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Tag Archives: Climate models

End of Snowfalls Is Greatly Exaggerated

03 Monday Feb 2020

Posted by Nuetzel in Uncategorized

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Tags

Baby Boomers, Climate Change, Climate models, Gen X, global warming, Millenials, NOAA, Snowfalls, The Independent, Thomas Jefferson

Snowcover Anomoly

Everyone seems to think it snowed more in their youth than in recent years, but that’s generally incorrect, at least for for late-stage baby boomers, Gen Xers, and Millenials. Gregory Wrightstone thought the same thing as he reflected on his youth in Pittsburgh, but after checking snowfall records he was surprised to find an upward trend. In “Warming and the Snows of Yesteryear“, Wrightstone says his look at the records from other areas showed similar upward trends. The chart above from NOAA shows the Northern Hemisphere has experienced mostly positive snowfall anomalies over the past 20 years. So, the truth is that snowfalls have not decreased over the last 50+ years, contrary to our fond memories of big snows in childhood. Interestingly, Thomas Jefferson thought the same thing in 1801, but I’m not sure whether he was right.

We’ve been told by climate alarmists that “snowfalls are a thing of the past” due to global warming (The Independent in March, 2000). If anything, however, snowfalls have increased, and big snowfalls still happen. As with so many climate predictions over the years, this too is a bust. Most of those predictions have relied on predictive models fitted with an inadequate historical record of data, and the models are inadequately specified to capture the complexities of global climate trends. Don’t bet the house on them, and don’t presume to bet my house on them either, please!

Imprecision and Unsettled Science

21 Friday Apr 2017

Posted by Nuetzel in Global Warming, Propaganda

≈ 1 Comment

Tags

Abatement Cost, Carbon Abatement, Carbon Forcings, Carbon Limits, Charles Hooper, Climate models, Cloud Formation, Confidence Interval, David Henderson, Earth Day, Measurement Error, Natural Climate Variation, Solar Forcings, Statistical Precision, Surface Temperatures, Temperature Aggregation, William Nordhaus

 

 

 

 

 

 

 

 

 

Last week I mentioned some of the inherent upward biases in the earth’s more recent surface temperature record. Measuring a “global” air temperature at the surface is an enormously complex task, requiring the aggregation of measurements taken using different methods and instruments (land stations, buoys, water buckets, ship water intakes, different kinds of thermometers) at points that are unevenly distributed across latitudes, longitudes, altitudes, and environments (sea, forest, mountain, and urban). Those measurements must be extrapolated to surrounding areas that are usually large and environmentally diverse. The task is made all the more difficult by the changing representation of measurements taken at these points, and changes in the environments at those points over time (e.g., urbanization). The spatial distribution of reports may change systematically and unsystematically with the time of day (especially onboard ships at sea).

The precision with which anything can be measured depends on the instrument used. Beyond that, there is often natural variation in the thing being measured. Some thermometers are better than others, and the quality of these instruments has varied tremendously over the roughly 165-year history of recorded land temperatures. The temperature itself at any location is subject to variation as the air shifts, but temperature readings are like snapshots taken at points in time, and may not be representative of areas nearby. In fact, the number of land weather stations used in constructing global temperatures has declined drastically since the 1970s, which implies an increasing error in approximating temperatures within each expanding area of coverage.

The point is that a statistical range of variation exists around each temperature measurement, and there is additional error introduced by vagaries of the aggregation process. David Henderson and Charles Hooper discuss the handling of temperature measurement errors in aggregation and in discussions of climate change. The upward trend in the “global” surface temperature between 1856 and 2004 was about 0.8° C, but a 95% confidence interval around that change is ±0.98° C. (I believe that is probably small given the sketchiness of the early records.) In other words, from a statistical perspective, one cannot reject the hypothesis that the global surface temperature was unchanged for the full period.

Henderson and Hooper make some other salient points related to the negligible energy impulse from carbon forcings relative to the massive impact of variations in solar energy and the uncertainty around the behavior of cloud formation. It’s little wonder that climate models relying on a carbon-forcing impact have erred so widely and consistently.

