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GMD | Articles | Volume 12, issue 2
Geosci. Model Dev., 12, 829–847, 2019
https://doi.org/10.5194/gmd-12-829-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Geosci. Model Dev., 12, 829–847, 2019
https://doi.org/10.5194/gmd-12-829-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Methods for assessment of models 22 Feb 2019

Methods for assessment of models | 22 Feb 2019

The Cloud_cci simulator v1.0 for the Cloud_cci climate data record and its application to a global and a regional climate model

Salomon Eliasson et al.
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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
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
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To enable fair comparisons of clouds between climate models and the ESA Cloud_cci climate data record (CDR), we present a tool called the Cloud_cci simulator. The tool takes into account the geometry and cloud detection capabilities of the Cloud_cci CDR to allow fair comparisons. We demonstrate the simulator on two climate models. We find the impact of time sampling has a large effect on simulated cloud water amount and that the simulator reduces the cloud cover by about 10 % globally.
To enable fair comparisons of clouds between climate models and the ESA Cloud_cci climate data...
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