Photolysis rates in correlated overlapping cloud fields: Cloud-J 7.3c

A new approach for modeling photolysis rates (<i>J</i> values) in atmospheres with fractional cloud cover has been developed and is implemented as Cloud-J – a multi-scattering eight-stream radiative transfer model for solar radiation based on Fast-J. Using observations of the vertical co...

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Main Author: M. J. Prather
Format: Article
Language:English
Published: Copernicus Publications 2015-08-01
Series:Geoscientific Model Development
Online Access:http://www.geosci-model-dev.net/8/2587/2015/gmd-8-2587-2015.pdf
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spelling doaj-02cc600b3adb4dc88d1c873183e7d10c2020-11-24T21:55:18ZengCopernicus PublicationsGeoscientific Model Development1991-959X1991-96032015-08-01882587259510.5194/gmd-8-2587-2015Photolysis rates in correlated overlapping cloud fields: Cloud-J 7.3cM. J. Prather0Earth System Science Department, University of California, Irvine, California, USAA new approach for modeling photolysis rates (<i>J</i> values) in atmospheres with fractional cloud cover has been developed and is implemented as Cloud-J – a multi-scattering eight-stream radiative transfer model for solar radiation based on Fast-J. Using observations of the vertical correlation of cloud layers, Cloud-J 7.3c provides a practical and accurate method for modeling atmospheric chemistry. The combination of the new maximum-correlated cloud groups with the integration over all cloud combinations by four quadrature atmospheres produces mean <i>J</i> values in an atmospheric column with root mean square (rms) errors of 4 % or less compared with 10–20 % errors using simpler approximations. Cloud-J is practical for chemistry–climate models, requiring only an average of 2.8 Fast-J calls per atmosphere vs. hundreds of calls with the correlated cloud groups, or 1 call with the simplest cloud approximations. Another improvement in modeling <i>J</i> values, the treatment of volatile organic compounds with pressure-dependent cross sections, is also incorporated into Cloud-J.http://www.geosci-model-dev.net/8/2587/2015/gmd-8-2587-2015.pdf
collection DOAJ
language English
format Article
sources DOAJ
author M. J. Prather
spellingShingle M. J. Prather
Photolysis rates in correlated overlapping cloud fields: Cloud-J 7.3c
Geoscientific Model Development
author_facet M. J. Prather
author_sort M. J. Prather
title Photolysis rates in correlated overlapping cloud fields: Cloud-J 7.3c
title_short Photolysis rates in correlated overlapping cloud fields: Cloud-J 7.3c
title_full Photolysis rates in correlated overlapping cloud fields: Cloud-J 7.3c
title_fullStr Photolysis rates in correlated overlapping cloud fields: Cloud-J 7.3c
title_full_unstemmed Photolysis rates in correlated overlapping cloud fields: Cloud-J 7.3c
title_sort photolysis rates in correlated overlapping cloud fields: cloud-j 7.3c
publisher Copernicus Publications
series Geoscientific Model Development
issn 1991-959X
1991-9603
publishDate 2015-08-01
description A new approach for modeling photolysis rates (<i>J</i> values) in atmospheres with fractional cloud cover has been developed and is implemented as Cloud-J – a multi-scattering eight-stream radiative transfer model for solar radiation based on Fast-J. Using observations of the vertical correlation of cloud layers, Cloud-J 7.3c provides a practical and accurate method for modeling atmospheric chemistry. The combination of the new maximum-correlated cloud groups with the integration over all cloud combinations by four quadrature atmospheres produces mean <i>J</i> values in an atmospheric column with root mean square (rms) errors of 4 % or less compared with 10–20 % errors using simpler approximations. Cloud-J is practical for chemistry–climate models, requiring only an average of 2.8 Fast-J calls per atmosphere vs. hundreds of calls with the correlated cloud groups, or 1 call with the simplest cloud approximations. Another improvement in modeling <i>J</i> values, the treatment of volatile organic compounds with pressure-dependent cross sections, is also incorporated into Cloud-J.
url http://www.geosci-model-dev.net/8/2587/2015/gmd-8-2587-2015.pdf
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