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

Downloadstatistik des Dokuments (Auswertung nach COUNTER):

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

Version im Repositorium

Zum Zitieren der Version im Repositorium verwenden Sie bitte diesen DOI: https://doi.org/10.15488/4246

Zeitraum, für den die Download-Zahlen angezeigt werden:

Jahr: 
Monat: 

Summe der Downloads: 70




Kleine Vorschau
Zusammenfassung: 
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.
Lizenzbestimmungen: CC BY 4.0
Publikationstyp: article
Publikationsstatus: publishedVersion
Erstveröffentlichung: 2018
Die Publikation erscheint in Sammlung(en):Fakultät für Mathematik und Physik

Verteilung der Downloads über den gewählten Zeitraum:

Herkunft der Downloads nach Ländern:

Pos. Land Downloads
Anzahl Proz.
1 image of flag of Germany Germany 58 82,86%
2 image of flag of United States United States 8 11,43%
3 image of flag of Ukraine Ukraine 1 1,43%
4 image of flag of Russian Federation Russian Federation 1 1,43%
5 image of flag of China China 1 1,43%
6 image of flag of Brazil Brazil 1 1,43%

Weitere Download-Zahlen und Ranglisten:


Hinweis

Zur Erhebung der Downloadstatistiken kommen entsprechend dem „COUNTER Code of Practice for e-Resources“ international anerkannte Regeln und Normen zur Anwendung. COUNTER ist eine internationale Non-Profit-Organisation, in der Bibliotheksverbände, Datenbankanbieter und Verlage gemeinsam an Standards zur Erhebung, Speicherung und Verarbeitung von Nutzungsdaten elektronischer Ressourcen arbeiten, welche so Objektivität und Vergleichbarkeit gewährleisten sollen. Es werden hierbei ausschließlich Zugriffe auf die entsprechenden Volltexte ausgewertet, keine Aufrufe der Website an sich.

Suche im Repositorium


Durchblättern