Imperial College London
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DrEdwardGryspeerdt

Faculty of Natural Sciences, The Grantham Institute for Climate Change

Royal Society University Research Fellow
 
 
 
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Contact

 

+44 (0)20 7594 7900e.gryspeerdt Website

 
 
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Location

 

708Huxley BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Gryspeerdt:2018:10.5194/acp-18-6157-2018,
author = {Gryspeerdt, ERI and Quaas, J and Goren, T and Klocke, D and Brueck, M},
doi = {10.5194/acp-18-6157-2018},
journal = {Atmospheric Chemistry and Physics},
pages = {6157--669},
title = {An automated cirrus classification},
url = {http://dx.doi.org/10.5194/acp-18-6157-2018},
volume = {18},
year = {2018}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Cirrus clouds play an important role in determining the radiation budget of the earth, but many of their propertiesremain uncertain, particularly their response to aerosol variations and to warming. Part of the reason for this uncertainty isthe dependence of cirrus cloud properties on the cloud formation mechanism, which itself is strongly dependent on the localmeteorological conditions.In this work, a classification system (Identification and Classification of Cirrus or IC-CIR) is introduced to identify cirrusclouds by the cloud formation mechanism. Using re-analysis and satellite data, cirrus clouds are separated in four main types:orographic, frontal, convective and synoptic. Through a comparison to convection-permitting model simulations and back-trajectory based analysis, it is shown that these observation-based regimes can provide extra information on the cloud scaleupdraughts and the frequency of occurrence of liquid-origin ice, with the convective regime having higher updraughts and agreater occurrence of liquid-origin ice compared to the synoptic regimes. Despite having different cloud formation mecha-nisms, the radiative properties of the regimes are not distinct, indicating that retrieved cloud properties alone are insufficient tocompletely describe them.This classification is designed to be easily implemented in GCMs, helping improve future model-observation comparisonsand leading to improved parametrisations of cirrus cloud processes
AU  - Gryspeerdt,ERI
AU  - Quaas,J
AU  - Goren,T
AU  - Klocke,D
AU  - Brueck,M
DO  - 10.5194/acp-18-6157-2018
EP  - 669
PY  - 2018///
SN  - 1680-7316
SP  - 6157
TI  - An automated cirrus classification
T2  - Atmospheric Chemistry and Physics
UR  - http://dx.doi.org/10.5194/acp-18-6157-2018
UR  - http://hdl.handle.net/10044/1/57602
VL  - 18
ER  -
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