Target CO2

What is the long term sensitivity to increasing CO2? What, indeed, does long term sensitivity even mean? Jim Hansen and some colleagues (not including me) have a preprint available that claims that it is around 6ºC based on paleo-climate evidence. Since that is significantly larger than the ‘standard’ climate sensitivity we’ve often talked about, it’s worth looking at in more detail.

We need to start with some definitions. Sensitivity is defined as the global mean surface temperature anomaly response to a doubling of CO2 with other boundary conditions staying the same. However, depending on what the boundary conditions include, you can get very different numbers. The standard definition (sometimes called the Charney sensitivity), assumes the land surface, ice sheets and atmospheric composition (chemistry and aerosols) stay the same. Hansen’s long term sensitivity (which might be better described as the Earth System sensitivity) allows all of these to vary and feed back on the temperature response. Indeed, one can imagine a whole range of different sensitivities that could be clearly defined by successively including additional feedbacks. The reason why the Earth System sensitivity might be more appropriate is because that determines the eventual consequences of any particular CO2 stabilization scenario.

Traditionally, the decision to include or exclude a feedback from consideration has been based on the relevant timescales and complexity. The faster a feedback is, the more usual it is to include. Thus, changes in clouds (~hours) or in water vapour (~10 days) are undoubtedly fast and get included as feedbacks in all definitions of the sensitivity. But changes in vegetation (decades to centuries) or in ice sheets (decades(?) to centuries to millennia) are slower and are usually left out. But there are other fast feedbacks that don’t get included in the standard definition for complexity reasons – such as the change in ozone or aerosols (dust and sulphates for instance) which are also affected by patterns of rainfall, water vapour, temperature, soli moisture, transport and clouds (etc.).

Not coincidentally, the Charney sensitivity corresponds exactly to the sensitivity one gets with a standard atmospheric GCM with a simple mixed-layer ocean, while the Earth System sensitivity would correspond to the response in a (as yet non-existent) model that included interactive components for the cryosphere, biosphere, ocean, atmospheric chemistry and aerosols. Intermediate sensitivities could however be assessed using the Earth System models that we do have.

In principal, many of these sensitivities can be deduced from paleo-climate records. What is required is a good enough estimate of the global temperature change and measures of the various forcings. However, there are a few twists in the tale. Firstly, getting ‘good enough’ estimates for global temperatures changes is hard – this has been done well for the last century or so, reasonably for a few centuries earlier, and potentially well enough for the really big changes associated with the glacial-interglacial cycle. While sufficient accuracy in the last few centuries is a couple of tenths of a degree, this is unobtainable for the last glacial maximum or the Pliocene (3 million years ago). However, since the signal is much larger in the earlier periods (many degrees), the signal to noise ratio is similar.

Secondly, although many forcings can be derived from paleo-records (long-lived greenhouse gases from bubbles in the ice cores most notably), many cannot. The distribution of sulphate aerosols even today is somewhat uncertain, and at the last glacial maximum, almost completely unconstrained. This is due in large part to the heterogenity of their distribution and there are similar problems for dust and vegetation. In some sense, it is the availability of suitable forcing records that suggests what kind of sensitivity one can define from the record. A more subtle point is that the ‘efficacy’ of different forcings might vary, especially ones that have very different regional signatures, making it more difficult to add up different terms that might be important at any one time.


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