La présentation est en train de télécharger. S'il vous plaît, attendez

La présentation est en train de télécharger. S'il vous plaît, attendez

Forecasting severe weather events, more than 24 h ahead, at METEO FRANCE: An operational trial 11th EMS/10th ECAM, B. Gillet-Chaulet, DPREVI/PG January.

Présentations similaires


Présentation au sujet: "Forecasting severe weather events, more than 24 h ahead, at METEO FRANCE: An operational trial 11th EMS/10th ECAM, B. Gillet-Chaulet, DPREVI/PG January."— Transcription de la présentation:

1 Forecasting severe weather events, more than 24 h ahead, at METEO FRANCE: An operational trial 11th EMS/10th ECAM, B. Gillet-Chaulet, DPREVI/PG January , 15 H, Meteosat.

2 Context and motivations : Beyond the short range (24 H) at METEO FRANCE No equivalent oper. warning procedures available (not yet…) NWP improvements during recent years « Predictability » => Express uncertainty Xynthia windstorm : 3 days in advance !

3 Approach and Product : occurrence of severe weather events –Definition : orange or red level, Vigilance procedure, 24 h ahead. - Violent winds, - Heavy rains *, (not floods). - Violent thunderstorms, - Snow/Ice. (not temperatures). For one entire Day (00 to 24H), D+2, D+3… Zoning (fixed), administrative regions (significant) Risk Index (usual thunderstorms/fogs…) => Quantify the risk Risk Scale: 0, no risk, 1, low, 2, medium, 3, high.

4 In the past, (CNP -National Service- : December. 2004, ¼ de France). Reference/truth data : Vigilance level. Example : How much is a low risk (1), –Over the north-eastern regions, –Parameter –D+2 ? Approach and Product :

5 In the past, (CNP -National Service- : December. 2004, ¼ de France). Reference/truth data : Vigilance level. Example : How much is a low risk (1), –Over the north-eastern regions, –Parameter –D+2 ? Approach and Product :

6 In the past, (CNP -National Service- : December. 2004, ¼ de France). Reference/truth data : Vigilance level. Example : How much is a low risk (1), –Over the north-eastern regions, –Parameter –D+2 ? Approach and Product : nothing 20 % 1/5 in this example

7 D+2, Regions (in total): Fréq. Obs/Prév N Cases Period: 1st Nov – 1st April 2004/2005 to 2009/2010 (Winter before last) Approach and Product : Forecast No RiskLowMediumHigh Climatic frequency

8 Fréq. Obs/Prév Rare phenomena: Significant ? Period: 1st Nov – 1st April 2004/2005 to 2009/2010 (Winter before last) Approach and Product : D+2, Regions (in total): N Cases No RiskLowMediumHigh Forecast Climatic frequency And Feed-back (Low risk ?)

9 Fréq. Obs/Prév Latest Winter : 1st Nov – 1st April 2010/2011 Reliable ! Approach and Product : D+2, Regions (in total): N Cases HighMediumLowNo Risk Climatic frequency Forecast

10 Sample size, season, region, range, discrimination between indexes… Calibration (« Dressing » ) : Approach and Product : No Risk, Low, Medium, High. No Risk, Low, Medium, High.

11 Examples : Xynthia Valid for : Sunday 28/02/ days ahead2 days ahead D+3D+2 No Risk Low Medium High Calibrated Scale:

12 South-East, 7/09/2010 Valid for : Tuesday 7/09/ days ahead2 days ahead D+3D+2 Lyon, daily rainfall 104,1 mm Absolute Record (previous 1935) No Risk Low Medium High Calibrated Scale:

13 Paris under the snow, 8/12/2010 Valid for : Wednesday 8/12/ days ahead2 days ahead D+3D+2 FRANCE - A la mi-journée, la neige continuait de tomber sur la place de la Concorde à Paris. L'Île-de-France, comme dix-neuf autres départements, ont été placés par Météo France en vigilance orange neige et verglas ce mercredi. AFP/ Médina DE MIGUEL No Risk Low Medium High Calibrated Scale:

14 Events point of view (ROC) : D+2, Regions (in total), Period (01/11 – 01/04) : Probability of detection (POD) ( Hit Rate) : Probability of false detection (POFD) (False alarm rate) : Scale /10 ! 69%7% No Risk, Low, Medium, High. Scale ObservedNot Observed bad good

