April 2022
Climate Change Policy Should Be About Cooperation and Communication; Not Compliance, Concession, and Submission
Michael R. Arndt¹
Dr. Soon nails it. If the data doesn't fit then manipulate or exclude data to fit the narrative.
www.youtube.com/watch?v=4JJ3yeiNjf4Unbelievable! The head of the EPA in this video has no clue as to what percentage of the atmosphere is made up of CO2. We don't need figureheads shaping policy based on "we have more than 400 parts per million (ppmv) of CO2 in the atmosphere" when they don't even understand what that means other than they've been told that "it's bad"! These are the same people trying to tax you and claim climate extremism and establish climate policies. This is why we have no reasonable, well thought out climate policy because a bunch of bureaucratic puppets are doing what they are told. They are simply pawns that are doing what others tell them without questioning, and have no clue about atmospheric sciences and the complex relationships between the atmosphere, earth and oceans. They blindly accept whatever they are told and are adamant about it while not really understanding any of it.
We need bureaucrats that question and understand the complexity of the climate system and a policy that is created by those that have an intimate knowledge of climate and paleoclimates, weather, geology, paleontology and many other disciplines required to understand and implement a comprehensive climate policy and NO, that’s not John Kerry or Al Gore or the figurehead in this video! We need a reasonable, responsible, targeted, vulnerability-focused, well crafted climate policy.
Dr. Karl Svozil [1] and I can't get the local media to print any of our articles or even acknowledge any of the points we make when submitting articles for print. We can't even get a preprint approved through
arxiv.org moderators for publication even though they have approved more than 100 other previously submitted papers by Dr. Svozil on quantum mechanics, theoretical physics, computer science, and mathematics. Regarding climate change, if it's not promoting anthropogenic warming alarmism, they don't want to hear it or even acknowledge it.
‘Google and YouTube will soon prohibit advertisements on content that “contradicts well-established scientific consensus around the existence and causes of climate change,” Google announced Thursday. The decision will prevent the creators of such content from earning ad revenue from Google.’ [2]
As far as they are concerned the science is settled. They will not even allow a discussion on how to address climate issues here or abroad. It’s extremely frustrating. They don't want cooperation and communication of ideas; they want compliance and eventually they want concession. They don't want a discussion; they want submission!
Science is questioning, science is continuous learning, and science is always changing.
Science isn't settled because there is a consensus. Consensus is nothing more than the nonexistence of reliable, complete, and conclusive science. Consensus doesn't imply truth; on the contrary, consensus implies doubt. Consensus is tentative, uncertain hyperbole. Science doesn't need consensus, science stands on its own.
Science isn't settled because of climate models.
‘Global Climate Models are trying to predict an uncertainty, the future climate, while having numerous uncertainties themselves... Numerous uncertainties, including a vast amount of climate sensitivity and feedback uncertainty, are propagated in climate models ultimately casting doubts on specificity, accuracy, reliability, and credibility of climate projection outputs... Global Climate Models will never be perfect or even near perfect but they are tools that, in my opinion, will eventually be reliable enough to guide, not dictate, future global interest decisions regarding climate change.’ [3]
Smith [4] states…
‘The perfect model scenario is a useful but misleading fiction. And there is no simple stochastic fix. This does not imply that increasing resolution, improving parameterizations, introducing stochastic physics, and the like, will not significantly improve our current models but it does suggest that careful thought is required in quantifying exactly what we mean by ‘‘improve.’’ ’
Unfortunately, much of the message of climate change by the scientific community and media that is conveyed to the public tends to ignore these model deficiencies, and by deficiencies I mean the extreme difficulty of modeling the climate not the lack of scientific endeavor to do it, and characterize the model outputs as unquestionably accurate, reliable, and trustworthy representations of future climate states.
We need to realize the non-linear, chaotic aspects of climate components and understand the complexities and uncertainties of the future climate and not succumb to obsessive hypothetical conjecture based on the most extreme climate state scenarios. We have knowledge, we have ideas, we have data, we have imagination, and we have logic.
We understand climate models including atmospheric (AGCM), ocean (OGCM), coupled atmospheric/ocean (AOGCM), Regional Climate Models (RCMs), and many other types of models and sub models.
We understand spacial scales and downscaling methods.
We understand hind-casting merely allows a model to fit to the past and provides no assurances that it will also fit to the future.
We understand climate oscillations and the difficulty modeling them.
We understand paleoclimatology, including paleoclimate cycles and we acknowledge and subscribe to paleoclimate analogs with a variety of established, recognized, accepted and published paleoclimate proxy data.
We understand surface and atmospheric observations and instrumentation, tropospheric and stratospheric composition and the physical and chemical processes of the atmosphere.
We understand the parametric and structural uncertainties in climate modeling.
We understand the Laws of Thermodynamics.
We understand the conservation of energy and mass over multi-decadal and centennial time scales.
We understand continuum assumption fluid mechanics.
We understand horizontal (advection) and vertical (convection) transport.
