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

A ten-year experiment of real-time

Potential Vorticity modifications and

inversions at

Météo-France

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Forecaster Expertise

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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 modelsChose the “best member “ among several solutions provided by

deterministic forecasts and scenarios from ensemblesMonitor 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

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Forecaster Expertise

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Un état initial incertain conduit à une prévision incertaine

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 prévision d’ensemble transporte l’incertitude dans le temps et l’espace renseigne la confiance dans la prévision

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)

Deux méthodes pour propager l’incertitude :

Forecaster Expertise

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Un état initial incertain conduit à une prévision incertaine

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 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

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)

Deux méthodes pour propager l’incertitude :

Forecaster Expertise

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8

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Forecaster Expertise

Objective link between WV and dynamics , particlcle filter (Wirth, Michel, Guth)

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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 inversionRerun of the model …

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1997 1998 2000 2002 2004 2006 2008 2010 2012 2014

4DVar

global

More and more sat. Data are assimilatedh and v resolution increase(5010km over Europe)

Explicit

microphysics

global LAM NH

2.5km

Global ensemble

35 members

Global ensemble

11 members

3DVar

global

Global EDA

Lothar&Martin

KlausXynthia

1st PV in

version with

Forecast improvement

MF project kick-off

QGPV +simple corre

ctions

(Hello et a

l., 2004 M

et.

Apps)

Ertel P

V graphical

modif+inversion+model ru

n

Suite in

operation

(Arbogast et a

l, 2008 Q

JRMS, 2011

W&F)

Experiment involving senior forecasters ?

Decision taken

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Improvement of initial state through PV improvement

Outline of the method

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

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

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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)

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

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“model to satellite” approach to reduce the uncertainty

Observation (Meteosat 8) 6h forecast

Valid time :1200UTC 23 January 2009

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Iso-PV

PV

PV correction (z) after 1D-var

x

y

z

Methodology PV modifications

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PV inversion

Before modification

After modification

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PV inversion at the Météo-France’s weather room

Outcomes of the experiments in real-time of not:

1. Particularly efficient when type-B cyclogenesis is present2. Reliable approach in average 3. Marginal computational cost 4. Suitable for surface systems 5. Suitable in cases of mesoscale convections (not only windstorms)

But

1. Difficult to monitor the initial state for explosive cyclogenesis without pre-existing upper PV features (Lothar, December 1999)

2. Less forecast busts to be corrected with time (more observations,  flow-dependant B matrices)

3. Growing importance of ensembles

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Resultat Klaus

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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)

t

12 UTC23 Jan 2009

12UTC24 Jan 200906 UTC

23 Jan 2009

Operational run

Modified runs

Operational run

obse

rvat

ions

obse

rvat

ions

obse

rvat

ions

Experiments design:

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PV inversion at the Météo-France’s weather room

Outcomes of the experiments in real-time of not:

1. Particularly efficient when type-B cyclogenesis is present2. Reliable approach in average 3. Marginal computational cost 4. Suitable for surface systems 5. Suitable in cases of mesoscale convections (not only windstorms)

But

1. Difficult to monitor the initial state for explosive cyclogenesis without pre-existing upper PV features (Lothar, December 1999)

2. Less forecast busts to be corrected with time (more observations,  flow-dependant B matrices)

3. Growing importance of ensembles

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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 ?

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3 first EOFs of the 14x14 covariance matrix of the perturbations set

(resp 50%, 9%,5% of the total variance)

The projection onto the first EOF maximizes the forecast skill

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Forecast skill (24h)

better than R6 AND R12 oper

Worst than R6 AND R12 oper

RMS Error for MSLPRMS Error for 10m wind magnitude

Oper 1200UTC MSLP RMSE

Oper 1200UTC wind RMSE

Oper R12 RMSE

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AS TEMPERATURE CTPIni v.2007

EQM CTPIni

EQM ARPEGE

+15h(~Tx J)

+27h(~Tn J+1)

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PV inversion at the Météo-France’s weather room

Outcomes of the experiments in real-time of not:

1. Particularly efficient when type-B cyclogenesis is present2. Reliable approach in average 3. Marginal computational cost 4. Suitable for surface systems 5. Suitable in cases of mesoscale convections (not only windstorms)

But

1. Difficult to monitor the initial state for explosive cyclogenesis without pre-existing upper PV features (Lothar, December 1999)

2. Less forecast busts to be corrected with time (more observations,  flow-dependant B matrices)

3. Growing importance of ensembles

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TSR 9-10h

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PV inversion at the Météo-France’s weather room

Outcomes of the experiments in real-time of not:

1. Particularly efficient when type-B cyclogenesis is present2. Reliable approach in average 3. Marginal computational cost 4. Suitable for surface systems 5. Suitable in cases of mesoscale convections (not only windstorms)

But

1. Difficult to monitor the initial state for explosive cyclogenesis without pre-existing upper PV features (Lothar, December 1999)

2. Less forecast busts to be corrected with time (more observations,  flow-dependant B matrices)

3. Growing importance of ensembles

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Situation du 28 mars 2008

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Situation le 28 mars 2008 à 06TU

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35 35

36 36

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PV inversion at the Météo-France’s weather room

Outcomes of the experiments in real-time of not:

1. Particularly efficient when type-B cyclogenesis is present2. Reliable approach in average 3. Marginal computational cost 4. Suitable for surface systems 5. Suitable in cases of mesoscale convections (not only windstorms)

But

1. Difficult to monitor the initial state for explosive cyclogenesis without pre-existing upper PV features (Lothar, December 1999)

2. Less forecast busts to be corrected with time (more observations,  flow-dependant B matrices)

3. Growing importance of ensembles

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39 R.d.Hullessen, Le Midi Libre

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After corrections

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

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PV

18UTC 00UTC

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Argence, Vich,

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PV inversion at the Météo-France’s weather room

Outcomes of the experiments in real-time of not:

1. Particularly efficient when type-B cyclogenesis is present2. Reliable approach in average 3. Marginal computational cost 4. Suitable for surface systems 5. Suitable in cases of mesoscale convections (not only windstorms)

But

1. Difficult to monitor the initial state for explosive cyclogenesis without pre-existing upper PV features (Lothar, December 1999)

2. Less forecast busts to be corrected with time (more observations,  flow-dependant B matrices)

3. Growing importance of ensembles

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PV inversion at the Météo-France’s weather room

Outcomes of the experiments in real-time of not:

1. Particularly efficient when type-B cyclogenesis is present2. Reliable approach in average 3. Marginal computational cost 4. Suitable for surface systems 5. Suitable in cases of mesoscale convections (not only windstorms)

But

1. Difficult to monitor the initial state for explosive cyclogenesis without pre-existing upper PV features (Lothar, December 1999)

2. Less forecast busts to be corrected with time (more observations,  flow-dependant B matrices)

3. Growing importance of ensembles

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

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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.

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En bleu Pearp éch03 en marron CTpini

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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.)

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4DVar assimilation instead of inversion