climate science part 3 - climate models and predicted climate change
TRANSCRIPT
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Climate Science:Part 3. Climate Models and Predicted Climate Change
Pam Knox, Agricultural Climatologist, University of Georgia
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Topics you will learn about
• Review: Causes of changes in climate
• Carbon dioxide and other gases
• Methods for predicting climate
• Predicted changes in climate
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Climate and Energy Balance
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Climate of the Last 100 Years
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Changes in Atmospheric Composition
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Changes in Atmospheric Composition
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Review of Climate Trends
What kinds of trends are there?
• Linear• Exponential• Changing variability• Change in slope• Step function
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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.
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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.
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Climate Models
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Increasing Model Complexity
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Global Climate Models
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Global Climate Models
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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
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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
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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.
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Scenario ModelingModelers 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?
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Sea Ice
For sea ice, the observed decline in sea ice cover in the Arctic is faster than any of the models predicted.
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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 evaporationhttp://www.globalchange.gov/nca3-downloads-materials (new site with similar material has replaced original site)
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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
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Secondary Impacts-Sea Level
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Secondary Impacts-Other
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Things that are Harder to Predict
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Summary of Part 3
In this section we have covered:
• Changes in atmospheric composition• Climate models• Trends in climate
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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.