Good news for the earth’s climate system?

Guest Commentary by Jim Bouldin (UC Davis)

How much additional carbon dioxide will be released to, or removed from, the atmosphere, by the oceans and the biosphere in response to global warming over the next century? That is an important question, and David Frank and his Swiss coworkers at WSL have just published an interesting new approach to answering it. They empirically estimate the distribution of gamma, the temperature-induced carbon dioxide feedback to the climate system, given the current state of the knowledge of reconstructed temperature, and carbon dioxide concentration, over the last millennium. It is a macro-scale approach to constraining this parameter; it does not attempt to refine our knowledge about carbon dioxide flux pathways, rates or mechanisms. Regardless of general approach or specific results, I like studies like this. They bring together results from actually or potentially disparate data inputs and methods, which can be hard to keep track of, into a systematic framework. By organizing, they help to clarify, and for that there is much to be said.

Gamma has units in ppmv per ÂșC. It is thus the inverse of climate sensitivity, where CO2 is the forcing and T is the response. Carbon dioxide can, of course, act as both a forcing and a (relatively slow) feedback; slow at least when compared to faster feedbacks like water vapor and cloud changes. Estimates of the traditional climate sensitivity, e.g. Charney et al., (1979) are thus not affected by the study. Estimates of more broadly defined sensitivities that include slower feedbacks, (e.g. Lunt et al. (2010), Pagani et al. (2010)), could be however.

Existing estimates of gamma come primarily from analyses of coupled climate-carbon cycle (C4) models (analyzed in Friedlingstein et al., 2006), and a small number of empirical studies. The latter are based on a limited set of assumptions regarding historic temperatures and appropriate methods, while the models display a wide range of sensitivities depending on assumptions inherent to each. Values of gamma are typically positive in these studies (i.e. increased T => increased CO2).

To estimate gamma, the authors use an experimental (“ensemble”) calibration approach, by analyzing the time courses of reconstructed Northern Hemisphere T estimates, and ice core CO2 levels, from 1050 to 1800, AD. This period represents a time when both high resolution T and CO2 estimates exist, and in which the confounding effects of other possible causes of CO2 fluxes are minimized, especially the massive anthropogenic input since 1800. That input could completely swamp the temperature signal; the authors’ choice is thus designed to maximize the likelihood of detecting the T signal on CO2. The T estimates are taken from the recalibration of nine proxy-based studies from the last decade, and the CO2 from 3 Antarctic ice cores. Northern Hemisphere T estimates are used because their proxy sample sizes (largely dendro-based) are far higher than in the Southern Hemisphere. However, the results are considered globally applicable, due to the very strong correlation between hemispheric and global T values in the instrumental record (their Figure S3, r = 0.96, HadCRUT basis), and also of ice core and global mean atmospheric CO2.

The authors systematically varied both the proxy T data sources and methodologicalvariables that influence gamma, and then examined the distribution of the nearly 230,000 resulting values. The varying data sources include the nine T reconstructions (Fig 1), while the varying methods include things like the statistical smoothing method, and the time intervals used to both calibrate the proxy T record against the instrumental record, and to estimate gamma.

Figure 1. The nine temperature reconstructions (a), and 3 ice core CO2 records (b), used in the study.

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