Monday, 5 March 2012

30 year trend

We have earlier commented on trends in temperature (When is a trend not a trend?) Here we look quite simply at the 30-year trend line from three different temperature data sets and a 23-model ensemble hind-cast/projection. The trends were calculated using LINEST function in Excel. The year shown in the chart is the final year of each 30-year regression period. As can be seen the 30-year trend is positive for most of the last hundred or so years. It reached a peak in 2004 or 2005, depending on the data series, and has since declined slightly. Whilst the three data sets, not surprisingly, show very similar trends, the modelled trends are quite different. 

Since 1883 there has been a peak or a trough in the trend line roughly every 30 years. Your guess as to what will happen in the future is as good as mine.

On 25 March 2012, the above paragraph was hanged with '30' replacing '25. The following was also added.

In the next graph we look at the 30-ear trend  for 7 models. The choice of models was based on those listed on Table 6 of the IPCC “General Guidelines on the Use of Scenario Data for Climate Impact and Adaptation Assessment”, Version 2, June 2007.  Where a model has more than one published simulation its results were average before being include in the graph. The siulation results come from the climate explorer site. 

 Elswhere we have shown the results of  the same seven models. Showing the difference as 30-year trends appears to demonstrate how widely different the simulations of the models were.


Carl Greeff said...

I think it would be interesting to graph the same thing for the individual model runs, rather than just the ensemble average. Then one would get a feel for how big the unforced fluctuations are, at least in the models.

Administrator said...

I've done what you suggested and it does indeed shown that the models give widely different results.

Carl Greeff said...

Well, this is not exactly what I was asking for. Ideally, one would show several realizations of the same model with different initial conditions. The point is that some aspects of the dynamics are chaotic, so, even if the model has perfect physics, you do not expect it to match the observed data. The best it can do is to match the trend and statistical aspects of the fluctuations.

What you show is good enough, though, to illustrate that there is nothing unusual in the fluctuations of the data (for instance the fact that there are periods of negative trend) compared to the models.