Journal cover Journal topic
Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

Journal metrics

  • IF value: 4.252 IF 4.252
  • IF 5-year value: 4.890 IF 5-year
    4.890
  • CiteScore value: 4.49 CiteScore
    4.49
  • SNIP value: 1.539 SNIP 1.539
  • SJR value: 2.404 SJR 2.404
  • IPP value: 4.28 IPP 4.28
  • h5-index value: 40 h5-index 40
  • Scimago H <br class='hide-on-tablet hide-on-mobile'>index value: 51 Scimago H
    index 51
Volume 6, issue 4
Geosci. Model Dev., 6, 1261-1273, 2013
https://doi.org/10.5194/gmd-6-1261-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
Geosci. Model Dev., 6, 1261-1273, 2013
https://doi.org/10.5194/gmd-6-1261-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.

Methods for assessment of models 22 Aug 2013

Methods for assessment of models | 22 Aug 2013

Automated tracking of shallow cumulus clouds in large domain, long duration large eddy simulations

T. Heus1 and A. Seifert2 T. Heus and A. Seifert
  • 1Max Planck Institute for Meteorology, Hamburg, Germany
  • 2Hans-Ertel Centre for Weather Research, Deutscher Wetterdienst, Hamburg, Germany

Abstract. This paper presents a method for feature tracking of fields of shallow cumulus convection in large eddy simulations (LES) by connecting the projected cloud cover in space and time, and by accounting for splitting and merging of cloud objects. Existing methods tend to be either imprecise or, when using the full three-dimensional (3-D) spatial field, prohibitively expensive for large data sets. Compared to those 3-D methods, the current method reduces the memory footprint by up to a factor 100, while retaining most of the precision by correcting for splitting and merging events between different clouds. The precision of the algorithm is further enhanced by taking the vertical extent of the cloud into account. Furthermore, rain and subcloud thermals are also tracked, and links between clouds, their rain, and their subcloud thermals are made. The method compares well with results from the literature. Resolution and domain dependencies are also discussed. For the current simulations, the cloud size distribution converges for clouds larger than an effective resolution of 6 times the horizontal grid spacing, and smaller than about 20% of the horizontal domain size.

Publications Copernicus
Download
Citation
Share