Science, as in historical records, geological records, proxies records, logic, empirical measurements, real world observations and unadjusted data in addition to experimental results all tells us, there’s no Man Made Global Warming, AGW (what they today call “Climate Emergency”), never was, and never will be (based on CO2)!
R. J. L.
By Charles Rotter – WUWT
A failure of self-correction in science has compromised climate science’s ability to provide plausible views of our collective future.
This is an excellent article by Roger Pielke Jr. and Justin Ritchie. Here are some excerpts.
The integrity of science depends on its capacity to provide an ever more reliable picture of how the world works. Over the past decade or so, serious threats to this integrity have come to light. The expectation that science is inherently self-correcting, and that it moves cumulatively and progressively away from false beliefs and toward truth, has been challenged in numerous fields—including cancer research, neuroscience, hydrology, cosmology, and economics—as observers discover that many published findings are of poor quality, subject to systemic biases, or irreproducible.
In a particularly troubling example from the biomedical sciences, a 2015 literature review found that almost 900 peer-reviewed publications reporting studies of a supposed breast cancer cell line were in fact based on a misidentified skin cancer line. Worse still, nearly 250 of these studies were published even after the mistaken cell line was conclusively identified in 2007. Our cursory search of Google Scholar indicates that researchers are still using the skin cancer cell line in breast cancer studies published in 2021. All of these erroneous studies remain in the literature and will continue to be a source of misinformation for scientists working on breast cancer.
In 2021, climate research finds itself in a situation similar to breast cancer research in 2007. Our research (and that of several colleagues) indicates that the scenarios of greenhouse gas (GHG) emissions through the end of the twenty-first century are grounded in outdated portrayals of the recent past. Because climate models depend on these scenarios to project the future behavior of the climate, the outdated scenarios provide a misleading basis both for developing a scientific evidence base and for informing climate policy discussions. The continuing misuse of scenarios in climate research has become pervasive and consequential—so much so that we view it as one of the most significant failures of scientific integrity in the twenty-first century thus far. We need a course correction.
In calling for this change, we emphasize explicitly and unequivocally that human-caused climate change is real, that it poses significant risks to society and the environment, and that various policy responses in the form of mitigation and adaptation are necessary and make good sense. However, the reality and importance of climate change does not provide a rationale or excuse for avoiding questions of research integrity any more than does the reality and importance of breast cancer. To the contrary, urgency makes attention to integrity that much more important.
The emissions scenarios the climate community is now using as baselines for climate models depend on portrayals of the present that are no longer true. And once the scenarios lost touch with reality, so did the climate, impact, and economic models that depend on them for their projections of the future. Yet these projections are a central part of the scientific basis upon which climate policymakers are now developing, debating, and adopting policies.
The article gives background and history as to how we got here.
Why, then, did the IPCC choose RCP8.5 as its only business-as-usual baseline? Not because it explicitly judged it the world’s most likely or even plausible future, although the designation implies both. Rather, it selected RCP8.5 in part to facilitate continuity with scenarios of past IPCC reports, both SRES and earlier baseline scenarios, so that results of climate modeling research across decades could be comparable. It also chose RCP8.5 to help climate modelers explore the differences between climate behavior under hypothesized extreme conditions of human-caused climate forcing and natural variability. The difference between the high (8.5 W/m2) and low (2.6 W/m2) RCP forcing pathways created, as scenario developers explained, “a good signal-to-noise ratio for evaluating the climate response in AOGCM [atmospheric-oceanic general circulation model] simulations.” The technical requirements of climate modeling, and not climate policy, drove the design of IPCC scenarios.
In our research on the plausibility of IPCC scenarios, we have discovered it is not just RCP8.5 that is implausible, but the entire set of baseline scenarios used by the IPCC. In some ways this is unsurprising. As events unfold in a complex world, even the near-term futures anticipated by scenarios will drift away from reality. As a matter of scientific integrity, however, the reputation of science as a source of uniquely reliable knowledge depends on its internal capacity for self-correction. In the case of the RCPs (as with the example of breast cancer research after 2007), what we are seeing instead amounts to a stubborn commitment to error. This wouldn’t matter if climate scenarios had no implications for the world outside of science. But they lie at the heart of scientific efforts to understand the future of climate change and society’s decisions about how to respond.
The authors sum up the issues very well.
The consequences of pervasive, implausible climate scenarios extend far beyond the IPCC process and the academic literature these scenarios have enabled. A continued focus on implausible emissions scenarios in climate research is a failure of science’s supposed internal quality assurance mechanisms and thus a failure of scientific integrity. The persistent use of implausible scenarios introduces error and bias widely across climate research. They are now woven through the climate science literature in ways that will be very difficult to untangle.
Many of these thousands of published papers project future impacts of climate change on people, the economy, and the environment that are considerably more extreme than an actual understanding of emissions and forcing pathways would suggest is likely. As scientists’ understanding of climate change continues to improve, perhaps scientists will someday conclude that the most extreme impacts are also plausible under lower emissions trajectories. But that is not the consensus at present. And so, with any attempts at scientific nuance lost in technical language, these implausible projections of apocalyptic impacts decades hence are converted by press releases, media coverage, and advocates—as in an extended game of telephone—into assertions that climate change is now catalyzing dramatic increases in extreme events such as hurricanes, droughts, and floods, events that foreshadow imminent global catastrophe.
At the same time, and unsurprisingly, some opponents of climate policies are politically exploiting problems with the IPCC emissions scenarios. Groups such as the Global Warming Policy Foundation in London and the Competitiveness Enterprise Institute in Washington, DC, are highlighting the misuse of RCP8.5 to call into question the quality and legitimacy of climate science and assessments as a whole. But unlike many attacks on climate science, in this case these organizations have a good point.
Implausible climate scenarios are also introducing error and bias into actual policy and business decisions today. For example, the US government derives its social cost of carbon estimates, which it uses for cost-benefit analysis of federal regulations, from the IPCC scenarios. The financial sector also customizes IPCC scenarios for its use. The emerging market for climate scenario products has led to a $40 billion “climate intelligence” industry, involving familiar companies such as Swiss Re and McKinsey, and start-ups such as Jupiter Intelligence and Cervest. These companies are using implausible RCP scenarios to develop various predictive products that they sell to governments and industry, who will depend on these products to help guide policy and business decisions in the future.