Model Uncertainties Too Great To Reliably Advise Policymakers, German Scientists Say. German scientists Dr. Sebastian Lüning and Prof. Fritz Vahrenholt — and new recent studies — show climate models have a long way to go before they can be used for advising policymakers. Climate sciences cannot reliably advise policymakers as long as model uncertainties cannot be reduced By Dr. On November 3, 2017, the Institute of Atmospheric Physics, Chinese Academy of Sciences put out a press release concerning the quality check of climate models: A new method to evaluate overall performance of a climate modelMany climate-related studies, such as detection and attribution of historical climate change, projections of future climate and environments, and adaptation to future climate change, heavily rely on the performance of climate models. It is highly satisfying to see that climate modelers are now taking the quality checks of their models seriously.
Ancell et al. (2018) has shown that some models are dominated by chaos. Also see the discussion at WUWT on this paper. Climate Models Are Uncertain, but We Can Do Something About It. Model uncertainty is one of the biggest challenges we face in Earth system science, yet comparatively little effort is devoted to fixing it. A well-known example of persistent model uncertainty is aerosol radiative forcing of climate, for which the uncertainty range has remained essentially unchanged through all Intergovernmental Panel on Climate Change assessment reports since 1995. From the carbon cycle to ice sheets, each community will no doubt have its own examples. We argue that the huge and successful effort to develop physical understanding of the Earth system needs to be complemented by greater effort to understand and reduce model uncertainty.
Without such reductions in uncertainty, the science we do will not, by itself, be sufficient to provide robust information for governments, policy makers, and the public at large. Model Wiggle Room As British statistician George Box famously said, “all models are wrong, but some are useful.” What We Lose When Settling on One Model Variant. A veneer of certainty stoking climate alarm.
By Judith Curry In private, climate scientists are much less certain than they tell the public. – Rupert Darwall Rupert Darwall has written a tour-de-force essay “A Veneer of Certainty Stoking Climate Alarm“, which has been published by CEI [link to full essay]. Foreword I was invited to write a Foreword to the essay, which provides context for the essay: While the nations of the world met in Bonn to discuss implementation of the Paris Climate Agreement, the Trump administration was working to dismantle President Obama’s Clean Power Plan and to establish a climate “red team” to critically evaluate the scientific basis for dangerous human-caused climate change and the policy responses.
The mantra of “settled science” is belied by the inherent complexity of climate change as a scientific problem, the plethora of agents and processes that influence the global climate, and disagreements among scientists. The transcript of the workshop is a remarkable document. Excerpts Introduction. Dr. Dr. In-depth: Scientists discuss how to improve climate models.
While global climate models do a good job of simulating the Earth’s climate, they are not perfect. Despite the huge strides taken since the earliest climate models, there are some climatic processes that they do not simulate as accurately as scientists would like. Advances in knowledge and computing power mean models are constantly revised and improved. As models become ever more sophisticated, scientists can generate a more accurate representation of the climate around us. But this is a never-ending quest for greater precision. In the third article in our week-long climate modelling series, Carbon Brief asked a range of climate scientists what they think the main priorities are for improving climate models over the coming decade. These are their responses, first as sample quotes, then, below, in full: Prof Stefan Rahmstorf: “I think a key challenge is non-linear effects, or tipping points.
Prof Pete SmithChair in plant and soil science University of Aberdeen Three is better observations. Uncertainties, Errors In Radiative Forcing Estimates 10 – 100 Times Larger Than Entire Radiative Effect Of Increasing CO2. Scott Pruitt, the new head of the U.S. Environmental Protection Agency, has recently been characterized as a climate science “denialist” by world news organizations. A UK Guardian headline, for example, has claimed that “EPA head Scott Pruitt denies that carbon dioxide causes global warming“. The “denialist” characterization stems from an interview with CNBC’s Joe Kernen in which Pruitt was asked whether he believes that CO2 has been proven to be the climate’s “control knob”. Pruitt replied that “we don’t know that yet” and that “there’s tremendous disagreement about the degree of impact.”
Scott Pruit: “No. In a Washington Post analysis of Pruitt’s comments entitled “EPA Chief’s Climate Change Denial Easily Refuted…”, the host’s reply to Pruitt’s last statement about the need to continue debating the degree of human impact was included: “That’s the whole point of science. “Well, sure. 1. Feldman et al., 2015 2. Stephens et al., 2012 4. Frank, 2008 5. 6. Dr. Judith Curry speaks out on climate science’s fatal flaw – the failure to explore and understand uncertainty | Watts Up With That? Guest essay by Larry Hamlin Dr.
