02_2 Earth Systems Forcings
Unifying Theories
Definition of a theory:
A hypothesis that has survived repeated testing and has been modified as needed
Confirmed by extensive observations by numerous scientists
Still a “living” statement and can be slightly modified over time
Examples of unifying theories mentioned:
Evolution
Quantum Chemistry
Earth Systems
Plate Tectonics
The dynamic climate system
Climate is a complex, dynamic system with many interacting parts
Figure 1.1 (Mathez, 2009) emphasizes that Earth’s climate is complicated
Implication: understanding climate requires looking at how components interact, not just isolated parts
Systems science: foundational definitions
System: a group of components that interact with each other
Component: objects, groups of objects (a subsystem), or measurable quantities like temperature or pressure
Implication: studying subsystems helps understand the whole, and subsystems can be analyzed individually or in combination
Digestive System (example of a system in the body)
Questions to frame system study:
What are some of the components?
How would you diagnose a problem?
Example components listed:
Liver, Colon, Finger, Gallbladder, Tongue, Esophagus, Stomach, Pancreas, Small Intestine
Source link: http://www.strangebuttrewe.com/knitGl.htm
Subsystems of the human body
Each subsystem is a component of the body
Subsystems can be studied separately or together with other parts of the body
Other subsystems mentioned:
Nervous
Cardiovascular
Digestive
Muscular
Skeletal
Respiratory
Integumentary (Skin, hair, nails)
Earth Systems Theory (introductory framework)
The climate system can be split into subsystems: Gases, Water (includes Cryosphere), Solid Earth, All living things (biosphere: plants, animals, humans, microorganisms, etc.)
Cryosphere is a subsystem of the Hydrosphere and refers to ice
Subsystems interact with each other, leading to feedbacks and responses in the climate
Subsystems listed: Lithosphere, Biosphere, Hydrosphere, Cryosphere, Atmosphere
Source for Cryosphere: https://newsela.com/read/natgeo-lithosphere/id/44339/
Interactions among subsystems and expertise
Subsystems interact with each other, producing feedbacks and responses in climate
Different scientists specialize in different subsystems (analogous to medical specialists):
Geochemist (air chemistry changes like smog)
Glaciologist (ice thickness changes)
Paleontologist (fossil species through geologic time)
Analogy: like neurologist, cardiologist in medicine
Summary of Earth Systems Theory
The climate system can be split into subsystems
Each subsystem or component can be studied separately
Interactions between subsystems lead to past or future climate changes
Subsystems include Lithosphere, Biosphere, Hydrosphere, Cryosphere, Atmosphere
Forcings and Feedbacks in the climate system
How we frame climate interactions:
Forcing: Any process or disturbance that drives a change
Feedback: A process that alters changes underway in the climate
Positive feedback: amplifies or enhances change
Negative feedback: reduces or moderates change
Climate Forcing (examples)
Forcing is any process that drives change; examples across subsystems:
Lithosphere: changes in plate tectonic motion
Biosphere: changes in Earth’s orbit
Hydrosphere: changes in strength of the Sun
Cryosphere: changes in human behavior
Atmosphere: other forcings (e.g., emissions, aerosols)
Framing note: forcings initiate changes that propagate through interactions among subsystems
Feedback: how the climate responds
Forcing acts as the initial driver; feedbacks are the system’s responses
Positive feedback examples: amplification of the initial change
Negative feedback examples: moderation or dampening of the initial change
Visualization elements referenced as Fig A (positive) and Fig B (negative)
Feedback loops: examples
Grassland-forestry vegetation feedback (illustrative loop)
Grassland converts to forest, leading to changes in transpiration and precipitation
Forest increases transpiration and precipitation, reinforcing forest cover
Diagrammatic sequence (summary): Grassland → Forest replacement → Increased transpiration → Increased precipitation → More forest growth
Purpose: to illustrate how vegetation can create feedbacks with climate variables
Pancreas and blood sugar: a feedback loop example
Pancreas feedback loop (biological example):
Insulin released → Blood sugar lowered
Glucagon released → Blood sugar increased
Body detects blood sugar too low → triggers responses
Question raised: Is this loop best described as negative or positive feedback?
