No Cover Image

Journal article 879 views 194 downloads

Spatial Variation of Extreme Rainfall Observed From Two Century‐Long Datasets

Han Wang, Yunqing Xuan Orcid Logo

Geophysical Research Letters, Volume: 48, Issue: 8

Swansea University Authors: Han Wang, Yunqing Xuan Orcid Logo

  • 55563.pdf

    PDF | Version of Record

    © 2021. The Authors. This is an open access article under the terms of the Creative Commons Attribution License

    Download (2.58MB)

Check full text

DOI (Published version): 10.1029/2020gl091933

Abstract

This paper presents the spatial variation of area‐orientated annual maximum daily rainfall (AMDR), represented by well‐fitted generalized extreme value (GEV) distributions, over the last century in Great Britain (GB) and Australia (AU) with respect to three spatial properties: geographic locations,...

Full description

Published in: Geophysical Research Letters
ISSN: 0094-8276 1944-8007
Published: American Geophysical Union (AGU) 2021
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa55563
Tags: Add Tag
No Tags, Be the first to tag this record!
Abstract: This paper presents the spatial variation of area‐orientated annual maximum daily rainfall (AMDR), represented by well‐fitted generalized extreme value (GEV) distributions, over the last century in Great Britain (GB) and Australia (AU) with respect to three spatial properties: geographic locations, sizes, and shapes of the region‐of‐interest (ROI). The results show that the spatial variation of GEV location‐scale parameters is dominated by geographic locations and area sizes. In GB, there is an eastward‐decreasing banded pattern compared with a concentrically increasing pattern from the middle to coasts in AU. The parameters tend to decrease with increased area sizes in both studied regions. Although the impact of the ROI shapes is insignificant, the round‐shaped regions usually have higher‐valued parameters than the elongated ones. These findings provide a new perspective to understand the heterogeneity of extreme rainfall distribution over space driven by the complex interactions between climate, geographical features, and the practical sampling approaches.
College: Faculty of Science and Engineering
Funders: The authors would like to thank the Center of Hydrology and Ecology (CEH) and The Bureau of Meteorology, AU for providing the datasets, which are available in public domain online at https://doi.org/10.5285/33604ea0-c238- 4488-813d-0ad9ab7c51ca for the GEAR data set and http://www.bom.gov.au/jsp/awap/rain/index.jsp for the ADAM data set. This research is supported by the Chinese Scholarship Council and the College of Engineering, Swansea University, UK via their PhD scholarships offered to the co-author Han Wang and the Academy of Medical Sciences GCRF Networking Grant (REF: GCRFNGR4_1165) which are gratefully acknowledged.
Issue: 8