In a recent video, German theoretical physicist Sabine Hossenfelder, PhD, addresses a critical issue in the field of climate science: the lack of transparency in the presentation of temperature data. Hossenfelder points out that the common practice of using temperature anomalies rather than absolute temperatures in climate graphs conceals significant discrepancies in climate models.
The Temperature Anomaly Issue
Hossenfelder begins by discussing a familiar graph from the most recent Intergovernmental Panel on Climate Change (IPCC) report, which projects temperature increases due to continued fossil fuel emissions. The graph displays temperature anomalies—deviations from a baseline temperature—rather than absolute temperatures. This approach, she explains, can be misleading.
Hiding Facts
“Climate scientists usually don’t tell you the actual temperature. They tell you a temperature anomaly,” Hossenfelder notes. She adds that while this method helps to normalize data, it also hides the fact that climate models predict wildly different absolute temperatures.
Discrepancies in Climate Models
Hossenfelder reveals a critical detail: the variance in absolute temperature predictions among different climate models. “The thin lines here, those are the absolute temperatures for the different models. As you can see, they differ by as much as three degrees!” she emphasizes. This variance exceeds the total warming observed over the period, highlighting a significant issue in the physical basis of these models.
Bad Models
The use of temperature anomalies rather than absolute temperatures, Hossenfelder argues, masks these discrepancies. “The reason climate scientists talk about the temperature relative to a baseline is that their models are really bad at getting absolute temperatures right,” she asserts.
Implications for Policy and Public Perception
Hossenfelder criticizes this lack of transparency, suggesting it leads to underestimating the risks associated with climate change. “Downplaying the shortcomings of the models leads people to underestimate the risk of delaying the energy transition,” she warns. She stresses that policy decisions, including net-zero plans, rely on these mean estimates, potentially overlooking worse-case scenarios.
Uncertainty in Climate Projections
Another point of contention is the way climate scientists calculate uncertainty in their projections. Hossenfelder explains that each model carries its own inherent uncertainty, which is often not explicitly communicated. “Each model on its own has an uncertainty already which is missing here. It’s missing because they don’t know what it is,” she says, pointing out a gap in the representation of data.
A Call for Greater Transparency
Hossenfelder’s analysis calls for greater transparency in how climate data is presented. She argues that acknowledging and communicating the limitations and uncertainties in climate models is crucial for making informed decisions about climate policy. “None of what I just told you is news to climate scientists. They know this full well. At least I hope they do. But I don’t like it that they don’t mention it,” she says.
“More Accurate About Their Uncertainties”
People in the comments shared their thoughts: “I asked a former NCAR employee why given all of the advances in tech they still can’t get weather forecasts right. He said ‘the tech only allows them to be more accurate about their uncertainties’”
Another commenter added: “It is not something we hide. It is not only models but also observations. From the uneven ccverage of the planet with weatherr stations we have, it is easier to calculate the change (‘anomaly’) in the global temperature than its absolute value. Weird but true”
One person concluded: “‘Extrapolation’ will multiply errors in the future, especially if it can’t get the actual past and present correct.”
Important Questions Raised
The video by Sabine Hossenfelder raises important questions about the transparency and accuracy of climate science. By highlighting the discrepancies in climate models and the reliance on temperature anomalies, Hossenfelder urges scientists and policymakers to be more forthcoming about the limitations and uncertainties in climate data. This transparency, she argues, is essential for accurately assessing the risks of climate change and making informed decisions about mitigating its impacts.
Potential Risks
What do you think? How do you think the use of temperature anomalies rather than absolute temperatures affects public perception of climate change? What are the potential risks of underestimating the uncertainties in climate models? How can climate scientists improve transparency in their data presentation?
Explore the full insights by viewing the video on Sabine Hossenfelder’s YouTube channel here.