Short-term, platform- like inhomogeneities in observed climatic time series Peter Domonkos Centre for Climate Change University Rovira i Virgili, Tortosa, Spain
Introduction Series of experiments show that observed climatic time series usually contain large number of platform- like inhomogeneities (IHs). These IHs mostly have short durations and relatively small magnitudes, therefore their direct detection is usually impossible. They act as a special kind of noise when the homogenizer is looking for large, persistent IHs. Platform-like IHs have considerable impact on the IH-detection results.
Connection between real and detected IHs: 5 shifts per 100 years
Connection between real and detected IHs: 5 platforms per 100 years
Standard Dataset: Statistical properties of detected IHs are similar to the ones detected in real temperature time series
Large number of small, platform- like IHs: Why? Observation-errors often persist only for limited time, because they are eliminated after their realisation. Changes in climatic gradients IHs in the components of reference series Anything is their origination: they exist when homogenizers work.
Statistics of detection frequency IH(all)IH(S)IH(all)IH(S) IH(all) Sur(temp) %0.31% 5.44% Syn(temp) %0.32% 5.98% Real(temp) %1.28% 18.80% IH(all) = all the IHs detected with ACMANT IH(S) = IHs detected with the Secondary detection The frequency of short-term IHs is lower in the simulated datasets than in the observed datasets.
1 break per time-series (100 years), M = 3.5σ
5 breaks per 100 years, M mean = 3.5
5 platforms per 100 years, M mean = 3.5
Standard Dataset
5 platforms per 100 years, M mean = 1
Frequency of detecting at least one IH per time series
Conclusions Small, platform-like IHs occur with large frequency in observed climatic time series. The presence of small, platform-like IHs changes the performance of homogenisation methods, therefore they should be present also in simulated datasets for testing the efficiencies of homogenisation methods.
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