The Government-Climate Complex

by Rud Istvan

Groundbreaking science is sometimes a global collaborative effort (CERN, Higgs boson, July 4). It is more often a contact sport—especially when individuals challenge a prevailing paradigm. In 1926 the president of the American Philosophical Society called Wegener’s theory of continental drift “utter damn rot”. Climate science has become just such a contact sport. There is a consensus paradigm represented by 4^th IPCC. There are apparent  flaws and uncertainties in that consensus. The government-climate complex stifles healthy scientific discourse about them.

JC note:  this is another contributed post responding to Garth Paltridge’s essay (see also Andy Lacis’ response).

Since climate is intrinsically important, this situation reflects deeply on the present practice of science generally, and on its interaction with government policy agendas in many other areas. Grant money flows to consensus research in a closed loop system, as Dr. Paltridge pointed out in his article “Science held hostage in climate debate” recently posted on Climate Etc. The scarier the finding, the more money flows. That incentive reinforces the closed loop. There becomes less to gain, and more to lose, by scientifically challenging the consensus even though portions of it are not backed by replicated observations.

This is deeply concerning. It is an alternative form of what President Eisenhower warned about in his last speech before leaving office. Instead of a military-industrial complex, we have a UN sponsored, agenda rich government-climate research complex seeking to reorder the world.

The thesis can be demonstrated with recent examples in three categories:

1. Signal to noise ratio (paleoclimate)
2. GCM oversensitivity
3. Consequences

Signal to noise

Tyndall proved in 1861 that both water vapor and CO₂ were greenhouse gases (Phil. Trans. Royal Soc. London 151: 1-36). There should be some anthropogenic global warming contribution in addition to natural variation in solar insolation, sunspots, ocean oscillations, galactic cosmic rays, and the like. The question is how much? This is AGW’s signal to noise ratio problem. The consensus asserts a strong AGW signal. The IPCC 4^th Assessment Report said natural factors could fully explain warming before about 1960 (e.g. SPM.4). The question is AGW’s relative contribution thereafter, since these natural factors have not disappeared. The IPCC consensus has arguably overstated the anthropogenic signals.

An example is the infamous ‘hockey stick’ controversy about ‘hiding the decline’ in recent tree ring data (see for example Youtube 8BQpciw8suk, and the ‘Hiding the Decline’ commentary by Climate Etc on 2/22/11). A bigger “hostage science” issue in this saga is selection bias. Other proxies show higher Medieval Warming Period temperatures than at present. These also show that higher MWP temperatures were global rather than European. The paleoclimate signal to noise is weak to nil, rather than strong. The most recent such proxy is ikaite in Antarctica. (Lu et. al., An ikaite record…, Earth and Planetary Science Letters 325-326: 108-115 (2012))  See in general for paleoclimate proxy selectivity Lansner’s Making Holocene Spaghetti Sauce by Proxy, posted on WUWT 4/11/09:

Selecting only the data that supports a hypothesis contradicts bedrock principals of science. It is a deeper problem than ‘mere’ academic misconduct.

There is stunningly a second example of misrepresented AGW signal to noise in the new ‘Australian hockey stick’ paper by Gergis et. al., Evidence of unusual late 20th century warming… , Journal of Climate (2012), formerly available at journals.ametsoc.org as JCLI-D-11-00649.1. This paper used 27 proxies but rejected 35 others using a version of the screening fallacy. The chosen 27 were then improperly detrended. This paper has been ‘put on hold’ (quoting the senior author) after selection bias and inability to replicate results were outed by Climate Audit. (Postings 5/31, 6/3, 6/4, 6/6, and 6/8).

GCM Oversensitivity “S”

S (equilibrium climate sensitivity) is an emergent GCM parameter for an equilibrium temperature given the standard doubling of CO₂ concentration. S describes the net result of all embedded positive and negative feedbacks beyond the direct CO₂ forcing itself. The mean S in all 4^th IPCC GCMs is 3.2 (WG1 8.6.2.3 table 8.2). The inferred S from its consensus 3.4°C warming by 2100 under SRES A2 is 3. Only one of the several historically constrained PDF estimations with a distinct mode has a likely value for S as high as 3 (WG1 10.5 Box 1).

As an example of ‘hostage science’, Nic Lewis questioned the PDF “S≈3” estimate by Forest et. al. on Climate Etc, posted 6/25/12.  Not only has the original source data been ‘lost’, pre-processed versions provided two other papers are inconsistent and contradictory. The lesser problematic of the two suggests the probable S is 1, not 3. Forest et al. are presumably preparing a response to the issues that have now been raised.

