Roger Pielke, Jr. described the underappreciated importance of climate variability in a recent post. It is increasingly obvious that there are so many issues coming up with the New York Climate Leadership & Community Protection Act (Climate Act) net zero transition that we need to pause implementation and figure out how best to proceed. Pielke’s article raises another example.
I am convinced that implementation of the Climate Act net-zero mandates will do more harm than good because the proposed green energy programs are crimes against physics. The energy density of wind and solar energy is too low and the resource intermittency too variable to ever support a reliable electric system relying on those resources. I have followed the Climate Act since it was first proposed, submitted comments on the Climate Act implementation plan, and have written over 500 articles about New York’s net-zero transition. The opinions expressed in this article do not reflect the position of any of my previous employers or any other organization I have been associated with, these comments are mine alone.
Overview
The Climate Act established a New York “Net Zero” target (85% reduction in GHG emissions and 15% offset of emissions) by 2050. It includes an interim reduction target of a 40% GHG reduction by 2030. The Climate Action Council (CAC) was responsible for preparing the Scoping Plan that outlined how to “achieve the State’s bold clean energy and climate agenda.” After a year-long review, the Scoping Plan was finalized at the end of 2022. Since then, the State has been trying to implement the Scoping Plan recommendations through regulations, proceedings, and legislation. However, in the rush to meet Climate Act mandates fundamental concepts and concerns are being ignored.
Climate Variability
One of the frustrating characteristics of climate advocates is the constant attribution of any unusual weather to climate change. I have noted that a climatological average is normally based on a 30-year averaging period and explained that climate change could be defined as the difference. As is the case with all aspects of climate change issues, there is more nuance and detail than obvious at first glance.
Roger Pielke, Jr. provides nuance and detail to the question “what is climate change.”
One of the most pervasive misunderstandings of climate — even among some who publish on climate — is the belief that any long-term trend in a measured climate variable indicates a change in climate, as defined by the Intergovernmental Panel on Climate Change (IPCC}. In practice, “long-term” is often defined to be only a few decades worth of observations. Some trends in observational data are not an indication of a change in climate, and others are — telling the difference is not easy when it comes to extreme weather events.
He explains that the first issue is that climate data like any observation set of natural phenomena fluctuates naturally. A post at Climate Etc. explains:
According to the IPCC, “climate variability refers to variations in the mean state and other statistics (such as standard deviations, the occurrence of extremes, etc.) of the climate on all spatial and temporal scales beyond that of individual weather events. Variability may be due to natural internal processes within the climate system (internal variability), or to variations in natural or anthropogenic external forcing (external variability).”
Pielke explains why this should be considered when estimating climate change effects:
The IPCC AR6 explains that the detection of a change in climate requires some certainty that the trend is not simply due to climate variability: “An identified change is detected in observations if its likelihood of occurrence by chance due to internal variability alone is determined to be small, for example, <10%.”
Quantifying internal variability with respect to any climate metric is challenging, typically with multiple valid interpretations possible. Superimposed upon the challenge is the fact that internal variability itself has been influenced by human factors, notably the emission of greenhouse gases.
Pielke notes that a common simplifying assumption is that the observed weather would not change were it not for “human influence”. The problem is that it is too frequently applied to short observational records to claim climate change impacts. Pielke notes that this is flawed because:
The current climate varies on timescales both greater and less than 30 years. The IPCC AR6 defines climate variability:
“Deviations of climate variables from a given mean state (including the occurrence of extremes, etc.) at all spatial and temporal scales beyond that of individual weather events. Variability may be intrinsic, due to fluctuations of processes internal to the climate system (internal variability), or extrinsic, due to variations in natural or anthropogenic external forcing (forced variability).”
