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Coupled modelling – ocean and sea ice (from a climate perspective). Helge Drange [email protected] Potential predictability based on ocean memory (4 coupled climate models). Collins et al., J. Climate , 2006. Potential predictability based on ocean memory (4 coupled climate models).

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Potential predictability based on ocean memory

(4 coupled climate models)

Collins et al., J. Climate, 2006


Potential predictability based on ocean memory

(4 coupled climate models)

Collins et al., J. Climate, 2006


Simulated SAT anomaly related to strength of AMOC

(C per Sverdrup)

x

Potential predictability in the N-Atl/Arctic, weak signals over land

Collins et al., J. Climate, 2006


Observed variability at

high northern latitudes


Observed

Dec-Jan SAT anomalies

Jim Overland, NOAA/Pacific Marine Environmental Laboratory


Observed

April SAT anomalies

Large variations on seasonal to decadal time scales.

(Partly) Predictable?

Jim Overland, NOAA/Pacific Marine Environmental Laboratory


1995/96 shift in the North Atlantic climate

First pointed out by Rhines and Häkkinen (Science, 2004), based on ~20 cm drop in SSH in the central parts of the North Atlantic sub-polar gyre

Jon Robson,

U. of Reading

Anomalies relative to 1941-1996 climatology


Observed temperature (1950-2008)

Holliday et al. GRL (2008)


Associated warming off the coast of Greenland

(mean temperature, 150-600 m)

Holland et al., Nature Geosci. (2008)


Simulated dynamics of the

North Atlantic Sub-Polar Gyre

Ocean-sea ice model forced with atm reanalysis fields

Possible mechanism for the 1995/96 shift

Is the 1995/96 shift predictable?

Hatún et al., Science (2005),

Lohmann et al., Clim. Dynamics (2009), GRL (2009), Ocean Dynamics (2010)


Hatun et al., Science (2005); Prog. Ocenogr. (2009)

Irminger (I) Faroe (F) Rockall (R)

Observedand simulated salinity anomalies at three locations in the northern North Atlantic


Hatun et al., Science (2005); Prog. Ocenogr. (2009)

Irminger (I) Faroe (F) Rockall (R)

Observedand simulated salinity anomalies at three locations in the northern North Atlantic


Hatun et al., Science (2005); Prog. Ocenogr. (2009)

Irminger (I) Faroe (F) Rockall (R)

Observedand simulated salinity anomalies at three locations in the northern North Atlantic

Why post-95 change?

(T, S, marine biota)



NAO+

NAO-

NAOn

Repeating

(i) NAO+, (ii) NAO- or (iii) NAOn forcing fields for 40 years

Normalized NAO index


Sea surface height, NAO+ minus NAOn(starting from 1961)

meter

meter

Yr 4-14: Intensified gyre


Sea surface height, NAO+ minus NAOn(starting from 1961)

meter

meter

Yr 4-14: Intensified gyre

Yr 15-25: Weakened gyre


Mixed layer T and S, NAO+ minus NAOn(starting from 1961)

oC

oC

psu

psu


Mixed layer T and S, NAO+ minus NAOn(starting from 1961)

oC

oC

Advection of warm and saline waters

psu

psu


Sea surface height, NAO- minus NAOn

Gradual weakening


Conclusions (1)

  • NAO+ forcing 

  • - Initial strengthening of SPG

  • - After 5-10 years replaced by weakening of SPG, despite continued NAO+ forcing

  • - Mechanism: Advection of warm water counteracts local cooling

  • NAO- forcing 

  • - Gradual weakening of SPG, approaching a minimum value

  • Asymmetry 

  • - Non-linear response for NAO+ forcing;

  • linear response for NAO- forcing


Sensitivity experiments

  • Same model as before (Bergen isopycnic OGCM)

  • Post 1995 forcing applied to initial conditions from 1975, 1980, 1985, 1990, 2000, 2005, and every year between 1991 and 1997


Post 1995 forcing

Control integration (1995; “real model world”)


Conclusions (2)

  • SPG drop in 1995 

  • SPG at maximum strength and approaching break-down after a long period with NAO+ forcing

  • NAO forcing changed from high to low value the winter 1995/96

  • The combined effect lead to an unprecedented collapse of SPG

  • Note

  • SPG would also have collapsed in 1994 with post-1995 forcing

  • Otherwise no collapse for the period 1960-2005 with post-95 forcing

  • Predictability

  • Ocean initial state of crucial importance


Changes

since 1995


Met office ocean analysis upper 500 m
Met Office Ocean analysis (upper 500 m)

Jon Robson,

U of Reading

anomalies relative to 1941-1996 climatology


Met office ocean analysis and prediction
Met Office Ocean analysis and prediction

Jon Robson, Doug Smith, pers. comm. (2010)

Sep 1995


Met office ocean analysis and prediction1
Met Office Ocean analysis and prediction

Jon Robson, Doug Smith, pers. comm. (2010)

Mar 1991


Sea Ice Predictability in a Rapidly Changing Arctic Environment

Thanks to Marika Holland, NCAR


Relationship of winter ice conditions and Sept extent Environment

Holland et al., Clim. Dyn (2010, 2008)


Holland et al., Clim. Dyn (2010, 2008)


Using ccsm3 to assess seasonal interannual predictability
Using CCSM3 to Assess EnvironmentSeasonal-Interannual Predictability

Model experiments:

  • 20+ member ensembles of CCSM3 with same initial ice-ocean-land state

  • Run for 2 years

  • Perform 3 sets with initial conditions obtained from 20th-21st century runs

Holland et al., Clim. Dyn (2010, 2008)


1 Environment

September sea ice extent

1

2

m

2

4

3

3

2

1

  • Initialize runs with identical ice-ocean-land conditions from CCSM3

  • Use 3 sets of Jan 1 initial conditions

  • Each ensemble set has ~20 members

  • Run forward 2-years

0

3

Holland et al., Clim. Dyn (2010, 2008)


Ensemble 1 Environment

Thick ice

Potential predictability

Ice extent

Ensemble 2

Thinner ice

Ensemble 3

Thinnest ice

Holland et al., Clim. Dyn (2010, 2008)


Ensemble 1 Environment

Thick ice

Potential predictability

Ice extent

Ensemble 2

Thinner ice

Ensemble 3

Thinnest ice

Holland et al., Clim. Dyn (2010, 2008)


Ensemble 1 Environment

Thick ice

Potential predictability

Ice extent

  • Higher predictability for thick ice regime (ensemble 1)

  • Sept ice cover predictable during first year (2 yrs for thick regime; ensemble 1)

Ensemble 2

Thinner ice

Ensemble 3

Thinnest ice

Holland et al., Clim. Dyn (2010, 2008)


Ensemble 1 Environment

Thick ice

Potential predictability

Ice thickness

  • Ice thickness has much higher potential predictability than extent

  • Variance across the ensemble set remains small compared to control runs

  • Predictability for >2 years (except in thicker ice regime)

Ensemble 2

Thinner ice

Ensemble 3

Thinnest ice

Holland et al., Clim. Dyn (2010, 2008)


Wrap up ocean and sea ice
Wrap-Up, Ocean and sea ice Environment

  • Rapid fluctuations in high-latitude weather/climate (even on multi-decadal time scales)

  • Ocean heat anomalies provide an opportunity for predictability

  • The 1995/96-shift provides a unique test-bed for process understanding, predictability experiments and potential impacts

  • Winter sea ice extent provides – at most – 1 yr memory

  • Sea ice thickness more “robust” ice feature than extent

  • Likely that sea ice memory decreases as sea ice thickness decreases


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