Distinguishing coupled oceanatmosphere. background noise in the North Pacific - David W. Pierce (2001) Patrick Shaw 4/5/06

Transcription

1 Distinguishing coupled oceanatmosphere interactions from background noise in the North Pacific - David W. Pierce (2001) Patrick Shaw 4/5/06

2 Outline Goal - Pose Overlying Questions Methodology noise and models Conclusions - Answer Overlying Questions Implications with Other Papers

3 Goal Determine if chaotic atmospheric forcings are a physical mechanism for decadal variability. Compare coupled atmospheric/ocean models with noise forcing to see if variability is random or results from coupled modes.

4 Overlying Questions Does white noise forcing affect variability on decadal time scales? Do coupled atmosphere ocean models support or refute this idea? How do regime shifts relate to noise forcing? Can decadal variability be predicted, or is it just a response to chaotic atmospheric forcing?

5 Noise White noise no memory, but equal power at all time scales, in this case Q Bucket analogy:? = overall power constant,? = frequency,? = density,? z = depth, cp = specific heat, T = temperature,? = climate damping

6 White Noise to Red Noise? Figure 1 Expected power spectrum of white noise forcing for oceanic mixed layer white noise forcing from atmosphere yields red noise response in SST

7 Red Noise and the PDO Figure 2 PDO Spectrum, best fit AR(1) (heavy) and 95% confidence interval (dashed) significant departures from noise spectrum occur on ~7 year/cycle period decadal frequencies cannot be identified here

8 Red Noise and Regime Shifts Figure 3 actual PDO time series and seven year boxcar average (line) and four random number generated time series with same AR(1) characteristics which is the real PDO? show artificial regime changes without deterministic physical meaning so what about actual 1976/77 shift?

9 Time Series Spectra Figure 4 multi-taper time spectral time series of same five time series Actual PDO and (a) both have one peak above 95% level (b), (d) and (e) each have more

10 Atmo. Forcing, Ocean Dynamics For ocean-atmosphere mode (spectral peak) to be generated, there must be spatial pattern and underlying ocean mechanism Rossby waves are possible when ocean dynamics are present

11 EOF and Time Diagram t/2 Figure 5 spatial forcing distribution (latent heat flux EOF), direction of information propagation

12 Decadal Frequency Derivation Time for information to travel across path is t t/2 is time to reach zero point of contours Max response occurs when forcing has f with half a cycle taking t/2 time These frequencies result from mechanisms that are usually decadal* * Saravanan & McWilliams (1998)

13 How to Identify Coupled Modes with Background Noise Using noise alone does not predict coupled modes Use hierarchal series of models to compare different model complexity and identify low frequency variability

14 Different Models, Different EOF s Figure 6 pattern arises only from atmospheric variability even w/ ocean thermodynamics, internal atmospheric variability sets spatial pattern variability increases, but spatial pattern stays the same

15 Ocean Dynamics Variability Figure 8 divide SD of full atmo-ocean model SSTA by model with only mixed layer settings KOE variability increases, necessary for coupled model

16 Enhancement of Model Figure 8 Spectral density of SST in KOE, ratio between full physics coupled model and mixed layer model variability enhanced at f of 20 years/cycle that could be coupled atmo-ocean mode

17 Random Mechanisms or Coupled Interactions? Logic test if forcing fields are randomly generated and SST response still has spectral peak, must be stochastic. If not, must be coupled. ANSWER no spectral peak for random forcing, so a coupled mechanism is required

18 Logic Test Results Figure 10 SST spectrum in KOE coupled model stand alone ocean model, nonrandom stand alone ocean model, randomly generated

19 Problems Red-noise response does not give deterministic signal Model does not give complete spatial pattern of actual PDO, only KOE Model may lack undiscovered physics and/or has errors (sea ice, etc.) Global warming effects need to be addressed

20 Conclusions Answering Questions White noise forcing can have red noise (decadal) responses Noised induced regime shifts do not have physical significance Models of increasing complexity showed atmospheric variability & ocean thermo have red noise decadal response Ocean dynamics add preferred spatial distribution and temporal variability on top of white noise atmospheric forcing, some variability (20 years/cycle) comes form coupled ocean-atmo. modes

21 PDO Prediction? Most of variability comes from white noise atmospheric forcing, unpredictable Some variability may come from coupled modes, which as of now are not understood Issue not settled yet

22 Tie In Time Venzke, et al. PDO regime shifts are predictable, especially 1976/77 Karspeck and Cane wind forcing in tropics can model PDO, but winds not explained Schneider and Cornuelle PDO only a statistical superposition of other forcings Federov and Philander ENSO depends on background state