INDG 401 Lecture Notes - Lecture 3: Chaos Theory, Statistical Mechanics, Core Data
9 Jun 2018
School
Department
Course
Professor
Lecture 3 - ENVR 400
How’s the weather?
• What is the climate/environment?
• What have humans done to the environment/climate
• What can/should we do?
The climate is what you expect, weather is what you get → the prof disagrees
A voyage through scales: Space, 0.1mm-10,00km
• See all those structures and since there is wind and the wind actually has structures itself and
pushes this along
• Wind average = 10m per second → 10 day time sale
• We have real data → we can go back millions of years we have data stored in shells
• Main point is that its quite variable
• Ice core data from the south pole, Greenland → more reliable indicators
Dust fluxes from an Antartica ice core
• Analyze dust content → huge variability
o Some indicator of the state of the atmosphere (not all clear → what is clear is that there is
variability)
Instrumental temperatures
• Picture
Zooming in space
• Within the curve → enormous fluctuation → take the differene between one point and another
• Huge spikes
Which chaos?
• How does God play dice?
Stochastic or deterministic chaos?
• Wind speed data
• If you want to understand that you can make a model
• Stochastic = random
• Deterministic = rule
• They both have some similar characteristic to the real data. Whih approach is the better way to
model the data?
Cosmos versus chaos through the ages
• Chaos - Cosmos (ancient Greks)
• Scientific ideas about determinism and randomness
• Determinism: God supplies the initial conditions (ex: planets in orits, Newton, 1670s)
o “if a sufficiently vast intelligence exists”
• Chance: ignore, subjective
o “Chance is noting”
• Chance: Irrelevance of the details
o Statistical mechanics ex: the bell curve distribution of molecur velocities in a gas
• Chance: objective
o Quantum mechanics: Born interpretation of the wave function
find more resources at oneclass.com
find more resources at oneclass.com
Document Summary
The climate is what you expect, weather is what you get the prof disagrees. Ice core data from the south pole, greenland more reliable indicators. Dust fluxes from an antartica ice core: analyze dust content huge variability, some indicator of the state of the atmosphere (not all clear what is clear is that there is variability) Zooming in space: within the curve enormous fluctuation take the differene between one point and another, huge spikes. If you want to understand that you can make a model: wind speed data, stochastic = random, deterministic = rule, they both have some similar characteristic to the real data. Cosmos versus chaos through the ages: chaos - cosmos (ancient greks, scientific ideas about determinism and randomness, determinism: god supplies the initial conditions (ex: planets in orits, newton, 1670s) If a sufficiently vast intelligence exists : chance: ignore, subjective. New worlds versus scaling: from van leeuwenhoek to mandelbrot: scalebound thinking and the missing quadrillion.
