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Lessons from Past Climate Predictions: IPCC AR4 (update)

Posted on 23 September 2011 by dana1981

Note: this is an update on the previous version of this post.  Thanks to readers Lucia and Zeke for providing links to the IPCC AR4 model projection data in the comments, and Charlie A for raising the concern about the quality of the original graph digitization.

In 2007, the IPCC published its Fourth Assessment Report (AR4).  In the Working Group I (the physical basis) report, Chapter 8 was devoted to climate models and their evaluation.  Section 8.2 discusses the advances in modeling between the Third Assessment Report (TAR) and AR4.

"Model improvements grouped into three categories. First, the dynamical cores (advection, etc.) have been improved, and the horizontal and vertical resolutions of many models have been increased. Second, more processes have been incorporated into the models, in particular in the modelling of aerosols, and of land surface and sea ice processes. Third, the parametrizations of physical processes have been improved. For example, as discussed further in Section 8.2.7, most of the models no longer use flux adjustments (Manabe and Stouffer, 1988; Sausen et al., 1988) to reduce climate drift."

In the Frequently Asked Questions (FAQ 8.1), the AR4 discusses the reliability of  models in projecting future climate changes.  Among the reasons it cites that we can be confident in model projections is their ability to model past climate changes in a process known as "hindcasting".

"Models have been used to simulate ancient climates, such as the warm mid-Holocene of 6,000 years ago or the last glacial maximum of 21,000 years ago (see Chapter 6). They can reproduce many features (allowing for uncertainties in reconstructing past climates) such as the magnitude and broad-scale pattern of oceanic cooling during the last ice age. Models can also simulate many observed aspects of climate change over the instrumental record. One example is that the global temperature trend over the past century (shown in Figure 1) can be modelled with high skill when both human and natural factors that influence climate are included. Models also reproduce other observed changes, such as the faster increase in nighttime than in daytime temperatures, the larger degree of warming in the Arctic and the small, short-term global cooling (and subsequent recovery) which has followed major volcanic eruptions, such as that of Mt. Pinatubo in 1991 (see FAQ 8.1, Figure 1). Model global temperature projections made over the last two decades have also been in overall agreement with subsequent observations over that period (Chapter 1)."

AR4 hindcast

Figure 1: Global mean near-surface temperatures over the 20th century from observations (black) and as obtained from 58 simulations produced by 14 different climate models driven by both natural and human-caused factors that influence climate (yellow). The mean of all these runs is also shown (thick red line). Temperature anomalies are shown relative to the 1901 to 1950 mean. Vertical grey lines indicate the timing of major volcanic eruptions.

Projections and their Accuracy

The IPCC AR4 used the IPCC Special Report on Emission Scenarios (SRES), which we examined in our previous discussion of the TAR.  As we noted in that post, thus far we are on track with the SRES A2 emissions pathChapter 10.3 of the AR4 discusses future model projected climate changes, as does a portion of the Summary for Policymakers.  Figure 2 shows the projected change in global average surface temperature for the various SRES.

AR4 projections

Figure 2: Solid lines are multi-model global averages of surface warming (relative to 1980–1999) for the scenarios A2, A1B, and B1, shown as continuations of the 20th century simulations. Shading denotes the ±1 standard deviation range of individual model annual averages. The orange line is for the experiment where concentrations were held constant at year 2000 values. The grey bars at right indicate the best estimate (solid line within each bar) and the likely range assessed for the six SRES marker scenarios.

Figure 3 compares the multi-model average for Scenario A2 (the red line in Figure 2) to the observed average global surface temperature from NASA GISS. In the previous version of this post, we digitized Figure 2 in order to create the model projection in Figure 3.  However, given the small scale of Figure 2, this was not a very accurate approach.  Thanks again to Zeke and lucia for pointing us to the model mean data file.

AR4 projections

Figure 3: IPCC AR4 Scenario A2 model projections (blue) vs. GISTEMP (red) since 2000

The linear global warming trend since 2000 is 0.18°C per decade for the IPCC model mean, vs. 0.15°C per decade according to GISTEMP (through mid-2011).  This data falls well within the model uncertainty range (shown in Figure 2, but not Figure 3), but the observed trend over the past decade is a bit lower than projected.  This is likely mainly due to the increase in human aerosol emissions, which was not expected in the IPCC SRES, as well as other short-term cooling effects over the past decade (see our relevant discussion of Kaufmann 2011 in Why Wasn't The Hottest Decade Hotter?).

What Does This Tell Us?

