What is a first-order climate forcing?

Roger Pielke Sr. (Colorado State) has a blog (Climate Science) that gives his personal perspective on climate change issues. In it, he has made clear that he feels that apart from greenhouse gases, other climate forcings (the changes that affect the energy balance of the planet) are being neglected in the scientific discussion. Specifically, he feels that many of these other forcings have sufficient ‘first-order’ effects to prevent a clear attribution of recent climate change to greenhouse gases.

In general, I heartily agree – other forcings are important, even essential, for understanding observed climate variability and, as a community, we are only just starting to get to grips with some of the more complicated effects. Obviously, though, not all forcings are of the same magnitude (either globally or regionally) and so it is useful to separate the ‘first-order’ forcings from those that are relatively minor. But what exactly is ‘first-order’ and what is not?

It is helpful to distinguish forcings that are important in the global mean, from those which might be important locally but not have much impact for ‘global warming’. A good metric for the importance of a global forcing is the radiative forcing (i.e. the global mean radiation impact at the tropopause for an instantaneous change – the so-called “instantaneous forcing”). There are other definitions (e.g. the “adjusted forcing” where stratospheric temperatures are allowed to adjust), but for the purpose of this article these differences are not that important (for those who are interested there is a good discussion of the different forcing definitions in Hansen et al (2005, JGR)).

While the definition of a forcing may appear a little arbitrary, the reason why radiative forcing is used is because it (conveniently) gives quite good predictions of what happens in models to the global mean temperature once the climate system has fully responded to the change. Thus the forcing can be used as a shorthand for the climate response without having to do the experiment.

Of course, the global mean temperature isn’t the only useful metric of climate change – regional temperatures and precipitation are arguably much more societally relevant – but it does have a good signal-to-noise ratio. That is, changes to the system are more clearly discerned in the global mean temperature than at a regional level, mainly because the noisy ‘weather’ component increases as you go to smaller scales.

Global Mean Forcings 1750-2000

Figure 1: Two breakdowns of the global mean forcings since the pre-industrial. Factors causing warming are red, cooling factors, blue. The top panel shows the direct effects of the individual components, while the second panel attributes various indirect factors (associated with atmospheric chemistry, aerosol cloud interactions and albedo effects) and includes a model estimate of the ‘efficacy’ of the forcing that depends on its spatial distribution. (From Hansen et al (2005, JGR)). Subjective uncertainties associated with the well-mixed GHGs are around ~0.15 W/m2, for ozone ~0.07 W/m2, tropospheric aerosols around ~1 W/m2 and solar ~0.3 W/m2.

The figure here gives one estimate for how many of those forcings have changed over the industrial period (1750-2000). This assessment is from my own lab and so I may be a little biased, but although there are significant uncertainties (particular for the aerosol indirect effects), it probably gives a reasonable idea of the current thinking. The forcings illustrated here are from the well mixed greenhouse gases (GHGs) (CO2, CH4, N2O, CFCs), tropospheric and stratospheric O3, direct aerosol effects (from sulphates, nitrates, organic and black carbon), land use change, solar irradiance, volcanic aerosols, and various indirect effects (on clouds, stratospheric water vapour, snow albedo etc.). Reasonable estimates of these 16 different effects (and counting…) were included in the GISS simulations for the upcoming IPCC assessment.

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