A critical assessment of the Science of climate change
This is a personal assessment of the question of the imminent danger of climate change and the indicted responsible parties—human beings and animals in general. This post was curated using AI.
Concerns about the models on climate change
The general narrative about “climate change” is well summarized here:
The strongest claim made by climatologists regarding climate change is that human activities, particularly the burning of fossil fuels, are the primary drivers of the observed increase in global temperatures. This claim is supported by extensive scientific research and consensus within the scientific community.
The Intergovernmental Panel on Climate Change (IPCC), which is a leading international body for assessing climate change, has stated that it is highly likely that more than half of the observed increase in global average surface temperature since the mid-20th century is due to human influence. This human influence primarily stems from the emission of greenhouse gases, such as carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O), into the atmosphere.
While there is a strong correlation between rising global temperatures and increasing levels of CO2 emissions, it is important to note that causality works both ways. The burning of fossil fuels releases CO2 into the atmosphere, contributing to the greenhouse effect and global warming. On the other hand, rising temperatures can also lead to feedback mechanisms that release additional CO2 into the atmosphere, such as the melting of permafrost or the reduced capacity of oceans to absorb CO2.
Therefore, the relationship between temperature and CO2 emissions is intertwined and complex. While the link between human activities, including CO2 emissions, and global warming is well-established, the specific details of the interactions and feedback between temperature and emissions require ongoing scientific investigation and modeling.
At least, this is the AI response to my question. And by the way, it is really scary that AI keeps repeating the same doctrine without admitting any contradiction [6].
Implications of no sufficient knowledge in transdisciplinary science
Climate change is a pressing global issue that demands thorough examination and analysis. In this post, we delve into the methods used and conclusions drawn regarding the attribution of the alarming temperature increase to human and animal activities. While the consensus among the scientific community overwhelmingly supports the role of human-induced factors in climate change, it is crucial to critically assess the arguments presented. Through a careful evaluation of the evidence, we aim to identify any weak points in the reasoning that may challenge the notion of human and animal responsibility for the observed temperature rise. By engaging in this analysis, we strive to foster a nuanced understanding of the complex dynamics driving climate change and encourage an informed dialogue on the topic.
The Social, Economic, and Civilizational Impact of the Climate Change Urgency Amid Uncertain Scientific Arguments
Climate change urgency, driven by the potential consequences of rising global temperatures, has sparked considerable debate and concern across the globe. While scientists have put forth arguments linking human activity to the observed changes, it is important to acknowledge the ongoing uncertainties and limitations in our understanding of this complex phenomenon. In light of these uncertainties, it is essential to examine the potential social, economic, and civilizational impacts that could arise if scientists encounter a precipitous loss of confidence in their arguments. This post explores the multifaceted ramifications of climate change urgency in a scenario where scientific arguments become more fragile, aiming to shed light on the possible consequences that could be faced by societies, economies, and civilizations in the absence of robust scientific consensus. By considering the potential implications, we can better grasp the significance of scientific argumentation in shaping policies and actions to mitigate and adapt to the challenges posed by climate change.
One of the concerns that emerges in the absence of strong scientific arguments is the potential for excessive restrictions imposed on citizens. As policymakers strive to address the urgency of climate change, there is a possibility that stringent regulations and limitations may be imposed on individuals and communities. Citizens may face restrictions on various aspects of their lives, including their travel options, energy consumption, and even dietary choices. Such restrictions, if not carefully balanced, could potentially infringe upon personal freedoms and impact societal dynamics.
Additionally, the emergence of uncertain scientific arguments could lead to the implementation of increased CO2 fees and a new branch of CO2 finances. Governments and regulatory bodies might introduce higher taxes or fees on carbon emissions, aiming to curb greenhouse gas emissions. While the intention behind such measures is to encourage sustainable practices, the economic implications should be carefully considered. Increased fees on CO2 emissions could impact businesses, particularly small and medium-sized enterprises, and lead to potential job losses and economic instability.
Another concern is the potential reevaluation of land ownership and usage. With climate change becoming an urgent issue, arguments may arise suggesting that certain lands should be treated as common resources and managed by the state or international organizations to ensure responsible land use and conservation. This could lead to changes in land ownership rights and affect individuals’ ability to possess and utilize land for various purposes, including agriculture, housing, and development. Such shifts in land ownership dynamics could have far-reaching social and economic consequences, impacting livelihoods and traditional practices.
Furthermore, the uncertainties surrounding scientific arguments might undermine public trust in climate change initiatives and policies. A lack of confidence in the scientific basis could result in skepticism and resistance from certain segments of society, hindering collective action and impeding progress in addressing the climate crisis. Building consensus and fostering trust among the public becomes even more crucial in the absence of indisputable scientific evidence.
It is essential to recognize these concerns and engage in open and inclusive discussions that involve scientists, policymakers, citizens, and various stakeholders. By promoting transparency, robust scientific research, and an understanding of the potential consequences, societies can navigate the challenges of climate change urgency (if there is one at all!) in a manner that ensures a balanced and sustainable future for all.
