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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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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