendencies –Tuned NMC-based estimate (lagged forecast pairs)

3. 3 EnKF/3DVar hybrid J : Penalty (Fit to background + Fit to observations + Constraints) x’ : Analysis increment (x a – x b ) ; where x b is a background B Var : Background error covariance H : Observations (forward) operator R : Observation error covariance (Instrument + representativeness) y o ’ : Observation innovations J c : Constraints (physical quantities, balance/noise, etc.) B is typically static and estimated a-priori/offline

4. 4 Current background error for GFS Although flow-dependent variances are used, confined to be a rescaling of fixed estimate based on time tendencies –No multivariate or length scale information used –Does not necessarily capture ‘errors of the day’ Plots valid 00 UTC 12 September 2008

5. 5 Why Hybrid? VAR (3D, 4D) EnKFHybridReferences Benefit from use of flow dependent ensemble covariance instead of static B xx Hamill and Snyder 2000; Wang et al. 2007b,2008ab, 2009b, Wang 2011; Buehner et al. 2010ab Robust for small ensemble x Wang et al. 2007b, 2009b; Buehner et al. 2010b Better localization for integrated measure, e.g. satellite radiance x Campbell et al. 2009 Easy framework to add various constraints xx Framework to treat non- Gaussianity xx Use of various existing capabilities in VAR xx

6. 6 Hybrid Variational-Ensemble Incorporate ensemble perturbations directly into variational cost function through extended control variable –Lorenc (2003), Buehner (2005), Wang et. al. (2007), etc.  f &  e : weighting coefficients for fixed and ensemble covariance respectively x t : (total increment) sum of increment from fixed/static B (x f ) and ensemble B  k : extended control variable; :ensemble perturbation L: correlation matrix [localization on ensemble perturbations]

7. 7 Hybrid with (global) GSI Control variable has been implemented into GSI 3DVAR* –Full B preconditioning Working on extensions to B 1/2 preconditioned minimization options –Spectral filter for horizontal part of A Eventually replace with (anisotropic) recursive filters –Recursive filter used for vertical –Dual resolution capability Ensemble can be from different resolution than background/analysis (vertical levels are the exception) –Various localization options for A Grid units or scale height Level dependent (plans to expand) –Option to apply TLNMC (Kleist et al. 2009) to analysis increment *Acknowledgement: Dave Parrish for original implementation of extended control variable

8. 8 Single Observation Single 850mb Tv observation (1K O-F, 1K error)

9. 9 Single Observation Single 850mb zonal wind observation (3 m/s O-F, 1m/s error) in Hurricane Ike circulation

10. EnKF member update member 2 analysis high res forecast GSI Hybrid Ens/Var high res analysis member 1 analysis member 2 forecast member 1 forecast recenter analysis ensemble Dual-Res Coupled Hybrid member 3 forecast member 3 analysis Previous CycleCurrent Update Cycle

11. Status Coding/parallel scripting completed –Except possible changes due to NPP and GOES-15 data Optimized version of post being used – so no delay in delivery of post fields expected. Some data handling issues being worked. Parallel without relocation and ozone hybrid from June 1, 2011- Oct. 7, 2011 –Problems with extrapolation of ozone into data void regions (South Pole) –Initial hurricane location degraded (forecast improved) 11

12. Status Modification to system –Reinstate hurricane relocation –Uncouple ozone analysis from hybrid New parallels started –Rerun beginning June 1, 2011 (will start when backup machine returns) –Real time catch up starting Nov. 1, 2011 (up to Nov. 15, 2011) Results that follow are from previous parallel –Significant changes to meteorological fields not expected (except hurricane relocation) 12

13. 500mb Anomaly Correlation 13

14. 1000mb Anomaly Correlation 14

15. 200mb Tropical winds 15

16. 850mb Tropical winds 16

17. 12-36 hour precipitation scores 17

18. 36-60 hour precipitation scores 18

19. 60-84 hour precipitation scores 19

20. 20

21. 21

22. 22

23. Hurricane track 23

24. More complete diagnostics 24 http://www.emc.ncep.noaa.gov/gmb/wd20rt/experiments/ prd12q3h/vsdb/ http://www.emc.ncep.noaa.gov/gmb/wd20rt/experiments/ prd12q3r/vsdb/ Retrospective Real Time catch up

25. 25 Cost Analysis/GSI side –Minimal additional cost (~2 nodes) Reading in ensemble (3-9 hour forecast from previous cycle) Some additional computations in J calculations 1 additional field Coding complete/in place Additional “GDAS” Ensemble (T254L64 GDAS) –EnKF-based perturbation update Cost comparable to current analysis [ 8-10 nodes, <40 minutes] –Includes ensemble of GSI runs to get O-F and actual ensemble update step Work ongoing to optimize coding and scripting –9hr forecasts, needs to be done only in time for next (not current) cycle

26. Concerns Rain/no-rain for 12-36 hour forecast (spin-up?) Changes in initial clouds –Part of spin-up? Tasked to attempt to incorporate NPP data. Biggest concern is computer resources to catch up to real time. 26

27. NPP ATMS data available –Needs some development because of different size FOVs for different channels (code change or preprocessor) –Quality control check out –Bias correction spin up CrIS instrument to be turned on in Dec. –Major calibration of CrIS – Jan. 15 –Should be similar to AIRS and IASI – significant development (code changes) unlikely –Quality control check out –Bias correction spin up 27

28. NPP Tentative Schedule –RFC to NCO 1/3/12 –Complete development for ATMS ~1/15/12 –Major calibration update for CrIS 1/15/12 –Check out quality control/bias correction 2/6/12 –Short off-line test ends 2/16/12 –NCO parallel testing begins 2/16/12 –Implementation 4/1/12 –Any unexpected finding that delays the schedule will stop the implementation of NPP. No chance for completion of NPP impact studies prior to NCO parallel. (JCSDA) 28