In conclusion: should we head to a New Renaissance?
As you, reader, may have noticed, the actual view of this science is dangerous. And we humans—we can think otherwise—be faithful to us, humans. I remember Vladimir Vernadsky, a prominent Soviet and Ukrainian scientist who made significant contributions to several scientific disciplines, including biogeochemistry, geochemistry, and the concept of the biosphere. His ideas about the biosphere and the interconnectedness of life on Earth have had a lasting impact on ecological and environmental thinking. It’s worth noting that Vernadsky’s work laid the foundation for understanding the Earth as a complex system and the influence of human activities on global processes. And this leads to our actual point of view, which coincides with the one advocated by Vladimir Vernadsky’s concept of the biosphere, emphasizing the integral role of humans as part of the Earth’s interconnected systems, rather than viewing them as separate or intruding entities, the kind of mammals in excess on Earth, preferably under strict birth control or extinction. He recognized that human activities are intertwined with natural processes and that humans can significantly influence the environment. Vernadsky’s perspective highlighted the importance of understanding human interactions within the biosphere and promoting sustainable practices that harmonize with natural systems rather than seeking to eradicate or exclude humans from the equation. His ideas laid the groundwork for recognizing the interdependence of human society and the natural world, which is relevant to discussions on climate change and environmental stewardship today. We need a human revolution. And as I was kindly helped with AI tools to write this text, why shouldn’t we humans, leveraged by the AI revolution, embark on a truly new direction worth living in?
REFERENCES:
[1] Larsson, R., & Persson, E. (2018). What is the link between temperature, carbon dioxide, and methane? A multivariate Granger causality analysis based on ice core data from Dome C in Antarctica. Theoretical and Applied Climatology, 131(1–2), 457–468.
[2] Kivimäki, E., & Kumpula, T. (2021). Atmospheric Temperature and CO2: Hen-or-Egg Causality? Atmosphere, 12(2), 1–14. https://doi.org/10.3390/atmos12020157
[3] https://towardsdatascience.com/time-series-analysis-and-climate-change-7bb4371021e
[5] Critics of the method:
The method based on the information flow concept, like any statistical technique used to investigate causal relationships, can raise several doubts and concerns when interpreting its results. Here are some potential concerns that researchers and users of this method should be aware of:
- Correlation vs. Causation: Establishing a statistical relationship between two variables does not necessarily imply causation. Even if the information flow analysis suggests a causal direction between global radiative forcing and global mean surface temperature anomalies, it does not prove a direct cause-and-effect relationship. Other factors and variables may be influencing the observed relationship.
- Directionality: The information flow concept assumes a unidirectional or directional flow of information from one variable to another. However, in complex systems like climate dynamics, there can be feedback loops and bidirectional relationships that are not adequately captured by simple directional analysis. It’s important to consider the possibility of feedback mechanisms and indirect effects that may impact the observed causal relationships.
- Data Limitations: The quality, reliability, and availability of data used for the analysis can affect the results. Data gaps, measurement errors, or uncertainties in the collected data may introduce biases or limitations in the conclusions drawn from the analysis. Researchers need to ensure the accuracy and representativeness of the data to minimize potential biases.
- Model Assumptions: The information flow analysis relies on certain assumptions and models to estimate the information transfer between variables. These assumptions may simplify or overlook certain aspects of the underlying system dynamics. Researchers should carefully evaluate the appropriateness of the chosen assumptions and models for the specific analysis and consider potential limitations associated with them.
- External Factors: The analysis may not account for all relevant external factors or confounding variables that can influence the relationship between radiative forcing and temperature anomalies. The climate is influenced by a wide range of natural and anthropogenic factors, and omitting or inadequately addressing these factors in the analysis can lead to incomplete or misleading conclusions.
- Time Lag: The information flow analysis may not capture the time delays or lags between the cause and effect in the system. There can be a temporal mismatch between the radiative forcing and temperature anomalies, and the analysis may not capture the full extent of these delays. This can affect the interpretation of the causal relationship and the timing of its effects.
- Contextual Understanding: While the information flow analysis provides insights into the statistical relationship between variables, it may lack the contextual understanding and domain knowledge necessary to fully explain the underlying mechanisms. It is important to complement the statistical analysis with a comprehensive understanding of the physical processes and dynamics governing climate change to avoid misinterpretation or oversimplification of the results.
To mitigate these concerns, it is crucial to adopt a cautious and comprehensive approach when interpreting the results obtained from the method based on the information flow concept. Researchers should consider these limitations, conduct robust sensitivity analyses, and corroborate the findings with other evidence and complementary methods to ensure a more accurate understanding of the causal relationships under investigation.
[6] And to my great surprise, during the period of writing and questioning AI tools, I surprisingly found AI sympathetic to me…
Originally published at http://science2be.wordpress.com on July 11, 2023.
