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Use of COSMIC data in ECMWF’s global data assimilation system for numerical weather prediction

Use of COSMIC data in ECMWF’s global data assimilation system for numerical weather prediction. Sean Healy Presented by Erik Andersson. Outline. Performance of GPSRO in a recent adjoint-based impact study: forecast error sensitivity to observations (FSO)

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Use of COSMIC data in ECMWF’s global data assimilation system for numerical weather prediction

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  1. Use of COSMIC data in ECMWF’s global data assimilation system for numerical weather prediction Sean Healy Presented by Erik Andersson COSMIC in Global NWP

  2. Outline • Performance of GPSRO in a recent adjoint-based impact study: forecast error sensitivity to observations (FSO) • Investigating the surface pressure information derived from GPSRO measurements • GRAS/COSMIC consistency • Summary COSMIC in Global NWP

  3. Forecast Error Sensitivity to Observations (FSO) • Data assimilation scientists have developed adjoint-based tools to estimate by how much various observation types contribute to the reduction of 24-hour forecast error. • www.ecmwf.int/newsevents/meetings/workshops/2009/Diagnostics_DA_System_Performance • Carla Cardinali has recently completed this type of calculation for the ECMWF 4D-Var data assimilation system • GPSRO has performed well COSMIC in Global NWP

  4. J is a measure ofthe forecast error (“dry energy norm”, ps, T, u,v) Forecast error sensitivity to the analysis Forecast sensitivity to observations (FSO) Analysis solution Rabier F, et al. 1996. Analysis sensitivity to observation and background The tool provides FSO for each assimilated observation, which can be accumulated by observation type, subtype, variable or level δy COSMIC in Global NWP

  5. Observations’ contributions to decreased forecast errorOperational FC system, Sept-Dec 2008 COSMIC in Global NWP

  6. Observations’ contributions to decreased forecast errorOperational FC system, Sept-Dec 2008 GPS-Radio Occultation COSMIC in Global NWP

  7. Mean sensitivity of An to Obs Global observation influence on analysis: GI=7% Summary statistics by observation type Global background influence I-GI=93% Information content (DFS) COSMIC in Global NWP

  8. Surface pressure information derived from GPSRO measurements • The integration of the hydrostatic equation is part of the GPSRO observation operator because the bending angle and refractivity values are given as a function of a height co-ordinate. • 1D-Var studies (Healy and Eyre, 2000) suggest that it should be possible to derive useful surface pressure information from the GPSRO measurements. • We have recently performed experiments where all surface pressure information is blacklisted to see if COSMIC and GRAS can constrain the surface pressure field. • Period June-July, 2009. Verified against ECMWF operations. COSMIC in Global NWP

  9. COSMIC in Global NWP

  10. Southern Hemisphere results (24 hour forecast mean error) GPSRO bias quite stable Similar temporal evolution in NH and tropics COSMIC in Global NWP

  11. SH – sigma of 24 Hour error COSMIC in Global NWP

  12. 500Z height score (SH) COSMIC in Global NWP

  13. GRAS-COSMIC mean differences • We expect GPSRO measurements from different instruments to have similar bias characteristics, but operational monitoring has shown that the GRAS and COSMIC bending angle biases differ by about 0.2% in the lower-mid stratosphere. • In operations, the COSMIC departures were in better agreement with ECMWF forecasts and we initially assumed that the problem was with the GRAS processing. • However, Christian Marquardt (EUMETSAT) demonstrated at the January 2009 AMS meeting that the problem was caused by the smoothing of the COSMIC phase delays at UCAR. • UCAR proposed modifications to their processing and made 3 months (Nov, Dec, 08 and Jan 09) data available to the NWP centres. We used this data to investigate the GRAS COSMIC consistency. • Revised data processing at UCAR has been operational since October 11, 2009. COSMIC in Global NWP

  14. Global bending angle (o-b)/b departure statistics from ECMWF operations for Aug. 20 to Sept. 20, 2009 GRAS COSMIC-6 COSMIC-4 COSMIC in Global NWP

  15. Experiments with Modified COSMIC data Statistics for Dec 08 (NH) COSMIC-6 COSMIC-4 GRAS Good agreement between GPSRO instruments, but what causes the –ve bias? COSMIC in Global NWP

  16. Dec 08 Statistics when aircraft temperatures are blacklisted Part of the bias is caused by aircraft temp measurements which are known to be biased warm – stratospheric model levels too high, so the simulated bending angles are biased high. COSMIC in Global NWP

  17. Summary • FSO diagnostics show that GPSRO is an important observing system. • We are currently investigating the surface pressure information content of GPSRO. • Consistency between GRAS and COSMIC measurements much better since the processing change at UCAR. Part of the negative bending angle bias is caused by biased Aircraft T measurements. • We plan to bias correct the aircraft Temperature measurements. COSMIC in Global NWP

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