We understand stochastic and deterministic analysis, complex multivariate distributions, Bayesian processes and relative entropy (KL-divergence), and other processes and analysis methods for climate modeling.
We understand that many exclusions, parameterizations, simplifications, and assumptions are applied while creating climate models.
We understand and acknowledge that the mathematical and numerical analysis required to discretize and solve the complicated and recurrent nonlinear partial differential equations required for climate models are not always consistent, complete, appropriate, or true. Significant physical processes are only partially or implicitly resolved or may remain completely unresolved leading to additional parameterizations.
We understand model simulations, ensembles, and multi-model ensembles.
We understand spurious numerical oscillations in spectral and nonspectral models.
We understand Lagrangian, semi-Lagrangian, Eulerian and related methods for horizontal transport.
We understand stationarity and non-stationarity in climate modeling.
We acknowledge and understand climate sensitivity uncertainty and realistic risk assessment and mitigation.
Most of all, considering what we don't know, we understand that surprisingly unexpected and conflicting results are also likely to happen with any forcing, including anthropogenic forcing.
What we don't understand is why we don't have an AUDIENCE that wants to hear anything other than fossil fuels are destroying the earth at an alarming rate if we don't act now. Why are we being shunned by not only the media but the research community as well? We present well documented empirical data/methods and established, recognized, accepted and published paleoclimate proxy data. We don't rely solely on experimental climate models, but do acknowledge their incredible complexity and usefulness. Models are a tool, not the end all and be all, i.e. ‘All models are wrong, but some are useful’ [5] by a British statistician named George Box. We acknowledge but don't rely or base decisions on attribution climate science, especially event attribution, which is mainly used for public alarmism, making climate policy decisions and litigation (litigation was the reason it was developed). Nobody wants to discuss the data or the science because under the auspices of consensus, the science is settled. In fact, the data has become irrelevant. ‘Climate alarmism has become a pseudo-religious cult with political relevance’ [1]. It's no longer just the science. Chaos theory, nonlinearity, complexity, parametric and structural uncertainty have been replaced with non-chaotic, linear, simplified, unmitigated certainty. It's absurd! More importantly, it has become what is happening now due to CO2 emissions is somehow worse than all paleoclimate analogs and what will happen in the future is not in doubt, it's certain! The data, come hell or high water, must subscribe to that outcome. We will continue to voice our concerns based on facts and science, not partial truths, conjecture, and hyperbole. We will not be silenced, we will not comply, we will not concede, and we will certainly not submit!
Michael R. Arndt, DOD U.S. Army Atmospheric Sciences Laboratory, NOAA-NWS (retired)
¹Michael R. Arndt is a former meteorologist/atmospheric scientist specializing in middle and upper atmospheric research, atmospheric profiling, paleoclimatology, applied meteorology and climatology, operational meteorological project support, meteorological and climatological data analysis, and operational, environmental and other types of weather forecasting with applied field experience in all phases of meteorological functions and atmospheric observation and instrumentation.
[1] Dr. Karl Svozil is a renowned expert in theoretical and quantum physics, recursion theory, algorithm
information theory and mathematics.
tph.tuwien.ac.at/~svozil/[2] Tori B Powell, CBS News, October 8, 2021. Retrieved from
www.cbsnews.com/news/climate-change-youtube-google-monetization-advertisements/[3] Arndt, M. R. (2018). Global Climate Models: Exploring the Reliability, Consistency, Limitations,
Deficiencies, Uncertainties, and Methods of Global Climate Models in a Nonlinear and Chaotic Climate System. Retrieved from
www.semanticscholar.org/paper/Global-Climate-Models-Exploring-the-Reliability%2C-of-Arndt/37586e383506467731b62aa49d5ae76075f5bbdc[4] Smith, L.A., 2002. What might we learn from climate forecasts?
Proceedings of the National Academy of Sciences of the United States of America, 99(suppl 1), 2487–2492. DOI:10.1073/pnas.012580599
Retrieved from
www.pnas.org/content/pnas/99/suppl_1/2487.full.pdf[5] Box, George E. P. (1976), "Science and statistics" (PDF), Journal of the American Statistical
Association, 71 (356): 791–799, doi:
10.1080/01621459.1976.10480949Dr. Karl Svozil books:
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link.springer.com/book/10.1007%2F978-3-319-70815-7•
www.amazon.com/exec/obidos/ASIN/981020809XMichael Arndt recent papers, blogs, and articles:
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climate.metman1.com/attachments/BLOG-Climate-Hyperbole-Shouldn%E2%80%99t-Supersede-Climate-Policy-that-is-Responsible-and-Sensible.pdf•
www.semanticscholar.org/paper/Global-Climate-Models-Exploring-the-Reliability%2C-of-Arndt/37586e383506467731b62aa49d5ae76075f5bbdc•
www.climate.metman1.com/attachments/Global-Climate-Change-A-Recent-Paleoclimatological-Perspective.pdf• Website:
www.climate.metman1.com/
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