Undeniable Mood Change With Regards To Quality Of Modelling Grips Climate Science…Trust Gone!

Mood change in climate modeling: Trust in the scientific community is disappearing
By Sebastian Lüning and Fritz Vahrenholt
(German text translated/edited by P Gosselin)

In the last few days we wrote two posts on the shocking deficits seen in the current climate models (see here and here). In our last part today we will look at how scientists estimate the modeling situation and look to see if there are new ideas to solve the problems.

In August 2014 a lead author of the 5th IPCC climate report, Richard Betts, publicly commented in a surprising manner. Betts directs the climate impact department of the UK Met Office, and at his website he describes himself as a climate modeling expert. In a comment at Bishop Hill, Betts wrote:

Bish, as always I am slightly bemused over why you think GCMs are so central to climate policy. Everyone* agrees that the greenhouse effect is real, and that CO₂ is a greenhouse gas. Everyone* agrees that CO₂ rise is anthropogenic. Everyone** agrees that we can’t predict the long-term response of the climate to ongoing CO₂ rise with great accuracy. It could be large, it could be small. We don’t know. The old-style energy balance models got us this far. We can’t be certain of large changes in future, but can’t rule them out either.”

In a footnote Betts added the 2 comments:

*OK so not quite everyone, but everyone who has thought about it to any reasonable extent
**Apart from a few who think that observations of a decade or three of small forcing can be extrapolated to indicate the response to long-term larger forcing with confidence.”

Betts no longer gives climate models a central role in climate policy. There are still too many unknowns, he admits. Quite obviously even IPCC authors are now getting cold feet and are no longer able to exclude that CO2 may have only a minor impact on climate.

A month earlier in July 2014 in the Wall Street Journal climate modeler Robert Caprara conceded that a variety of freely selectable parameters exist in climate models, which allow the desired result to be “modeled in”. Caprara writes:

My first job was as a consultant to the Environmental Protection Agency. I was hired to build a model to assess the impact of its Construction Grants Program, a nationwide effort in the 1970s and 1980s to upgrade sewer-treatment plants. […] When I presented the results to the EPA official in charge, he said that I should go back and “sharpen my pencil.” I did. I reviewed assumptions, tweaked coefficients and recalibrated data. But when I reran everything the numbers didn’t change much. At our next meeting he told me to run the numbers again. After three iterations I finally blurted out, “What number are you looking for?” He didn’t miss a beat: He told me that he needed to show $2 billion of benefits to get the program renewed. I finally turned enough knobs to get the answer he wanted, and everyone was happy.”

In the climate debate Caprara recommends having an open discussion and listening to the arguments of the other side instead of cursing the other side in an attempt to disqualify them:

So here is my advice: Those who are convinced that humans are drastically changing the climate for the worse and those who aren’t should accept and welcome a vibrant, robust back-and-forth. Let each side make its best case and trust that the truth will emerge. Those who do believe that humans are driving climate change retort that the science is “settled” and those who don’t agree are “deniers” and “flat-earthers.” Even the president mocks anyone who disagrees. But I have been doing this for a long time, and the one thing I have learned is how hard it is to convince people with a computer model.”

Already in a paper from October 2012 a team of scientists led by Clara Deser in Nature Climate Change admitted that the strong natural climate variability that had been underestimated had been poorly accounted for by the climate models and so the models could not fulfill the high expectations of the political decision makers. The paper’s abstract states:

Communication of the role of natural variability in future North American climate
As climate models improve, decision-makers’ expectations for accurate climate predictions are growing. Natural climate variability, however, poses inherent limits to climate predictability and the related goal of adaptation guidance in many places, as illustrated here for North America. Other locations with low natural variability show a more predictable future in which anthropogenic forcing can be more readily identified, even on small scales. We call for a more focused dialogue between scientists, policymakers and the public to improve communication and avoid raising expectations for accurate regional predictions everywhere.”

Also well-known climate scientist Judith Curry has little trust in climate modeling. In October 2013 she complained in her blog about the missing estimations of climate historical studies – to the benefit of climate models. Huge sums had been invested in the models, without a correct result. The falsely claimed consensus by the IPCC catapulted the climate sciences backward at least a decade, said Curry:

My point is that ambitious young climate scientists are inadvertently being steered in the direction of analyzing climate model simulations, and particularly projections of future climate change impacts — lots of funding in this area, in addition to high likelihood of publication in a high impact journal, and a guarantee of media attention. And the true meaning of this research in terms of our actual understanding of nature rests on the adequacy and fitness for purpose of these climate models. And why do these scientists think climate models are fit for these purposes? Why, the IPCC has told them so, with very high confidence. The manufactured consensus of the IPCC has arguably set our true understanding of the climate system back at least a decade, in my judgment. The real hard work of fundamental climate dynamics and development and improvement of paleo proxies is being relatively shunned by climate scientists since the rewards (and certainly the funding) are much lower. The amount of time and funding that has been wasted by using climate models for purposes for which that are unfit, may eventually be judged to be colossal.

A more precise knowledge of paleoclimatology is essential and should have absolute priority ahead of free-style modeling because historical data are important calibration and check data for climate models. When the formulae are not correct, then even the largest super-computers are unable to deliver anything useful.

Also astrophysicist Richard Lindzen of the Massachusetts Institute of Technology (MIT) has no trust in climate models, as he explained at an event at Sandia National Labs, a research and development facility of the US Department of Energy.

The IPCC should finally open itself up to alternative models. In our “The Neglected Sun” book we presented a semi-quantitive approach where solar and ocean cycles played an important role. The awful accuracy rate of the IPCC models shows that it is time for a change. A serious check of the ideas of IPCC critics has to be conducted. Here models by Nicola Scafetta and Frank Lemke, which reproduce the temperature curve better than the IPCC forecasts, must be given serious attention. When it comes to oceans cycles, scientists have already given in and have even started to insert them into the models, thus making reliability of the climate prognosis dramatically better. An approach is for example DelSole et al. 2013 in a paper in the Geophysical Research Letters.