Planetary energy imbalance?

The recent paper in Science Express by Hansen et al (on which I am a co-author) has garnered quite a lot of press attention and has been described as the ‘smoking gun’ for anthropogenic climate change. We have discussed many of the relevant issues here before, but it may be useful to go over the arguments again here.

The key points of the paper are that: i) model simulations with 20th century forcings are able to match the surface air temperature record, ii) they also match the measured changes of ocean heat content over the last decade, iii) the implied planetary imbalance (the amount of excess energy the Earth is currently absorbing) which is roughly equal to the ocean heat uptake, is significant and growing, and iv) this implies both that there is significant heating “in the pipeline”, and that there is an important lag in the climate’s full response to changes in the forcing.

As we have discussed previously, looking in the ocean for climate change is a very good idea. Since the heat capacity of the land surface is so small compared to the ocean, any significant imbalance in the planetary radiation budget (the solar in minus the longwave out) must end up increasing the heat content in the ocean. This idea was explored by Levitus et al (long term observations of ocean heat content) and Barnett et al (modelling of such changes) in a couple of Science papers a few years ago. Since then, the models have got better (for instance, coupled models generally do not require ‘flux corrections’ to prevent excessive model drift any more), and the estimates of ocean heat changes, particularly over the last ten years have improved enourmously. The observational improvements come from incorporating satellite altimeter data (which mainly reflects changes in heat content) and, more recently, the ARGOS float network which is providing unparallelled coverage in sub-surface waters (particularly in the southern oceans). This implies that the estimates of ocean heat content changes over the last 10 years are the most accurate that we have had to date and thus provide a good target to compare against the models.

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