Von Storch Revisited

Given my personal feeling that variability is the climate change bugaboo that matters the most, I spent a lot of time thinking and asking about last year’s Science paper by Hans von Storch about variability in the paleo record. Now there’s a new paper in Journal of Climate by Mann, Rutherford, Wahl and Amman that sheds some new light on the issue.

To recap briefly, von Storch’s paper questioned whether the methodology behind the classic hockey stick climate reconstructions by Mann Bradley and Hughes understated climatic variability over the last few millennia. Von Storch did this by using a climate model to generate “pseudoproxy data”, then testing to see whether the MBH methodology would adequately capture the variability in the underlying simulated climate. In the von Storch simulation, it did not:

The centennial variability of the NH temperature is underestimated by the regression-based methods applied here, suggesting that past variations may have been at least a factor of 2 larger than indicated by empirical reconstructions.

Since variability on various spatial and temporal time scales is the thing I’m most interested in, this seemed like a pretty interesting result to me.

Mann et al., in their new Journal of Climate paper, have done precisely the same thing, but come up with a quite different answer.

Two widely used statistical approaches to reconstructing past climate histories from climate “proxy” data such as tree rings, corals, and ice cores are investigated using synthetic “pseudoproxy” data derived from a simulation of forced climate changes over the past 1200 yr. These experiments suggest that both statistical approaches should yield reliable reconstructions of the true climate history within estimated uncertainties, given estimates of the signal and noise attributes of actual proxy data networks.

So what’s the difference?

Mann et al. argue, in essence, that von Storch’s GKSS climate model was unrealistic, using unusually large natural climate forcings and also suffering from what the climate modelers call a “spin-up” effect – unnatural jitters in a climate model when you first turn it on, before it has a chance to settle down into a natural sort of rhythm.

These arguably unrealistic features in the GKSS simulation make the simulation potentially inappropriate for use in testing climate reconstruction methods.

(There’s a preprint on Mann’s web site.)

One Comment

  1. I thought the most important point in this new paper was

    “CFR methods are known to perform poorly in capturing patterns of variability that are entirely or largely missing during the calibration period”

    In other words if variability differs during the calibration period and the period of the proxy reconstructions the method fails or at best does not work well. This is a hard hurdle for proxy reconstructions to meet over long periods of time if variability is not constant over the entire period and is quite close to what McKitrick and McIntyre have been saying about anomolous growth in the bristlecome pine series. I don’t think Mann et al, have really fully explored the implications of this for their work.

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