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Investigating a perturbed physics scheme in a wave ensemble system

Investigating a perturbed physics scheme in a wave ensemble system. Ray Bell (Line manager: Francois-Bocquet) Ocean Iced Tea 14/09/2010. Table of Contents Wave ensemble system Perturbed physics scheme Sensitivity studies – Effective wind stress

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Investigating a perturbed physics scheme in a wave ensemble system

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

  2. 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. 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 Why the need for a Wave ensemble system?

  4. Wave ensemble system • 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 NAE

  5. 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. Introduction perturbed physics scheme

  7. 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. 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. Perturbed physics scheme • Indentify the key parameters in WW3 likely to cause uncertainty – Lit review (Tolman, 2002) and ‘expert’ discussions, - Effective wind stress, Ue – (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. Sensitivity study Effective wind stress

  11. Effective wind stress (Ue) • Ue governs a more accurate representation of how wind energy is transferred to waves in the presence of different atmospheric conditions (temperature and moisture stratification) • c0 (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. STABSH NAE buoy locations (ndbc)

  13. STABSH Observations STABSH = 1.5 .. STABSH = 1.3 North west of Scotland 7/09/09

  14. STABSH

  15. 13/09/09 Track 1203 Hs spread has Non-linear relation with wind speed, possibly related to wind direction as well

  16. STABSH

  17. STABSH

  18. STABSH

  19. STABSH

  20. STABSH

  21. STABSH Default is 1.38. A lower value (1.3) gives better statistics against observations for this time period

  22. STABSH 15% Sep 09 – NAE domain

  23. Random STABSH Perturb every 12 hours in the forecast length winds still fixed 7.5%

  24. Sensitivity study Swell attenuation

  25. Swell attenuation filter factor (Xs) • Swell dissipation due to opposing or weak winds is improved using a filtered input source term: • Xs 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. SWELLF

  27. SWELLF – 4bin output • Small effect on Hs, 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 Hs • Very Localised change in time and space.

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

  29. Perturbed winds vs. Perturbed winds and perturbed physics

  30. RMSE plots Perturbed winds Perturbed winds and physics Increase spread of ~5% 1/09/09 – 27/09/09

  31. Talagrand diagrams (Hs) Perturbed winds and physics Perturbed winds Underspread – No clear improvement with perturbed physics scheme Only one month worth of data

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

  33. Spatial Hs difference 19/09 Mean Spread Perturbed winds and physics Perturbed winds

  34. 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. 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 Hs in the NAE domain. However, can’t be directly compared to operational model due to resolution differences • Strong test bed for further studies

  36. 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. 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 NCEP’s 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

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