1. Predictability of the NAO? Adam Scaife
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2. Winters depend on which way the wind blows:
The North Atlantic Oscillation
Winter 1962/63
Weak P Gradient
Cold advection
into Europe
Cold, calm
and dry
Winter 2009/10
Winter 2011/12 c.f. 2013/14!
Strong P Gradient
Warm advection
into Europe
Mild, stormy
and wet
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3. GloSea5 Global Seasonal Forecast System 5
Model: HadGEM3H N216L85O(0.25)
Initialisation: NWP state + NEMOVAR + Sea Ice
Winter Hindcasts: 24 members starting around 1 November 20 years: 1992/3 – 2012/13
Now Operational: 2 members per day -> 2 months members per day -> 7months
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4. Operational forecasts: January 2013
Observations
Signals appearing in forecasts from 21st Dec
Warning provided to Dept for Transport 4th Jan
Prolonged snow from ~Jan 20th onwards
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5. Individual winters Individual winters from 1992/3 to 2011/12
Pattern of ensemble mean similar in many cases but not all
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6. Winter NAO hindcasts Correlation score = 0.62
Extended to 20 years and 24 members for DJF
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7. Seasonal Skill for surface climate
Forecast skill
from NAO alone
Storms
Temp
Wind
Skilful predictions of extreme events months ahead
Skill in E Atlantic and Europe is from the NAO
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Scaife et al 2014

8. Sources of predictability…
Strongest minus weakest cases for November predictors:
ENSO, Atlantic Ocean, Kara sea-ice and Quasi Biennial Oscillation
Response is weaker in model than obs
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9. Large ensembles are needed
24 member ensemble shows strong sensitivity to ensemble size
Nothing special about 0.62 and higher values are possible!
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10. Daily extremes and impacts
Prediction of the NAO
Prediction of winter extremes
Prediction of Impacts
Cold days (energy, transport..)
Storms (insurance…)
Windspeed (renewables…)
Hydrology (river flows…)
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Svensson et al, 2014

11. Summary: Skilful seasonal forecasts for the NAO, Europe & N America
Low signal to noise – this is a paradox and a key research topic
Risk of daily extremes governed by large scale flow
Predictability of useful quantities like storminess or windspeed
Further Development:
Much work to do with partners on predicting impacts…
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