Transcript The Decadal Climate Prediction Project (DCPP)

Decadal Climate Prediction
Project (DCPP)
Co chairs:
George Boer, Environment Canada, [email protected]
Doug Smith, Met Office, [email protected]
http://wcrp-climate.org/dcpp-project/dcpp-introduction
The DCPP consists of three components:
• Component A: Hindcasts. The design and organization of a coordinated decadal prediction (hindcast) component of
CMIP6 in conjunction with the seasonal prediction and climate modelling communities
• Component B: Forecasts. The ongoing production of experimental quasi-operational decadal climate predictions in support
of multi-model annual to decadal forecasting and the application of the forecasts
• Component C: Predictability, mechanisms and case studies. The organization and coordination of decadal climate
predictability studies and of case studies of particular climate shifts and variations including the study of the mechanisms that
determine these behaviours
Component A: Hindcasts
WGSIP
WGCM
Component C: Hiatus+ : Accelerated and retarded rates of global temperature
change and associated regional climate variations
• Assess likely forecast skill
• Remove bias from forecasts
• Investigate the origin, mechanisms and predictability of long timescale variations in global mean temperature and
regional variables including periods of both enhanced warming and cooling with a focus on the current “hiatus”
• Link to GMMIP
Smith et al, 2010, Nat. Geosci.
Kosaka and Xie, 2013, Nature
Doblas-Reyes et al, 2013, Nature Comms
Pohlmann et al, 2013, Clim. Dyn.
Hurricane shift 1995
England et al, 2014, Nature Climate Change
• High skill for temperature, including extremes, from
warming trend
• Improvement from initialisation mainly in the North
Atlantic
• Comes from improved prediction of ocean dynamics
• Some skill for associated climate impacts
 Atlantic hurricane frequency
 Rainfall over US, Sahel, Europe associated with
rapid Atlantic warming in mid 1990s
• Model signal-to-noise ratio too small – need large
ensembles
• Need improved models to reproduce climate impacts
over land
Smith et al, 2014, J. Clim.
Eade et al, 2015, GRL
Rainfall changes after 1995 Atlantic warming
McGregor et al, 2014, Nature Climate Change
• Warming slowdown driven by tropical east
Pacific SSTs
• Negative PDO driven by increase in Pacific
trade winds drives
• Possible role of North Atlantic?
Robson et al, 2013, J. Clim.
Component B: Forecasts
Component C: Volcanoes
• Informal exchange of decadal predictions since 2011
• http://www.metoffice.gov.uk/research/climate/seasonal-to-decadal/long-range/decadal-multimodel
• Aim to formalise following WMO seasonal forecasting framework
•Link to VolMIP
Smeed et al, 2014, Ocean Science
Hermanson et al, 2014, GRL
• Atlantic overturning circulation weakening
• Atlantic predicted to cool
• Likely climate impacts:
 cold winters and wet summers in Europe less likely
 fewer hurricanes than recent peaks
 reduced Sahel rainfall
 reduced risk of drought in SW USA
• More work needed to understand mechanisms
→ Component C
• What is the effect of volcanoes on multi-model forecast skill?
• What is the potential effect of a volcano on future forecasts?
• What are the mechanisms through which volcanoes influence climate?
Met Office FitzRoy Road, Exeter, Devon, EX1 3PB United Kingdom
© Crown copyright 09/2015 | Met Office and the Met Office logo are registered trademarks