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

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Presentation on theme: "© Crown copyright Met Office Decadal Climate Prediction Doug Smith, Nick Dunstone, Rosie Eade, Leon Hermanson, Adam Scaife."— Presentation transcript:

1 © Crown copyright Met Office Decadal Climate Prediction Doug Smith, Nick Dunstone, Rosie Eade, Leon Hermanson, Adam Scaife

2 © Crown copyright Met Office Contents Motivation for decadal predictions Practical issues Initial results Future priorities

3 © Crown copyright Met Office 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

4 © Crown copyright Met Office El Niño Southern Oscillation (ENSO) Smith et al, 2011

5 © Crown copyright Met Office Atlantic multi-decadal variability (AMV) Smith et al, 2011

6 © Crown copyright Met Office Impact of Atlantic on Europe? (Sutton and Dong 2012)

7 © Crown copyright Met Office Impact of Atlantic on Europe? (Sutton and Dong 2012)

8 © Crown copyright Met Office Potential climate impacts of North Atlantic sea surface temperatures North Atlantic SST Sahel rainfall India rainfall Hurricanes (Zhang and Delworth, 2006)

9 © Crown copyright Met Office Atlantic ocean circulation (Dunstone and Smith 2010) Idealised experiments suggest that North Atlantic ocean currents are potentially predictable on decadal timescales Full depth observationsObservations in upper 2000m Year

10 © Crown copyright Met Office Contents Motivation for decadal predictions Practical issues Initial results Future priorities

11 © Crown copyright Met Office Sub-surface ocean observations Need historical tests to assess likely skill of forecasts Far fewer sub-surface ocean observations in the past

12 © 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

13 © Crown copyright Met Office Time Temperature 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

14 © Crown copyright Met Office Contents Motivation for decadal predictions Practical issues Initial results Future priorities

15 © 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

16 © Crown copyright Met Office (Pohlmann et al. 2011, in revision) AMOC at 45 o N in assimilation experiments No historical observations – must rely on models Consistent signal: increase from 1960 to 1995, decrease thereafter Agrees with related observations

17 © Crown copyright Met Office (Pohlmann et al. 2011, in revision) AMOC at 45 o N in hindcast experiments Initialised hindcasts Externally-forced hindcasts Some skill in initialised predictions, but not in uninitialised predictions

18 © Crown copyright Met Office 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

19 © Crown copyright Met Office Impacts of 1995 SPG warming (Robson et al. 2012) Temperature Precipitation Initialisation impacts temperature and precipitation following the 1995 SPG warming

20 © Crown copyright Met Office 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

21 © Crown copyright Met Office Remote influences on Atlantic hurricanes (Smith et al. 2010)

22 © Crown copyright Met Office (Eade et al. in press) Skill of temperature extremes Hindcasts start Nov 1 st each year 1960 to 2005, with 9 ensemble members Assess extremes using daily data Moderate extremes (10 th percentile) 4 definitions (e.g. cold days, cold nights, warm days, warm nights)

23 © Crown copyright Met Office (Eade et al. in press) Skill of wet extremes Assessed from daily data Wet: precipitation rate greater than 90 th percentile (of rainy days)

24 © Crown copyright Met Office Contents Motivation for decadal predictions Practical issues Initial results Future priorities

25 © Crown copyright Met Office Multi-model forecasts of 2011 (Smith et al. submitted)

26 © Crown copyright Met Office Impact of initialisation Initialised – uninitialised, stippled where not significant (Smith et al. submitted)

27 © Crown copyright Met Office Solar variability : winter (solar min – solar max) Model Observations Ineson et al., 2011, NGEO Winter sea level pressure, solar min minus solar max

28 © Crown copyright Met Office 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

29 © Crown copyright Met Office Better models: skill for temperature years 2-5 Old modelNew modelDifference

30 © Crown copyright Met Office 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

31 © Crown copyright Met Office Thank you Any questions?


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