Pielke’s post goes on to address the question “How near or far into the past does one need to go to adequately characterize a ‘current climate’?” to use as the baseline for a climate change comparison. He uses flood data for various periods to show how easy it is to find a “convincing” trend showing larger floods over time since 1897 consistent with the hypothesis that increased greenhouse gases are causing the increase based on the data used. However, when data prior to 1897 Hirsch (2011) explain that:
. . . we get a very different and more complex picture. . . Now we would say that although there has been some increase in flood magnitudes over time, the pattern is no longer very consistent with a hypothesis that this is driven by greenhouse gas increases in the atmosphere. The high values in the 19th Century are inconsistent with this hypothesis. In fact, one could put forward the argument that there are two populations of annual floods at this location. One is the population that spanned the years of about 1900 to 1941, and the other population existed before 1900 and after 1942. Without the benefit of the longer record, we could easily conclude that the data were highly supportive of a greenhouse-gas driven trend in flood magnitudes, but with it we find ourselves having to entertain other highly plausible hypotheses about an abruptly shifting population, with shifts that take place at time scales of many decades. The data do not negate the possibility that greenhouse forcing is a significant factor here, but they make it much more difficult to argue that these data provide a clear demonstration of the effect of enhanced greenhouse gas forcing on flood magnitudes.
Pielke goes on to describe how this issue affects the US government’s approach to flood policy. He notes that a common application of flood risk fails to account for this problem. This challenge has been long recognized by flood experts. Leslie Bond described this 20 years ago:
In the statistical estimation of a flood peak of a specific recurrence interval requires that all of the recorded peak flows be accurate and that the record be stable over the period of the record and the period for which the estimate is to be applied. That is, if there is a 50-year record of stream flow from 1931 through 1980, and you want a current estimate of the 1% flood to be valid for 30 years, the hydrology, the meteorology and the hydraulics must be stable from 1930 through 2034. In fact, we do not have sufficient historic rainfall data to be sure that the meteorology is stable, and few watersheds in the world are not changing as a result of urbanization, deforestation, agriculture, grazing or other causes.
Climate Act Implications
I have long-standing concerns about wind and solar resource availability. The issues described by Pielke related to long-term weather observations are relevant to that problem. It is obvious that we need to know the worst-case scenario for low wind and solar resource availability to determine how much long-term storage and/or some magical dispatchable emissions-free resource is needed to provide sufficient energy during resource droughts. His references to floods are apropos because I believe we need to develop a probabilistic resource drought parameter equivalent to the 100-year flood.
I have always believed that we should use as long a period of data as possible to determine that parameter. These results complicate wind and solar-depending electrical system planning because it means even using the longest period of data may specify requirements incorrectly. Also note that we apparently must worry about not just storage but also whatever weather conditions that cause extreme inertial frequency fluctuations that can lead to blackouts like in Spain.
My ultimate concern is that electrical planners currently base their reliability projections based on decades of experience with power plant outages that are uncorrelated. They have a good handle on the failure probabilities and how much installed reserve capacity is needed as backup. In the future the reliability requirements for wind and solar resource availability will be driven by weather that is fickler than plant shutdown variability. In addition, this variability correlates over large areas so many of the wind and solar resources will behave the same.
In my opinion, the likelihood of exceeding the planning parameters is much greater for a weather dependent electric system than today’s grid. When everybody and everything possible is electrified, and the resource drought planning criteria are exceeded, the results will be catastrophic.
Conclusion
Pielke concludes:
A main reason why the IPCC has not achieved detection of trends in most measures of extreme weather events, and does not expect to this century, is the magnitude of expected trends — based on model projections — in the context of documented variability.
This does not mean that humans are not influencing the climate system or extreme events, or that such influences are not important. It certainly does not mean that we should forget about mitigation and adaptation policies.
What it does mean is that the climate is more variable than many appreciate. A quest to identify trends and ascribe causality to them should not obscure the fact that whatever role humans play in altering the climate, society needs to be robust to a much wider range of possibilities than we’ve observed.
Weather-dependent resources add reliability risks. There has been insufficient consideration of this risk and Pielke’s work indicates that there will be a wider range of possibilities than what we can estimate using available data. This is another reason that we need to pause the Climate Act implementation process. It appears that if you want to decarbonize safely then nuclear power is the way to go because it removes these risks.
Pragmatic Environmentalist of New York 