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ECMWF Training Course 2005 slide 1 Forecast sensitivity to Observation Carla Cardinali

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ECMWF Training Course 2005 slide 2 Outline Part 2: Forecast Sensitivity Forecast Sensitivity to Observation Sensitivity gradient A-TReC campaigns Comparing Observation Analysis Influence and Observation Forecast Impact Results and Conclusion

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ECMWF Training Course 2005 slide 3 Forecast Sensitivity to Observation J is measures the forecast error: its gradient respect the observation vector y gives the forecast error sensitivity respect observations used in the initial condition for model forecast the sensitivity respect the initial condition x a Analysis sensitivity with respect the observation

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ECMWF Training Course 2005 slide 4 Define Forecast Sensitivity

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ECMWF Training Course 2005 slide 5 Change of Variable

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ECMWF Training Course 2005 slide 6 Computation z Linear system to solve zaza

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ECMWF Training Course 2005 slide 7 Forecast Sensitivity to Observations Tangent Linear Model ResolutionT95 L60

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ECMWF Training Course 2005 slide 8 Sensitivity Gradients Sensitive area Verification area T1T1 100* TE at t=0 100* KE at t=0 TE at t=T 1 KE at t=T 1 500 hPa Temperature Sensitivity Gradients

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ECMWF Training Course 2005 slide 9 Fc Sensitivity to Aircraft Temperature 500 hPa

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ECMWF Training Course 2005 slide 10 Fc Sensitivity to Surface Pressure

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ECMWF Training Course 2005 slide 11 Observation Campaign 5 Dec 18 UTC---Verification 7 Dec 12 UTC AtreC 13% MSLP Relative Fc Improvement 9% Total Energy Targeting = Verification Region Lat(30,50)-Lon(-85,-60) 42 h TargetIN/NOTargetIN % AMDAR 2.5 SONDE 5.5 An 5 Dec 18 UTC

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ECMWF Training Course 2005 slide 12 Observations Contribution to Forecast Total Contribution Mean Contribution

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ECMWF Training Course 2005 slide 13 Forecast and Analysis Sensitivity to Targeted Observations

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ECMWF Training Course 2005 slide 14 200-300 hPa Targeted Aircraft Temperature Forecast Error

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ECMWF Training Course 2005 slide 15 Aircraft Observation U-Comp 200-300 hPa Forecast Impact Observation Influence in Analysis Background Influence = 1-Observation Influence

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ECMWF Training Course 2005 slide 16 TEMP Observation Temperature 850-1000 hPa Forecast Impact Observation Influence in Analysis Background Influence = 1-Observation Influence

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ECMWF Training Course 2005 slide 17 Total Forecast Error 5 Dec 2003 TargetIN/NOTargetIN 8%

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ECMWF Training Course 2005 slide 18 Observation Campaign 8 Dec 18 UTC---Verification 11 Dec 00 UTC TargetIN/NOTargetIN % AMDAR 2.6 SONDE 0.9 AtreC -71% MSLP Relative Fc Degradation -7% Total Energy Targeting Lat(30,60)-Lon(-70,-15) Verification Lat(45,65)-Lon(-15,+10) 54 h

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ECMWF Training Course 2005 slide 19 200-300 hPa Targeted Aircraft U Forecast Error

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ECMWF Training Course 2005 slide 20 Total Forecast Error 8 Dec 2003 TargetIN/NOTargetIN 3.5%

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ECMWF Training Course 2005 slide 21 Conclusions Forecast sensitivity to observations has been computed for the campaigns showing an impact (ATreC-Cntr)/Cntr ± 10% 13 cases out of 38: 9 positive and 4 negative Two campaigns have been shown 5 Dec at 18 UTC - Targeted observations improved the forecast of a cyclone moving along the east coast of North America for which severe weather impact was forecast 8 Dec at 18 UTC – Targeted observations deployed to clarify the models uncertainties for the remnants of the east cost storm, degraded the forecast over Northern Europe – UK However, differences in forecast impact between ATreC and Cntr come also from the continuous assimilation cycling that provides different model trajectories Forecast Impact computed for the cancelled campaigns gives on average ±10% in term of RMSE in the verification area

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ECMWF Training Course 2005 slide 22 END

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ECMWF Training Course 2005 slide 23 Singular vectors brief definition Singular vectors was one of technique used in AtreC-TOST campaign to find sensitivity areas where releasing additional observations Singular vectors (SVs) define perturbations with fastest growth during a finite time interval (optimization time interval). They are defined by: The model characteristics: T L 95L60, dry, with simplified physics The norm used to measure growth: localized total energy The optimization time interval: 42-54 hours Diagnostic Singular vectors have been computed to investigate the observation impact in the forecast time Sensitive area Verification area

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ECMWF Training Course 2005 slide 24 Linear combination of 10 Diagnostic SVs valid at observation time AtreC observation time forecast step T 1 localized total energy maximum in verification area eigenvalues decomposition forecast error step T 1 proj. fc error onto SVs Back to the observation time Sensitive area Verification area T1T1

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