All Scientists are Sceptics ~Professor Bob Carter

Whenever someone asserts that a scientific question is “settled,” they tell me immediately that they don’t understand the first thing about science. Science is never settled. Dr David Deming

Perhaps the most frustrating aspect of the science of climate change is the lack of any real substance in attempts to justify the hypothesis ~Professor Stewart Franks

A lie told often enough becomes the truth.
-- Vladimir Ilyich Lenin - See more at: http://thepeoplescube.com/lenin/lenin-s-own-20-monster-quotes-t185.html#sthash.aTrSI3tG.dpuf
A lie told often enough becomes the truth.
-- Vladimir Ilyich Lenin - See more at: http://thepeoplescube.com/lenin/lenin-s-own-20-monster-quotes-t185.html#sthash.aTrSI3tG.dpuf
A lie told often enough becomes the truth.
-- Vladimir Ilyich Lenin - See more at: http://thepeoplescube.com/lenin/lenin-s-own-20-monster-quotes-t185.html#sthash.aTrSI3tG.dpuf

Sunday, 30 December 2012

Peer Reviewed Paper finds climate models exaggerate projected warming

Geophysical Research Letters
GEOPHYSICAL RESEARCH LETTERS, VOL. 39, L24705, 5 PP., 2012
doi:10.1029/2012GL053650 

Temperature dependent climate projection deficiencies in CMIP5 models (link)

Key Points
  • GCMs suffer from temperature-dependent biases
  • This leads to an overestimation of projections of regional temperatures
  • We estimate that 10-20% of projected warming is due to model deficiencies
Jens H. Christensen
Danish Climate Centre, Danish Meteorological Institute, Copenhagen, Denmark
Fredrik Boberg
Danish Climate Centre, Danish Meteorological Institute, Copenhagen, Denmark

Monthly mean temperatures for 34 GCMs available from the CMIP5 project are compared with observations from CRU for 26 different land regions covering all major land areas in the world for the period 1961–2000 by means of quantile-quantile (q-q) diagrams. A warm period positive temperature dependent bias is identified for many of the models within many of the chosen climate regions. However, the exact temperature dependence varies considerably between the models. We analyse the role of this difference as a contributing factor for some models to project stronger regional warming than others by looking at the entire ensemble rather than individual models. RCP4.5 temperature projections from all GCMs for two time periods (2021–2050 and 2071–2100) are compared against a linear fit to the 50% warmest months from the respective q-q plot for each model and region. Taken together, we find that in general models with a positive temperature dependent bias tend to have a large projected temperature change, and these tendencies increase with increasing global warming level. We argue that this appears to be linked with the ability of models to capture complex feedbacks accurately. In particular land-surface atmosphere interactions are treated differently and with different degree of realism between models.  

H/t Hockey Shtick  and Climate Depot

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