Validity of climate change forecasting for public policy decision making
Date
2009
Authors
Green, K.C.
Armstrong, J.S.
Soon, W.
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Journal article
Citation
International Journal of Forecasting, 2009; 25(4):826-832
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Abstract
Policymakers need to know whether prediction is possible and, if so, whether any proposed forecasting method will provide forecasts that are substantially more accurate than those from the relevant benchmark method. An inspection of global temperature data suggests that temperature is subject to irregular variations on all relevant time scales, and that variations during the late 1900s were not unusual. In such a situation, a "no change" extrapolation is an appropriate benchmark forecasting method. We used the UK Met Office Hadley Centre's annual average thermometer data from 1850 through 2007 to examine the performance of the benchmark method. The accuracy of forecasts from the benchmark is such that even perfect forecasts would be unlikely to help policymakers. For example, mean absolute errors for the 20- and 50-year horizons were 0.18 ring operatorC and 0.24 ring operatorC respectively. We nevertheless demonstrate the use of benchmarking with the example of the Intergovernmental Panel on Climate Change's 1992 linear projection of long-term warming at a rate of 0.03 ring operatorC per year. The small sample of errors from ex ante projections at 0.03 ring operatorC per year for 1992 through 2008 was practically indistinguishable from the benchmark errors. Validation for long-term forecasting, however, requires a much longer horizon. Again using the IPCC warming rate for our demonstration, we projected the rate successively over a period analogous to that envisaged in their scenario of exponential CO2 growth-the years 1851 to 1975. The errors from the projections were more than seven times greater than the errors from the benchmark method. Relative errors were larger for longer forecast horizons. Our validation exercise illustrates the importance of determining whether it is possible to obtain forecasts that are more useful than those from a simple benchmark before making expensive policy decisions.
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Data source: Supplementary material, https://doi.org/10.1016/j.ijforecast.2009.05.011
Link to a related website: https://repository.upenn.edu/cgi/viewcontent.cgi?article=1161&context=marketing_papers, Open Access via Unpaywall
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Copyright 2009 International Institute of Forecasters