The IPCC AR4 was only published a few years ago, and thus it's difficult to evaluate the accuracy of its projections at this point.  We will have to wait another decade or so to determine whether the models in the AR4 projected the ensuing global warming as accurately as those in the FAR, SAR, and TAR

Section 10.5.2 of the report discusses the sensitivity of climate models to increasing atmospheric CO2.

"Fitting normal distributions to the results, the 5 to 95% uncertainty range for equilibrium climate sensitivity from the AOGCMs is approximately 2.1°C to 4.4°C and that for TCR [transient climate response] is 1.2°C to 2.4°C (using the method of Räisänen, 2005b). The mean for climate sensitivity is 3.26°C and that for TCR is 1.76°C."

Thus the reasonable accuracy of the IPCC AR4 projections thus far suggests that it will add another piece to the long list of evidence that equilibrium climate sensitivity (including only fast feedbacks) is approximately 3°C for doubled CO2.  However, it will similarly take at least another decade of data to accurately determine what these model projections tell us about real-world climate sensitivity.

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Comments 101 to 104 out of 104:

  1. Matthew @99: 1) You are projecting temperatures with a linear trend, so of course your projections understate IPCC projections. 2) Taking a 5 year mean at the start and the end of a period is not an accurate method of determining a linear trend in any event. Mathematically, therefore, you cannot do what you purport to do (find a trend) with the methods you use. 3) If you take a five year mean, the value arrived at is the value for the median year of the mean. Consequently when you take a 2006-2010 mean, you determine a value for 2008, not 2010 as you suppose. 4) Most importantly, El Nino's and La Nina's do not neatly alternate. Sometimes, as for example 2002-2007, you get a string of El Nino's with only neutral conditions or weak La Nina's (2006) intervening. Nor are all ENSO fluctuations of equal strength. The 1997/1998 El Nino was particularly strong, while the following 1999-2001 La Nina episodes were moderate. Consequently a simple five year mean will not eliminate ENSO effects from the data. For example, a 5 year mean centered on 2000 would include a strong El Nino year, 2 moderate and a weak La Nina, and a moderate El Nino, probably resulting in a slightly positive (El Nino) average. A five year mean ending with 2011 will include a moderate, a strong and a very strong La Nina and two moderate El Nino's, probably being net negative as a result. As noted @ 23, Tamino has already produced temperature indices adjusted for ENSO, vulcanism, and solar variation. The result shows a 0.17 degree per decade warming, just shy of the 0.18 projected by the AR4 A2 multi-model mean. That is certainly well within error.
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  2. I'm very disappointed by the standard of arguments by Carrick, Lucia, Charlie and others. They've been unable to suggest anything other than cherry-picking reasons for changing the 2000 start date. They've been unable to pick any good reason why not to use GISS, other than empty suggestions of deception. Most importantly, they've been unable to indicate why Dana's conclusions are incorrect. Given the neutral-negative ENSO and negative solar forcing over that period, global temperatures are just where you would rationally expect them to be, slightly below model projections, even if you use the non-global NCDC or HADCRUT products. If the critics can't actually show that this post's conclusions are in error, they're left with empty nit-picking, and really, is that all they have?
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  3. Agreed skywatcher - there's not much to disagree with in the conclusions, which are pretty darn wishy-washy (as necessary due to the lack of data available), so the criticisms are necessarily nitpicky. Regarding the claim that starting in 2000 was a cherrypick - aside from the fact that the AR4 model run began in 2000, it wasn't a particularly cold year either. By 2000-2010 standards sure, but at the time, it was the 6th-hottest year on record, and hotter than the 1990-1999 average. The only reason it was relatively cold is that the past decade has been so hot! It's funny that the same people who are arguing there's been little to no warming over the past decade are also arguing that 2000, which at the time was exceptionally hot (6th-hottest year on record) now must be considered a cold year. As for ENSO, the end of 2010 saw a moderate La Nina which was reflected in the early 2011 temperatures, which I could have excluded by looking at just 2000-2010 or 2001-2010 observational data. But I didn't, I included all data through July 2011, including those months impacted by La Nina. In short, that particularl nitpick is just plain wrong.
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  4. In all the huffing and puffing it seems that a most important post by Bernard J @56 has passed unnoticed ... worth considering:
    If you want to raise an eyebrow and impute falsification, one first needs to demonstrate that certain assumed model inputs have actually behaved as was assumed at the time of modelling. As others have noted, solar output has been much lower than was expected at the time of modelling for AR4. Such a result does not falsify the models. Unless, of course, one revisits the models and repeats them with the inclusion of the real-world parameters obtained subsequent to the original runnings, and gets a result that then invalidates the predictions.
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