Judith Curry conducted an interview on British radio on February 6th addressing, among many topics, how the politicalization of climate science created and driven by the UN IPCC process has robbed scientists of the opportunity to explore the legitimate, extremely important and yet unaddressed issues of how natural climate change drivers impact the earth’s climate. Her excellent broadcast can be found here: During the course of her interview Dr. Curry addressed the underlying assumptions contained in the UN IPCC process at its very beginning which simply assumed without establishing scientific evidence that anthropogenic activity was driving “global warming” (which was subsequently modified to “climate change” after the global temperature “pause”). Dr. In these prior articles she concluded that in using this model driven detection and attribution technique “the IPCC has failed to convincingly demonstrate ‘detection.’
Dr. In these prior articles Dr. Dr. No Certain Doom: On the Accuracy of Projected Global Average Surface Air Temperatures. Alternative approach to assessing climate risks | Climate Etc. By Judith Curry At one level, analyzing climate risks is a matter of due diligence, given mounting scientific evidence. However, there is no consensus about the means for doing so nor about whether climate models are even fit for the purpose. An alternative to the scenario- led strategy, such as an approach based on a vulnerability analysis (“stress test”), may identify practical options for resource managers. – Brown and Wilby At the recent Royal Society Workshop on Handling Uncertainty in Weather and Climate Prediction, among the interesting people that I met was Robert Wilby, who has an article in the latest issue of EOS.
Citation: Brown, C. and R. Some excerpts: The recognized limitations of GCMs, including the lack of credibility on extremes, imply that GCM-based projections may have difficulty providing the information decision makers typically look for or even adding value to a risk analysis . Like this: Like Loading... Taming the Uncertainty Monster | Climate Etc. By Judith Curry The concluding section in my draft paper on “Climate Science and the Uncertainty Monster” (discussed previously on this thread) is entitled “Taming the uncertainty monster.” Uncertainty monster refresher In case you missed my original post on the Uncertainty Monster, here is a brief recap: The “uncertainty monster” is a concept introduced by van der Sluijs (2005) in an analysis of the different ways that the scientific community responds to uncertainties that are difficult to cope with.
A monster is understood as a phenomenon that at the same moment fits into two categories that were considered to be mutually excluding. An adaptation of van der Sluijs’ strategies of coping with the uncertainty monster at the science-policy interface is described below. Monster hiding. Monster exorcism. Monster simplification. Monster detection. Monster assimilation. Below is the text from the concluding chapter of my draft paper: 5. The monster is too big to hide, exorcise or simplify.
Two (+1) new uncertainty papers | Climate Etc. By Judith Curry My paper “Reasoning about climate uncertainty” has now been published online at Climatic Change; it looks like mine is the first to make it online of the papers in the special issue entitled Framing and Communicating Uncertainty and Confidence Judgments by the IPCC. Also of relevance, there is a new working paper from the LSE Grantham Research Institute entitled “Scientific uncertainty: a user’s guide” (h/t Bishop Hill). Reasoning about climate uncertainty Judith Curry Received: 1 April 2011 / Accepted: 14 June 2011 # The Author(s) 2011.Climatic Change DOI 10.1007/s10584-011-0180-zThis article is published with open access at Springerlink.com Abstract.
You may recall the previous thread here where I posted an earlier draft of the paper for comments. Acknowledgements. Its always interesting to go back and read your own paper after not thinking about it for a few months. Once the special issue is published, we will have a thread discussing the other papers. Seamus Bradley. Verification, validation, and uncertainty quantification in scientific computing | Climate Etc. By Judith Curry I think I am gaining some insight into the debate between scientists versus engineers regarding climate model verification and validation. For background, the previous relevant posts at Climate Etc. are: Of particular relevance is the post Climate model verification and validation, where the starkly different perspectives of Steve Easterbrook and Dan Hughes are contrasted.
Steve Easterbrook’s new post Steve Easterbrook has a new post entitled “Formal verification for climate models?” Valdivino, who is working on a PhD in Brazil, on formal software verification techniques, is inspired by my suggestion to find ways to apply our current software research skills to climate science. 1.) Excerpts from Easterbrook’s response: Climate models are built through a long, slow process of trial and error, continually seeking to improve the quality of the simulations (See here for an overview of how they’re tested). Dan Hughes responds The following was cut by Steve Easterbrook Abstract. Uncertainty in health impacts of climate change | Climate Etc. By Judith Curry Health risks arise from the interaction of uncertain future climatic changes with complex ecological, physical, and socio-economic systems, which are simultaneously affected by numerous other changes, e.g. globalisation, demographic changes, and changes in land use, nutrition, health care quality.
