Continuation of Exercise 14.16. Suppose that you assume that \(\mathrm{CO}_{2}\) concentration is \(10 \%\) lower than your forecast from the model developed in Exercise 14.16. What impact does the decrease in predicted \(\mathrm{CO}_{2}\) have on the predicted mean surface temperature?

Data From Exercise 14.16

Consider the global mean surface temperature and \(\mathrm{CO}_{2}\) concentration from Table B.17. Suppose that you want to use the Cochrane-Orcutt model from Exercise 14.1 to predict the global mean surface temperature. To do this, you would need to develop a method of forecasting the \(\mathrm{CO}_{2}\) concentration. What model would you propose? Suppose that you use this model to predict the \(\mathrm{CO}_{2}\) concentration 10 years in the future. What is your forecast of the mean surface temperature at that point in time? Find a prediction interval for this forecast.

Data From Exercise 14.1

Table B. 17 contains data on the global mean surface air temperature anomaly and the global CO2${\mathrm{????}\mathrm{????}}_2$ concentration. Fit a regression model to these data, using the global CO2${\mathrm{????}\mathrm{????}}_2$ concentration as the predictor. Analyze the residuals from this model. Is there evidence of autocorrelation in these data? If so, use one iteration of the Cochrane-Orcutt method to estimate the parameters.

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