oceanography 569 oceanographic data analysis laboratory kathie kelly applied physics laboratory 515...
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Oceanography 569Oceanographic Data Analysis Laboratory
Kathie KellyApplied Physics Laboratory
515 Ben Hall IR Bldgclass web site:
faculty.washington.edu/kellyapl/classes/ocean569_2014/
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Applying Analysis Tools practice exercise for project
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Sea Level Variability in the Eastern Mediterranean Sea
Data:% sshm - weekly sea surface height anomaly (SSH)% Qnet - daily net surface heat flux (OAFlux)% alf _rho_cp - alpha/(rho*cp)% where alpha is the coefficient of thermal expansion% cp is the specific heat of sea water, rho is density of sea water% txqs, tyqs - daily QuikSCAT wind stress components% coastline - lon, lat for graphics
Model:% thermal expansion from seasonal heating (vertical integral of temperature,converted to SSH using the coefficient of thermal expansion)%% d(SSH)/dt = alf*Qnet/(rho*c_p)%
Other candidate (for statistical comparison):% wind stress
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Sea Level Variability in the Eastern Mediterranean Sea
Look at time-longitudeto determine obvious signals
Seasonal cycle apparentNo evidence of RW propagation
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Sea Level Variability in the Eastern Mediterranean Sea
Run the heating model and compare with observed SSH
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Sea Level Variability in the Eastern Mediterranean Sea
Run the heating model and compare with observed SSH
One outcome:Assess skill
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Sea Level Variability in the Eastern Mediterranean Sea
Compare winds with (nonseaonal) SSH
Match integral time scales of ssh and winds (approximately)
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Sea Level Variability in the Eastern Mediterranean Sea
What analysis tools do we have for comparing data without a model?
Compare winds with (nonseaonal) SSH
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Sea Level Variability in the Eastern Mediterranean Sea
Compare winds with (nonseaonal) SSH
1) SSH 1 and stress 1 correlated with zero lag: Northward winds high sea level
2) SSH 2 and stress 2 marginally correlated
3) Stress 1 leads stress 2: Northward winds lead cyclone (eastward propagation of storms)
Overall: heating accounts for much of seasonal cycle Rest is wind-driven, but mechanism unclear
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Applying Analysis Tools practice exercise for project
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Projects
Chose either project 1 or 2• Use analysis tools from class (including models for the project)• Write up results in a slide presentation (approximately 30 min)• Do NOT include your Matlab code – think of this as a seminar!
Include in presentation: • What is the science question?• What is your analysis plan? Why?• What special considerations are there? • What tools did you use? models, statistical procedures, etc• Show metrics: skill, significance tests, etc• What did you conclude? Why?• Show data examples, analysis outcomes, etc
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Project 1: What Causes SST Variability in the Gulf Stream?
Data: SST, climatological MLD, Gulf Stream path, winds
One dimensional mixed layer model: dT/dt = (Q-qrad)/(rho*cp*h)
where qrad is the radiative flux leakage for the given climatological MLD h
1) Climatological analysis:• Do you see climatological errors?
(errors that recur each year)• Is there a pattern to the errors?• How would you correct for an error in
climatological Q/h?
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Project 1: What Causes SST Variability in the Gulf Stream?
2) Analyze residual:dT/dt(model) - dT/dt(obs)
What are the errors in the heating model?
Other candidates: • Gulf Stream path changes • Winds
How do each of these affect SST?
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Project 1: What Causes SST Variability in the Gulf Stream?
What are the missing terms in this mixed layer model?
Without writing a new model can you relate these candidate variables to the residual? (statistical relationships)
• What are some ways that wind can effect dT/dt?
(Note: changes in wind speed are accounted for in Q)
• How does the change in Gulf Stream path affect dT/dt?
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Project 2: What causes SSH anomalies in tropical Atlantic?
Candidates:
surface heating(OAFlux/ISCCP net surface flux)
wind-forced Rossby waves (QuikSCAT wind stress curl)
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Project 2: What causes SSH anomalies in tropical Atlantic?
response to surface heating:
dη/dt = Qnet*α/(rho*c_p)
wind-forced Rossby waves:
dη/dt = c*dη/dx –r*η -C*curl
where c is the phase speed of the Rossby waves and r is a damping factor (eddy diffusion)
RW model needs an eastern boundary condition (because waves travel westward), so use SSH interpolated to the model t grid
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Project 2: What causes SSH anomalies in tropical Atlantic?
More information:
RW model does not include thermosteric sea level, so remove heating response from SSH first
RW model has some fungible parameters, g’, r (damping), and phase speed, c.
Estimate phase speed, but adjust to reduce errors. Reduced gravity (g’) can be adjusted also.
The damping factor (alf/r) has been optimized so no need to change it.