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}
}
RIS format (EndNote, RefMan)
TY - CPAPER
AB - <jats:p><p>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.&#160;</p><p>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.</p><p>- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -</p><p><strong>References:</strong></p><ul><li>Glassmeier, F., F. Hoffmann, J. S. Johnson, T. Yamaguchi, K. S. Carslaw and G. Feingold (2019): &#8220;An emulator approach to stratocumulus susceptibility&#8221;, Atmos. Chem. Phys., 19, 10191- 10203, doi: 10.5194/acp-19-10191-2019</li><li>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 -