Policymaking on adaptation to health risks of climate change thus faces substantial uncertainty. – Wardekker et al. Health risks of climate change: An assessment of uncertainties and its implications for adaptation policy JA Wardekker, A deJong, L vanBree, WC Turkenburg, J van der Sluijs Abstract Background: Projections of health risks of climate change are surrounded with uncertainties in knowledge. Methods: We made an inventory of conceivable health impacts of climate change, explored the type and level of uncertainty for each impact, and discussed its implications for adaptation policy. [Link] to online paper. Excerpts: Level of Precision Scale Conclusions Like this: Like Loading... Throwing down the gauntlet on reproducibility in Climate Science – Forest et al. (2006) | Watts Up With That? After spending a year trying to get the data from the author without success, Nic Lewis has sent a letter to the editor of Geophysical Research Letters (GRL) and has written to me to ask that I bring attention to his letter published at Judith Curry’s website, and I am happy to do so.
He writes: I would much appreciate it if you could post a link at WUWT to an article of mine (as attached) that has just been published at Climate Etc. It concerns the alteration of data used in an important climate sensitivity study, Forest 2006, with a radical effect on the resulting climate sensitivity estimated PDF. I’m including the foreword here (bolding mine) and there is a link to the entire letter to the editor of GRL. Questioning the Forest et al. (2006) sensitivity study By Nicholas Lewis Re: Data inconsistencies in Forest, Stone and Sokolov (2006) GRL paper 2005GL023977 ‘Estimated PDFs of climate system properties including natural and anthropogenic forcings‘ Nic Lewis -Anthony Like this: Uncertainty in observations of the Earth’s energy balance | Climate Etc. By Judith Curry This lack of precise knowledge of surface energy fluxes profoundly affects our ability to understand how Earth’s climate responds to increasing concentrations of greenhouse gases. – Graeme Stephens et al.
An update on Earth’s energy balance in light of the latest global observations Graeme L. Stephens, Juilin Li, Martin Wild, Carol Anne Clayson, Norman Loeb, Seiji Kato, Tristan L’Ecuyer, Paul W. Abstract. Citation: Nature Geoscience 5, 691–696 (2012) doi:10.1038/ngeo1580 [link] The punchline of the paper is this Figure, which is essentially a re-do of the Kiehl and Trenberth figure: Am I surprised by any of this?
JoNova has post on this [here]. This paper rattles the whole table of key numbers, with empirical results. The models are hunting for imbalances and build-ups in planetary energy. Another major implications is that water is churning up and falling out of the sky faster than the experts thought. JoNova’s post aptly describes a rational skeptics response. Graeme L. Meta-uncertainty in the determination of climate sensitivity | Climate Etc. By Judith Curry Two heavyweight climate scientists have published very different ideas about how much the Earth is going to warm in the coming decades. – Washington Weather Gang A post last December by the Washington Weather Gang Studies differ on climate change and warming severity, researchers trade jabs lays down the controversy: Two heavyweight climate scientists have published very different ideas about how much the Earth is going to warm in the coming decades.
And neither has much regard for the other’s estimate – casting light on a long-standing, thorny issue in climate science. Future warming is likely to be on the high end of predictions says Kevin Trenberth of the National Center for Atmospheric Research who has been a lead author for the United Nations Intergovernmental Panel on Climate Change (IPCC). In response to the recent Economist article (see this previous post), Michael Mann and Dana Nucitelli wrote an opinion piece for the ABC entitled How the Economist got it wrong. R. Uncertainty in SST measurements and data sets | Climate Etc. By Judith Curry Two new papers that discuss uncertainty in surface temperature measurements.
The issue of uncertainty in surface temperature measurements is getting some much needed attention, particularly in context of the HadCRUT datasets. For context, some previous Climate Etc. posts on this topic: The first paper, by John Kennedy of UK Met Office, provides a comprehensive and much needed uncertainty analysis of sea surface temperature measurements and analyses: A review of uncertainty in in situ measurements and data sets of sea-surface temperature John Kennedy Abstract. Published in Reviews of Geophysics, link to abstract and full manuscript. Excerpts: In using SST observations and the analyses that are based on them, it is important to understand the uncertainties inherent in them and the assumptions and statistical methods that have gone into their creation.
Section 2 provides a classification of uncertainties. JC comment: Uncertain T. Kevin Cowtan and Robert Wray Abstract. JC assessment. Ocean heat content uncertainties | Climate Etc. Are the deep oceans cooling? | Climate Etc. Ethics of communicating scientific uncertainty | Climate Etc. Stalking the uncertainty monster | Climate Etc. Managing uncertainty in predictions of climate change and impacts | Climate Etc. Alternative approach to assessing climate risks | Climate Etc. Coping with deep climate uncertainty | Climate Etc. Deep Uncertainty of Climate Sensitivity Estimates: Sources and Implications. Judith Curry - Climate Science and the Uncertainty Monster.