Climate Change and Chaos Theory

By Daniel Brouse
February 5, 2024

Global warming is caused by an increase in thermal energy. Atmospheric circulation together with ocean circulation is how thermal energy is redistributed throughout the world. Chaos theory offers insights into the complex, nonlinear dynamics of climate systems role in the redistribution of thermal energy. The Earth’s climate is a highly complex and dynamic system, influenced by various factors such as ocean currents, atmospheric circulation, and feedback loops.

Circulation systems of air and/or water include:
* doldrums, trade winds, horse latitudes, prevailing westerlies, polar front zone, and polar easterlies
* each hemisphere has three cells — Hadley cell, Ferrel cell and Polar cell in which air circulates through the entire depth of the troposphere
* usually each hemispheres has two jet streams — a subtropical jet stream and a polar-front jet stream
* waves, tides, currents, downwelling, upwelling move water
* there are over 24 currents — Benguela Current, California Current, Falkland Current, Labrador Current, Brazil Current, Florida Current, Gulf Stream, West Australian Current, Canary Current, Kuroshio Current, North Pacific Current, Somali Current, Antarctic Circumpolar Current, Antarctica Current, Antilles Current, Mozambique Current, North Atlantic Drift, Norwegian Current, Oyashio Current, West Wind Drift, Agulhas Current, South Equatorial Current, Humboldt or Peruvian Current, Monsoon Current
* five major ocean-wide gyres —- the North Atlantic, South Atlantic, North Pacific, South Pacific, and Indian Ocean
* thermohaline (temperature and salinity) circulation systems — Gulf Stream, Atlantic Meridional Overturning circulation (AMOC), Pacific Meridional Overturning Circulation (PMOC)
* ocean-atmosphere oscillations — La Nina / El Niño-Southern Oscillation (ENSO), Antarctic Oscillation (AAO), Arctic Oscillation (AO), Atlantic Multidecadal Oscillation (AMO),
Indian Ocean Dipole (IOD), Madden-Julian Oscillation (MJO), North Atlantic Oscillation (NAO), North Pacific Gyre Oscillation (NPGO), North Pacific Oscillation (NPO), Pacific Decadal Oscillation (PDO), Pacific-North American (PNA) Pattern

How does chaos theory explain thermal energy redistributed throughout the world?

1. Nonlinear Dynamics:
   • Chaos theory emphasizes the nonlinear dynamics of complex systems, meaning that small changes in initial conditions can lead to disproportionately large and unpredictable outcomes. In the context of climate, this nonlinearity is evident in how the redistribution of thermal energy is influenced by factors like ocean currents and atmospheric circulation, which can exhibit chaotic behavior.
2. Sensitive Dependence on Initial Conditions:
   • Chaos theory also highlights the concept of sensitive dependence on initial conditions, commonly known as the butterfly effect. In climate systems, small variations in initial conditions, such as temperature or atmospheric pressure, can lead to significant changes in the distribution of thermal energy over time.
3. Complex Feedback Loops:
   • Climate systems involve intricate feedback loops, where changes in one component can influence others. These feedback loops contribute to the complexity and unpredictability of thermal energy redistribution. Chaos theory helps us understand how these feedback mechanisms can amplify or dampen the effects of perturbations in the system.
4. Emergent Patterns:
   • Chaos theory recognizes the emergence of complex patterns from seemingly chaotic systems. In climate science, emergent patterns may include large-scale phenomena like El Niño or the Madden-Julian Oscillation, which play roles in redistributing thermal energy on a global scale.
5. Climate Variability and Change:
   • Chaos theory is particularly relevant in studying climate variability and change. While long-term trends such as global warming are discernible, the inherent chaos in the climate system introduces variability and uncertainty, making it challenging to precisely predict how thermal energy will be redistributed over shorter timescales.
6. Atmospheric Rivers and Droughts:
   • Atmospheric rivers are concentrated bands of moisture in the atmosphere, and their behavior is influenced by various atmospheric factors. Chaos theory comes into play when trying to predict the exact paths and intensities of atmospheric rivers, especially as small changes in initial conditions can lead to vastly different outcomes over time. Droughts result from complex interactions between atmospheric conditions, precipitation patterns, land use, and water management. Chaos theory highlights the sensitivity of drought conditions to initial conditions and the potential for nonlinear responses, making it difficult to precisely predict the onset, duration, and severity of drought events.

Complex Feedback Loops:

Complex feedback loops in climate science refer to interactions between different components of the Earth’s climate system that can amplify or dampen the effects of initial changes, leading to non-linear and often unpredictable outcomes. These feedback loops play a crucial role in shaping the behavior of the climate system and can influence various climate phenomena, including temperature changes, ice melt, and precipitation patterns.

Tipping points are Critical Milestones that directly impact the rate of acceleration in climate change by multiplying the number and intensity of feedback loops. Identifying and understanding these tipping points is crucial for climate science and policymaking. Crossing multiple tipping points could lead to a domino effect, resulting in a much more rapid and severe climate change than currently projected.

