Research

SAX-Quantile Based Multiresolution Approach for Finding Heatwave Events in Summer Temperature Time Series


Reference:

Herrera, M., Ferreira, A. A., Coley, D. and de Aquino, R. R. B., 2016. SAX-Quantile Based Multiresolution Approach for Finding Heatwave Events in Summer Temperature Time Series. AI Communications, 29 (6), pp. 725-732.

Related documents:

[img]
Preview
PDF (aicom_16-467) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Download (155kB) | Preview

    Official URL:

    https://doi.org/10.3233/AIC-160716

    Abstract

    Time series pattern discovery is of great importance in a large variety of environmental and engineering applications, from supporting predictive models to helping to understand hidden underlying processes. This work develops a multiresolution time series method for extracting patterns in weather records, particular temperature data. The topic is important, as, given a warming climate, morbidity and mortality are expected to rise as heatwave frequency and intensity increase. By analysing summer temperature quantiles at different levels of coarseness, it was found that compounding models can contain a complete description of severe weather events. This new multiresolution quantile approach is developed as an extension of the symbolic aggregate approximation of the temperature time series in which quantiles are computed at every stretch of the piecewise partition. The process is iterated at different scales of the partition, and it was found to be a very useful approach for finding patterns related to both heatwave periods and intensities. The method is successfully tested using real weather records from Brazil (Recife) and the UK (London), and it was found that in both locations heatwave intensity and frequency are increasing at a substantial rate. In addition, it was found that the rate of increase in intensity of the heatwaves is far outstripping the rate of increase in mean summer temperature: by a factor of 2 in Recife and a factor of 6 in London. The approach will be of use to those looking at the impact of future climates on civil engineering, water resources, energy use, agriculture and health care, or those looking for sustained extreme events in any time series.

    Details

    Item Type Articles
    CreatorsHerrera, M., Ferreira, A. A., Coley, D. and de Aquino, R. R. B.
    DOI10.3233/AIC-160716
    DepartmentsFaculty of Engineering & Design > Architecture & Civil Engineering
    Research CentresCentre for Doctoral Training in Decarbonisation of the Built Envinronment (dCarb)
    EPSRC Centre for Doctoral Training in Statistical Mathematics (SAMBa)
    RefereedYes
    StatusPublished
    ID Code52480

    Export

    Actions (login required)

    View Item

    Document Downloads

    More statistics for this item...