Another Paper That Short Curcuits The Scientific Method: Ganguly Et Al 2009 in the Proceedings Of The National Academy of Sciences

In post on June 4 2009 on my weblog titled

Short Circuiting The Scientific Process – A Serious Problem In The Climate Science Community

I wrote

There has been a development over the last 10-15 years or so in the scientific peer reviewed literature that is short circuiting the scientific method

What the current publication process has evolved into, at the detriment of proper scientific investigation, are the publication of untested (and often untestable) hypotheses.  The fourth step in the scientific method “Test Your Hypothesis by Doing an Experiment” is bypassed.

This is a main reason that the policy community is being significantly misinformed about the actual status of our understanding of the climate system and the role of humans within it.

There is new paper (made available today) which is

Auroop R. Ganguly, Karsten Steinhaeuser, David J. Erickson, III, Marcia Branstetter, Esther S. Parish, Nagendra Singh, John B. Drake, and Lawrence Bujad, 2009: Higher trends but larger uncertainty and geographic variability in 21st century temperature and heat waves. Proceedings of the National Academy of Sciences. http://www.pnas.org cgidoi 10.1073 pnas.0904495106

that fits into this type of article.

The abstract  of this paper reads

“Generating credible climate change and extremes projections remains a high-priority challenge, especially since recent observed emissions are above the worst-case scenario. Bias and uncertainty analyses of ensemble simulations from a global earth systems model show increased warming and more intense heat waves combined with greater uncertainty and large regional variability in the 21st century. Global warming trends are statistically validated across ensembles and investigated at regional scales. Observed heat wave intensities in the current decade are larger than worst-case projections. Model projections are relatively insensitive to initial conditions, while uncertainty bounds obtained by comparison with recent observations are wider than ensemble ranges. Increased trends in temperature and heat waves, concurrent with larger uncertainty and variability, suggest greater urgency and complexity of adaptation or mitigation decisions.”

The text includes the statements

“Statistically Higher Warming Trends. First, we show that the global average temperatures from the middle to end of the 21st century
are likely to be higher than previously believed …. “

“Here we compare A1FI-driven CCSM 3.0 … model projections and NCEP Reanalysis … observations for 2000–2007, when both are available, and develop grid-based estimates for model bias and standard deviation. We use the results to generate bias-corrected ‘‘most likely’’ projections and corresponding confidence bounds based on three standard deviations at each grid cell. Grid-based decadal averages are calculated for three time periods:The current ‘‘2000’’ decade, the mid-century ‘‘2050’’ decade, and the end-century ‘‘2100.’’

The biases between the model and the reanalysis are shown in Figure 2 and are over 5 degrees Celsius in large areas! This is the test being applied in this modeling study which  writes, for example,  

“The globally averaged intensity of heat waves at decadal scales shows that the observed intensities are higher than the worst-case model projections in the current decade, which implies further exacerbation of heat waves compared to what has been already suggested by previous researchers.” [Note: The use of the term “observed” in this sentence is clearly an error as these later decades have not even occured yet!].

While such studies provide useful excercises on the sensitivity of the model results to different climate forcings, their use to provide definitive forecasts (even as an ensemble of best and worst case scenarios) is misleading policymakers and others on the actual lack of skill in such multi-decadal global climate predictions.

The Gangulya et al 2009 paper, no matter how well intentioned, is yet another case of short curcuiting the science.