1. Ice-Albedo Feedback:
   • As the Earth warms, ice and snow melt, reducing the surface area covered by highly reflective materials (high albedo). This leads to a decrease in the Earth’s overall reflectivity, or albedo, as darker surfaces (like open water or bare ground) absorb more solar radiation. The increased absorption of sunlight further warms the surface, accelerating ice melt in a self-reinforcing loop.
2. Water Vapor Feedback:
   • Warmer temperatures can lead to increased evaporation of water from oceans and other bodies of water. Since water vapor is a greenhouse gas, higher atmospheric water vapor concentrations can enhance the greenhouse effect, trapping more heat and further raising temperatures. This positive feedback loop can contribute to the amplification of global warming.
3. Carbon Cycle Feedback:
   • The carbon cycle involves the exchange of carbon dioxide (CO2) between the atmosphere, oceans, and terrestrial ecosystems. As the climate warms, it can influence processes like the release of carbon from thawing permafrost or changes in vegetation. The additional release of carbon dioxide can amplify the greenhouse effect, leading to further warming and affecting the carbon cycle in a feedback loop.
4. Ocean Circulation Feedback:
   • Changes in temperature and salinity affect ocean circulation patterns. Alterations in ocean circulation can, in turn, influence heat distribution across the globe. For example, a slowdown in the Atlantic Meridional Overturning Circulation (AMOC) could impact regional climate patterns and further affect ocean circulation in a complex feedback loop.
5. Vegetation-Climate Feedback:
   • Climate changes can affect vegetation patterns, altering the amount of sunlight absorbed and the release of water vapor through transpiration. Changes in vegetation cover can influence local and regional climates, creating feedback loops that may further impact ecosystems and climate patterns.
6. Cloud Feedback:
   • Changes in temperature and atmospheric composition can affect cloud cover and properties. While clouds can both reflect sunlight and trap heat, the net effect depends on factors like cloud altitude and type. Changes in cloud cover and properties can influence the Earth’s radiation balance, creating feedback loops that can either amplify or dampen climate changes.

Chaos theory provides a framework for understanding the inherent complexity, sensitivity, and unpredictability of climate systems, including the redistribution of thermal energy. The interconnectedness of various factors and the nonlinear interactions within the Earth’s climate contribute to the intricate patterns observed in thermal energy distribution on a global scale. Climate models use principles from chaos theory to simulate these dynamic interactions.

The Earth is a climate system. Many subsystems make up our climate. Perhaps the most important factor impacting our climate is us. The biggest influence on climate change is the increase in greenhouse gas concentrations in the Earth’s atmosphere, primarily driven by human activities. The largest drivers of human induced climate change include: burning of fossil fuels, deforestation and land use, industrial processes, agriculture, waste management, and use of fluorinated gases.

Human induced climate change is an exponential component of an unordered system (chaos theory).Chaos theory plays a role in understanding the dynamics and potential unpredictability of social-ecological systems’ impact on climate change. Social-ecological systems encompass the interconnectedness of human societies and the ecosystems they are part of, and their behavior is influenced by a myriad of factors, including human activities, policies, resource use, and environmental changes. Chaos theory contributes insights into the complexity, sensitivity to initial conditions, and potential nonlinearities within these systems.

Here are several aspects in which chaos theory can be relevant to forecasting the impact of social-ecological systems on climate change:

1. Nonlinear Interactions:
   • Social-ecological systems involve nonlinear interactions between human activities and environmental responses. Small changes in policies, resource management, or societal behaviors can lead to disproportionately large and unpredictable outcomes in terms of climate change impacts.
2. Sensitivity to Initial Conditions:
   • The sensitivity of social-ecological systems to initial conditions highlights the importance of understanding how small changes or decisions can lead to significant and sometimes unexpected consequences over time. This sensitivity is crucial when forecasting the trajectory of climate change impacts resulting from human activities.
3. Feedback Loops:
   • Feedback loops within social-ecological systems can amplify or dampen the effects of interventions or changes. For example, policies to reduce greenhouse gas emissions may lead to unforeseen economic or social consequences, creating feedback loops that influence climate change impacts.
4. Emergent Properties:
   • Chaos theory recognizes emergent properties that arise from the interactions within complex systems. In the context of social-ecological systems, emergent properties may include new social norms, economic trends, or environmental patterns that affect and potentially amplify or mitigate the impacts of climate change.
5. Thresholds and Tipping Points:
   • Social-ecological systems can exhibit thresholds and tipping points, where small changes gradually accumulate until a critical point is reached, leading to abrupt and sometimes irreversible changes. Chaos theory helps to understand the potential for sudden shifts in behavior within these systems.
6. Adaptive Capacity:
   • Chaos theory encourages consideration of the adaptive capacity of social-ecological systems. The ability to adapt to changing conditions, learn from experiences, and adjust strategies is essential for forecasting and managing the impacts of climate change within these systems.
7. Uncertainty and Systemic Risks:
   • Chaos theory underscores the inherent uncertainty in complex systems. Social-ecological systems are subject to systemic risks, where interconnected factors can amplify vulnerabilities. Understanding and managing these uncertainties are crucial for forecasting and responding to climate change impacts.

Incorporating chaos theory into forecasting models for social-ecological systems helps researchers and policymakers recognize the limitations of linear thinking and deterministic approaches. Embracing complexity and uncertainty can lead to more robust and adaptive strategies for addressing the multifaceted challenges posed by climate change within the context of human societies and ecosystems.

Our model attempts to adequately account for humans and forecasts an increase of 9 degrees Celsius above pre-industrial levels.

Toppled Tipping Points: The Domino Effect Brouse and Mukherjee (2023)Tipping Cascades, Social-Ecological Systems, and the Hottest Year in History Brouse (2024)
The Reign of Violent Rain Brouse and Mukherjee (2023)
The Age of Loss and Damage Brouse (2023)
Climate Change Impacts on Flood Risks and Real Estate Values Sidd Mukherjee and Daniel Brouse (2023)