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Spatial Variation of Extreme Rainfall Observed From Two Century‐Long Datasets
Geophysical Research Letters, Volume: 48, Issue: 8
Swansea University Authors: Han Wang, Yunqing Xuan
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DOI (Published version): 10.1029/2020gl091933
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,...
|Published in:||Geophysical Research Letters|
American Geophysical Union (AGU)
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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.
Faculty of Science and Engineering
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.