Junk Science Week: Climate models fail reality test | FP Comment | Financial Post
I have read about random walks before but I did not realize that the HadCRU data is a near perfect random walk with a Hurst Exponent only slightly showing a small regression to the mean. (0.475 compared to a perfect 0500)
Just how good are climate models at predicting regional patterns of climate change? I had occasion to survey this literature as part of a recently completed research project on the subject. The simple summary is that, with few exceptions, climate models not only fail to do better than random numbers, in some cases they are actually worse.
There are two reasons why this is important. First, it tells us something about our lack of understanding of the climate. There are various different theories to explain the rising trend in the global average temperature over the past century. Climate models embed one such theory, based on a relatively high sensitivity to greenhouse gases and strong amplifying effects from a positive water-vapour feedback, and relative insensitivity to other things. In this setup, the only way to get a climate model to mimic the 20th-century average warming is to feed in the observed increase in greenhouse gases. Therefore, the argument goes, greenhouse gases are to blame.
A 2011 study in the Journal of Forecasting took the same data set and compared model predictions against a random walk alternative, consisting simply of using the last periods value in each location as the forecast for the next periods value in that location. The test measures the sum of errors relative to the random walk. A perfect model gets a score of zero, meaning it made no errors. A model that does no better than a random walk gets a score of 1. A model receiving a score above 1 did worse than uninformed guesses. Simple statistical forecast models that have no climatology or physics in them typically got scores between 0.8 and 1, indicating slight improvements on the random walk, though in some cases their scores went as high as 1.8.
The climate models, by contrast, got scores ranging from 2.4 to 3.7, indicating a total failure to provide valid forecast information at the regional level, even on long time scales. The authors commented: This implies that the current [climate] models are ill-suited to localized decadal predictions, even though they are used as inputs for policymaking.
I have read about random walks before but I did not realize that the HadCRU data is a near perfect random walk with a Hurst Exponent only slightly showing a small regression to the mean. (0.475 compared to a perfect 0500)