A perspective on uncertainty and climate science [Marcia Wyatt]

This past summer I was asked to give a presentation on science and ethics. The person who asked me was motivated by the Pope’s encyclical, the comments regarding climate change.

The group to which I was to present – its members most interested and well-informed about climate, yet also confused by the strong opinions of dignitaries and luminaries, such as the Pope – wanted a climate scientist’s perspective. I could not help them with their ethical outlook, but I realized what people really need is not the tit-for-tat, back-and-forth endless debate, with each side being “right”; they needed to understand that we scientists really don’t know what climate is doing or will do! No one does. We only have degrees of uncertainty. Thus, the presentation evolved, with the originally requested topic modified to discuss my perspective on the uncertainties in climate science. After giving the talk, I realized there could be many versions of such a presentation, with different levels of detail and scientific background. I would like this information to be communicated to the public, as well as to college and high-school students. In the past, I could ignore the dissemination of misleading information to the general public. No longer can I. The stakes are too high; the consequences too dire.

Uncertainty in Climate Science

The complete .ppt presentation can be downloaded here [http://www.wyattonearth.net/images/Uncertainty_in_Climate_Science_10_9_2015.ppt]

Introduction:

Word “around town” is that science is truth. Sorry to damp the zeal, but science is NOT truth. By definition, science equates to varying degrees of uncertainty, with hypotheses and theories bookending the uncertainty spectrum – to some, a rather boring outlook. Hypotheses – suggested explanations for how things work, and based upon observed evidence, offering potential prediction of phenomena whose correlative relationships may be causal – must be both testable and falsifiable. A hypothesis cannot be proven to be true; it can only be proved false. For a hypothesis to be elevated to theory – a rare and significant promotion – the hypothesis must survive multiple replications of results with a wide set of data, and it must be tested under a variety of circumstances. Even then, while uncertainty of a theory is minimized; it is never zero. Hence, science is the constant process of trying to figure out how things might work. To a scientist, this is exhilarating. To the non-scientist wanting a solid answer, not so much!

Well, this is all relatively bad news for those of us who study climate. Climate, by nature, does not lend itself well to being tested. We can’t isolate its parts and study them in a lab. We can’t condense decades and millennia into hours and days in order to extract multiple data points and long records. Intertwined and multiple “parts” of the climate system render its evaluation stymied by the endless unknown unknowns! So what do we do? We seek out proxy data – riddled with caveats. We invoke computer climate models – riddled with caveats. No matter which way we turn, we are faced with caveats, but it’s the best we’ve got. Sometimes “we” get so used to working within these constraints imposed upon us, we begin to lose sight of our assumptions, and the attendant biases, caveats, and uncertainties laced throughout our research format. In time, it is not difficult to see how we come to believe the little fantasy world we have made for ourselves in attempt to make sense of nature’s vast stomping grounds. And when it is demanded of us to stop equivocating, to make the discussion short and sweet, packaging into sound bites the complexities of 4.6 billion years’ perspective on climate and how its changing character of today differs from any time past and how we humans and other earthly creatures will survive an onslaught that, by human perception, appears unprecedented and unendurable; “What can we do”!!!! Politics enters the stage, followed closely by celebrities and media. Messages are surgically edited to be woven into stories far more captivating than those told by the equivocating egg-heads; and photographers, accompanied by narrators with scholarly accents and compelling rhetoric, come in to educate the public. And the public find no choice but to believe. Uncertainty is forgotten, actually no, it is abandoned. Uncertainty is not for the impatient. Good intentions pave the path forward. So where does that leave us? How does one make policy decisions based on science, with uncertainty’s role demoted to nuisance status?

It might be of interest to know that historically, skepticism has fueled forward movement of scientific discovery. Uncertainty has always motivated inquiry. Conversely, certainty has squelched it. Certainty entrenches paradigms. Examples dot history of paradigms kept on life support with increasingly complicated constructs to explain phenomena or occurrences inconsistent with hypothesized dynamics and behavior – the 1600-year-long geocentric model being a most vivid example. Upending of faulty paradigms often relies on evolution of technology. New evidence reveals surprises – those “unknown unknowns”. Ironically, those most educated in a field often are not the ones in history to have revolutionized thought. Lay persons and scientists of different specialties often were the ones who “saw” what was hidden from the hardened mental filters of those overly invested in a paradigm’s survival. Skepticism has gotten a bad rap in recent years. Instead, it should be embraced. It is skepticism – not conformity – that provides the checks and balances to humans’ tendency to see the expected.

How does one make good decisions in context of uncertainty? One must gather good evidence – not hearsay, not sound bites, nor “consensus”. Good evidence can be garnered only through understanding how conclusions are reached – the methodology and data used to construct them. This is not easy, but just accepting what others say – their filtered conclusions, even those of “respected” scientists or trusted dignitaries – not investigating the scientific process employed in generating a conclusion, and not exploring alternate possible explanations for observed phenomena, destines its victims to the unintended consequences.

Slide01Scientists do agree: Temperatures have increased since 1850; CO2 has too. CO2 is an infrared warmer. With no positive or negative feedback responses, a doubling of it will lead to an approximate 1.1ºC temperature increase. Disagreement erupts over just how much temperature has risen; what part is due to CO2; what part to land-use changes; what part due to natural or intrinsic influences. How well do models represent climate; what is climate’s sensitivity; are the data reliable? Is there really a problem? Is it a problem that can be solved with proposed solutions? And what are potential consequences of proposed solutions? It is said to be certain, to be “settled science”. Really!?!

1.Hypotheses overview:  More than one hypothesis can explain observed behavior.

Two general and contrasting views exist on climate behavior. One view is the “consensus” hypothesis, where external forcing – both natural and anthropogenic – dominates climate behavior (“climate change”) — a modification of the former anthropogenic global warming (AGW) hypothesis. The contrasting view allows a greater role for internally generated dynamics, especially on decadal-plus time scales.

According to the external-forcing view, parts of a system operate relatively independently; the system is prone to instability, is not resilient, and, with continued anthropogenic greenhouse-gas-emission increases, is projected to result in catastrophic climatic changes.

In contrast, the intrinsic-dynamics view envisions network-behavior dominating climate behavior, where parts of the ocean, ice, and atmosphere sub-systems self-organize over decadal-plus time scales, interacting with one another, and thereby initiating intra-network communication, conveying resilience and relative stability to the climate system.

The external forcing hypothesis is based on strong understanding of greenhouse-gas forcing, but low-to-very-low levels of understanding of other external forcings – clouds, aerosols, solar influence, for examples. Extreme increases in projected temperatures rely on incomplete understanding of reinforcing consequences of the original CO2-induced warming, i.e. positive feedbacks. Little is understood about potential damping mechanisms – e.g. clouds, aerosols, atmospheric convection, and precipitation. Likewise, little is fully understood about, or attributed to, intrinsic dynamics. None of these weaknesses guarantees this hypothesis is wrong, but the uncertainties involved are striking. More striking is that the hypothesis is not testable. It cannot be falsified. The alternate hypothesis, the network hypothesis, is rooted in observation, among a variety of indices. Mechanisms have been elucidated as possible dynamics underlying climate-signal evolution. Uncertainties underlie this hypothesis, as well. Yet, its strength lies on observations. They are consistent with the hypothesis, and in time – years to decades – this hypothesis is testable and falsifiable. Seguir leyendo...