Posted on September 23rd, 2013
Correlation between seasonal mean precipitation (Dec-Jan-Feb) and sea surface temperatures in the eastern equatorial Pacific (Niño 3.4: 120W-170W and 5S-5N) in observations (GPCP) and in a free-running coupled atmosphere-ocean model (GFDL’s CM2.1), from Wittenberg et al 2006. Green areas are wetter in El Niño and drier in La Niña winters; red areas are drier in El Niño and wetter in La Niña.
(Sept 30: I have moved a few sentences around to make this read better, without changing anything of substance.)
It is old news to farmers and water resource managers in the southern tier of the continental US that La Niña is associated with drought, especially with rainfall deficits in the winter months. Since the major El Niño event of 1997-8, our climate system has been reluctant to generate El Niño at the expected frequency and instead the Pacific has seen several substantial La Niña events with mostly near neutral conditions in between. This La Niña flavor to the past 15 years has been identified as causing at least part of the hiatus in global warming over this same period by simple empirical fitting and more recently by Kosaka and Xie 2013, in which a climate model is manipulated by restoring temperatures to observations in the eastern equatorial Pacific. I find the excellent fit obtained in that paper compelling, having no free parameters in the sense that this computation was not contemplated while the model, GFDL’s CM2.1, was under development, and the model was not modified from the form in which it was frozen back in 2005. The explanation for the hiatus must, in appears, flow through the the equatorial Pacific. (I have commented on this paper further here.) These authors mention briefly an important implication of this connection — the extended drought in the Southern US and the hiatus in global mean warming are related.
The figure at the top compares the response of precipitation to ENSO in an observational estimate and in the same climate model as utilized by Kosaka and Xie. This result is obtained with a free-running model, producing its own ENSO variability. (The correlation averages over any asymmetries between warm El Niño and cold La Niña phases, which are not exact mirror images of each other, but does not change the basic picture.) The model evidently generates a reasonable simulation of the precipitation response over the US, justifying the discussion by Kosaka and Xie of the connection to the hiatus. Results such as these are what make the case that global models are of value in estimating the broad-scale changes in precipitation associated with climate change if not, as yet, detailed regional features.
In passing, I just want to put in a good word for the simulation of ENSO in current climate models. This comes in for a lot of criticism it seems, but from my perspective, having been around for a while, I am impressed by how far we have come. ENSO variability develops spontaneously, of course, just like midlatitude storms on much shorter time scales. The ENSO simulation in this model is not without its problems, needless to say. Its amplitude is too strong and the structure has some problems as well, most notably temperature anomalies spread too far westward on the equator in the Pacific, distorting the Indonesian drying among other things. This model was developed a decade ago — we (that is, my GFDL colleagues) are confident that we can do better now (Delworth et al 2012). Are these model’s good enough to simulate the response of ENSO to increasing greenhouse gases or changing aerosols?
When I first started this blog I thought that I would try to focus on things other than the global mean surface temperature time series, but if you are a regular reader you know that I haven’t been very successful at this. And it becomes even harder with the emphasis on the hiatus. But this connection between US drought and the hiatus emphasizes for me how important it is to look at things more broadly, especially when there is more than one thing going on (ie two different kinds of external forcing or external forcing plus internal variability). This model, like most others (see the canonical figure from the AR4 Summary for Policymakers) predicts that increasing well-mixed greenhouse gases will dry the Southwest and South central US. So El Niño and increasing greenhouse gases have the same sign effect on global mean temperature, but opposite effects on rainfall in the Southern US.
We think of the response of precipitation to greenhouse gas forcing as a combination of a part that is controlled by the temperature increase — specifically the increase in water vapor accompanying the temperature increase, as discussed in Post #13 — and a part related to changes in atmospheric circulation. The response to ENSO is mostly due to changes in atmospheric circulation, which have little resemblance to the circulation changes induced by greenhouse gas forcing – in fact they tend to have the opposite character, with the large-scale circulation shifting equatorward rather than poleward with global mean warming — as indicated in the following figure, from Lu et al 2008:
This plot shows results from CM2.1 once again, focusing on the zonal mean (the average around a latitude circle) of the zonal wind (positive if from the west). The contours in each plot are the model’s climatological mean in Dec-Jan-Feb and the colors the change due to ENSO (El Niño – La Niña) on the left and the trend over the 21st century in a projection using the A2 scenario on the right. Red is positive and green negative, so comparing the colors to the climatology, you can see that El Niño moves this entire pattern equatorwards while the model’s 21st century trend, dominated by the response to greenhouse gases, moves it polewards. Flipping the sign on the left to correspond to the La Niña state would make the figures look more similar. The rainfall pattern outside of the tropics goes along for the ride on these circulation changes. There is a lot of literature on the theory for these large-scale shifts in circulation, some of it using variants of the fruit fly model (post #28). One thing these model results are telling us is that global mean warming, or the warming of the tropics in isolation, cannot be the primary reason for these shifts in circulation in general.
The magnitudes in this figure are also telling us something. It takes a century of global warming to reach the amplitude of the change in circulation associated with a flip from El Niño to La Niña. This might seem small, until you think about the implications of a shift in the mean comparable to the peak-to-peak variations in the ENSO cycle. Well before this point one would reach a situation in which the shift in the mean is comparable to changes in circulation or rainfall averaged over one or two decades. Whether we are already approaching the latter point is obviously a key question in climate research. The magnitude of the precipitation changes in the US due to an increase in greenhouse gases varies from model to model, so estimates of what role global warming has played in precipitation changes over the US during the hiatus will be model dependent. Some of the inter-model spread here is itself likely to be related to the spread in the response of the equatorial Pacific to greenhouse gas forcing.
[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.]