Improving collisional growth in Lagrangian cloud models: Development and verification of a new splitting algorithm

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dc.identifier.uri http://dx.doi.org/10.15488/4246
dc.identifier.uri https://www.repo.uni-hannover.de/handle/123456789/4280
dc.contributor.author Schwenkel, Johannes
dc.contributor.author Hoffmann, Fabian
dc.contributor.author Raasch, Siegfried
dc.date.accessioned 2018-12-20T14:20:23Z
dc.date.available 2018-12-20T14:20:23Z
dc.date.issued 2018
dc.identifier.citation Schwenkel, J.; Hoffmann, F.; Raasch, S.: Improving collisional growth in Lagrangian cloud models: Development and verification of a new splitting algorithm. In: Geoscientific Model Development 11 (2018), Nr. 9, S. 3929-3944. DOI: https://doi.org/10.5194/gmd-11-3929-2018
dc.description.abstract Lagrangian cloud models (LCMs) are increasingly used in the cloud physics community. They not only enable a very detailed representation of cloud microphysics but also lack numerical errors typical for most other models. However, insufficient statistics, caused by an inadequate number of Lagrangian particles to represent cloud microphysical processes, can limit the applicability and validity of this approach. This study presents the first use of a splitting and merging algorithm designed to improve the warm cloud precipitation process by deliberately increasing or decreasing the number of Lagrangian particles under appropriate conditions. This new approach and the details of how splitting is executed are evaluated in box and single-cloud simulations, as well as a shallow cumulus test case. The results indicate that splitting is essential for a proper representation of the precipitation process. Moreover, the details of the splitting method (i.e., identifying the appropriate conditions) become insignificant for larger model domains as long as a sufficiently large number of Lagrangian particles is produced by the algorithm. The accompanying merging algorithm is essential to constrict the number of Lagrangian particles in order to maintain the computational performance of the model. Overall, splitting and merging do not affect the life cycle and domain-averaged macroscopic properties of the simulated clouds. This new approach is a useful addition to all LCMs since it is able to significantly increase the number of Lagrangian particles in appropriate regions of the clouds, while maintaining a computationally feasible total number of Lagrangian particles in the entire model domain. eng
dc.language.iso eng
dc.publisher Göttingen : Copernicus GmbH
dc.relation.ispartofseries Geoscientific Model Development 11 (2018), Nr. 9
dc.rights CC BY 4.0 Unported
dc.rights.uri https://creativecommons.org/licenses/by/4.0/
dc.subject Lagrangian cloud models (LCMs) eng
dc.subject cloud microphysics eng
dc.subject.ddc 550 | Geowissenschaften ger
dc.title Improving collisional growth in Lagrangian cloud models: Development and verification of a new splitting algorithm
dc.type article
dc.type Text
dc.relation.issn 1991959X
dc.relation.doi https://doi.org/10.5194/gmd-11-3929-2018
dc.bibliographicCitation.issue 9
dc.bibliographicCitation.volume 11
dc.bibliographicCitation.firstPage 3929
dc.bibliographicCitation.lastPage 3944
dc.description.version publishedVersion
tib.accessRights frei zug�nglich


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