1. Presented by: David Groff NOAA/NCEP/EMC IM Systems Group
Observing System Forecast Impact for the FY16 GFS Based on Ensemble Forecast Sensitivity to Observation (EFSO) Calculations
Presented by: David Groff
NOAA/NCEP/EMC IM Systems Group

2. Outline Introduction Results Summary and Discussion
The Ensemble Forecast Sensitivity to Observation (EFSO) formulation
Application of EFSO to the ensemble component of the GFS 4DEnVar system
Results
Total EFSO Impact Versus Innovation
Aircraft Data Impact
Summary and Discussion

3. The Ensemble Forecast Sensitivity to Observation (EFSO) formulation
Seminal Papers
(Langland and Baker, 2004)
(Zhu and Gelaro, 2007)
(Gelaro and Zhu, 2008)
(Kalnay et al., 2010)
(Ota et al., 2013)

4. An Ensemble Estimate of Forecast Sensitivity to Observation Impact
Forecast Errors
Two sets of ensemble forecasts valid at the same time are required
The verification can be anything considered close to the truth relative to the forecast
T = -6 hours
T = 0 hours

5. EFSO Background Information
The approach is applicable for ensemble data assimilation algorithms.
The approach requires two sets of ensemble forecasts valid at the same time.
For results shown in this presentation, the forecasts are verified against the analyses. However, in general any quantities considered to be close to the truth can be applied.

6. Forecast Error and True Forecast Error Reduction
Forecast Error: True Forecast Error Reduction for all Observations:
(1)
(2)

7. The Tangent-Linear Approximation
The approximation that relates forecast difference to observations: Substituting this approximation into the true forecast error reduction relationship:
(3)
(4)

8. The EFSO Relationship Innovation
(5)
Innovation
Sensitivity Component
Matrix of Energy Weighting Coefficients

9. Application of EFSO to the ensemble component of the GFS 4DEnVar system

10. Cycling Experiment Design
2016 version of the GDAS/GFS at reduced resolution.
4DEnVar Hybrid (80 ensembles, T254)
T670 Semi-Lagrangian
Winter season DJF (2014/2015)

11. EFSO Calculations
Forecast impact from the surface to 100 hPa is included.
The forecast error metrics are integrated quantities of wind, temperature/mass and latent heat. The calculations in this presentation are based on integrated quantities of wind and mass.
EFSO calculations only apply EnKF products from the cycling experiments.

12. Ensemble Forecasts
All ensemble forecasts applied in the calculation are based on inflated and recentered analyses.
The verifying analyses are the ensemble mean of the EnKF update.

13. Total EFSO Impact Versus Innovation

14. Terminology For the special case of EFSO quantities
Negative quantities are hereafter referred to as being beneficial
Positive quantities are hereafter referred to as being detrmintal
The sign of all other quantities (eg. innovations) will be referred to as negative or positive based on their sign in the usual sense

15. AMSUA Channel (00Z)

16. CrIS Channel (OOZ)

17. IASI Channel 354 (00Z)

18. Mobile Marine Surface Winds @ (00Z)

19. Radiosonde Temperature Observations (00Z)

20. AIRS Channel 295 (00Z)

21. EFSO Suggested Aircraft Impact

22. GFS 4DEnVar (Current Study)
Total EFSO Impact
GFS 4DEnVar (Current Study)
Pure EnKF (Ota et. al, 2013)

23. Total Observation Counts
4DEnVar EnKF Products (2016)
Pure EnKF (Ota et. al, 2013)

24. Total Observation Counts
4DEnVar EnKF Products (2016)

25. EFSO Per Observation Impact
4DEnVar EnKF Products (2016)
Pure EnKF (Ota et. al, 2013)

26. The EFSO Relationship
(5)
Sensitivity Component

27. EFSO Sensitivity Component
4DEnVar EnKF Products (2016)
Pure EnKF (Ota et. al, 2013)
8E-5
3E-5

28. The EFSO Relationship
(5)
Ratio of Analysis Spread in Obs Space to Obs error

29. 4DEnVar EnKF Products (2016)
EFSO (HXa/R)
4DEnVar EnKF Products (2016)
Pure EnKF (Ota et. al, 2013)
0.4
0.3

30. Component of calculation that involves forecasts
The EFSO Relationship
(5)
Component of calculation that involves forecasts

31. 4DEnVar EnKF Products (2016)
Forecast Component
4DEnVar EnKF Products (2016)
Pure EnKF (Ota et. al, 2013)
4E-4
2E-3

32. Aircraft Temperature Observations (00Z)
4DEnVar EnKF Products (2016)
Pure EnKF (Ota et. al, 2013)

33. Summary
Plotting total EFSO impact as a function of binned innovation may highlight future directions for bias correction.
Total EFSO impact against binned innovations may provide insights as to how data is assimilated.
The number of assimilated aircraft observations in the ensemble component of the GSI 4DEnVar system has increased by a factor of two relative to Yoichoro’s previous EnKF study.
The relative per observation impact observing system contributions from observing systems for this study are very similar to the pure EnKF study.