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Climate Science:
Part 3. Climate Models and
Predicted Climate Change
Pam Knox, Agricultural Climatologist,
University of Georgia
Topics you will learn about
• Review: Causes of changes in climate
• Carbon dioxide and other gases
• Methods for predicting climate
• Predicted changes in climate
Climate and Energy Balance
Climate of the Last 100 Years
Changes in Atmospheric Composition
Changes in Atmospheric Composition
Review of Climate Trends
What kinds of trends are there?
• Linear
• Exponential
• Changing variability
• Change in slope
• Step function
Atmospheric Window
The “atmospheric window” refers to the
wavelengths at which light can enter the
Earth’s atmosphere as solar radiation (rainbow
at left) or leave it as terrestrial radiation (red
bar).
As the amount of carbon dioxide, methane,
water vapor and other greenhouse gases
increases, the part of the window that lets
light energy back to space gets pinched and
energy stays in the climate system, which
causes the climate to get warmer.
How to Predict Climate
You can predict climate by predicting trends, but that depends
on things continuing the same way they have in the past. Not
always a good assumption!
Instead, climatologists use climate models to simulate the
future climate based on physics and predictions of future CO2
and other emissions.
Climate Models
Increasing Model Complexity
Global Climate Models
Global Climate Models
Problems with Models
• Coarse resolution leaves out
mountains, Great Lakes,
alters local conditions like
coastlines
• Simplification processes
make rainfall less believable
since most of it happens in
sub-gridscale processes like
thunderstorms
• They are not very good at
predicting current climate,
making them less believable
• No El Niño, hurricanes
Weather vs. Climate Models
Weather models are designed
to predict detailed hourly
weather information for up to 7
days across a continent.
Emphasis: short term,
individual storm evolution
Climate models are designed to
predict multi-year climate
conditions across the entire globe.
Emphasis: long-term, seasonal to
multi-year average climate
conditions
Models can separate out C02 effects
Models can be used to
separate out the effects of
individual factors to see
what effect each factor
has on the temperature
trend.
Scenario Modeling
Modelers use scenarios of
various projections of changing
CO2, changing energy efficiency,
etc. to produce a series of graphs
giving a range of expected
outcomes.
Observations don’t always agree with
predictions. So which is right?
Sea Ice
For sea ice, the observed decline in
sea ice cover in the Arctic is faster
than any of the models predicted.
Predictions of Future Temperature
• Temperatures will increase, day and night
• Amount of warming is not certain (5-10 F in next
100 years)
• Longer growing season
• Increased evaporation
http://www.globalchange.gov/nca3-downloads-materials (new site with
similar material has replaced original site)
Predictions for Future Precipitation
• Predictions of future rainfall are not well modeled
• Trends indicate increased rainfall intensity (more
thunderstorms) with longer dry spells in between
• Precipitation changes by season cannot be predicted
• Effects on El Niño and hurricane frequency not known
Secondary Impacts-Sea Level
Secondary Impacts-Other
Things that are Harder to Predict
Summary of Part 3
In this section we have covered:
• Changes in atmospheric composition
• Climate models
• Trends in climate
For a full list of references cited in this presentation, please visit:
www.animalagclimatechange.org
This project was supported by Agricultural and Food Research Initiative Competitive Grant
No. 2011-67003-30206 from the USDA National Institute of Food and Agriculture.

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Climate science part 3 - climate models and predicted climate change

  • 1. Climate Science: Part 3. Climate Models and Predicted Climate Change Pam Knox, Agricultural Climatologist, University of Georgia
  • 2. Topics you will learn about • Review: Causes of changes in climate • Carbon dioxide and other gases • Methods for predicting climate • Predicted changes in climate
  • 4. Climate of the Last 100 Years
  • 7. Review of Climate Trends What kinds of trends are there? • Linear • Exponential • Changing variability • Change in slope • Step function
  • 8. Atmospheric Window The “atmospheric window” refers to the wavelengths at which light can enter the Earth’s atmosphere as solar radiation (rainbow at left) or leave it as terrestrial radiation (red bar). As the amount of carbon dioxide, methane, water vapor and other greenhouse gases increases, the part of the window that lets light energy back to space gets pinched and energy stays in the climate system, which causes the climate to get warmer.
  • 9. How to Predict Climate You can predict climate by predicting trends, but that depends on things continuing the same way they have in the past. Not always a good assumption! Instead, climatologists use climate models to simulate the future climate based on physics and predictions of future CO2 and other emissions.
  • 14. Problems with Models • Coarse resolution leaves out mountains, Great Lakes, alters local conditions like coastlines • Simplification processes make rainfall less believable since most of it happens in sub-gridscale processes like thunderstorms • They are not very good at predicting current climate, making them less believable • No El Niño, hurricanes
  • 15. Weather vs. Climate Models Weather models are designed to predict detailed hourly weather information for up to 7 days across a continent. Emphasis: short term, individual storm evolution Climate models are designed to predict multi-year climate conditions across the entire globe. Emphasis: long-term, seasonal to multi-year average climate conditions
  • 16. Models can separate out C02 effects Models can be used to separate out the effects of individual factors to see what effect each factor has on the temperature trend.
  • 17. Scenario Modeling Modelers use scenarios of various projections of changing CO2, changing energy efficiency, etc. to produce a series of graphs giving a range of expected outcomes. Observations don’t always agree with predictions. So which is right?
  • 18. Sea Ice For sea ice, the observed decline in sea ice cover in the Arctic is faster than any of the models predicted.
  • 19. Predictions of Future Temperature • Temperatures will increase, day and night • Amount of warming is not certain (5-10 F in next 100 years) • Longer growing season • Increased evaporation http://www.globalchange.gov/nca3-downloads-materials (new site with similar material has replaced original site)
  • 20. Predictions for Future Precipitation • Predictions of future rainfall are not well modeled • Trends indicate increased rainfall intensity (more thunderstorms) with longer dry spells in between • Precipitation changes by season cannot be predicted • Effects on El Niño and hurricane frequency not known
  • 23. Things that are Harder to Predict
  • 24. Summary of Part 3 In this section we have covered: • Changes in atmospheric composition • Climate models • Trends in climate
  • 25. For a full list of references cited in this presentation, please visit: www.animalagclimatechange.org This project was supported by Agricultural and Food Research Initiative Competitive Grant No. 2011-67003-30206 from the USDA National Institute of Food and Agriculture.

Editor's Notes

  1. Weather and climate have had significant impacts on animal agriculture over the last 2,000 years. This module provides an introduction to the changes that have occurred and the challenges they present -- to producing a consistent and quality product for consumers. OR YOU COULD END THE SENTENCE – to maintaining a reliable food supply OR to maintaining a reliable business income.
  2. Thank you for your attention and please visit the project websites listed here for more information.