predicting future climates- lqc 15 Flashcards

1
Q

extrapolation

A

An inference about the future based on known facts and observations. Example: to extend the line on a graph following the previous trend of data.

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2
Q

What does extrapolation enable scientists to do and what are they assuming?

A

Make predictions about a future course of events i.e. climate change
1. there is enough data to establish the trend accurately
2. present trends continue

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3
Q

what are the limitations of extrapolation

A

The prediction will only be ‘accurate’ if there is no change in the ‘system’. For example, steps could be taken to reduce CO2 emissions or an increase in living standards in developing parts of the world might cause CO2 levels to rise.
Models are not expected to predict the future precisely, but to make the best prediction based on all the evidence available.

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4
Q

why is modelling climate change difficult

A

Carbon dioxide only plays a part in climate change. Many factors are involved.
If one is missed out then the accuracy of the prediction is decreased. One must also take into account the interactions between the factors as well – does one increase when another decreases?

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5
Q

what are the other factors that may affect climate change

A

Other greenhouse gases (methane, CFCs & N2O), aerosols, the degree of reflection from parts of the earth free from ice and snow, the fraction of the earth covered with ice and snow, the extent of cloud cover, changes in the sun’s radiation.

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6
Q

why might predictions of climate change be incorrect

A

Limited data, limited knowledge of how the climate system works, limitations in computing resources, failure to include all factors affecting the climate, changing trends in included factors i.e. faster than expected loss of snow and ice or greater CO2 emissions.

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7
Q

how are the models continually improving

A

Use of bigger data sets, incorporating more factors, considering more sophisticated interactions between the factors.
Testing the computer models:- taking data from past years, feeding that into the models and seeing if the predictions match what actually happened.
By comparing the outcomes with other outcomes from other models and comparing them with actual observations increases the scientific community confidence in the predictions.

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