IDEAS home Printed from https://ideas.repec.org/a/taf/japsta/v46y2019i2p286-303.html
   My bibliography  Save this article

Investigating precipitation extremes in South Carolina with focus on the state's October 2015 precipitation event

Author

Listed:
  • Brook T. Russell

Abstract

The October 2015 precipitation event in the Southeastern United States brought large amounts of rainfall to South Carolina, with particularly heavy amounts in Charleston and Columbia. The subsequent flooding resulted in numerous casualties and hundreds of millions of dollars in property damage. Precipitation levels were so severe that media outlets and government agencies labeled this storm as a 1 in 1000-year event in parts of the state. Two points of discussion emerged as a result of this event. The first was related to understanding the degree to which this event was anomalous; the second was related to understanding whether precipitation extremes in South Carolina have changed over recent time. In this work, 50 years of daily precipitation data at 28 locations are used to fit a spatiotemporal hierarchical model, with the ultimate goal of addressing these two points of discussion. Bayesian inference is used to estimate return levels and to perform a severity-area-frequency analysis, and it is determined that precipitation levels related to this event were atypical throughout much of the state, but were particularly unusual in the Columbia area. This analysis also finds marginal evidence in favor of the claim that precipitation extremes in the Carolinas have become more intense over the last 50 years.

Suggested Citation

  • Brook T. Russell, 2019. "Investigating precipitation extremes in South Carolina with focus on the state's October 2015 precipitation event," Journal of Applied Statistics, Taylor & Francis Journals, vol. 46(2), pages 286-303, January.
  • Handle: RePEc:taf:japsta:v:46:y:2019:i:2:p:286-303
    DOI: 10.1080/02664763.2018.1477926
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/02664763.2018.1477926
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/02664763.2018.1477926?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Palakorn Seenoi & Piyapatr Busababodhin & Jeong-Soo Park, 2020. "Bayesian Inference in Extremes Using the Four-Parameter Kappa Distribution," Mathematics, MDPI, vol. 8(12), pages 1-22, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:japsta:v:46:y:2019:i:2:p:286-303. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/CJAS20 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.