opinion & comment References 1. Norgaard, K. Living in Denial: Climate Change, Emotions, and Everyday Life (MIT Press, 2011). 2. Tilly, C. & Tarrow, S. Contentious Politics (Oxford Univ. Press, 2001). 3. Grossman, Z. Amer. Indian Culture Res. J. 32, 5–27 (2008). 4. Wright, R. A. & Boudet, H. S. Amer. J. Sociol. 3, 728–777 (2012). 5. Harlan, S. et al. in Climate Change and Society: Sociological
Perspectives (eds Dunlap, R. E. & Brulle, R. J.) 137–139 (Oxford Univ. Press, 2016). 6. Fox, J. Organ. Environ. 12, 162–184 (1999). 7. Lerner, S. Sacrifice Zones: The Front Lines of Toxic Exposure in the United States (MIT Press, 2010). 8. McAdam, D. & Boudet, H. Putting Social Movements in Their Place: Explaining Opposition to Energy Projects in the United States, 2000–2005 (Cambridge Univ. Press, 2012).
9. Crona, B., Wutich, A., Brewis, A. & Gartin, M. Climatic Change 119, 519–531 (2013). 10. Duggan, J. Kleeb’s Bold Nebraska Model is on the Move. Norfolk Daily News (8 May 2016). 11. Healy, J. North Dakota Oil Pipeline Battle: Who’s Fighting and Why. The New York Times (26 August 2016). 12. Song, L. 2017: Pipeline Resistance Gathers Steam from Dakota Access, Keystone Success. Inside Climate News (2 January 2017).
COMMENTARY:
Assessing temperature pattern projections made in 1989 Ronald J. Stouffer1* and Syukuro Manabe2 Successful projection of the distribution of surface temperature change increases our confidence in climate models. Here we evaluate projections of global warming from almost 30 years ago using the observations made during the past half century.
O
ver a quarter of a century has passed since the first global coupled atmosphere–ocean models were used to examine the transient climate response to increasing atmospheric CO2. Several studies have evaluated the projections of global temperature made in the first IPCC report 1. These projections used information from a combination of simple and complex models and subjective judgement of the authors of the IPCC report. Recently, these global surface temperature projections have been shown to be broadly consistent with the observed global temperature changes since 19902–4. Starting in 1989, we along with our Geophysical Fluid Dynamics Laboratory colleagues published a series of papers5–7 that describe results from a coupled atmosphere–ocean general circulation model (AOGCM). The model was radiatively forced by increasing the atmospheric CO2 concentration at a rate of 1% per year compounded. This rate is roughly equivalent to the rate of increase in the radiative forcing due to the increase of all greenhouse gas since the 1980s, not including ozone changes8. Two measures of the model’s sensitivity, the transient climate response and equilibrium climate sensitivity, are similar to those found in present day models9,10. More details on the model and integrations can be found in ref. 6. These are still early days in evaluating projection skill in climate models. Many
observational records are just now becoming long enough to provide reliable information for limited evaluations. This is an attempt to compare the distribution of the surface temperature predictions made more than 25 years ago with observations made during the past half century. An important caveat to keep in mind is that the model forcing used in this study involved increases in the equivalent CO2 concentration of greenhouse gases. Changes in other forcing agents such as man-made aerosols, solar and volcanoes were ignored. The forcing differences between solely CO2 versus all the known radiative forcing agents are likely to cause differences in the pattern and magnitude of the changes shown here. This causes problems in comparing models to observations and makes the comparisons shown here qualitative in nature. It is one of the reasons why we focus our attention on the geographical distribution of surface temperature change rather than the magnitude of change in this study.
Early comparisons
The geographical distribution of the difference in observed surface temperature between the recent 25-year period 1991–2015 and the 30-year reference period 1961–1990 is shown in Fig. 1b. The difference may be used as an indicator of the local temperature trends during the past half century when the multi-decadal rate of global warming is the most pronounced.
