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The forcing of sea ice characteristics by the NAO in HadGEM1
UK Sea Ice Workshop, 9 September 2005
Chris Durman1,2 and Jonathan Bamber2
1. Hadley Centre for Climate Prediction and Research, Met Office
2. Bristol Glaciology Centre, School of Geographical Sciences,University of Bristol
With thanks to: Tim Johns, Ann Keen, Alison McLaren and Jeff Ridley.
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Talk Outline
1. Introduction
2. Simulated NAO and climate response in comparison with observations
3. Mechanisms of ice response:• Beaufort Sea / East Arctic Basin• Labrador Sea
4. Conclusions
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The NAO and Arctic Sea Ice
• NAO dominant mode of atmospheric variability in the North Atlantic region (Hurrell, 1995).
• “See-saw” of intensification and weakening in PMSL between Azores High and Icelandic Low centres of action.
• NAO “high +ve state” when pressure gradient is at a maximum.
• Over the Arctic, modified circulation patterns result in perturbed geostrophic wind forcing → drives surface temperature changes.
• Correlation between geostrophic winds and ice motion can be as high as 0.8 in the central Arctic (e.g. Thomas, 1999).
• Perturbed surface temperatures influence the rate at which ice grows / melts thermodynamically.
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Experimental setup and data
HadGEM1 IPCC AR4 Control run:
• Fixed 1860 forcing levels for greenhouse gases, ozone, sulphur, other precursor emissions and land surface conditions.
• Spinup integration of 85 years in length was carried out from which the controlrun was initialised.
• Spinup ocean state initialised from September climatology of Levitus.
• Spinup Northern Hemisphere sea ice volume initialised from HadISST.
Data:
• First 300 years of control run analysed here.
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DJF PMSL
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DJF PMSL
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Leading order EOFs of DJF PMSL
Variance: 44.8% Variance: 41.1%
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HadGEM1 NAO Index
Index: Difference in PMSLbetween Azores and Iceland.
Normalisation: subtract meanand divide by standard deviation.
Define “High NAO Years” asthose where normalisedIndex exceeds unity.
300 year control run yields48 High NAO Years.
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HadGEM1 DJF PMSL
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DJF Surface Temperature Anomaly
DJF Ice Concentration Anomaly
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HadGEM1 DJF Ice Property Anomalies
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HadGEM1 DJF ice velocity
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HadGEM1 DJF Wind Velocity
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JJA Ice Response
Concentration Thickness
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Ice volume flux (m3 per season) through longitude180oW averaged between 70oN and 80oN
0
1E+11
2E+11
3E+11
4E+11
5E+11
6E+11
7E+11
8E+11
9E+11
DJF* MAM JJA SON
Climatology
NAO+
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DJF Labrador Sea Ice Anomalies
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DJF Labrador Sea Anomalies
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Implied DJF ice thickness response in the Labrador Sea
Average increase in rate of change of ice thickness due to thermodynamic processes = +2.07x10-8 ms-1.
=> anomalous thickness of 0.16m compared with model climatology.
But average thickness anomaly = 0.086m.
Thermodynamics not the whole story?
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DJF ice thermodynamics and velocity
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HadGEM1 DJF PMSL
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Conclusions
• HadGEM1 realistically simulates the NAO dipole pressure pattern.
• Simulated HadGEM1 surface temperature and Arctic sea ice concentrationanomaly patterns associated with the NAO are consistent with observations.
• The response of Arctic basin sea ice to high NAO events is a dipole with increased ice in the western Arctic and reduced ice in the east. This pattern is formed as a result of reduced ice transport due to perturbed wind forcing.
• Ice thickness anomalies in the Labrador Sea are largely initiated by thermodynamic processes but dynamic processes act to limit the anomalies.
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Extra slides
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Fram Strait ice export response
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Fram Strait export response?
(Zhang et al., 2000, J. Climate)
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HadGEM1 normalised NAO index vs average Fram Strait ice export
Corr = 0.03
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HadGEM1 DJF Wind Velocity
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Running 7-year means of simulated normalised NAO index
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(Ringer et al., 2005, J. Climate)