Source: https://commons.wikimedia.org/wiki/File:Negative%20Feedback%20Gif.gif
Note: The slide prompts debate on loop interpretation and whether this is the only way to draw the loop
Climate feedbacks in more detail
Forcings lead to feedbacks in the climate system across all subsystems: Lithosphere, Biosphere, Hydrosphere, Cryosphere, Atmosphere
Changes can occur in:
Human behavior
Plate tectonic motion
Strength of the Sun
Earth’s orbit
Other factors
Feedbacks result in changes to:
Chemistry of the atmosphere or oceans
Ice cover
Temperature
Precipitation
Species and ecosystems
Other factors
Timescales of climate changes (examples of slow vs fast changes)
Plate tectonics: slow changes, typically in the millions to tens of millions of years
Expressed as:
Atmospheric chemistry: fast changes, year-to-year timescales
Expressed as:
Emphasizes that different subsystems operate on very different timescales
Activity prompt example (for students)
Task: Write down an example of a positive or negative feedback (using scientific definitions, not social definitions) from your own life
Steps:
Choose one example from your group
Try drawing a feedback loop diagram for this example
Educational purpose: practice identifying forcing and feedback structures in real-world contexts
Cause and Effect: building hypotheses
To create a hypothesis, explain how two observations are related
Definitions:
Cause: the producer of a result or consequence
Effect: the result or consequence
Cause and Effect in practice
Bacteria / Cadaveric matter as cause; Sepsis / Childbed fever as effect
Counterpoint: in climate science, relationships are rarely this straightforward
Example: insomnia with multiple potential causes
Anxiety for tests
Staying up later
Drinking tea with caffeine at night
Could be all, none, or some of these
Diagrams:
Several pages present different orderings of these factors to illustrate how cause and effect can be ambiguous
Cause or Effect? graphic differentiation
Example orders shown to illustrate that cause/effect can be arranged differently in a diagram:
Staying up late, caffeine, anxiety, insomnia
Anxiety, caffeine, staying up late, insomnia
Anxiety, staying up late, insomnia, caffeine
Concept: Causality is not always obvious from a single diagram; the forcing may precede the effect, but feedbacks can complicate the sequence
On page 27: The idea that the “Forcing” is what happens first and the “Feedback” is the loop that results in the ongoing change
Causation vs Correlation
Correlation: two things may be related but one does not necessarily cause the other
Important caution: correlation does not imply causation
Observed correlation examples:
Positive correlation: both variables increase or decrease together
Negative correlation: one variable increases while the other decreases
Example link for spurious correlations: https://www.tylervigen.com/spurious-correlations
Global temperature vs pirates (illustrative plot)
A humorous example demonstrating correlation does not imply causation
Cartoon data shows a correlation between global average temperature and number of pirates, highlighting spurious relationships
Source: joke figure (reference to Flying Spaghetti Monster Wikipedia)
Causation or Correlation in climate science: methodological approach
How to determine relationships between many variables:
Look at data and observed trends
Build models (hypotheses) based on current scientific understanding
Use models to make predictions and test them against new data
Example focus: predicted changes in global temperature for the year 2100
Climate Models: applying Earth Systems Theory
Approach: models incorporate forcings to create changes; outputs include feedbacks
Subsystems are modeled and linked to form complex models
Subsystems included: Lithosphere, Biosphere, Hydrosphere, Cryosphere, Atmosphere
Forcings and feedbacks operate within and across these subsystems
Examples of forcing-driven changes:
Human behavior
Plate tectonic motion
Strength of the Sun
Earth’s orbit
Other factors
Climate model architecture (examples)
Models simulate interactions among atmosphere and ocean subsystems using grids:
Horizontal grid (spatial resolution)
Vertical grid (height or pressure)
Physical processes represented include:
Atmosphere dynamics
Ocean currents and heat transport
Sea ice and open ocean interactions
Land surface and hydrology
Example models and tools mentioned: -GENIE (Grid Enabled Integrated Earth system model) –
Hydrosphere, biosphere, atmosphere, lithosphere coupling
Website: www.genie.ac.uk
Core takeaways and implications
The climate system is a network of interacting subsystems; understanding requires looking at both individual components and their couplings
Forcings initiate changes; feedbacks determine the magnitude and direction of the response
Positive feedbacks can amplify changes, potentially leading to tipping points, while negative feedbacks can stabilize the system
Timescales vary widely across subsystems, from fast atmospheric chemistry to slow tectonic processes
Distinguishing causation from correlation is crucial in climate science; models and data are used to test hypotheses
Climate models integrate multiple subsystems and processes to simulate past, present, and future climate states; they rely on forcings, feedbacks, and observed data to validate predictions
Key references and links mentioned
Digestive system component image: http://www.strangebuttrewe.com/knitGl.htm
Negative/positive feedback GIF: https://commons.wikimedia.org/wiki/File:NegativeFeedbackGif.gif
Lithosphere/NatGeo lithosphere article: https://newsela.com/read/natgeo-lithosphere/id/44339/
Spurious correlations: https://www.tylervigen.com/spurious-correlations
GENIE model: www.genie.ac.uk