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What do large-scale patterns of extratropical atmospheric variability imply about memory and predictability? David W. J. Thompson Department of Atmospheric Science Colorado State University. What are the dominant “modes” of extratropical atmospheric variability? - PowerPoint PPT Presentation
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What do large-scale patterns of extratropical atmospheric variability
imply about memory and predictability?
David W. J. ThompsonDepartment of Atmospheric Science
Colorado State University
What are the dominant “modes” of extratropical atmospheric variability?• The Pacific-North America pattern• The Northern Hemisphere annular mode (aka, the North Atlantic Oscillation or Arctic Oscillation)• The Southern Hemisphere annular mode
Why is it important to predict these modes?
To what extent does the midlatitude ocean impact these modes?
What alternative processes may drive low-frequency variability in these modes?
500-hPa height regressed on an index of the PNA
The Pacific-North America pattern
e.g., Wallace and Gutzler 1981
The Pacific-North America pattern
• Resembles a wave train emanating from the North Pacific.
• Excited by barotropic instability in the vicinity of the Pacific jet.
• Reminiscent of the extratropical atmospheric response to ENSO.
• Time series resembles a red-noise process with an e-folding timescale of ~10 days.
The Northern Hemisphere annular mode (NAM)
Sea-level pressure regressed on an index of the NAM
e.g., Thompson and Wallace 2000
The Southern Hemisphere annular mode (SAM)
850-hPa height regressed on an index of the SAM
e.g., Kidson, Karoly, Trenberth, etc.
The annular modes
• Characterized by zonally symmetric fluctuations in the extratropical atmospheric circulation that extend from the surface to the stratosphere.
• Driven by interactions between transient eddies and the mean flow of the extratropical atmosphere.
• The NAM and the NAO are different interpretations of the same mode of variability.
• The time series of the NAM (and SAM) resembles a red-noise process with an e-folding timescale of ~10 days. But the NAM (and SAM) also exhibits increased power at lower frequencies…
Why do we care about the annular modes?
• Extensive climate impacts.
• Time series exhibit low-frequency variability that appears to exceed the timescale of tropospheric variability.
Climate impacts of the NAM
Surface temperature regressed on the NAM index
Provided courtesy of Todd Mitchell, UW
Climate impacts of the SAM
700-hPa winds and surface temperature regressed on the SAM index (longest vector is ~4 m/s).
Thompson and Solomon 2002
Recent climate trends and the annular modes
e.g., Hurrell 1995; Thompson et al. 2000; Thompson and Solomon 2002
Recent trends in SH 500-hPa Z (left; Dec-May 1979-1998) and NH SLP (right; Jan-March 1968-1997).
What are the dominant “modes” of extratropical atmospheric variability?• The Pacific-North America pattern• The Northern Hemisphere annular mode (aka, the North Atlantic Oscillation or Arctic Oscillation)• The Southern Hemisphere annular mode
Why is it important to predict these modes?
To what extent does the midlatitude ocean impact these modes?
What alternative processes may drive low-frequency variability in these modes?
To what extent does the midlatitude ocean impact these modes?
1) To what extent can the persistence of the midlatitude oceans be explained via stochastic atmospheric processes?
2) To what extent does the midlatitude ocean impact the midlatitude atmosphere?
From Frankignoul and Hasselmann (1977; FH)
Hc
TF
dt
Td
pρλ ′−′
=′
F′T ′
λρcp
H
SST anomaly
White noise atmospheric forcing
Fixed thermal damping parameter
Density of seawater
Heat capacity of seawater
Fixed ocean mixed layer depth
The null hypothesis for SST persistence
where
FH model yields an e-folding timescale for SSTs of ~3-5 months
The null hypothesis of SST persistence, modified to include reemergence
(from Deser et al., in press J. Climate)
The FH model, when extended to account for re-emergence, yields SST persistence on the order of years.
Sample results from the extended FH model(from Deser et al., in press J. Climate)
Observed SSTA
Observed heat content anomaly
SSTA, original FH model
Heat content anomaly, modified FH model
Heat content anomaly, modified FH model with λ =0 in summer
Discrepancies occur where the mixed layer depth is shallow, near coastlines.
Observed vs. modeled autocorrelation
(from Deser et al., in press J. Climate)
Shading denotes r>0.3.
Observed
Theory
To what extent does the midlatitude ocean impact these modes?
1) To what extent can the persistence of the midlatitude oceans be explained via stochastic atmospheric processes?
2) To what extent does the midlatitude ocean impact the midlatitude atmosphere?
“We can now say with confidence that the extratropical ocean does indeed influence the atmosphere outside the boundary layer, but that this influence is of modest amplitude compared to internal atmospheric variability”Kushnir et al. 2002
The basic effects of atmosphere/ocean thermal coupling on midlatitude variability
(Barsugli and Battisti 1998)
• The original formulation by FH was extended by Barsugli and Battisti to include thermal feedbacks between the ocean and the atmosphere
- Ta, To are the surface temperatures of the atmosphere and ocean.
- a-d are dimensionless parameters that incorporate surface fluxes, radiative damping (b also includes any ocean dynamical feedback).- corresponds to the ratio of the heat capacity of the ocean mixed layer and the troposphere (~40). - N is atmospheric white noise forcing.
The basic effects of atmosphere/ocean thermal coupling on midlatitude variability
(Barsugli and Battisti 1998)
• Thermal coupling between the atmosphere and ocean increases the variance at low frequencies, and the persistence in both media.
• Simulations run with specified SST anomalies (i.e., without damped thermal coupling) yield spuriously large surface fluxes between the ocean and atmosphere.
Interpretation of AMIP-style simulations
Bretherton and Battisti (2000):
• The correlation between the simulated and observed NAO reflects the ensemble averaging, which acts to filter the noise in each ensemble member.
• As per the null hypothesis outlined in Barsugli and Battisti (1998), at low frequencies the correlation between the simulated and observed NAO approaches r=1.0 as the ensemble size approaches infinity.
• The results do not PROVE any predictability of the NAO beyond the persistence of the SST anomalies.
• Caveat: Barsugli and Battisti do NOT include advection by the gyre and/or thermohaline circulations (Czaja and Marshall 2000; Marshall et al. 2001).
What are the dominant “modes” of extratropical atmospheric variability?• The Pacific-North America pattern• The Northern Hemisphere annular mode (aka, the North Atlantic Oscillation or Arctic Oscillation)• The Southern Hemisphere annular mode
Why is it important to predict these modes?
To what extent does the midlatitude ocean impact these modes?
What alternative processes may drive low-frequency variability in these modes?
Concluding remarks
There is no conclusive evidence that variability in the midlatitude ocean has a significant impact on the
dominant modes of extratropical atmospheric variability.
Concluding remarks
The most compelling observational evidence of predictability on timescales longer than the limits of
deterministic weather prediction derives from stratosphere/troposphere coupling, not via coupling with
the midlatitude ocean.
Concluding remarks
1) A large fraction of the persistence of midlatitude SSTs is predicted by a simple model driven by stochastic atmospheric forcing.
caveat:Ocean dynamics likely plays an important role (e.g., the “inter-gyre gyre”), particularly in the vicinity of the western boundary currents.
2) There is increasing consensus that the atmospheric response to midlatitude SSTs is modest.
caveat:The annular modes have a pronounced impact on the climate of their respective hemispheres. A “modest” increase in the predictability of the NAM or SAM would likely be very useful.