Preface
  1. Zooming through scales by the billion
  2. What is weather? What is climate?
Why they are not enough
1.2Zooming in time: the variability never stops
1.3From milliseconds to the age of the earth
An illustrated voyage through scales in time
Box:Removing annual, daily cycles
1.4Zooming in space: from the size of the planettomillimeters
See the structures within structures within structures
1.5The unfinished nonlinear revolution
Complexity, emergent laws, scales, scaling
Complexity or scaling simplicity?
Comparing geo andcosmic complexity
1.6Overview of the book
2.New worlds versus scaling: from van Leeuwenhoek to Mandelbrot and beyond
2.1 A new world in a drop of water: scale bound thinking
Antoni van Leeuwenhoek, and the “powers of ten” paradigm
2.2 Scaling: Big whirls have little whirls and little whirls have lesser whirls
Fractals and wiggliness: From PerrinandSteinhaus to Benoit Mandelbrot: the wiggliness of the coast of Brittany, the river Vistula.
Case study: The wiggliness of cloud perimeters
Case Study: Flight 101: fractal bumpiness
Case Study:Falling through unstable fractal layers
Case study: Clouds above Montreal
Fractals and sparseness
Case study: The distribution of weather stations
Case study: The distribution of rain drops
Cascades and multifractals
Case study: Zooming out from Nimes precipitation
Case study: Zooming out from aircraft temperature transects
Stochastic versus deterministic chaos
Statistics versus deterministic mechanisms
“Fractals: where’s the physics?”
2.3: Scale as an emergent property: and the phenomenological fallacy
Atmospheric stratification: What is the dimension of atmospheric motions?
Case study: Zooming into Vancouver’s smog
Case Study: Atmospheric convection: scaling or scale bound?
Case study: Numerical Weather models: 23/9 dimensional?
Is isotropic turbulence relevant in the atmosphere?
2.4Fluctuations as a microscope
What are fluctuations?
Case Study:Our Planet: An empirical overview in time: fluctuation analysis from milliseconds to hundreds of millions of years
Case Study: The missing scale bound quadrillion
Understanding the fluctuation exponent H: the H model
Case Study: An empirical overview in space from millimeters to the size of the planet
3. Weather, macroweather, climate, macroclimate and megaclimate
3.1Nothing but turbulence: the weather
Space and time: scaling or scale bound dynamics?
Case Study: Clouds over the Pacific
Turbulent laws
Case study:The wind from milliseconds to days: the Kolmogorov law
Case Study: Space-time “Stommel” diagrammes for the atmosphere and ocean
Lifetime-size relations determined by solar forcing
Case Study: The atmosphere versus the ocean
Case Study:Earthversus Mars
Box: A Martian picnic
Numerical models of the weather and climate
3.3Expect Macroweather: fluctuations decreasing with scale
Sizes and lifetimes in macroweather
Case Study: The Pause in the warming
Case Study: The post war cooling and return periods
3.4 Don’t expect the climate: fluctuations increasing (again) with scale
30 year climate “normals” and the anthropocene
Case Study: How accurately do we know the temperature of the Earth? (instrumental and multiproxies)
Solar, volcanic climate forcings are scaling
3.5The ice agesand macroclimate: scaling or cycles?
Doubling CO2 and Svante Arrhenius
Astronomical forcing and MilutinMilankovitch
Case study: The last eight ice ages
3.6Long term atmospheric instability in megaclimate
The end of Gaia
4.Extremes: Black Swans or tipping points?
4.1White, Grey and Black Swan events, the multifractal butterfly effect
Black swans versus outliers and tipping points
4.2Weather
Case Study: World record winds: Mt. Washington versus Barrow Island
Case Study:Extreme precipitation and flooding
4.3 Macroweather
Case Study:Extreme global temperature changes
Case Study: Droughts
4.4 Climate
Climate tipping pointsor black swans?
Case Study:Dansgaard-Oeschger events
5. What about us?
5.1Why the warming can’t be natural
Anthropogenic warming
Case Study: The little Ice age, the medieval warming event
Climate closure: “A mephitic ectoplasmic emanation of the forces of darkness”
5.2Giant Natural Fluctuations and Anthropogenic warming
Case Study: The $100,000 climate contest
6. Why it’s hard to predict… and how scaling can help
6.1Hours, days, a week: Weather forecasting
Texas tornadoes and Brazilian butterflies: deterministic predictability limits
Random numbers already help!
6.2Next month, next season, next year and decade: Macroweather forecasting
Stochastic predictability limits
Long range memoryand how toexploit it
Case Study: Return periods and the post war cooling
Case Study: Predicting the “Pause”
The Stochastic Seasonal and Interannual Prediction System (StocSIPS)
Case Study: An example fromStocSIPS
The future of weather and climate forecasting
6.3 What will it be like in 2050?
Projecting the climate: GCM’s versus historical projections
7. Earth, water, fire, air
7.1Scaling in the hydrosphere
Precipitation and river flows
Case Study: The Mississippi river
7.2Scalingin volcanoes
Case Study: Kilauea lava flows
Case Study: Bubbles in lava
Case Study: Temporal distribution of volcanic eruptions since 500 A.D.
7.3Scalingin the solid earth
Stratification
Multifractality
Case Study: Earthquakes