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| Titel |
In search of the best match: probing a multi-dimensional cloud microphysical parameter space to better understand what controls cloud thermodynamic phase |
| VerfasserIn |
Ivy Tan, Trude Storelvmo |
| Konferenz |
EGU General Assembly 2015
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 17 (2015) |
| Datensatznummer |
250114509
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| Publikation (Nr.) |
 EGU/EGU2015-15297.pdf |
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| Zusammenfassung |
| Substantial improvements have been made to the cloud microphysical schemes used in the
latest generation of global climate models (GCMs), however, an outstanding weakness of
these schemes lies in the arbitrariness of their tuning parameters, which are also notoriously
fraught with uncertainties. Despite the growing effort in improving the cloud microphysical
schemes in GCMs, most of this effort has neglected to focus on improving the ability of
GCMs to accurately simulate the present-day global distribution of thermodynamic phase
partitioning in mixed-phase clouds. Liquid droplets and ice crystals not only influence the
Earth’s radiative budget and hence climate sensitivity via their contrasting optical properties,
but also through the effects of their lifetimes in the atmosphere. The current study
employs NCAR’s CAM5.1, and uses observations of cloud phase obtained by NASA’s
CALIOP lidar over a 79-month period (November 2007 to June 2014) guide the
accurate simulation of the global distribution of mixed-phase clouds in 20∘ latitudinal
bands at the -10∘ C, -20∘C and -30∘C isotherms, by adjusting six relevant cloud
microphysical tuning parameters in the CAM5.1 via Quasi-Monte Carlo sampling.
Among the parameters include those that control the Wegener-Bergeron-Findeisen
(WBF) timescale for the conversion of supercooled liquid droplets to ice and snow in
mixed-phase clouds, the fraction of ice nuclei that nucleate ice in the atmosphere, ice
crystal sedimentation speed, and wet scavenging in stratiform and convective clouds.
Using a Generalized Linear Model as a variance-based sensitivity analysis, the
relative contributions of each of the six parameters are quantified to gain a better
understanding of the importance of their individual and two-way interaction effects on the
liquid to ice proportion in mixed-phase clouds. Thus, the methodology implemented
in the current study aims to search for the combination of cloud microphysical
parameters in a GCM that produce the most accurate reproduction of observations of
cloud thermodynamic phase, while simultaneously assessing the weaknesses of the
parameterizations in the model. We find that the simulated proportion of liquid to
ice in mixed-phase clouds is dominated by the fraction of active ice nuclei in the
atmosphere and the WBF timescale. In a follow-up to this study, we apply these
results to a fully-coupled GCM, CESM, and find that cloud thermodynamic phase
has profound ramifications for the uncertainty associated with climate sensitivity
estimates. |
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