Intro to Climate Modeling

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Intro to Climate Modeling
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Climate Model Types

• Box Model ecosystems/studies of ocean
  circulation
• Zero-dimensional effect of changes in solar
  output without addressing temperature
  distribution on earth
• Radiative-determine effects of varying greenhouse
  gas concentrations
• Higher dimension expanded from zero to account
  for temperature distribution on earth

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Basic Concepts to Cover

• GCM
• Resolution (Horizontal, Vertical)
• Ocean Coupling
• Time-Step
• Parameterization
• Ensemble

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What is a GCM?

• Global Climate Model
• Rather than a simple model of the climate system,
  a GCM tries to account for nearly everything.
  (Brainstorm what features this might mean)
• Radiation in/out, gases, precipitation, cloud
  cover, vegetation, ocean, snow/ice cover

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Factors in a GCM
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Resolution

• Resolution is how finely your model runs. It
  describes how big your boxes of air and water
  are, both horizontally and vertically.
• Analogy Think of resolution on a TV or computer
  monitor.
• What do you suppose is the resolution of a
  typical GCM?

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Resolution ctd.
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Ocean Coupling

• The climate is not just about the air. The
  atmosphere passes material and energy back and
  forth between it and the ocean.
• Therefore, the GCM is often coupled to an ocean
  model with its own resolution and equations.
• Usu. run the air calculations, then run the water
  calculations, then the air calculations, etc.

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Ocean Coupling Visual
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Time-Step

• Time-step is like the resolution of your modeled
  time.
• If you want to model every second of the weather,
  its going to take the computer way too long.
• Typical time-step is on the order of a day.

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Parameterization

• Problem You need clouds in a model of the
  weather, but CLOUDS ARE NOT AS BIG AS YOUR GRID
  BOX.
• Thats why the model uses parameterization.
• Mathematically treating a box as 50 cloudy
  without specifying exactly where the clouds might
  be.

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Ensemble

• Ensemble just means a large set of trials.
• Often, climatologists run those trials with
  slightly different starting conditions.
• Small changes at the start can lead to big
  changes by the end. (See The Butterfly Effect,
  described here http//www.realclimate.org/index.p
  hp/archives/2005/11/chaos-and-climate/ )
• But if most of your ensemble ends up predicting
  warmer temperatures