New paper finds climate models exaggerate projected warming

A paper published today in Geophysical Research Letters finds climate models "suffer from temperature-dependent biases" which "leads to an overestimation of projections of regional temperatures." According to the authors, "10-20% of projected warming is due to model deficiencies." The paper adds to many other peer-reviewed papers demonstrating that climate models exaggerate global warming, regional warming, extreme weather, cyclones, extreme precipitation, wind storms, droughts, and floods.

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

Temperature dependent climate projection deficiencies in CMIP5 models

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.