Philippe Arbogast, Karine Maynard CNRM-GAME (Météo-France & CNRS)

1. A ten-year experiment of real-time Potential Vorticity modifications and inversions at Météo-France Philippe Arbogast, Karine Maynard CNRM-GAME (Météo-France & CNRS)

2. Forecaster Expertise

3. Senior forecaster expertise at Météo-France: • Verify NWP outputs at the very short range against observations in real time • Recognize coherent dynamical features using conceptual models • Chose the “best member “ among several solutions provided by deterministic forecasts and scenarios from ensembles • Monitor severe weather warning • In particular: • Assessment of upper-level dynamics expressed in terms of PV/dynamical tropopause within NWP using satellite images (WV channels from geostationnary satellites) • And since 2005 : • PV modifications of global analyses (or +3h,+6h forecasts) in real time

4. Forecaster Expertise

5. On peut estimer l’incertitude de l’état analysé en chaque point d’observation (radiances, RS, avions commerciaux…) par comparaison entre ébauche, observations et analyse La sensibilité aux conditions initiales indique la position des erreurs initiales qui ont leur maximum d’amplification en 30h dans la zone cible (polygone violet) Forecaster Expertise Un état initial incertain conduit à une prévision incertaine Deux méthodes pour propager l’incertitude : La prévision d’ensemble transporte l’incertitude dans le temps et l’espace  renseigne la confiance dans la prévision

6. On peut estimer l’incertitude de l’état analysé en chaque point d’observation (radiances, RS, avions commerciaux…) par comparaison entre ébauche, observations et analyse La sensibilité aux conditions initiales indique la position des erreurs initiales qui ont leur maximum d’amplification en 30h dans la zone cible (polygone violet) Forecaster Expertise Un état initial incertain conduit à une prévision incertaine Deux méthodes pour propager l’incertitude : La prévision d’ensemble transporte l’incertitude dans le temps et l’espace  renseigne la confiance dans la prévision Finalement…. À une prévision incertaine correspond une erreur de prévision

9. Forecaster Expertise Objective link between WV and dynamics , particlcle filter (Wirth, Michel, Guth)

10. Improvement of initial state through PV improvement • tropopause 2D modification/correction (surface with potential vorticity=1.5pvu) et MSLP (SYNERGIE) • 3D PV correction buiding (using vertical PV covariance errors) • PV inversion • Rerun of the model …

11. 1997 1998 2000 2002 2004 2006 2008 2010 2012 2014 Lothar&Martin Xynthia Klaus Explicit microphysics global LAM NH 2.5km 4DVar global 3DVar global Global EDA More and more sat. Data are assimilated h and v resolution increase(5010km over Europe) 1st PV inversion with Forecast improvement Global ensemble 11 members Global ensemble 35 members Ertel PV graphical modif+inversion+model run Suite in operation (Arbogast et al, 2008 QJRMS, 2011 W&F) Experiment involving senior forecasters ? Decision taken MF project kick-off QGPV +simple corrections (Hello et al., 2004 Met. Apps)

12. Improvement of initial state through PV improvement • Outline of the method

13. Case study: windstorm Klaus (23-24 January 2009)

14. Case study: windstorm Klaus (23-24 January 2009)

16. 1st step: • What can be inferred from comparison between model and satellite/surface observations using Global ARPEGE run at 0600UTC and observations between 0600UTC and 1200UTC ? (decision required at 1200UTC)

17. It appears clearly that the amplitude of the upper-level feature is underestimated by the model.

18. “model to satellite” approach to reduce the uncertainty Observation (Meteosat 8) 6h forecast Valid time :1200UTC 23 January 2009

19. PV correction (z) after 1D-var DPV Iso-PV Methodology PV modifications z y x

20. Before modification PV inversion After modification

21. PV inversion at the Météo-France’s weather room • Outcomes of the experiments in real-time of not: • Particularly efficient when type-B cyclogenesis is present • Reliable approach in average • Marginal computational cost • Suitable for surface systems • Suitable in cases of mesoscale convections (not only windstorms) • But • Difficult to monitor the initial state for explosive cyclogenesis without pre-existing upper PV features (Lothar, December 1999) • Less forecast busts to be corrected with time (more observations,  flow-dependant B matrices) • Growing importance of ensembles

22. Resultat Klaus

23. observations observations observations t Operational run Modified runs Operational run 12UTC 24 Jan 2009 12 UTC 23 Jan 2009 06 UTC 23 Jan 2009 Experiments design: • 25 experiments/attempts of model state improvement have been achieved by 4 different senior forecasters and 3 scientists. • A subset of 14 randomly chosen runs has been built (2 runs for each forecaster/scientist)

24. PV inversion at the Météo-France’s weather room • Outcomes of the experiments in real-time of not: • Particularly efficient when type-B cyclogenesis is present • Reliable approach in average • Marginal computational cost • Suitable for surface systems • Suitable in cases of mesoscale convections (not only windstorms) • But • Difficult to monitor the initial state for explosive cyclogenesis without pre-existing upper PV features (Lothar, December 1999) • Less forecast busts to be corrected with time (more observations,  flow-dependant B matrices) • Growing importance of ensembles

25. Purpose : • Do several forecasters come to the same conclusion in terms of initial conditions errors and modifications (in terms of dynamical tropopause) that could be applied? • Common features among modifications ?

