I recently covered a press release from Dr. Ben Santer where it was claimed that:
In order to separate human-caused global warming from the “noise” of purely natural climate fluctuations, temperature records must be at least 17 years long, according to climate scientists.
Bob Tisdale decided to run the numbers on Ar4 models:
17-Year And 30-Year Trends In Sea Surface Temperature Anomalies: The Differences Between Observed And IPCC AR4 Climate Models
By Bob Tisdale
We’ve illustrated and discussed in a number of recent posts how poorly the hindcasts and projections of the coupled climate models used in the Intergovernmental Panel on Climate Change’s 4th Assessment Report (IPCC AR4) compared to instrument-based observations. And this post is yet another way to illustrate that fact. We’ll plot the 17-year and 30-year trends in global and hemispheric Sea Surface Temperature anomalies from January 1900 to August 2011 (the updates of HADISST data used in this post by the Hadley Centre can lag by a few months) and compare them to the model mean of the Hindcasts and Projections of the coupled climate models used in the IPCC AR4. As one would expect, the model mean show little to no multidecadal variability, which is commonly known. Refer to the June 4, 2007 post at Nature’s Climate Feedback: Predictions of climate, written by Kevin Trenberth. But there is evidence that the recent flattening of Global Sea Surface Temperature anomalies and the resulting divergence of them from model projections is a result of multidecadal variations in Sea Surface Temperatures.
WHY 17-YEAR AND 30-YEAR TRENDS?
A recent paper by Santer et al (2011) Separating Signal and Noise in Atmospheric Temperature Change: The Importance of Timescale, state at the conclusion of their abstract that, “Our results show that temperature records of at least 17 years in length are required for identifying human effects on global-mean tropospheric temperature.” Sea surface temperature data is not as noisy as Lower Troposphere temperature anomalies, so we’ll assume that 17 years would be appropriate timescale to present sea surface temperature trends on global and hemispheric bases as well. And 30 years: Wikipedia defines Climate “as the weather averaged over a long period. The standard averaging period is 30 years, but other periods may be used depending on the purpose.”
But we’re using monthly data so the trends are actually for 204- and 360-month periods.
ABOUT THE GRAPHS IN THIS POST
This post does NOT present graphs of sea surface temperature anomalies, with the exception of Figures 2 and 3, which are provided as references. The graphs in this post present 17-year and 30-year linear trends of Sea Surface Temperature anomalies in Deg C per Decade on a monthly basis, and they cover the period of January 1900 to August 2011 for the observation-based Sea Surface data and the period of January 1900 to December 2099 for the model mean hindcasts and projections. Figure 1 is a sample graph of the 360-month (30-year) trends for the observations, and it includes descriptions of a few of the data points. Basically, the first data point represents the linear trend of the Sea Surface Temperature anomalies for the period of January 1900 to December 1929, and the second data point shows the linear trend of the data for the period of February 1900 to January 1930, and so on, until the last data point that covers the most recent 360-month (30-year) period of September 1981 to August 2011.
Note also how the trends vary on a multidecadal basis. The model-mean data do not produce these variations, as you shall see. And you’ll also see why they should, because they are important. Observed trends are dropping, but the model mean trends are not.
I’ve provided the following two comparisons of the “raw” Sea Surface Temperature anomalies and the 360-month (Figure 2) and 204-month (Figure 3) trends as references.
COMPARISONS OF SEA SURFACE TEMPERATURE ANOMALY TRENDS OF CLIMATE MODEL OUTPUTS AND INSTRUMENT-BASED OBSERVATIONS
In each of the following graphs, I’ve included the following notes. The first one reads,
The Models Do Not Produce Multidecadal Variations In Sea Surface Temperature Anomalies Comparable To Those Observed, Because They Are Not Initialized To Do So. This, As It Should Be, Is Also Evident In Trends.
And since those notes in red are the same for Figure 4 through 9, you’ll probably elect to overlook them. The other note on each of the graphs describes the difference between the observed trends for the most recent period and the trends hindcast and projected by the models. And they are significant, so don’t overlook those notes.
There’s no reason for me to repeat what’s discussed in the notes on the graphs, so I’ll present the comparisons of the 360-month and 204-month trends first for Global Sea Surface Temperature anomalies, then for the Northern Hemisphere data, and finally for the Southern Hemisphere Sea Surface Temperature anomaly data. Some of you may find the results surprising.
GLOBAL SEA SURFACE TEMPERATURE COMPARISONS
NORTHERN HEMISPHERE SEA SURFACE TEMPERATURE COMPARISONS
SOUTHERN HEMISPHERE SEA SURFACE TEMPERATURE COMPARISONS
Table 1 shows the observed Global and Hemispheric Sea Surface Temperature anomaly trends, 204-Month (17-Year) and 360-Month (30-Year), for period ending August 2011. Also illustrated are the trends for the Sea Surface Temperature anomalies as hindcast and projected by the model mean of the coupled climate models employed in the IPCC AR4.
Comparing the 204-month and 360-month hindcast and projected Sea Surface Temperature anomaly trends of the coupled climate models used in the IPCC AR4 to the trends of the observed Sea Surface Temperature anomalies is yet another way to show the models have no shown no skill at replicating and projecting past and present variations in Sea Surface Temperature on multidecadal bases. Why should we believe they have any value as a means of projecting future climate?
Both the HADISST Sea Surface Temperature data and the IPCC AR4 Hindcast/Projection (TOS) data used in this post are available through the KNMI Climate Explorer. The HADISST data is found at the Monthly observations webpage, and the model data is found at the Monthly CMIP3+ scenario runswebpage.