Diversity in global patterns of observed precipitation variability and change on river basin scales

Diversity in global patterns of observed precipitation variability and change on river basin scales Climatic Change https://doi.org/10.1007/s10584-018-2225-z Diversity in global patterns of observed precipitation variability and change on river basin scales A conditional quantile approach 1 1 Anne M. Lausier · Shaleen Jain Received: 28 September 2017 / Accepted: 13 May 2018 © Springer Science+Business Media B.V., part of Springer Nature 2018 Abstract Comprehensive characterization of diversity in global patterns of precipitation variability and change is an important starting point for climate adaptation and resilience assessments. Capturing the nature of precipitation probability distribution functions (PDF) is critical for assessing variability and change. Conventional linear regression-based analy- ses assume that slope coefficients for the wet and dry tails of the PDF are consonant with the conditional mean trend. This assumption is not always borne out in the analyses of historical records. Given the relationship between sea surface temperature (SST) and pre- cipitation, recent trends in global SST complicate interpretations of precipitation variability and risk. In this study, changes in the PDF of annual precipitation (1951–2011) at the global river basin scale were analyzed using quantile regression (QR). QR is a flexible approach allowing for the assessment of precipitation variability conditioned on the leading empirical orthogonal function (EOF) patterns of global SST that reflect El http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Climatic Change Springer Journals

Diversity in global patterns of observed precipitation variability and change on river basin scales

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Publisher
Springer Netherlands
Copyright
Copyright © 2018 by Springer Science+Business Media B.V., part of Springer Nature
Subject
Earth Sciences; Atmospheric Sciences; Climate Change/Climate Change Impacts
ISSN
0165-0009
eISSN
1573-1480
D.O.I.
10.1007/s10584-018-2225-z
Publisher site
See Article on Publisher Site

Abstract

Climatic Change https://doi.org/10.1007/s10584-018-2225-z Diversity in global patterns of observed precipitation variability and change on river basin scales A conditional quantile approach 1 1 Anne M. Lausier · Shaleen Jain Received: 28 September 2017 / Accepted: 13 May 2018 © Springer Science+Business Media B.V., part of Springer Nature 2018 Abstract Comprehensive characterization of diversity in global patterns of precipitation variability and change is an important starting point for climate adaptation and resilience assessments. Capturing the nature of precipitation probability distribution functions (PDF) is critical for assessing variability and change. Conventional linear regression-based analy- ses assume that slope coefficients for the wet and dry tails of the PDF are consonant with the conditional mean trend. This assumption is not always borne out in the analyses of historical records. Given the relationship between sea surface temperature (SST) and pre- cipitation, recent trends in global SST complicate interpretations of precipitation variability and risk. In this study, changes in the PDF of annual precipitation (1951–2011) at the global river basin scale were analyzed using quantile regression (QR). QR is a flexible approach allowing for the assessment of precipitation variability conditioned on the leading empirical orthogonal function (EOF) patterns of global SST that reflect El

Journal

Climatic ChangeSpringer Journals

Published: Jun 4, 2018

References

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