Nic Lewis is probably correct in his suspicions. There are a number of ways to infer climate sensitivity from observation without relying completely on GCMs, and a number of results. They point to sensitivity less than 3, most likely to something between 1.1 and 1.7. Details are covered in a separate comment, “What Climate Sensitivity says about IPCC Consensus Science”.

Asking why this is so leads to a subtler example of ‘hostage science’. Sensitivity comes nonlinearly from net positive feedback. The two main feedbacks are water vapor and clouds. For purposes of this comment, consider just the IPCC water vapor/lapse rate consensus. GCM’s produce a roughly constant relative humidity result at all altitudes under greenhouse gas forcing  [i]

The question is whether nature does. Mean constant relative surface humidity (at least over oceans) is generally correct.[ii] Upper troposphere relative humidity (UTrH) is important for radiative balance, but more difficult to observe and admittedly less certain. 4^th IPCC 3.4.2.2 rejected all UTrH radiosonde data as unreliable without discussing the declining UTrH it shows [iii]^, [iv]:

The IPCC AR4 then noted and rejected (because of possible ENSO influences) a satellite study showing UTrH decreasing away from the tropics, and especially in the Southern Hemisphere.[v] It noted and then ignored another (below). It did not even note two other satellite studies touching on UTrH that existed at that time. [vi]^, [vii] One of these showed a GCM systemically overestimated UTH. The IPCC consensus basically relied on only one satellite study.[viii] That study used HIRS to show that specific humidity was increasing, in a way roughly consistent with constant UTrH from one AGCM. IPCC 3.4.2.2 ended by saying, “To summarize, the available data do not indicate a detectable trend in upper-troposphere relative humidity.” Especially when selection bias makes the contrary data unavailable.

The IPCC AR4 ignored  the satellite study by Minschwaner and Dessler, Water Vapor Feedback in the Tropical Upper Troposphere, J. Climate 17:1272-1282 (2004). This paper showed interannual specific humidity increasing with temperature, but at a rate much lower than required by constant UTrH.

ERA-Interim shows UTrH declining since at least 1990.[ix]

NOAA-15 showed declining UTrH at the time the 4^th IPCC consensus was being formed. [The decline is real even after diurnal drift correction. The satellite shows declining UTrH on both the descending and the ascending nodes of its polar orbit.] In fairness, this paper itself was published after 4^th IPCC.

John et. al., Clear-sky biases in satellite infrared estimates of upper tropospheric humidity and its trends, J. Geophys. Res. 116: D14108 (2011).

The IPCC AR4  ‘consensus’ about roughly constant UTrH suggests selection bias. A lot of data now indicates the conclusion is wrong, and a reason for GCM oversensitivity.

Consequences

My previous Climate Etc post on crop yields and NRC’s 2011 booklet Warming World revealed a ‘deliberate’ misrepresentation, and a deeply flawed statistical study published in PNAS. Since the original data were not available to PNAS reviewers (an abridged portion was only made available later), peer review could not have caught the flaws. This shows yet again why original data should be archived, and made available for scrutiny and results replication. Even though that is official policy for US grant purposes, in climate science it appears often honored in the breach. Nic Lewis’ effort to obtain the Forest data is just one of many examples. See Boulton’s recent comment in Nature 486: 441 (2012).

Conclusion

Rather than provide additional consequence examples (there are many in my next book), it suffices to quote Why We Disagree about Climate Change, (2009). Author Michael Hulme is now a visiting fellow at the Tyndall Centre for Climate Studies at University of East Anglia:

“The function of climate change I suggest, is not as a lower-case environmental phenomenon to be solved. Solving climate change should not be the focus of our efforts any more than we should be ‘solving’ the idea of human rights or liberal democracy. It really is not about stopping climate chaos. Instead, we need to see how we can use the idea of climate change – the matrix of ecological functions, power relationships, cultural discourses and materials flows that climate change reveals – to rethink how we take forward our political, social, economic and personal projects over the decades to come.”

In other words, the science of climate change doesn’t really matter. The mere idea is useful for ‘political, social, economic, and personal projects’. Dr. Garth Paltridge is correct. True climate science has been ‘taken hostage’ by the government-research complex for political and personal agendas. We need to take it back.