Advice to Climatistas: Stop Sniffing Model Glue

Science Daily summarizes a new study in Geophysical Research Letters, one of the leading climate science journals, about how climate models are struggling (to put it mildly) to explain decade-by-decade climate variability.  On the one hand, the study seems to attempt to downplay the significance of the recent temperature “pause,” but at the price of inadvertently undermining the climate models themselves.  At least that’s how I read this summary:

A new Duke University-led study finds that most climate models likely underestimate the degree of decade-to-decade variability occurring in mean surface temperatures as Earth’s atmosphere warms. The models also provide inconsistent explanations of why this variability occurs in the first place.

These discrepancies may undermine the models’ reliability for projecting the short-term pace as well as the extent of future warming, the study’s authors warn. As such, we shouldn’t over-interpret recent temperature trends.

“The inconsistencies we found among the models are a reality check showing we may not know as much as we thought we did,” said lead author Patrick T. Brown, a Ph.D. student in climatology at Duke’s Nicholas School of the Environment.

Don’t know as much as we thought we did?  But settled science!  And 97 percent!

There’s more:

“When you look at the 34 models used in the IPCC report, many give different answers about what is causing this decade-to-decade variability,” he said. “Some models point to the Pacific Decadal Oscillation as the cause. Other models point to other causes. It’s hard to know which is right and which is wrong.”

Hopefully, as the models become more sophisticated, they will coalesce around one answer, Brown said.  (Emphasis added.)

In other words: “C’mon people—we need to get our story straight!”

P.S. There’s this curious bit in the middle of this summary:

To conduct their study, they analyzed 34 climate models used by the Intergovernmental Panel on Climate Change (IPCC) in its fifth and most recent assessment report, finalized last November.

The analysis found good consistency among the 34 models explaining the causes of year-to-year temperature wiggles, Brown noted. The inconsistencies existed only in terms of the model’s ability to explain decade-to-decade variability, such as why global mean surface temperatures warmed quickly during the 1980s and 1990s, but have remained relatively stable since then.

So let’s see if we have this straight: we can explain annual changes fairly well, but can’t get longer-term changes right?  Isn’t this exactly the opposite of what you’d expect—unless it means the annual model runs are being tweaked to match up with the temperature record of the individual year in question?  This sounds like doing the TV weather forecast a day later.