In addition to reinforcing the difficulty of measuring surface temperatures and modeling the climate, the implication of the Henderson and Hooper article is that policy should not be guided by measurements and models subject to so much uncertainty and such minor impulses or “signals”. The sheer cost of abating carbon emissions is huge, though some alternative means of doing so are better than others. Costs increase as the degree of abatement increases (or replacement of low-carbon alternatives), and I suspect that the incremental benefit decreases. Strict limits on carbon emissions reduce economic output. On a broad scale, that would impose a sacrifice of economic development and incomes in the non-industrialized world, not to mention low-income minorities in the developed world. One well-known estimate by William Nordhaus involved a 90% reduction in world carbon emissions by 2050. He calculated a total long-run cost of between $17 trillion and $22 trillion. Annually, the cost was about 3.5% of world GDP. The climate model Nordhaus used suggested that the reduction in global temperatures would be between 1.3º and 1.6º C, but in view of the foregoing, that range is highly speculative and likely to be an extreme exaggeration. And note the small width of the “confidence interval”. That range is not at all a confidence interval in the usual sense; it is a “stab” at the uncertainty in a forecast of something many years hence.  Nordhaus could not possibly have considered all sources of uncertainty in arriving at that range of temperature change, least of all the errors in measuring global temperature to begin with.

Climate change activists would do well to spend their Earth Day educating themselves about the facts of surface temperature measurement. Their usual prescription is to extract resources and coercively deny future economic gains in exchange for steps that might or might not solve a problem they insist is severe. The realities are that the “global temperature” is itself subject to great uncertainty, and its long-term trend over the historical record cannot be distinguished statistically from zero. In terms of impacting the climate, natural forces are much more powerful than carbon forcings. And the models on which activists depend are so rudimentary, and so error prone and biased historically, that taking your money to solve the problem implied by their forecasts is utter foolishness.

Precaution Forbids Your Rewards

19 Thursday Feb 2015

Posted by Nuetzel in Regulation

≈ 2 Comments

Tags

Carbon forcing, Climate models, Climate Warming, Coyote Blog, GMOs, Precautionary Principle, psuedoscience, regulation, Risk Management, Warren Meyer

health-and-safety-cartoon

The precautionary principle (PP) is often used to justify actions that radically infringe on liberty, but it is an unreliable guide to managing risk, both for society and for individuals. Warren Meyer makes this point forcefully in a recent post entitled “A Unified Theory of Poor Risk Management“. The whole post is worth reading, but PP is the focus of second section. Meyer offers the following definition of the PP from Wikipedia:

“The precautionary principle or precautionary approach to risk management states that if an action or policy has a suspected risk of causing harm to the public or to the environment, in the absence of scientific consensus that the action or policy is not harmful, the burden of proof that it is not harmful falls on those taking an action.”

He goes on to explain several problems with PP, the most important of which is its one-sided emphasis on the risks of an activity while dismissing prospective benefits of any kind. Enough said! That shortcoming immediately disqualifies PP as a guide to action. Rather, it justifies  compulsion to not act, which is usually the desired outcome when PP is invoked. We are told to stop burning fossil fuels because CO2 emissions might lead to catastrophic global warming. Yet burning fossil fuels brings enormous benefits to humanity, including real environmental benefits. We are told to stop the cultivation of GMOs because of perceived risks, yet the potential benefits of GMOs are routinely ignored, such as higher yields, improved nutrition, drought resistance and reduced environmental damage. Meyer asks whether there is an irony in ignoring these potential gains, as it entails an acceptance of certain risks. Forced energy shortages would bring widespread economic decline. Less-developed countries face risks of continuing poverty and malnutrition that could otherwise be mitigated.

The terrifying risks cited by PP adherents are generally not well-founded. For example, climate models based on CO2 forcings have extremely poor track records. And whether such hypothetical warming would be costly or beneficial, on balance, is open to debate. The supposed risks of GMOs are largely based on pseudoscience and ignore a vast body of evidence of their safety. As Meyer says:

“… the principle is inherently anti-progress. The proposition requires that folks who want to introduce new innovations must prove a negative, and it is very hard to prove a negative — how do I prove there are no invisible aliens in my closet who may come out and eat me someday, and how can I possibly get a scientific consensus to this fact? As a result, by merely expressing that one ‘suspects’ a risk (note there is no need listed for proof or justification of this suspicion), any advance may be stopped cold. Had we followed such a principle consistently, we would still all be subsistence farmers, vassals to our feudal lord.”

The PP has obvious appeal to statists and fits comfortably into the philosophy of the regulatory state. But it’s a reasonable conjecture that widespread application of the PP exposes the world to greater natural and economic risks than without the PP. Under laissez-faire capitalism, human action is guided by the rational balancing of benefits against costs and risks, which has brought prosperity everywhere it’s been practiced.

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