A multi-diagnostic approach to cloud evaluation

Most studies evaluating cloud in general circulation models present new diagnostic techniques or observational datasets, or apply a limited set of existing diagnostics to a number of models. In this study, we use a range of diagnostic techniques and observational datasets to provide a thorough e...

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Main Authors: K. D. Williams, A. Bodas-Salcedo
Format: Article
Language:English
Published: Copernicus Publications 2017-07-01
Series:Geoscientific Model Development
Online Access:https://www.geosci-model-dev.net/10/2547/2017/gmd-10-2547-2017.pdf
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spelling doaj-4e49147108ca4cffacbb55f1afe3842f2020-11-24T23:51:54ZengCopernicus PublicationsGeoscientific Model Development1991-959X1991-96032017-07-01102547256610.5194/gmd-10-2547-2017A multi-diagnostic approach to cloud evaluationK. D. Williams0A. Bodas-Salcedo1Met Office, FitzRoy Road, Exeter, EX1 3PB, UKMet Office, FitzRoy Road, Exeter, EX1 3PB, UKMost studies evaluating cloud in general circulation models present new diagnostic techniques or observational datasets, or apply a limited set of existing diagnostics to a number of models. In this study, we use a range of diagnostic techniques and observational datasets to provide a thorough evaluation of cloud, such as might be carried out during a model development process. The methodology is illustrated by analysing two configurations of the Met Office Unified Model – the currently operational configuration at the time of undertaking the study (Global Atmosphere 6, GA6), and the configuration which will underpin the United Kingdom's Earth System Model for CMIP6 (Coupled Model Intercomparison Project 6; GA7). <br><br> By undertaking a more comprehensive analysis which includes compositing techniques, comparing against a set of quite different observational instruments and evaluating the model across a range of timescales, the risks of drawing the wrong conclusions due to compensating model errors are minimized and a more accurate overall picture of model performance can be drawn. <br><br> Overall the two configurations analysed perform well, especially in terms of cloud amount. GA6 has excessive thin cirrus which is removed in GA7. The primary remaining errors in both configurations are the in-cloud albedos which are too high in most Northern Hemisphere cloud types and sub-tropical stratocumulus, whilst the stratocumulus on the cold-air side of Southern Hemisphere cyclones has in-cloud albedos which are too low.https://www.geosci-model-dev.net/10/2547/2017/gmd-10-2547-2017.pdf
collection DOAJ
language English
format Article
sources DOAJ
author K. D. Williams
A. Bodas-Salcedo
spellingShingle K. D. Williams
A. Bodas-Salcedo
A multi-diagnostic approach to cloud evaluation
Geoscientific Model Development
author_facet K. D. Williams
A. Bodas-Salcedo
author_sort K. D. Williams
title A multi-diagnostic approach to cloud evaluation
title_short A multi-diagnostic approach to cloud evaluation
title_full A multi-diagnostic approach to cloud evaluation
title_fullStr A multi-diagnostic approach to cloud evaluation
title_full_unstemmed A multi-diagnostic approach to cloud evaluation
title_sort multi-diagnostic approach to cloud evaluation
publisher Copernicus Publications
series Geoscientific Model Development
issn 1991-959X
1991-9603
publishDate 2017-07-01
description Most studies evaluating cloud in general circulation models present new diagnostic techniques or observational datasets, or apply a limited set of existing diagnostics to a number of models. In this study, we use a range of diagnostic techniques and observational datasets to provide a thorough evaluation of cloud, such as might be carried out during a model development process. The methodology is illustrated by analysing two configurations of the Met Office Unified Model – the currently operational configuration at the time of undertaking the study (Global Atmosphere 6, GA6), and the configuration which will underpin the United Kingdom's Earth System Model for CMIP6 (Coupled Model Intercomparison Project 6; GA7). <br><br> By undertaking a more comprehensive analysis which includes compositing techniques, comparing against a set of quite different observational instruments and evaluating the model across a range of timescales, the risks of drawing the wrong conclusions due to compensating model errors are minimized and a more accurate overall picture of model performance can be drawn. <br><br> Overall the two configurations analysed perform well, especially in terms of cloud amount. GA6 has excessive thin cirrus which is removed in GA7. The primary remaining errors in both configurations are the in-cloud albedos which are too high in most Northern Hemisphere cloud types and sub-tropical stratocumulus, whilst the stratocumulus on the cold-air side of Southern Hemisphere cyclones has in-cloud albedos which are too low.
url https://www.geosci-model-dev.net/10/2547/2017/gmd-10-2547-2017.pdf
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