The long-awaited prequel to “Can the Last Glacial Maximum constrain climate sensitivity?” is now up on CPD and open for comment. This latest episode is set back in the mid-Pliocene warm period 3-3.3Ma BP (MPWP, sometimes also called mid-Piacenzian by people who care deeply about the conventions for paleoclimate nomenclature). The particular reason for looking at the MPWP is that it’s the most recent period when CO2 was relatively high (at least compared to pre-industrial, though perhaps not so high compared to today) and the climate was correspondingly warm. This means that it avoids some of the major complications that arise when studying the Last Glacial Maximum, where there is the question of how directly a strong cooling informs about a strong warming, and large ice sheets provide a substantial forcing to the atmosphere-ocean system that does not necessarily combine linearly with other forcings such as GHGs. Thus, PlioMIP was born around 2009, and by 2015 lots of different modelling groups had produced simulations of the MPWP to compare with each other and with the data assembled by the USGS. Being much further back in time than the LGM, the data are much more sparse (even though the interval of time is also far broader) and more uncertain. Also, the boundary conditions such as atmospheric CO2 level are not known with great precision. One might be suspicious that choice of value used in the simulations, 405ppm, could have been been influenced by political considerations 🙂
Although theres been a fair bit of analysis of the model results, no-one had looked directly at how the simulations depended on the equilibrium climate sensitivities of the models. So we did the usual thing, of comparing the tropical temperature change at the MPWP, to the equilibrium sensitivity of the models. It looks like there might be some sort of relationship there, though it’s far from certain.
Here’s the main result, with the model results represented by red dots.
The temperature data for the MPWP is a bit less well developed than for the LGM, so we didn’t really have a good uncertainty estimate but instead just tried a few possible values as a sensitivity test. It is also notable that the model ensemble seems to generally show more warming here than the data, although with substantial overlap if uncertainty is taken into account. It is possible that the forcing is too strong, or that the models are too sensitive in this region, or it may be that the data are wrong, or to be more precise, misinterpreted in terms of climate. I try to be avoid saying things like “the data are wrong” especially when talking to the data specialists, as at some level the data are definitely correct, real stuff has been measured and the measurements themselves are not in any real doubt. It’s how these real measurements are translated into a putative climate variable that is where the difficulties lie. Another interesting and possibly disconcerting aspect of this result is that the regression line does not pass through (or close to) the origin, implying that a hypothetical model with zero sensitivity to CO2 would show a significant tropical cooling at the MPWP. It is hard to see how that might arise, although it is also hard to see how a model with zero sensitivity to CO2 could arise anyway. It is perhaps not completely impossible that increased latitudinal transport would result in a tropical cooling accompanied by a high latitude warming so as to cancel out the change on the global average. After all, there has to be some explanation as to why a small change in model sensitivity seems to correspond to such a large change in MPWP tropical warming in this sample. We’ve presented this work a few times and no-one has come up with any great ideas about it.
Anyway, we don’t have any strong conclusions, it might be possible to generate a meaningful constraint out of this, but we don’t have any real confidence in the specific result presented here. PlioMIP2 is being planned, with various improvements over the original PlioMIP. Most importantly perhaps, the researchers are aiming for a true “time slice” in which orbital and other forcings are near enough constant (and so, hopefully, the climate was in some sort of equilibrium with this), rather than aiming for some sort of average over the warm peaks within a longer interval, as PlioMIP did. The main problem with this is that the data become even more sparse, but it should in principle enable a more meaningful model-data comparison. Watch this space!