1. © Crown copyright Met Office Investigating a perturbed physics scheme in a wave ensemble system Ray Bell (Line manager: Francois-Bocquet) Ocean Iced Tea 14/09/2010

2. © Crown copyright Met Office Table of Contents Wave ensemble system Perturbed physics scheme Sensitivity studies – Effective wind stress - Swell attenuation filter factor Perturbed winds vs. Perturbed winds and perturbed physics Conclusions Future Work

3. © Crown copyright Met Office Why the need for a Wave ensemble system? Limitations of deterministic models - Can miss extreme events. Obtain reliable probabilities of wave events happening. - Time window of calm waves important for offshore lifting applications. Act as a re-tuning exercise for the operational model

4. © Crown copyright Met Office NAE 24-member ensemble designed for short-range forecasting Regional ensemble over N. Atlantic and Europe (NAE) (24km resolution) to T+54 Global ensemble (~90km resolution) to T+60 ETKF for initial condition pert Stochastic physics Global run at 0Z and 12Z. Regional run at 6Z & 18Z Global creates boundary conditions for the NAE Wave ensemble system

5. © Crown copyright Met Office WAVEWATCH3 – The Met Office wave model Spectral model (24 directions X 25 frequencies resolution) Tolman-Chalikov source terms Restart each ensemble member from the previous cycles forecast (T+12) => Maintain spread at low lead times. esp. swell waves

6. © Crown copyright Met Office Introduction perturbed physics scheme

7. © Crown copyright Met Office Uncertainties Uncertainties in the model: Initial conditions (Wind forcing, waves) Model structure – grid size Parameterization of physics Previous work investigating the initial conditions have been able to account for 50% of the uncertainty in the wave ensemble system. (Jan 09-Apr 09) Adding a perturbed physics scheme aims to increase this and capture more uncertainty. Assess over a 3 month period. (Sep 09-Nov 09) 50%

8. © Crown copyright Met Office What is a perturbed physics scheme? Physics stay the same but the parameter value varies. Fine tuning of the processes in WW3 occur through tuning knobs to avoid unbalancing input and dissipation terms. Processes occur on scales to small to be resolved e.g dissipation => the need to parameterize Leads to uncertainty associated with empirical parameters.

9. © Crown copyright Met Office Perturbed physics scheme Indentify the key parameters in WW3 likely to cause uncertainty – Lit review (Tolman, 2002) and expert discussions, - Effective wind stress, U e – (STABSH) - Swell attenuation (SWELLF) - Non-linear interaction terms? - Dissipation? Treat a selected group of parameters as stochastic variables (Random sampling from uniform distribution) Chosen from appropriate limits

10. © Crown copyright Met Office Sensitivity study Effective wind stress

11. © Crown copyright Met Office Effective wind stress (U e ) U e governs a more accurate representation of how wind energy is transferred to waves in the presence of different atmospheric conditions (temperature and moisture stratification) c 0 (STABSH) assigned values of 1.3, 1.35, 1.4, 1.45 and 1.5 (default is 1.38). Tolman (2002) originally investigated 1.35, 1.38, 1.4 and 1.42 Ran for a month with fixed winds. STABSH

12. © Crown copyright Met Office STABSH NAE buoy locations (ndbc)

13. © Crown copyright Met Office STABSH North west of Scotland 7/09/09 STABSH = 1.5 STABSH = 1.3. Observations

14. © Crown copyright Met Office STABSH

15. © Crown copyright Met Office 13/09/09 Track 1203 H s spread has Non-linear relation with wind speed, possibly related to wind direction as well

16. © Crown copyright Met Office STABSH

17. © Crown copyright Met Office STABSH

18. © Crown copyright Met Office STABSH

19. © Crown copyright Met Office STABSH

20. © Crown copyright Met Office STABSH

21. © Crown copyright Met Office STABSH STABSH values RMSE (m)Bias (m)Corr (r) 1.30.4950.0400.911 1.350.5150.1090.913 1.40.5490.1750.912 1.450.5890.2440.913 1.50.6370.3120.913 Default is 1.38. A lower value (1.3) gives better statistics against observations for this time period

