© Crown copyright Met Office Decadal Climate Prediction Doug Smith, Nick Dunstone, Rosie Eade, Leon...

© Crown copyright Met Office

Decadal Climate PredictionDoug Smith, Nick Dunstone, Rosie Eade, Leon Hermanson, Adam Scaife


Contents

• Motivation for decadal predictions

• Practical issues

• Initial results

• Future priorities


Decadal prediction

“Global warming” trend

Natural internal variability, or errors in simulation of external forcing

• Need to take into account all sources of predictability• External forcing: greenhouse gases, aerosols, volcanoes, solar• Natural internal variability – need to start predictions from the

current state of the climate system

UK 9-year mean temperature


El Niño Southern Oscillation (ENSO)

Smith et al, 2011


Atlantic multi-decadal variability (AMV)

Smith et al, 2011


Impact of Atlantic on Europe?

(Sutton and Dong 2012)


Impact of Atlantic on Europe?

(Sutton and Dong 2012)


Potential climate impacts of North Atlantic sea surface temperatures

North Atlantic SST

Sahel rainfall

India rainfall

Hurricanes

(Zhang and Delworth, 2006)


Atlantic ocean circulation

(Dunstone and Smith 2010)

• Idealised experiments suggest that North Atlantic ocean currents are potentially predictable on decadal timescales

Full depth observations Observations in upper 2000m

10 20 30 40 50

Year

10 20 30 40 50


Contents



• Initial results



Sub-surface ocean observations

19801960 2007

• Need historical tests to assess likely skill of forecasts

• Far fewer sub-surface ocean observations in the past

© Crown copyright Met Office(Hawkins and Sutton, 2011)

Uncertainties

• Large uncertainties in model response to external forcing• Need multi-model ensembles• and to understand physical mechanisms

Projections of Dec-Feb decadal rainfall


Time

Tem

peratu

re

Ensembles of forecasts:• Uncertainties in the initial conditions• Model errors

Forecasts

Actual

An optimistic view:

Uncertainties

Not accounted for:• Uncertainties in greenhouse gas and aerosol emissions• Volcanoes, changes in solar output


Contents



• Initial results


© Crown copyright Met Office(Smith et al. 2010)

Surface temperature predictions(five year means)

Initialised - UninitialisedSkill of initialised predictions

• Skilful almost everywhere (positive correlations)

• Mostly due to external forcing

• Initialisation gives improved skill mainly in North Atlantic and tropical Pacific

© Crown copyright Met Office (Pohlmann et al. 2011, in revision)

AMOC at 45oN in assimilation experiments

• No historical observations – must rely on models

• Consistent signal: increase from 1960 to 1995, decrease thereafter

• Agrees with related observations

© Crown copyright Met Office(Pohlmann et al. 2011, in revision)

AMOC at 45oN in hindcast experiments

Initialised hindcasts Externally-forced hindcasts

• Some skill in initialised predictions, but not in uninitialised predictions


North Atlantic sub-polar gyre (SPG)

(Robson et al. 2012, also Yeager et al. 2012)

SPG 500m temp

Meridional heat transport

Overturning circulation

Observations

Initialised (DePreSys)

Uninitialised (NoAssim)

• Improved skill for 1995 rapid warming results from initialisation of increased Atlantic overturning circulation and meridional heat transport


Impacts of 1995 SPG warming

(Robson et al. 2012)

Tem

pera

ture

Pre

cipi

tatio

n

• Initialisation impacts temperature and precipitation following the 1995 SPG warming


Tropical storm predictions beyond the seasonal range

(Smith et al. 2010)

Skill from external forcing and initialisation

5 year means

Initialised

Uninitialised

Observations

Initialised

Uninitialised

Persistence


Remote influences on Atlantic hurricanes

(Smith et al. 2010)

© Crown copyright Met Office(Eade et al. in press)

Skill of temperature extremes

• Hindcasts start Nov 1st each year 1960 to 2005, with 9 ensemble members

• Assess extremes using daily data

• Moderate extremes (10th percentile)

• 4 definitions (e.g. cold days, cold nights, warm days, warm nights)

© Crown copyright Met Office(Eade et al. in press)

Skill of wet extremes

• Assessed from daily data

• Wet: precipitation rate greater than 90th percentile (of rainy days)


Contents



• Initial results



Multi-model forecasts of 2011

(Smith et al. submitted)


Impact of initialisation 2012-16

Initialised – uninitialised, stippled where not significant

(Smith et al. submitted)


Solar variability : winter(solar min – solar max)

Model Observations

Ineson et al., 2011, NGEO

Winter sea level pressure, solar min minus solar max


Arctic Sea Ice

Arctic Sea Ice is systematically melting

Last few years have seen record melt

Observed climate records and climate models indicate cold easterly winter winds in response to ice melt

Recent Winter Pressure

Reproduced by Climate Model


Better models:skill for temperature years 2-5

Old modelNew model Difference


Summary

• Already have skill from climate change signal

Skilful predictions of extreme temperatures

• Initialisation improves N. Atlantic and tropical Pacific

Improved predictions of AMOC and SPG

• Skilful predictions of tropical Atlantic storms

• Emerging importance of external factors: aerosols, volcanoes, solar, greenhouse gases via sea ice?

• Need improved models to predict atmospheric response over land better

• Need to understand physical mechanisms to gain confidence in forecasts


Thank youAny questions?

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