Understanding Climate Risk

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But is it just red noise?

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I gave a seminar yesterday at the ARC Centre of Excellence for Climate System Science at the University of New South Wales. Thanks Alvin Stone and Andrea Taschetto for organising it. It’s the first time I’ve had the opportunity to go through the entire ‘step change’ hypothesis of how the climate changes, the theoretical background, structural models developed from that and how the testing was set up, prior to showing a whole raft of test results.

One of the questions I got at the end, which also comes up quite often in the literature, was about the potential cause of the step changes in temperature data. It came from a question as to whether we had tested the step change model with artificial data that had been ‘reddened’ – that is, made dependent on the previous data. Such time series can have long-term persistence and contain a number of different quasi-periodic timescales, so do not conform to a single statistical model. This line of questioning alludes to whether a step or nonlinear response in a time series needs to be have an underlying cause that can be linked to an external source or whether it’s the result of random variations (see paper by Rodionov for a more more technical description). I gave a somewhat flip answer – because there is real energy in the system we are assessing (the climate system), whether a rapid shift is due to red noise or not matters less than understanding what that means for risk.

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Written by Roger Jones

May 29, 2016 at 8:35 pm