22. © Crown copyright Met Office STABSH Sep 09 – NAE domain 15%

23. © Crown copyright Met Office Random STABSH Perturb every 12 hours in the forecast length winds still fixed 7.5%

24. © Crown copyright Met Office Sensitivity study Swell attenuation

25. © Crown copyright Met Office Swell attenuation filter factor (X s ) Swell dissipation due to opposing or weak winds is improved using a filtered input source term: X s was assigned values of 0.1, 0.105 and 0.11 (default is 0.1). Tolman (2002) originally investigated 0.087, 0.1, 0.11 and 0.125 Ran for a month with fixed winds. SWELLF

26. © Crown copyright Met Office SWELLF

27. © Crown copyright Met Office SWELLF – 4bin output Small effect on H s, does it effect wave period? 4bin gives the energy present in different wave systems and partitions waves into waves periods of 0-5s, 5-10s, 10-15s and 15-20s (level 1). Information can be lost when investigating H s Very Localised change in time and space.

28. © Crown copyright Met Office 4bin difference 19/09/09 Lv. 2. (10-15s) NAE domain Very localised change in time and space. Influence on this part of the wave field are still small Wave height SWELLF = 1.1 Wave height SWELLF = 1.11 Middle – top plot -0.1m 0.1m

29. © Crown copyright Met Office Perturbed winds vs. Perturbed winds and perturbed physics

30. © Crown copyright Met Office RMSE plots Perturbed windsPerturbed winds and physics 1/09/09 – 27/09/09 Increase spread of ~5%

31. © Crown copyright Met Office Talagrand diagrams (H s ) Perturbed winds Perturbed winds and physics Underspread – No clear improvement with perturbed physics scheme Only one month worth of data

32. © Crown copyright Met Office Talagrand diagram (Wind speed) Perturbed winds run (same for perturbed winds and physics) still underspread in the system

33. © Crown copyright Met Office Spatial H s difference 19/09 Perturbed winds Perturbed winds and physics Mean Spread

34. © Crown copyright Met Office Spread-skill diagrams Perturbed winds Perturbed winds and physics Only valid up to a spread of ~0.5m. Little difference between the two runs

35. © Crown copyright Met Office Conclusions Increase in spread with the perturbed physics added is not as large as expected. Randomly changing a physical parameter onto the wind members has a tendency to lose the increase in spread caused by the wind speed. STABSH and wind intensity are not correlated. Interaction between parameters values – Trade of between improving negative biases in the tropics and positive biases in the storm tracks (changes in STABSH and SWELLF are interlinked) (Tolman, 2002) A slightly lower STABSH value provided better statistics for H s in the NAE domain. However, cant be directly compared to operational model due to resolution differences Strong test bed for further studies

36. © Crown copyright Met Office Future work Gain a better understanding of STABSH and SWELLF – how changes affect the wave field in space and time. 3 month validation. Use satellite data in the validation process (RMSE) Possibility of Perturbing more physical parameters. Compare to a dressed ensemble – bias and std of model given from comparisons to observations at site specific locations. Pros and cons of each approach.

37. © Crown copyright Met Office Any Questions ??? References Bocquet, Francois-Xavier, Sauler, A. and Bunney, C. (2009) Wave ensemble scoping study. Bowler, N.E., Arribas, A., Mylne, K.R., Robertson, B.K., and Beare, S.E. (2008) The MOGREPS short-range ensemble prediction system. Q. J. Meteorol. Soc. 134, 703-722. pp. 703-722. Tolman, H.L. (2002) Testing of WAVEWATCH III version 2.22 in NCEPs NWW3 ocean wave model suite. Technical note. July 2002. Tolman, H.L. and Chalikov, D. (1996) Source terms in a third-generation wind wave model. J. of Phys. Oc. 26, pp. 2497-2518