1 / 15

Impact of Short-term Platform-like Inhomogeneities on Climate Time Series Detection

This study investigates the prevalence and implications of short-term platform-like inhomogeneities (IHs) in observed climatic time series. Our experiments reveal that despite their brief durations and small magnitudes, these IHs significantly influence IH detection outcomes. The frequency of detected IHs differs between simulated and observed datasets, and these subtle inhomogeneities introduce a unique form of noise that complicates homogenization efforts. Understanding and incorporating these IHs into simulation datasets is crucial for improving the accuracy of homogenization methodologies.

analu
Télécharger la présentation

Impact of Short-term Platform-like Inhomogeneities on Climate Time Series Detection

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Short-term, platform-like inhomogeneities in observed climatic time seriesPeter DomonkosCentre for Climate ChangeUniversity Rovira i Virgili, Tortosa,Spain

  2. 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.

  3. Connection between real and detected IHs: 5 shifts per 100 years

  4. Connection between real and detected IHs: 5 platforms per 100 years

  5. Standard Dataset: Statistical properties of detected IHs are similar to the ones detected in real temperature time series

  6. 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.

  7. Statistics of detection frequency 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.

  8. 1 break per time-series (100 years), M = 3.5σ

  9. 5 breaks per 100 years, Mmean= 3.5

  10. 5 platforms per 100 years, Mmean= 3.5

  11. Standard Dataset

  12. 5 platforms per 100 years, Mmean= 1

  13. Frequency of detecting at least one IH per time series

  14. 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.

  15. Thank you for your attention!

More Related