The observed change thus obtained is compared with Fig. 1a, which illustrates the distribution of the predicted change in surface air temperature in response to the doubling of atmospheric concentration of CO2. In order to facilitate comparison between the geographical patterns of predicted and observed surface temperature changes that are different by a factor of ~5, colours are chosen such that the values at the various colour thresholds in Fig. 1a are five times as large as those in Fig. 1b, highlighting the warming patterns. Comparing the observed change with the model projections, one notes that the land areas warm faster than adjacent ocean areas in both the model and in the observations11. The warming tends to be largest in high northern latitudes due mainly to the positive albedo feedback of snow and sea ice5,6. In the model results (Fig. 1a), warming is a minimum in the northern North Atlantic: this is not so pronounced in the observations (Fig. 1b). In the model, this minimum is attributable not only to deep, convective mixing of heat but also to the weakening of the Atlantic meridional overturning circulation5,6,12. In sharp contrast to most of the high northern latitudes, temperature change is small in the Southern Ocean in the model results. The area of small temperature change is also seen in the observations. If the observed trend of little or no warming continues in the Southern Ocean, it will confirm this
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surprising early model finding. The pattern in the surface air temperature response, highlighted above, is also seen in the multimodel ensemble found in the recent IPCC Working Group I Fifth Assessment Report (ref. 13; Figs 12.10 and 12.11). It is quite surprising that the observed and projected pattern of surface temperature change are very similar to each other, when one realizes that the distribution of the thermal forcing of the model is likely to be different from that of the actual forcing. The similarity between the two patterns suggests that the geographical distribution of surface 164
temperature change may not depend critically upon that of thermal forcing. It also suggests that the model likely contains the key physical processes that control the geographical pattern of global warming at the earth surface. Zonally averaging the relatively short observational data can help improve the signal-to-noise ratio. This is particularly the case when looking at sub-annual changes. As shown in Fig. 2 (and ref. 14), the Northern Hemisphere high latitude warming is large in the late autumn through to winter and into the spring, though there is a summer minimum
in both the model and observations. In sharp contrast, in the observations near 57.5 °S, there is a minimum in the warming throughout the year. Further south there is not enough data to reliably compute the monthly means in winter. In the model, the warming minimum extends southward toward Antarctica. The seasonal and latitudinal profile of the observed warming appears to be broadly consistent with that of the warming obtained from the model, though there are notable differences in details. For a full discussion of the physical mechanisms of the seasonal variation of surface temperature change, see refs 7, 15 and 16. As is the case with surface air temperature, the observed 50-year trends of zonally averaged temperature in the upper 2,000 m layer of ocean17 shown in Fig. 3b have a similar pattern to the model projections5. As seen in the projected change (Fig. 3a), the positive temperature trends are large in the near-surface layer of ocean and decrease with depth. It is of particular interest that the layer of positive temperature change penetrates deeply in the Antarctic Ocean around 60° S and 75° S as well as in the northern North Atlantic Ocean around 75° N. In these regions, where deep convection predominates, the effective thermal inertia of the ocean is very large due mainly to the deep mixing of heat6. Thus, the warming at the oceanic surface is reduced greatly and is small in these regions as shown in Fig. 1a. Broadly speaking, the distribution of the simulated oceanic temperature change described above is in qualitative agreement with that of observed change, though the observed temperature change is not shown below the depth of 2 km because of poor data coverage. Nevertheless, it is encouraging that in the high southern latitudes, the layer of positive temperature change extends downward to a depth of at least 2 km.
Discussion
As the observed record becomes longer, more and more evaluations of past climate model projections will be able to be reliably performed. What we present here is an assessment of climate model projections from more than 25 years ago of the patterns of temperature change. While the comparison shown here is qualitative, we believe that based on observations available to date, the model is able to make reliable projections of the warming pattern. As the observational record lengthens, this evaluation should be made again, potentially using more climate variables. The success of these projections will increase our
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confidence in current model projections of future climate changes. When the model results used here were published, we did our best to make the model’s simulation of the current climate as realistic as possible. However, we did not adjust our model in any way to simulate the future climate changes for the obvious reason that we did not know how the climate was going to change when the simulation was made. This is why we are very much encouraged to find
that the salient features of climate change distribution projected by the model are becoming evident in the observations. In other words, the projections shown here were made before the observations confirmed them as being correct, striking at the heart of the argument that modellers tune their models to yield the correct climate change results. ❐ Ronald J. Stouffer is at the Geophysical Fluid Dynamics Laboratory, NOAA, Princeton, New Jersey
1. Bretherton, F. P., Bryan, K. & Woods, J. D. in Climate Change: The IPCC Scientific Assessment (eds Houghton, J. T., Jenkins, G. J. & Ephraums, J. J.) 173–193 (IPCC, Cambridge Univ. Press, 1990). 2. Rahmstorf, S., Foster, G. & Cazenave, A. Environ. Res. Lett. 7, 044035 (2012). 3. Frame D. J. & Stone, D. A. Nat. Clim. Change 3, 357–359 (2013). 4. Le Treut, H. et al. in Climate Change 2007: The Physical Science Basis (eds Solomon, S. et al.) 93–128 (IPCC, Cambridge Univ. Press, 2007). 5. Stouffer, R. J., Manabe, S. & Bryan, K. Nature 342, 660–662 (1989). 6. Manabe, S., Stouffer, R. J., Spelman, M. J. & Bryan, K. J. Clim. 4, 785–818 (1991). 7. Manabe, S., Spelman, M. J. & Stouffer, R. J. J. Clim. 5, 105–126 (1992). 8. Schimel, D. et al. in Climate Change 1995: The Science of Climate Change (eds Houghton, J. T. et al.) 65–132 (IPCC, Cambridge Univ. Press, 1995). 9. Stouffer, R. J. & Manabe, S. J. Clim. 12, 2224–2237 (1999). 10. Bindoff, N. L. et al. in Climate Change 2013: The Physical Science Basis (eds Stocker, T. F. et al.) 867–952 (IPCC, Cambridge Univ. Press, 2013). 11. Joshi, M. M., Lambert, F. H. & Webb, M. J. Clim. Dynam. 41, 1853–1869 (2013). 12. Rahmstorf, S. et al. Nat. Clim. Change 5, 475–480 (2015). 13. Collins, M. et al. in Climate Change 2013: The Physical Science Basis (eds Stocker, T. F. et al.) 1029–1136 (IPCC, Cambridge Univ. Press, 2013). 14. Manabe, S., Ploshay, J. & Lau, N.-C. J. Clim. 24, 3817–3821 (2011). 15. Manabe, S. & Stouffer, R. J. J. Geophys. Res. 85, 5529–5554 (1980). 16. Held, I. M. Icarus 50, 449–461 (1982). 17. Rhein, M. et al. in Climate Change 2013: The Physical Science Basis (eds Stocker, T. F. et al.) 255–316 (IPCC, Cambridge Univ. Press, 2013). 18. Morice, C. P., Kennedy, J. J., Rayner, N. A. & Jones, P. D. J. Geophys. Res. 117, D08101 (2012).
Author contributions R.J.S and S.M. equally participated in all aspects of this work.
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