Spring frost risk in a changing climate

While both the mean and variance of daily temperature are forecasted to increase in future climate scenarios, studies of spring frost risk to vegetation have relied on changes in mean temperature to understand frost risk in these scenarios. We present a probabilistic model of spring frost risk based...

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Main Authors: J. R. Rigby, Amilcare Porporato
Format: Article
Language:English
Published: Wiley 2008-06-01
Series:Geophysical Research Letters
Subjects:
Online Access:https://doi.org/10.1029/2008GL033955
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author J. R. Rigby
Amilcare Porporato
author_facet J. R. Rigby
Amilcare Porporato
author_sort J. R. Rigby
collection DOAJ
description While both the mean and variance of daily temperature are forecasted to increase in future climate scenarios, studies of spring frost risk to vegetation have relied on changes in mean temperature to understand frost risk in these scenarios. We present a probabilistic model of spring frost risk based on the stochastic‐crossing properties of a coupled temperature‐phenology model in which the mean, variance, and autocorrelation structure of spring temperature may be controlled through independent parameters. The model results show that frost risk to vegetation is as sensitive to increases in daily temperature variance (which increases frost risk) as to increases in the mean temperature (which decreases frost risk).
format Article
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institution OA Journals
issn 0094-8276
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language English
publishDate 2008-06-01
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series Geophysical Research Letters
spelling doaj-art-c34f7e81d8e44da0996df950daf95af52025-08-20T01:52:19ZengWileyGeophysical Research Letters0094-82761944-80072008-06-013512n/an/a10.1029/2008GL033955Spring frost risk in a changing climateJ. R. Rigby0Amilcare Porporato1Department of Civil and Environmental Engineering Duke University Durham North Carolina USADepartment of Civil and Environmental Engineering Duke University Durham North Carolina USAWhile both the mean and variance of daily temperature are forecasted to increase in future climate scenarios, studies of spring frost risk to vegetation have relied on changes in mean temperature to understand frost risk in these scenarios. We present a probabilistic model of spring frost risk based on the stochastic‐crossing properties of a coupled temperature‐phenology model in which the mean, variance, and autocorrelation structure of spring temperature may be controlled through independent parameters. The model results show that frost risk to vegetation is as sensitive to increases in daily temperature variance (which increases frost risk) as to increases in the mean temperature (which decreases frost risk).https://doi.org/10.1029/2008GL033955phenologyclimate change
spellingShingle J. R. Rigby
Amilcare Porporato
Spring frost risk in a changing climate
Geophysical Research Letters
phenology
climate change
title Spring frost risk in a changing climate
title_full Spring frost risk in a changing climate
title_fullStr Spring frost risk in a changing climate
title_full_unstemmed Spring frost risk in a changing climate
title_short Spring frost risk in a changing climate
title_sort spring frost risk in a changing climate
topic phenology
climate change
url https://doi.org/10.1029/2008GL033955
work_keys_str_mv AT jrrigby springfrostriskinachangingclimate
AT amilcareporporato springfrostriskinachangingclimate