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Coupled modelling – ocean and sea ice (from a climate perspective)

Coupled modelling – ocean and sea ice (from a climate perspective). Helge Drange helge.drange@gfi.uib.no. 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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Coupled modelling – ocean and sea ice (from a climate perspective)

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  1. Coupled modelling – ocean and sea ice(from a climate perspective) Helge Drangehelge.drange@gfi.uib.no

  2. Potential predictability based on ocean memory (4 coupled climate models) Collins et al., J. Climate, 2006

  3. Potential predictability based on ocean memory (4 coupled climate models) Collins et al., J. Climate, 2006

  4. 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

  5. Observed variability at high northern latitudes

  6. Observed Dec-Jan SAT anomalies Jim Overland, NOAA/Pacific Marine Environmental Laboratory

  7. Observed April SAT anomalies Large variations on seasonal to decadal time scales. (Partly) Predictable? Jim Overland, NOAA/Pacific Marine Environmental Laboratory

  8. 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

  9. Observed temperature (1950-2008) Holliday et al. GRL (2008)

  10. Associated warming off the coast of Greenland (mean temperature, 150-600 m) Holland et al., Nature Geosci. (2008)

  11. 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)

  12. 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

  13. 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

  14. 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)

  15. Normalized NAO index

  16. NAO+ NAO- NAOn Repeating (i) NAO+, (ii) NAO- or (iii) NAOn forcing fields for 40 years Normalized NAO index

  17. Sea surface height, NAO+ minus NAOn(starting from 1961) meter meter Yr 4-14: Intensified gyre

  18. Sea surface height, NAO+ minus NAOn(starting from 1961) meter meter Yr 4-14: Intensified gyre Yr 15-25: Weakened gyre

  19. Mixed layer T and S, NAO+ minus NAOn(starting from 1961) oC oC psu psu

  20. Mixed layer T and S, NAO+ minus NAOn(starting from 1961) oC oC Advection of warm and saline waters psu psu

  21. Sea surface height, NAO- minus NAOn Gradual weakening

  22. 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

  23. 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

  24. Post 1995 forcing Control integration (1995; “real model world”)

  25. 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

  26. Changes since 1995

  27. Met Office Ocean analysis (upper 500 m) Jon Robson, U of Reading anomalies relative to 1941-1996 climatology

  28. Met Office Ocean analysis and prediction Jon Robson, Doug Smith, pers. comm. (2010) Sep 1995

  29. Met Office Ocean analysis and prediction Jon Robson, Doug Smith, pers. comm. (2010) Mar 1991

  30. Sea Ice Predictability in a Rapidly Changing Arctic Environment Thanks to Marika Holland, NCAR

  31. Relationship of winter ice conditions and Sept extent Holland et al., Clim. Dyn (2010, 2008)

  32. Relationship of winter ice conditions and Sept extent • Arctic winter ice thickness more strongly determines Sept extent as ice thins • Other ice variables also show changing relationships with thinning ice cover Holland et al., Clim. Dyn (2010, 2008)

  33. Using CCSM3 to Assess Seasonal-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)

  34. 1 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)

  35. Ensemble 1 Thick ice Potential predictability Ice extent Ensemble 2 Thinner ice Ensemble 3 Thinnest ice Holland et al., Clim. Dyn (2010, 2008)

  36. Ensemble 1 Thick ice Potential predictability Ice extent Ensemble 2 Thinner ice Ensemble 3 Thinnest ice Holland et al., Clim. Dyn (2010, 2008)

  37. Ensemble 1 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)

  38. Ensemble 1 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)

  39. Wrap-Up, Ocean and sea ice • 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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