Explorative analysis of long time series of very high resolution spatial rainfall

Emma Dybro Thomassen, Hjalte Jomo Danielsen Sørup, Marc Scheibel, Thomas Einfalt, Karsten Arnbjerg-Nielsen

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    We examine rainfall characteristics of convective and front extreme events in high spatio-temporal resolution (5 minutes, 1x1 km) over an area of 1824 km2 covering the catchment of the Wupperverband, North Rhine-Westphalia. The main focus of the analysis is a description of the complexity of hourly and daily extreme rainfall with the purpose of identifying suitable characteristics that can be used in a spatial weather generator of similar resolution. The spatial and temporal properties of the extreme events are explored by means of principal component analysis, cluster analysis, and linear models. For each method a set of 17 variables are used to describe the properties of each event, e.g. duration, maximum volumes, spatial coverage and heterogeneity, and movement of cells. A total of 5-9 dimensions can be found in the data, which can be interpreted as a rough indication of how many independent variables a weather generator should employ. Both principal component analysis and cluster analysis show patterns that are in accordance with our understanding of physical properties of rainfall. In particular it seems that the differences between hourly and daily extremes can be described by relatively simple scaling across the set of variables, i.e. the level of each variable varies signicantly, but not the overall structure of the spatial precipitation. The analysis show that there is a good potential for making a spatial weather generator for high spatio-temporal precipitation for precipitation extremes. Before the method can be employed further work is necessary to describe non-linear correlation between the variables and also the tracking algorithm employed needs to be improved.
    Original languageEnglish
    Title of host publicationStochastic weather generators for hydrological applications - workshop book
    Place of PublicationBerlin, Germany
    PublisherFreie Universität Berlin
    Publication date2017
    Publication statusPublished - 2017
    EventStochastic Weather Generators for Hydrological Applications - Berlin, Germany
    Duration: 18 Sept 201720 Sept 2017


    WorkshopStochastic Weather Generators for Hydrological Applications


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