A guest post by Nicholas Lewis
A new paper in Nature by Jochem Marotzke and Piers Forster: ‘Forcing, feedback and internal variability in global temperature trends’[i] investigates the causes of the mismatch between climate models that simulate a strong increase in global temperature since 1998 and observations that show little increase, and the influence of various factors on model-simulated warming over longer historical periods. I was slightly taken aback by the paper, as I would have expected either one of the authors or a peer reviewer to have spotted the major flaws in its methodology. I have a high regard for Piers Forster, who is a very honest and open climate scientist, so I am sorry to see him associated with a paper that I think is very poor, even as co-author (a position that perhaps arose through him supplying model forcing data to Marotzke) and therefore not bearing primary responsibility for the paper’s shortcomings.
In putting together this note, I have had the benefit of input from two statistical experts: Professor Gordon Hughes (Edinburgh University) and Professor Roman Mureika (University of New Brunswick, now retired). Both of them regard the statistical methods in Marotzke’s paper as fatally flawed.
The Marotzke and Forster paper analyses trends in simulated global mean surface temperature (GMST) over all 15- and 62-year periods between 1900 and 2012, and relates them to contemporaneous trends in model effective radiative forcing (ERF) and to measures of model feedback strength (alpha) and model ocean heat uptake efficiency (kappa).
The paper is very largely concerned with the behaviour of climate models, specifically atmosphere-ocean general circulation models used in the CMIP5 simulations. In discussing relevance to the actual climate system, it ‘assumes that the simulated multimodel ensemble spread accurately characterizes internal variability’.
The authors’ principal conclusions are:
The differences between simulated and observed trends are dominated by random internal variability over the shorter timescale and by variations in the radiative forcings used to drive models over the longer timescale. For either trend length, spread in simulated climate feedback leaves no traceable imprint on GMST trends or, consequently, on the difference between simulations and observations. The claim that climate models systematically overestimate the response to radiative forcing from increasing greenhouse gas concentrations therefore seems to be unfounded.
Marotzke claims to have shown that in model simulations the structural (alpha and kappa) elements – which encapsulate model GMST responses to increases in CO2 forcing – contributed nothing even to recently-ending, longer-term GMST trends. It is difficult to see how that can be so if the models work properly. It is certainly possible (in fact likely) that over the period 1900–2012 the combined contribution of alpha and kappa to model GMST trends was largely obscured by countervailing variations in model ERF trends: high sensitivity models tend to have more negative aerosol forcing than lower sensitivity models, enabling both to match 20th century GMST trends. But aerosol levels have changed little over the last 35 years and higher sensitivity models have been warming much faster than observed GMST over that period.
In order to show why the paper’s conclusions are not justified, I need to explain what Marotzke has done.