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MPO 674 Lecture 15

MPO 674 Lecture 15

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MPO 674 Lecture 15

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  1. MPO 674 Lecture 15 3/22/12

  2. Outline • NCEP Gridpoint Statistical Interpolation (GSI) • Overview • One-observation increments • Surface wind observations • Dropwindsonde observations: Irene (2011) • QuikSCAT Study using NCEP System • NCEP versus ECMWF • 4d-Var … will present next week

  3. GSI cycle 9-h forecast for GSI 18Z 21Z 00Z 03Z Produce GSI analysis at 00Z based on observation window of 21Z-03Z 15-day GFS forecast 9-h forecast for GSI Includes late observations 00Z 03Z 06Z 09Z Produce GSI analysis at 06Z based on observation window of 03Z-09Z 15-day GFS forecast 9-h forecast for GSI 06Z 09Z 12Z 15Z

  4. GSI • Variational method. • Best estimate of atmospheric state at a given time, using info from observations and first guess. • Minimize an objective cost function: gives a weighted distance between the analysis and the observation and first guess fields. • Current GSI Pf matrix: not fully anisotropic or flow-dependent.

  5. GSI • Flexibility: used in several NCEP systems: • Global forecast system (presented here) • HWRF • Regional NDAS, NMM • Real Time Mesoscale Analysis (RTMA) • WRF Rapid Refresh • Global model resolution • T574 L64 (about 25km)

  6. GSI • Analysis variables • Streamfunction • unbalanced velocity potential • Temperature • surface pressure • normalized moisture • ozone, • cloud water

  7. 1-observation GSI increments from Kleist et al., 2009, WAF. • Assimilate 300 hPa zonal wind • 300 hPa zonal wind increment • Vertical cross-section T increment • Assimilate 850 hPa T • 850 hPa T increment • 850 hPa specific humidity increment

  8. SSI: before 5/1/07 Assimilate 300 hPa u. Analysis increment of 300 hPa u. GSI: after 5/1/07 Kleist et al., 2009, WAF.

  9. SSI: before 5/1/07 Assimilate 300 hPa u. Analysis increment of T. GSI: after 5/1/07 Kleist et al., 2009, WAF.

  10. SSI: before 5/1/07 Assimilate 850 hPa T. Analysis increment of 850 hPa T. GSI: after 5/1/07 Kleist et al., 2009, WAF.

  11. GSI Assimilation of 850 hPa temperature observation at 45°N, 90°W with a 1-K residual and observation error. Background RH [shaded, contour interval is 10%] Specific humidity analysis increment at 850 hPa (white contours, CI is 0.001 g kg−1) Multivariate coupling of moisture, T and p increments. Background error for humidity is a function of the humidity field. Kleist et al., 2009, WAF.

  12. 00Z 23 August – Analysis500-hPa geopotential height and difference field (CTRL-NODROP) Control No Drop Drops result in slightly stronger ridge north of Irene and higher heights on southeast flank of trough off the southeast U.S. coast

  13. 00Z 23 August – 12-h Forecast500-hPa geopotential height and difference field (CTRL-NODROP) Control No Drop Heights continue to be higher with drops north of Irene and east of Florida – trending toward a less pronounced weakness in the ridge

  14. 00Z 23 August – 24-h Forecast500-hPa geopotential height and difference field (CTRL-NODROP) Control No Drop Trend toward higher heights north and northwest of Irene continues to become more pronounced

  15. 00Z 23 August – 36-h Forecast500-hPa geopotential height and difference field (CTRL-NODROP) Control No Drop

  16. 00Z 23 August – 48-h Forecast500-hPa geopotential height and difference field (CTRL-NODROP) Control No Drop

  17. 00Z 23 August – 72-h Forecast500-hPa geopotential height and difference field (CTRL-NODROP) Control No Drop Differences now begin to decrease north of Irene, but slightly weaker trough moving into Mid-Atlantic

  18. 00Z 23 August – 96-h Forecast500-hPa geopotential height and difference field (CTRL-NODROP) Control No Drop Differences appear larger now, but partly due to more eastward track of Irene in NODROP run, but more ridging still present over Mid-Atlantic in CTRL (588-dam contour)

  19. 00Z 23 August – 120-h Forecast500-hPa geopotential height and difference field (CTRL-NODROP) Control No Drop

  20. Assimilation of QuikSCAT wind data: NCEP/EMC Study • Data denial experiments: • No QuikSCAT • QuikSCAT wind vectors processed by NESDIS • Nov. 2007 version of GFS system & GSI analysis (T382 L64) • 20050705-20051025 (Dennis through Wilma) • 20060801-20061004 (Chris through Isaac) Overall conclusion: Assimilating QuikSCAT data had little impact on hurricane track errors as well as extratropical scores (500 and 1000 hPa rms height differences in NH and SH).

  21. Possible reasons for minimal influence • Conservative QC; observation error (3.5 m/s) • Super-obs: obs averaged in 1o x 1o boxes • Significant wind vectors (>20 m/s) are thinned due to averaging • Recommendation: assimilate non-averaged wind vectors at 0.25o resolution • Short vertical error correlation lengthscale, appropriate for tropical cyclone?

  22. 2a. NCEP/EMC QuikSCATStudy Data denial experiments 2005/6: • No QuikSCAT • QuikSCAT wind vectors processed by NESDIS Overall conclusion: Assimilating QuikSCAT data had little impact on NCEP GFS hurricane track errors • Conservative QC; observation error (3.5 m/s) • Super-obs: obs averaged in 1o x 1o boxes • Significant wind vectors (>20 m/s) are thinned due to averaging • Recommendation: assimilate non-averaged wind vectors at 0.25o resolution • Short vertical error correlation lengthscale, appropriate for tropical cyclone?

  23. 2b. GSI Assimilation experiments • One assimilation time: 00 UTC, Sept 5th 2008 • Hurricane Ike in western Atlantic • Operational NCEP GSI as of 2008-9 • ~ 35 km resolution • Current capability: • Assimilating operational observations • Synthetic-observation experiments

  24. Operational GFS forecast

  25. Synthetic observations of u, v • Suppose that there were 4 new, near-perfect wind observations, reporting wind speeds 10 m/s higher than the first guess. • What would be their impact on the GSI analysis?

  26. Analysis increment (analysis – f.guess) in MSLP

  27. Analysis increment of 1000 hPa u, v v u

  28. Vertical E-W cross-section through Ike: Analysis increment T v

  29. Vertical E-W cross-section through Ike: Forecast increment through +24h T v

  30. Vertical E-W cross-section through Ike: Forecast increment through +48h T v

  31. 2c. Vertical error correlation lengthscale Lz • Minimal modification to the track of Ike due to assimilation of the 4 wind vectors. • Influence of ‘observations’ on the analysis only extended through the boundary layer. • This influence possessed no clear signal at later forecast times. • Any improvement if Lz is increased?

  32. Vertical E-W cross-section through Ike. Analysis increment: operational Lz T v

  33. Vertical E-W cross-section through Ike. Analysis increment: 2 x Lz T v

  34. Vertical E-W cross-section through Ike. Analysis increment: 4 x Lz T v

  35. NCEP vs ECMWF • Compare and contrast the next two slides showing NCEP and ECMWF analyses and forecasts of Hurricane Ike. • Data ingest: similar volume • Data assimilation: 3d-Var vs 4d-Var • Pf matrix: ECMWF incorporates more flow-dependence • Resolution • 25 km vs 15 km • Physics? • More sophisticated treatment of satellite obs at ECMWF: less conservative QC? correlated errors?