15 69%7% 6%0, % AROC = 0.81 ( 0.84, 0.79 ) Events point of view (ROC) : D+2, Regions (in total), Period (01/11 – 01/04) : Probability of detection (POD) ( Hit Rate) : Probability of false detection (POFD) (False alarm rate) : ObservedNot Observed Scale /10 ! Scale No Risk, Low, Medium, High. Scale No Risk, Low, Medium, High. good bad

16 Conclusion : Thanks to recent improvements (research, operational…) Signal at D+2, D+3, and beyond ! (7 Day test…) (Non deterministic) Proposal of synthesis… ->-> Since 1 st of March 2010, daily issue (14 H 30 local time ) : –COGIC, SCHAPI, CNIR, CRIR, INVS (feed back ?) CNP production (regions collaboration), Available on the internal Website Similar products already available on several Websites…(MET OFFICE)

17 Thank you for your attention

18 One Context back

19 Title : Forecasting severe weather events, more than 24 hours ahead, at METEO FRANCE: An operational trial. For the short range, typically 24 hours ahead, severe weather forecast procedures have been in effect for a long time. The French vigilance watch map celebrates its tenth anniversary in It puts in concrete form the first mission of METEO FRANCE in the domain of protection of people and goods, and has proved generally successful. Improvements in numerical weather prediction during recent years, now enable a focus on forecasting dangerous weather phenomena at longer ranges (e.g. within the Medium Range) and beyond the requirements for triggering a vigilance warning. However, this can not be just a simple extension of the validity of the vigilance watch map, because uncertainty generally quickly increases with the forecast range and makes a deterministic approach difficult. A systematic production, experienced on a daily basis since December 2004 at the national forecasting service of METEO FRANCE has tried to forecast the risk of occurrence of dangerous phenomena (violent winds, heavy rain, violent thunderstorms, snow/ice) that might reach orange or red warning levels of vigilance, several days ahead. Every morning, a risk index has been assessed by the forecasters, based on their study of deterministic models, numerous EPS products, for a given day from D+2 until D+7, and over given geographical areas of France. The index has been selected from no risk, unlikely, likely, certain. After choosing a reference or truth data (the colour of vigilance actually issued at the considered scale), accuracy and skill of the forecast has been shown. Then the idea has been to provide, in real time, the probabilities corresponding to the reliability of the chosen index taking into account the phenomenon, the samples representativeness and the discrimination between indexes. Since March 2010, encouraging results have allowed us to propose institutional partners of METEO FRANCE a forecast of the risk of occurrence of these phenomena in terms of probabilities at the scale of the administrative French regions for D+2 and D+3. First feed-back from the users is interesting, but shows that probabilities must be correctly interpreted. In fact, one still thinks that a probability of 50% corresponds to the toss of a coin, whereas it is significantly high when the climatological frequency of the phenomenon is low. Furthermore, decision makers have to learn how to make best use of this new type of information. Abstract:

20 Résumé : Ce travail concerne la prévision des phénomènes météorologiques présentant un risque pour la sécurité des personnes et des biens. A vingt-quatre heures déchéances, des procédures davertissement existent depuis longtemps : la « Vigilance » de Météo France fête ses dix ans dexistence en Les progrès notables réalisés en prévision ces dernières années permettent danticiper ces phénomènes à des échéances plus lointaines. Cependant, leur faible prévisibilité empêche une approche déterministe. Une production systématique, quotidienne, expérimentée depuis décembre 2004 à DPREVI/PG, sattache à prévoir le risque doccurrence des phénomènes « Vent violent, Pluie-innondation, Orages, Neige- verglas » susceptibles de relever des niveaux de vigilance orange ou rouge, à plusieurs jours déchéance. En mars 2010, les résultats encourageants ont permis de proposer aux partenaires institutionnels de Météo France une prévision du risque doccurrence de ces phénomènes, assortie dune probabilité calibrée, à léchelle des régions économiques françaises, pour les journées J+2 et J+3.


Télécharger ppt "Forecasting severe weather events, more than 24 h ahead, at METEO FRANCE: An operational trial 11th EMS/10th ECAM, B. Gillet-Chaulet, DPREVI/PG January."

Présentations similaires


Annonces Google