Seasonal Climate Forecasts Do Not Have Skill

http://wmbriggs.com/blog/?p=1899 ^ | William M. Briggs

[mattstat]

David Lavers is the lead author in a GRL paper “A multiple model assessment of seasonal climate forecast skill for applications.”

Lavers et al. checked eight different climate models and found that, “Results suggest there is a deficiency of skill in the forecasts beyond month-1, with precipitation having a more pronounced drop in skill than temperature.”

Nature magazine summarized:

‘Skill’ is the degree to which predictions are more accurate than simply taking the average of all past weather measurements for a comparable period.

…existing climate models show very little accuracy more than one month out. Even during the first month, predictions are markedly less accurate for the second half than the first. Current models simply cannot account for the chaotic nature of climate, researchers say.

My friend and former advisor Dan Wilks at Cornell (who wrote the most influential meteorological statistics textbook) completed a similar analysis about a decade ago and found much the same thing.

I’ve also done work on these (earlier) climate models (peer-reviewed!), too. Things have not really changed. The climate is so complicated that these models just aren’t that good.

But these seasonal models aren’t necessary the same as the global climate models that have people so flustered about Global “Don’t Call Me Climate Change” Warming. Some seasonal models are more statistical, some more physical. But they all try and guess the future, with, as we now know, limited success.

At the same time, Kevin Trenberth, an IPCCer, announces that the 2013 AR5 report will have at least one chapter “devoted to assessing the skill of climate predictions for timescales out to about 30 years.”

I’m guessing he’s using the word “skill” in a different way than is usual because...

[Paladin2]

One month out is weather, not climate. These models obviously have skill 10 to 100 years out as everyone will forget the predictions by then.