Sean Healy Presented by Erik Andersson
Use of COSMIC data in ECMWFs global data assimilation system for numerical weather prediction Sean Healy Presented by Erik Andersson COSMIC in Global NWP Outline Performance of GPSRO in a recent adjoint-based impact study:forecast error sensitivity to observations (FSO) Investigating the surface pressure information derived fromGPSRO measurements GRAS/COSMIC consistency Summary COSMIC in Global NWP Forecast Error Sensitivity to Observations (FSO)
Data assimilation scientists have developed adjoint-basedtools to estimate by how much various observation typescontribute to the reduction of 24-hour forecast error. Carla Cardinali has recently completed this type of calculationfor the ECMWF 4D-Var data assimilation system GPSRO has performed well COSMIC in Global NWP Forecast sensitivity to observations (FSO)
J is a measure of the forecast error (dry energy norm, ps, T, u,v) Forecast error sensitivity to the analysis Analysis solution Rabier F, et al 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 The forecast sensitivity (J is a scalar of the forecast error) equation can be expressed as a product of the forecast sensitivity with respect to the initial conditions and theanalysis sensitivity with respect to the observations. The analysis solution can be expressed as the contribution of the background information plus the innovation vector. If we take the analysis rel xa=xb+Kdy and compute the analysis sensitivity with respect to the observation we obtain the transpose of the K-matrix gain. After some substitutions and applying numerical techniques to solve dJ/dy (Krylov solution). Once dJ/dy is computed we can now take the delta J and rearrange it by substituting the xa= solution. The forecast error can be gathered over different subsets (type, subtype, variable and level) y COSMIC in Global NWP Observations contributions to decreased forecast error Operational FC system, Sept-Dec 2008
COSMIC in Global NWP Observations contributions to decreased forecast error Operational FC system, Sept-Dec 2008
GPS-Radio Occultation COSMIC in Global NWP Summary statistics by observation type
Mean sensitivity of An to Obs Global observation influence on analysis: GI=7% Global background influence I-GI=93% Information content (DFS) COSMIC in Global NWP Surface pressure information derived from GPSRO measurements
The integration of the hydrostatic equation is part ofthe GPSRO observation operator because the bendingangle and refractivity values are given as a function ofa height co-ordinate. 1D-Var studies (Healy and Eyre, 2000) suggest that itshould be possible to derive useful surface pressureinformation from the GPSRO measurements. We have recently performed experiments where allsurface pressure information is blacklisted to see ifCOSMIC and GRAS can constrain the surface pressurefield. Period June-July, Verified against ECMWFoperations. COSMIC in Global NWP Just to show the number of conventional Ps obs.
COSMIC in Global NWP Southern Hemisphere results (24 hour forecast mean error)
GPSRO bias quite stable The GPSRO seems to constrain the Ps bias. Control is the full observing system. Similar temporal evolution in NH and tropics COSMIC in Global NWP SH sigma of 24 Hour error COSMIC in Global NWP 500Z height score (SH) The Ps measurements dont have much impact from ~day-4 when GPSRO assimilated. HOWEVER, Im currently looking at another period to see if I can reproduce this result. COSMIC in Global NWP GRAS-COSMIC mean differences
We expect GPSRO measurements from differentinstruments to have similar bias characteristics, butoperational monitoring has shown that the GRAS andCOSMIC bending angle biases differ by about 0.2% in thelower-mid stratosphere. In operations, the COSMIC departures were in betteragreement with ECMWF forecasts and we initially assumedthat the problem was with the GRAS processing. However, Christian Marquardt (EUMETSAT) demonstrated atthe January 2009 AMS meeting that the problem was causedby the smoothing of the COSMIC phase delays at UCAR. UCAR proposed modifications to their processing and made3 months (Nov, Dec, 08 and Jan 09) data available to theNWP centres. We used this data to investigate the GRASCOSMIC consistency. Revised data processing at UCAR has been operationalsince October 11, 2009. COSMIC in Global NWP Global bending angle (o-b)/b departure statistics from ECMWF operations for Aug. 20 to Sept. 20, 2009 GRAS COSMIC-6 COSMIC-4 This is a typical result derived from operations before UCAR made the change. The COSMIC instruments agree with each Other but not with GRAS. COSMIC in Global NWP Experiments with Modified COSMIC data Statistics for Dec 08 (NH)
GRAS Much better consistency after UCAR processing change. But what causes the biases? Good agreement between GPSRO instruments, but what causes the ve bias? COSMIC in Global NWP Dec 08 Statistics when aircraft temperatures are blacklisted
Aircraft T values bias the analyis warm, peaking at 200 hPa by ~0.5 K. This shifts all the stratospheric model levels upwards, Increasing the forward modelled bending angles. Part of the bias is caused by aircraft temp measurementswhich are known to be biased warm stratospheric modellevels too high, so the simulated bending angles are biased high. COSMIC in Global NWP Summary FSO diagnostics show that GPSRO is an important observingsystem. We are currently investigating the surface pressureinformation content of GPSRO. Consistency between GRAS and COSMIC measurements muchbetter since the processing change at UCAR. Part of thenegative bending angle bias is caused by biased Aircraft Tmeasurements. We plan to bias correct the aircraft Temperaturemeasurements. COSMIC in Global NWP