Uncertainty in temperature variability

It is well known that there is considerable uncertainty in the projected response of climate models to increases in radiative forcing. However, there is also considerable uncertainty in the model simulated internal variability.

The top row of the figure shows the ranges in simulated variability (standard deviation) in annual mean surface air temperature from 15 GCMs – the differences are considerable – up to a factor of 9 in variance in some regions – in a similar way to global mean temperature. This can be compared to the range in the signal of response to prescribed radiative forcings at 2040 (bottom row) which is also considerable.

Both of these uncertainties play a key role in determining the signal-to-noise of any climate change, which is a key metric for climate impacts. We are uncertain in both the signal and the noise. When comparing with observations, the median model is slightly too variable in general (not shown here).

Ranges of temperature variability and signal
The 10th, 50th and 90th percentiles of simulated temperature variability (top row) and signal of temperature change in 2040 (bottom row) according to 15 CMIP3 GCMs. Note the non-linear colour scale.

About Ed Hawkins

Ed Hawkins (twitter: @ed_hawkins) is a climate scientist in NCAS-Climate at the Department of Meteorology, University of Reading. His research interests are in decadal variability and predictability of climate, especially in the Atlantic region, and in quantifying the different sources of uncertainty in climate predictions and impacts. Ed is a Contributing Author to IPCC AR5 and a member of the CLIVAR Scientific Steering Group.

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