26. The projection onto the first EOF maximizes the forecast skill • 3 first EOFs of the 14x14 covariance matrix of the perturbations set • (resp 50%, 9%,5% of the total variance)

27. better than R6 AND R12 oper Oper 1200UTC MSLP RMSE Oper 1200UTC wind RMSE Oper R12 RMSE Worst than R6 AND R12 oper RMS Error for MSLP RMS Error for 10m wind magnitude Forecast skill (24h)

28. +15h (~Tx J) +27h (~Tn J+1) EQM ARPEGE EQM CTPIni AS TEMPERATURE CTPIni v.2007

29. PV inversion at the Météo-France’s weather room • Outcomes of the experiments in real-time of not: • Particularly efficient when type-B cyclogenesis is present • Reliable approach in average • Marginal computational cost • Suitable for surface systems • Suitable in cases of mesoscale convections (not only windstorms) • But • Difficult to monitor the initial state for explosive cyclogenesis without pre-existing upper PV features (Lothar, December 1999) • Less forecast busts to be corrected with time (more observations,  flow-dependant B matrices) • Growing importance of ensembles

30. TSR 9-10h

31. PV inversion at the Météo-France’s weather room • Outcomes of the experiments in real-time of not: • Particularly efficient when type-B cyclogenesis is present • Reliable approach in average • Marginal computational cost • Suitable for surface systems • Suitable in cases of mesoscale convections (not only windstorms) • But • Difficult to monitor the initial state for explosive cyclogenesis without pre-existing upper PV features (Lothar, December 1999) • Less forecast busts to be corrected with time (more observations,  flow-dependant B matrices) • Growing importance of ensembles

32. Situation du 28 mars 2008 33

33. Situation le 28 mars 2008 à 06TU 34

34. 35

35. 36

36. PV inversion at the Météo-France’s weather room • Outcomes of the experiments in real-time of not: • Particularly efficient when type-B cyclogenesis is present • Reliable approach in average • Marginal computational cost • Suitable for surface systems • Suitable in cases of mesoscale convections (not only windstorms) • But • Difficult to monitor the initial state for explosive cyclogenesis without pre-existing upper PV features (Lothar, December 1999) • Less forecast busts to be corrected with time (more observations,  flow-dependant B matrices) • Growing importance of ensembles

38. R.d.Hullessen, Le Midi Libre

39. Initial state 1.5 PVU height and WV (M8) picture – Areas where corrections are applied are outlined After corrections

40. 18UTC 00UTC PV

42. Argence, Vich,

43. PV inversion at the Météo-France’s weather room • Outcomes of the experiments in real-time of not: • Particularly efficient when type-B cyclogenesis is present • Reliable approach in average • Marginal computational cost • Suitable for surface systems • Suitable in cases of mesoscale convections (not only windstorms) • But • Difficult to monitor the initial state for explosive cyclogenesis without pre-existing upper PV features (Lothar, December 1999) • Less forecast busts to be corrected with time (more observations,  flow-dependant B matrices) • Growing importance of ensembles

45. PV inversion at the Météo-France’s weather room • Outcomes of the experiments in real-time of not: • Particularly efficient when type-B cyclogenesis is present • Reliable approach in average • Marginal computational cost • Suitable for surface systems • Suitable in cases of mesoscale convections (not only windstorms) • But • Difficult to monitor the initial state for explosive cyclogenesis without pre-existing upper PV features (Lothar, December 1999) • Less forecast busts to be corrected with time (more observations,  flow-dependant B matrices) • Growing importance of ensembles

46. Avec l’outil CTPini on retrace (en marron) le champ de PVu qu’on souhaiterait avoir (l’original est en bleu).

47. Sur le réseau de ce 2 mai à 06TU sérieux problèmes de calage sur un retour d’est, que ce soit avec Arpège (en bas) ou avec Arome (en haut). On a au moins en altitude un noyau de PVu qui n’est pas au bon endroit.

49. En bleu Pearp éch03 en marron CTpini

50. Conclusion • Intrinsic uncertainty in human PV modifications • Fairly good reliability of corrections provided by different experts (common features) • Evidence of model improvement • Common expertise better than than individual one. • Future • Within ensemble (Vich et al 2012 in Tellus) • Training/tool for sensitivity study (Ricard et al.)