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We can measure the appropriateness of a model by looking at the difference between the values predicted by the model and the actual values recorded in the series. This difference between these two values is called the Residual.
A model is acceptable if the residuals stay within 10% of the overall range of values in the time series.
When trying to determine if a model is appropriate, look at the residuals towards the end of the series. These have more influence on the model (and its predictions) compared to the residuals earlier in the dataset.
If the residuals look like they are increasing towards the end of the series, then this would indicate that the model is becoming less accurate and would reduce the accuracy of its predictions.
Example of Appropriateness of Model discussion - Sea Ice
Example of Appropriateness of Model discussion - Sea Ice
Overall the model seems to fit the data very well. Most of the recomposed values match up with the raw data, however there does appear to be an increase in the difference since 2008 which may increase the levels of uncertainty in the forecasts for 2011 - 2013.
This increase in residuals might indicate a temporary climate event which will need investigating further.
Written Report - (so far)
Written Report - (so far)
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