The Cloud_cci simulator v1.0 for the Cloud_cci climate data record and its application to a global and a regional climate model
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Published:2019-02-22
Issue:2
Volume:12
Page:829-847
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ISSN:1991-9603
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Container-title:Geoscientific Model Development
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language:en
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Short-container-title:Geosci. Model Dev.
Author:
Eliasson SalomonORCID, Karlsson Karl Göran, van Meijgaard Erik, Meirink Jan FokkeORCID, Stengel MartinORCID, Willén Ulrika
Abstract
Abstract. The Cloud Climate Change Initiative (Cloud_cci) satellite simulator has been
developed to enable comparisons between the Cloud_cci climate data record
(CDR) and climate models. The Cloud_cci simulator is applied here to the
EC-Earth global climate model as well as the Regional Atmospheric Climate
Model (RACMO) regional climate model. We demonstrate the importance of using
a satellite simulator that emulates the retrieval process underlying the CDR
as opposed to taking the model output directly. The impact of not sampling
the model at the local overpass time of the polar-orbiting satellites used to
make the dataset was shown to be large, yielding up to 100 % error in
liquid water path (LWP) simulations in certain regions. The simulator removes
all clouds with optical thickness smaller than 0.2 to emulate the Cloud_cci
CDR's lack of sensitivity to very thin clouds. This reduces total cloud
fraction (TCF) globally by about 10 % for EC-Earth and by a few percent
for RACMO over Europe. Globally, compared to the Cloud_cci CDR, EC-Earth is
shown to be mostly in agreement on the distribution of clouds and their
height, but it generally underestimates the high cloud fraction associated
with tropical convection regions, and overestimates the occurrence and height
of clouds over the Sahara and the Arabian subcontinent. In RACMO, TCF is
higher than retrieved over the northern Atlantic Ocean but lower than
retrieved over the European continent, where in addition the cloud top
pressure (CTP) is underestimated. The results shown here demonstrate again
that a simulator is needed to make meaningful comparisons between modeled and
retrieved cloud properties. It is promising to see that for (nearly) all
cloud properties the simulator improves the agreement of the model with the
satellite data.
Funder
Swedish National Space Agency
Publisher
Copernicus GmbH
Reference66 articles.
1. Balsamo, G., Beljaars, A., Scipal, K., Viterbo, P., van den Hurk, B.,
Hirschi,
M., and Betts, A. K.: A Revised Hydrology for the ECMWF Model: Verification
from Field Site to Terrestrial Water Storage and Impact in the Integrated
Forecast System, J. Hydrometeorol., 10, 623–643, https://doi.org/10.1175/2008JHM1068.1, 2009. a 2. Ban-Weiss, G. A., Jin, L., Bauer, S. E., Bennartz, R., Liu, X., Zhang, K.,
Ming, Y., Guo, H., and Jiang, J. H.: Evaluating clouds, aerosols, and their
interactions in three global climate models using satellite simulators and
observations, J. Geophys. Res., 119, 10876–10901, https://doi.org/10.1002/2014JD021722, 2014. a 3. Baró, R., Jiménez-Guerrero, P., Stengel, M., Brunner, D., Curci, G.,
Forkel, R., Neal, L., Palacios-Peña, L., Savage, N., Schaap, M.,
Tuccella, P., Denier van der Gon, H., and Galmarini, S.: Evaluating cloud
properties in an ensemble of regional online coupled models against satellite
observations, Atmos. Chem. Phys., 18, 15183–15199,
https://doi.org/10.5194/acp-18-15183-2018, 2018. a 4. Bechtold, P., Semane, N., Lopez, P., Chaboureau, J.-P., Beljaars, A., and
Bormann, N.: Representing Equilibrium and Nonequilibrium Convection in
Large-Scale Models, J. Atmos. Sci., 71, 734–753, https://doi.org/10.1175/JAS-D-13-0163.1, 2014. a 5. Bodas-Salcedo, A., Webb, M. J., Bony, S., Chepfer, H., Dufresne, J.-L.,
Klein,
S. A., Zhang, Y., Marchand, R., Haynes, J. M., Pincus, R., and John, V. O.:
COSP: satellite simulation software for model assessment, B. Am.
Meteorol. Soc., 92, 1023–1043, https://doi.org/10.1175/2011BAMS2856.1, 2011. a
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