This is a continuation of the previous post in which I analyze the sources of my confidence that the warming trend of the past half-century is dominated by external forcing.
Taking a long control integration of CM2.1, a GCM that I have talked about here before, I’ve used the last 2,000 years from the simulation described by Wittenberg, 2009, and located the period with the largest positive 50-year trend in global mean surface air temperature. The picture below is of the trend at each point, the global average of which is 0.41C. The average over the Northern Hemisphere only is about twice as large.
I think we can agree that this looks nothing like the observed trends in the past half-century. The maximum amplitude is in the subpolar North Pacific, with little trend in the tropics. Changes in the vertical mixing and transport between surface waters and deeper layers undoubtedly play a key role in the generation of this pattern. It is interesting that the North Atlantic does not play a more important role in this largest-trend case, since it does dominate the oceanic variability on somewhat shorter ~20 year time scales in this model. (The northern Pacific is too active, due to a cold bias and excessive ice formation, resulting in too much communication with deeper oceanic layers.) But there is one aspect of this pattern that does not surprise me — that the center of action is in the subpolar oceans.
Here’s another plot, making the same qualitative point, from an older GFDL model– from Delworth and Knutson, 2000:
Shown as a function of latitude and time are averages over longitude of surface temperature from observations (here taken from Parker et al, 1994) in the upper left and from 5 realizations of the climate model’s simulation of the 20th century. The differences between realizations is the internal variability, and one can see quite a lot at high Northern latitudes in this model. In fact, one of the realizations (upper right) happens to capture considerable early century warming, peaking near mid-century in high northern latitudes, comparable to that observed. (This ability to capture early 20th century warming due to internal variability remains rare in models, with this result a bit of an outlier –whether this is due to underestimation of variability by models or the presence of other forcings remains the obvious question.) In any case, internal variability is unable to compete with the more uniformly distributed warming trend throughout the tropics and midlatitudes of both hemispheres in the latter half of the century.
DelSole et al 2011 provide a convenient figure (top of post) summarizing the spatial structure of low frequency variability of sea surface temperature in an ensemble of GCMs. They gather the control simulations from 14 models together into one pot and decompose the variability into patterns, isolating that pattern whose time series has the largest integral time scale (or decorrelation time). This is not the only way to summarize this information, but it serves my limited purpose here of illustrating how low frequency variability tends to be concentrated in the subpolar oceans across the model ensemble. (They exclude the Southern Oceans from their analysis.)
Water columns are much more strongly stratified in the tropics than in higher latitudes, so it takes a lot less energy to move parcels from deep oceanic layers to the surface in high latitudes — and, not surprisingly, this is where most communication occurs between deep and surface waters. On the other hand, it seems quite logical that one needs to tap into the heat capacity of these deeper layers to create internal variability on long time scales. So one can rationalize the result that the centers of action for internal variability in the oceans migrate poleward from the tropics and subtropics to higher latitudes as one moves to lower frequencies. By the same physical argument, one expects minima in the response to external forcing in the subpolar oceans, since these are being held back by their strong coupling to the deeper layers.
We can all question these model results, of course. For example, could unresolved mesoscale eddies create more energetic multi-decadal variations in the wind driven gyres by cascading energy to larger scales? Also, temperature anomalies like those in the figure at the top do influence tropical rainfall patterns. In fact, they may do so more efficiently than more uniform temperature change; warming one hemisphere with respect to the other is an excellent way of pulling monsoonal circulations and oceanic ITCZs towards the warm hemisphere (the last few years have seen numerous studies of this response, relevant for ice ages and aerosol forcing as well as the response to high latitude internal variability; Chiang and Bitz, 2005 is one of the first to discuss this, in the ice age context; I’ll try to return to this topic in a future post.) Could tropical cloud feedbacks, or the coupling to ENSO, amplify the effects of low latitude hydrological responses to high-latitude anomalies in these models?
In any case, it is good to have a list of what you have to question if , in particular, you want to argue that the warming in the past half-century has been dominated by internal variability. It is not enough to look at global or hemispheric means of surface temperature and note that the models are not that far from producing internal variability of the right magnitude — perhaps most existing models only do this once in a blue moon, but I can imagine increasing the variance at low frequencies by a factor of two, say, so that the required magnitude is achieved more frequently. But the spatial structure will be still be wrong. My intuition is that it will be harder to modify the structure than the amplitude of the variability.
If a model comes along with low frequency variability that is less polar concentrated and fits the century, or half-century, trend pattern better, that would be news. If it also has heat flowing into rather than out of the oceans during the growth of the warm phase of this mode, that would be even more dramatic news.
Can we analyze observations cleverly so as to separate forced from internal variations, with or without the use of models? If we had higher confidence in the evolution of the aerosol forcing over time it would be a lot easier. But there are a number of recent attempts, including the Delsole et al paper cited above, that we can discuss as we go along. In light of the plausible structure of internal variability (and the relatively rich set of observations of the North Atlantic ocean) a focus on high Northern latitudes, asking if some of the observed trend in this region is internal, might be more productive that a focus on global means.
[The views expressed on this blog are in no sense official positions of the Geophysical Fluid Dynamics Laboratory, the National Oceanic and Atmospheric Administration, or the Department of Commerce.]