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Dynamic amplification of extreme precipitation sensitivity

A useful starting hypothesis for predictions of changes in precipitation extremes with climate is that those extremes increase at the same rate as atmospheric moisture does, which is [Formula: see text] following the Clausius–Clapeyron (CC) relation. This hypothesis, however, neglects potential chan...

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Detalles Bibliográficos
Autores principales: Nie, Ji, Sobel, Adam H., Shaevitz, Daniel A., Wang, Shuguang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: National Academy of Sciences 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6156684/
https://www.ncbi.nlm.nih.gov/pubmed/30181273
http://dx.doi.org/10.1073/pnas.1800357115
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author Nie, Ji
Sobel, Adam H.
Shaevitz, Daniel A.
Wang, Shuguang
author_facet Nie, Ji
Sobel, Adam H.
Shaevitz, Daniel A.
Wang, Shuguang
author_sort Nie, Ji
collection PubMed
description A useful starting hypothesis for predictions of changes in precipitation extremes with climate is that those extremes increase at the same rate as atmospheric moisture does, which is [Formula: see text] following the Clausius–Clapeyron (CC) relation. This hypothesis, however, neglects potential changes in the strengths of atmospheric circulations associated with precipitation extremes. As increased moisture leads to increased precipitation, the increased latent heating may lead to stronger large-scale ascent and thus, additional increase in precipitation, leading to a super-CC scaling. This study investigates this possibility in the context of the 2015 Texas extreme precipitation event using the Column Quasi-Geostrophic (CQG) method. Analogs to this event are simulated in different climatic conditions with varying surface temperature ([Formula: see text]) given the same adiabatic quasigeostrophic forcing. Precipitation in these events exhibits super-CC scaling due to the dynamic contribution associated with increasing ascent due to increased latent heating, an increase with importance that increases with [Formula: see text]. The thermodynamic contribution (attributable to increasing water vapor; assuming no change in vertical motion) approximately follows CC as expected, while vertical structure changes of moisture and diabatic heating lead to negative but secondary contributions to the sensitivity, reducing the rate of increase.
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spelling pubmed-61566842018-09-27 Dynamic amplification of extreme precipitation sensitivity Nie, Ji Sobel, Adam H. Shaevitz, Daniel A. Wang, Shuguang Proc Natl Acad Sci U S A Physical Sciences A useful starting hypothesis for predictions of changes in precipitation extremes with climate is that those extremes increase at the same rate as atmospheric moisture does, which is [Formula: see text] following the Clausius–Clapeyron (CC) relation. This hypothesis, however, neglects potential changes in the strengths of atmospheric circulations associated with precipitation extremes. As increased moisture leads to increased precipitation, the increased latent heating may lead to stronger large-scale ascent and thus, additional increase in precipitation, leading to a super-CC scaling. This study investigates this possibility in the context of the 2015 Texas extreme precipitation event using the Column Quasi-Geostrophic (CQG) method. Analogs to this event are simulated in different climatic conditions with varying surface temperature ([Formula: see text]) given the same adiabatic quasigeostrophic forcing. Precipitation in these events exhibits super-CC scaling due to the dynamic contribution associated with increasing ascent due to increased latent heating, an increase with importance that increases with [Formula: see text]. The thermodynamic contribution (attributable to increasing water vapor; assuming no change in vertical motion) approximately follows CC as expected, while vertical structure changes of moisture and diabatic heating lead to negative but secondary contributions to the sensitivity, reducing the rate of increase. National Academy of Sciences 2018-09-18 2018-09-04 /pmc/articles/PMC6156684/ /pubmed/30181273 http://dx.doi.org/10.1073/pnas.1800357115 Text en Copyright © 2018 the Author(s). Published by PNAS. https://creativecommons.org/licenses/by-nc-nd/4.0/ This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Physical Sciences
Nie, Ji
Sobel, Adam H.
Shaevitz, Daniel A.
Wang, Shuguang
Dynamic amplification of extreme precipitation sensitivity
title Dynamic amplification of extreme precipitation sensitivity
title_full Dynamic amplification of extreme precipitation sensitivity
title_fullStr Dynamic amplification of extreme precipitation sensitivity
title_full_unstemmed Dynamic amplification of extreme precipitation sensitivity
title_short Dynamic amplification of extreme precipitation sensitivity
title_sort dynamic amplification of extreme precipitation sensitivity
topic Physical Sciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6156684/
https://www.ncbi.nlm.nih.gov/pubmed/30181273
http://dx.doi.org/10.1073/pnas.1800357115
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