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@unpublished{Gryspeerdt:2017:10.5194/acp-2017-723,
author = {Gryspeerdt, E and Quaas, J and Goren, T and Klocke, D and Brueck, M},
doi = {10.5194/acp-2017-723},
publisher = {Copernicus Publications},
title = {Technical note: an automated cirrus classification},
url = {http://dx.doi.org/10.5194/acp-2017-723},
year = {2017}
}

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TY  - UNPB
AB  - Cirrus clouds play an important role in determining the radiation budget of the earth, but many of their properties remain uncertain, particularly their response to aerosol variations and to warming. Part of the reason for this uncertainty is the dependence of cirrus clouds on the mechanism of formation, which itself is strongly dependent on the local meteorological conditions.In this work, a classification system (Identification and Classification of Cirrus or IC-CIR) is introduced to identify cirrus clouds by their formation mechanisms. Using re-analysis and satellite data, cirrus clouds are separated in four main types: orographic, frontal, convective and in-situ. Through a comparison to convection-permitting model simulations and back-trajectory based analysis, it is shown that the regimes can provide extra information on the properties and origin of cirrus that could not be provided by the retrieved cloud properties or reanalysis data alone. This classification is designed to be easily implemented in GCMs, helping improve future model-observation comparisons and leading to improved parametrisations of cirrus cloud processes.
AU  - Gryspeerdt,E
AU  - Quaas,J
AU  - Goren,T
AU  - Klocke,D
AU  - Brueck,M
DO  - 10.5194/acp-2017-723
PB  - Copernicus Publications
PY  - 2017///
TI  - Technical note: an automated cirrus classification
UR  - http://dx.doi.org/10.5194/acp-2017-723
UR  - http://hdl.handle.net/10044/1/57871
ER  -

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