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BibTex format

@inproceedings{Glassmeier:2022:10.5194/ems2022-701,
author = {Glassmeier, F and Hoffmann, F and Feingold, G and Gryspeerdt, E and van, Hooft A and Yamaguchi, T and Johnson, JS and Carslaw, KS},
doi = {10.5194/ems2022-701},
title = {Gaussian-process emulation for integrating data-driven aerosol-cloud physics from simulation, satellite, and ground-based data},
url = {http://dx.doi.org/10.5194/ems2022-701},
year = {2022}
}
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TY  - CPAPER
AB  - <jats:p>&lt;p&gt;Data-driven quantification and parameterization of cloud physics in general, and of aerosol-cloud interactions in particular, rely on input data from observations or detailed simulations. These data sources have complementary limitations in terms of their spatial and temporal coverage and resolution; simulation data has the advantage of readily providing causality but cannot represent the full process complexity. In order to base data-driven approaches on comprehensive information, we therefore need ways to integrate different data sources.&amp;#160;&lt;/p&gt;&lt;p&gt;We discuss how the classical statistical technique of Gaussian-process emulation can be combined with specifically initialized ensembles of detailed cloud simulations (large-eddy simulations, LES) to provide a framework for evaluating data-driven descriptions of cloud characteristics and processes across different data sources. We specifically illustrate this approach for integrating LES and satellite data of aerosol-cloud interactions in subtropical stratocumulus cloud decks. We furthermore explore the extension of our framework to ground-based observations of Arctic mixed-phase clouds.&lt;/p&gt;&lt;p&gt;- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -&lt;/p&gt;&lt;p&gt;&lt;strong&gt;References:&lt;/strong&gt;&lt;/p&gt;&lt;ul&gt;&lt;li&gt;Glassmeier, F., F. Hoffmann, J. S. Johnson, T. Yamaguchi, K. S. Carslaw and G. Feingold (2019): &amp;#8220;An emulator approach to stratocumulus susceptibility&amp;#8221;, Atmos. Chem. Phys., 19, 10191- 10203, doi: 10.5194/acp-19-10191-2019&lt;/li&gt;&lt;li&gt;Hoffmann, F., F. Glassmeier, T. Yamaguchi and G. Feingold (2020)
AU  - Glassmeier,F
AU  - Hoffmann,F
AU  - Feingold,G
AU  - Gryspeerdt,E
AU  - van,Hooft A
AU  - Yamaguchi,T
AU  - Johnson,JS
AU  - Carslaw,KS
DO  - 10.5194/ems2022-701
PY  - 2022///
TI  - Gaussian-process emulation for integrating data-driven aerosol-cloud physics from simulation, satellite, and ground-based data
UR  - http://dx.doi.org/10.5194/ems2022-701
ER  -
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