© crown copyright met office investigating a perturbed physics scheme in a wave ensemble system ray...
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© 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
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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
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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
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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
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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
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Introductionperturbed physics scheme
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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%
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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.
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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
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Sensitivity studyEffective wind stress
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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
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STABSH
NAE buoy locations (ndbc)
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STABSH
North west of Scotland 7/09/09
STABSH = 1.5
STABSH = 1.3
.
.
Observations
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STABSH
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13/09/09 Track 1203
Hs spread has Non-linear relation with wind speed, possibly related to wind direction as well
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STABSH
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STABSH
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STABSH
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STABSH
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STABSH
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STABSH
STABSH values
RMSE (m) Bias (m) Corr (r)
1.3 0.495 0.040 0.911
1.35 0.515 0.109 0.913
1.4 0.549 0.175 0.912
1.45 0.589 0.244 0.913
1.5 0.637 0.312 0.913
Default is 1.38. A lower value (1.3) gives better statistics against observations for this time period
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STABSH
Sep 09 – NAE domain
15%
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Random STABSHPerturb every 12 hours in the forecast length
winds still fixed
7.5%
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Sensitivity studySwell attenuation
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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
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SWELLF
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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.
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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
-0.1m0.1m
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Perturbed winds vs. Perturbed winds and perturbed physics
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RMSE plots
Perturbed winds Perturbed winds and physics
1/09/09 – 27/09/09 Increase spread of ~5%
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Talagrand diagrams (Hs)
Perturbed winds Perturbed winds and physics
Underspread – No clear improvement with perturbed physics scheme
Only one month worth of data
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Talagrand diagram (Wind speed)
Perturbed winds run (same for perturbed winds and physics)
still underspread in the system
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Spatial Hs difference 19/09
Perturbed winds Perturbed winds and physics
Mean
Spread
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Spread-skill diagrams
Perturbed winds Perturbed winds and physics
Only valid up to a spread of ~0.5m.
Little difference between the two runs
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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
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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.
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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