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Compound Wet/Windy Extremes in Australian Observational and Reanalysis Datasets.

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Title: Compound Wet/Windy Extremes in Australian Observational and Reanalysis Datasets.
Authors: Pepler, Acacia1 (AUTHOR) acacia.pepler@bom.gov.au, Dowdy, Andrew2,3 (AUTHOR)
Source: Journal of Climate. Dec2025, Vol. 38 Issue 23, p6929-6942. 14p.
Subjects: Rainfall, Windstorms, Extreme weather, Thunderstorms, Empirical research, Climate change
Geographic Terms: Australia
Abstract: The co-occurrence of extreme rain with extreme wind can result in enhanced impacts, and there is interest in understanding their occurrence, drivers, and potential changes. These compound events are frequently identified based on the co-occurrence of values above a locally defined extreme of the distribution, allowing them to be easily translated between datasets. In this study, we instead use consistent, impact-informed thresholds for daily maximum hourly rainfall and daily maximum wind gusts based on hourly station data from Australia, to better identify extreme events more likely to be associated with damaging impacts. Using this dataset, we evaluate the ability of three reanalyses with different spatial resolutions to identify wet/windy compound events and find that the global 0.25° ERA5 reanalysis underestimates the frequency of wet/windy compound extremes in tropical regions including those linked to thunderstorm activity when compared to observational data or a 0.04°-resolution regional reanalysis. These results highlight important uncertainties in global analyses and projections of wet/windy extremes when using datasets that do not resolve convective-scale processes. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Climate is the property of American Meteorological Society and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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PubType: Academic Journal
PubTypeId: academicJournal
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  Data: Compound Wet/Windy Extremes in Australian Observational and Reanalysis Datasets.
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  Data: <searchLink fieldCode="AR" term="%22Pepler%2C+Acacia%22">Pepler, Acacia</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> acacia.pepler@bom.gov.au</i><br /><searchLink fieldCode="AR" term="%22Dowdy%2C+Andrew%22">Dowdy, Andrew</searchLink><relatesTo>2,3</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Climate%22">Journal of Climate</searchLink>. Dec2025, Vol. 38 Issue 23, p6929-6942. 14p.
– Name: Subject
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  Data: <searchLink fieldCode="DE" term="%22Rainfall%22">Rainfall</searchLink><br /><searchLink fieldCode="DE" term="%22Windstorms%22">Windstorms</searchLink><br /><searchLink fieldCode="DE" term="%22Extreme+weather%22">Extreme weather</searchLink><br /><searchLink fieldCode="DE" term="%22Thunderstorms%22">Thunderstorms</searchLink><br /><searchLink fieldCode="DE" term="%22Empirical+research%22">Empirical research</searchLink><br /><searchLink fieldCode="DE" term="%22Climate+change%22">Climate change</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22Australia%22">Australia</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: The co-occurrence of extreme rain with extreme wind can result in enhanced impacts, and there is interest in understanding their occurrence, drivers, and potential changes. These compound events are frequently identified based on the co-occurrence of values above a locally defined extreme of the distribution, allowing them to be easily translated between datasets. In this study, we instead use consistent, impact-informed thresholds for daily maximum hourly rainfall and daily maximum wind gusts based on hourly station data from Australia, to better identify extreme events more likely to be associated with damaging impacts. Using this dataset, we evaluate the ability of three reanalyses with different spatial resolutions to identify wet/windy compound events and find that the global 0.25° ERA5 reanalysis underestimates the frequency of wet/windy compound extremes in tropical regions including those linked to thunderstorm activity when compared to observational data or a 0.04°-resolution regional reanalysis. These results highlight important uncertainties in global analyses and projections of wet/windy extremes when using datasets that do not resolve convective-scale processes. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Journal of Climate is the property of American Meteorological Society and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1175/JCLI-D-25-0022.1
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 14
        StartPage: 6929
    Subjects:
      – SubjectFull: Rainfall
        Type: general
      – SubjectFull: Windstorms
        Type: general
      – SubjectFull: Extreme weather
        Type: general
      – SubjectFull: Thunderstorms
        Type: general
      – SubjectFull: Empirical research
        Type: general
      – SubjectFull: Climate change
        Type: general
      – SubjectFull: Australia
        Type: general
    Titles:
      – TitleFull: Compound Wet/Windy Extremes in Australian Observational and Reanalysis Datasets.
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            NameFull: Pepler, Acacia
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            NameFull: Dowdy, Andrew
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          Dates:
            – D: 01
              M: 12
              Text: Dec2025
              Type: published
              Y: 2025
          Identifiers:
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              Value: 38
            – Type: issue
              Value: 23
          Titles:
            – TitleFull: Journal of Climate
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