Le sytème régional de prévisions des glaces (RIPS)

1. Le sytème régional de prévisions des glaces (RIPS) Optimisation du modèle et vérification des prévisions Jean-François Lemieux, Christiane Beaudoin Collaborateurs François Roy (CMC), Gregory Smith (RPNE), Frédéric Dupont (CMC), Mark Buehner (ARMA), Alain Caya (ARMA), Patricia DeRepentigny (CMC), André Plante (CMC), Paul Pestieau (CIS), Tom Carrières (CIS), Pierre Pellerin (RPNE), Gilles Garric (Mercator), Nicolas Ferry (Mercator) CMC 15 mars 2013

2. Plan • 1) Brève descriptionde RIPS • 2) Optimization du modèle avec les bouées dérivantes • 3) Méthode de vérification • 4) Expériences de sensibilité du modèle : • - profondeur de la couche de mélange (MLD) • - taille des floes • 5) Évaluation de RIPS • 6) Résumé et futur

3. Responsabilités du Canada dans le projetMETAREA - Émettre et disséminer les prévisions atmosphériques et maritimes (incluant la couverture de glace) pour les régions Metarea 17 et 18 - Phase 1 : RIPS (modèle de glace offline) utilisé pour produire les prévisions de glace - Phase 2 : Modèle de glace (CICE 4.1) couplé au modèle océanique (NEMO) CREG12 (F. Dupont) - Phase 3 : Modèle pleinement couplé Atmosphère/Glace/Océan

4. Description of the ice model The model used is the CICE Los Alamos sea ice model CICE version 4.1 (E.Hunke, W.Lipscomb - Documentation Nov 2008 ) It has several components : - a thermodynamic model that computes local growth rates of snow and ice - a ice dynamics model that predicts the velocity field of the ice pack - a transport model that describes the advection of the ice concentration, ice volumes and others state variables - a ridging parameterization that transfers ice among thickness categories The number of ice categories used : ncat = 8 WMO standard ice thickness categories + 1 category : 10 - 15 – 30 – 50 – 70 – 120 – 200 >200 cm

5. OFF LINE ICE FORECAST Initial time • 3d-var ice analysis Ice concentration (A) • Glorys1v1 climatology - Ice thickness (h) - Mixed layer depth (mld) • CMC SST analysis Sea surface temperature - Previous ice forecast Ice velocity (u0) Atmospheric forcing fields CMC RDPS forecast - Wind components - Temperature - Humidity - SW and LW Fluxes - Precipitation rates Sea ice model Mixed-layer ocean Ocean forcing field • Glorys1v1 climatology Ocean current (Uw) Ice forecast Ice concentration (A) Ice velocity (u) Ice pressure (P) Verification package Ice concentration

6. Climatologie -Glorys1v1 - réanalyses océaniques globales - période 7ans 2002-2008 - résolution .25 deg - forçages atmosphériques dérivés des analyses opérationnelles ECMWF - modèle océanique :Nemo - modèle de glace : Lim2 (2 catégories de glace)

7. - Ice model is run on 3d-var North American ice analysis grid - 5 km resolution (1640x1080) - Forced by Gem regional forecasts at 10km resolution - Time step = 1200s - Outputs every 3 hours - Issued 4 times a day 00z, 06z, 12z, 18z in experimental mode R&D since july 2012 Ice concentration 3d-var NA Analysis Valid 06 May 2010

8. RIPS and drifting buoys optimization We optimize using the ice strength parameter P* The resistance of ice to deformation P is proportional to P*. P = P* h exp [-C (1-A)] P = ice strength h = ice thickness C = empirical constant = 20 A = total ice concentration Dansereau and Tremblay (in prep) Kreysher et al. 2000

9. RIPS and drifting buoys optimization Averaging over one year About 20 buoys per day

10. RIPS and drifting buoys optimization

12. RMSE and bias calculations We calculate the following: where DSLO < 0.5 day and

13. Verification mask against 3Dvar analysis - dslo (days since last obs) < 0.5 and - change in Aice (ice concentration) > 10%

14. Verifications

15. F48h A0h A48h

17. Sensitivity to mixed layer depth 48h forecast NA region - The mixed layer depth (MLD) best constant value was found for each month - Climatological values (2-d fields) give results as good as best value for each month

18. Sensitivity to ice floes diameter (affecting the lateral melt) 48h forecast NA region - The value of 30m was found optimal

19. Prévisions faites pour toute l’année 2010 aves les paramètres optimaux :- Epaisseur de couche de mélange climatologique- Diamètre des floes de glace = 30m- P* = 12,5kN/m2 Vérification des prévisions RIPS

20. region=Bering lead=48 region=NA lead=48

21. region=NA lead =24h region=NA lead =48h

22. Error field for 48h forecast starting 8 march 2010 18z b : dynamics + thermodynamics c : dynamics only

23. Monthly verifications - better than persistence for all months of 2010 but - not statistically significant in January and March (bootstrap method 95%)

24. March persistence March forecast October persistence October forecast monthly RMSE

25. Monthly verifications - using the latest and improved RIPS2 3D-Var analyses - note that RMS and bias values of persistence and forecast are reduced

26. Merci!!!

27. RIPS ouputs available everyday http://whxlab3.dart.ns.ec.gc.ca/~murthaj/rips/rips.php

28. Summary • RIPS is in mode R&D (4-48h forecasts / day) since july 2012. • Objective tuning of RIPS against drifting buoys. • Mixed layer depth (MLD) climatology improves skill during growing season. • RIPS beats persistence almost all year (more difficult in january, february, march). • The two thickness category climatology is a weakness. • Publication soumise Q. J. R. Meteorol. Soc. (fév 2013) : • The Regional Ice Prediction System (RIPS) : model optimization and forecasts verification

29. Futur - Présentation CPOP 19 mars 2013 : Proposition de passe expérimentale pour le système régional des prévisions des glaces (RIPS) - RIPSlivréaux opérations du CMC printemps 2013 - Migration à la grille CREG12

31. De vieux proverbes nous donnent enfin des réponses !!! Processus thermodynamique simplifié : << Il n’y a ni neige ni glace que le soleil ne fonde >> Pour des prévisions de glace à long terme simples et précises : <<A la Saint-Mathias se fond et se brise la glace (14mai) >>