from The Global Warming Statistical Meltdown by Judith Curry in The Wall Street Journal

Excerpts:

Human-caused warming depends not only on increases in greenhouse gases but also on how “sensitive” the climate is to these increases. Climate sensitivity is defined as the global surface warming that occurs when the concentration of carbon dioxide in the atmosphere doubles. If climate sensitivity is high, then we can expect substantial warming in the coming century as emissions continue to increase. If climate sensitivity is low, then future warming will be substantially lower, and it may be several generations before we reach what the U.N. considers a dangerous level, even with high emissions.

We also estimated what the long-term warming from a doubling of carbon-dioxide concentrations would be, once the deep ocean had warmed up. Our estimates of sensitivity, both over a 70-year time-frame and long term, are far lower than the average values of sensitivity determined from global climate models that are used for warming projections. Also our ranges are narrower, with far lower upper limits than reported by the IPCC’s latest report. Even our upper limits lie below the average values of climate models.

Our paper is not an outlier. More than a dozen other observation-based studies have found climate sensitivity values lower than those determined using global climate models, including recent papers published in Environmentrics (2012),Nature Geoscience(2013) and Earth Systems Dynamics (2014). These new climate sensitivity estimates add to the growing evidence that climate models are running “too hot.” Moreover, the estimates in these empirical studies are being borne out by the much-discussed “pause” or “hiatus” in global warming—the period since 1998 during which global average surface temperatures have not significantly increased.

The sensitivity of the climate to increasing concentrations of carbon dioxide is a central question in the debate on the appropriate policy response to increasing carbon dioxide in the atmosphere. Climate sensitivity and estimates of its uncertainty are key inputs into the economic models that drive cost-benefit analyses and estimates of the social cost of carbon.

Continuing to rely on climate-model warming projections based on high, model-derived values of climate sensitivity skews the cost-benefit analyses and estimates of the social cost of carbon. This can bias policy decisions. The implications of the lower values of climate sensitivity in our paper, as well as similar other recent studies, is that human-caused warming near the end of the 21st century should be less than the 2-degrees-Celsius “danger” level for all but the IPCC’s most extreme emission scenario.

This slower rate of warming—relative to climate model projections—means there is less urgency to phase out greenhouse gas emissions now, and more time to find ways to decarbonize the economy affordably. It also allows us the flexibility to revise our policies as further information becomes available.

HKO

Reliance on models has created a delusional sense of urgency. When so much effort has been devoted to models for so long it is human nature for the designers of the models to develop defensiveness to facts that contradict them.

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