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

Journal metrics

IF value: 5.240
IF5.240
IF 5-year value: 5.768
IF 5-year
5.768
CiteScore value: 8.9
CiteScore
8.9
SNIP value: 1.713
SNIP1.713
IPP value: 5.53
IPP5.53
SJR value: 3.18
SJR3.18
Scimago H <br class='widget-line-break'>index value: 71
Scimago H
index
71
h5-index value: 51
h5-index51
Preprints
https://doi.org/10.5194/gmd-2019-343
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-2019-343
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: development and technical paper 11 Feb 2020

Submitted as: development and technical paper | 11 Feb 2020

Review status
A revised version of this preprint was accepted for the journal GMD and is expected to appear here in due course.

Collection/Aggregation in a Lagrangian cloud microphysical model: Insights from column model applications using LCM1D (v0.9)

Simon Unterstrasser1, Fabian Hoffmann2,3, and Marion Lerch1 Simon Unterstrasser et al.
  • 1Deutsches Zentrum für Luft- und Raumfahrt (DLR) – Institut für Physik der Atmosphäre, Oberpfaffenhofen, 82234 Wessling, Germany
  • 2Cooperative Institute for Research in Environmental Sciences (CIRES), University of Colorado Boulder, Boulder, Colorado, USA
  • 3NOAA Earth System Research Laboratory (ESRL), Chemical Sciences Division, Boulder, Colorado, USA

Abstract. Lagrangian cloud models (LCMs) are considered the future of cloud microphysical modeling. However, LCMs are computationally expensive due to the typically high number of simulation particles (SIPs) necessary to represent microphysical processes such as collection/aggregation successfully. In this study, the representation of collection/aggregation is explored in one-dimensional column simulations, allowing for the explicit consideration of sedimentation, complementing the authors' previous study on zero-dimensional collection in a single grid box. Two variants of the Lagrangian probabilistic all-or-nothing (AON) collection algorithm are tested that mainly differ in the assumed spaatial distribution of the droplet ensemble: The first variant assumes the droplet ensemble to be well-mixed in a predefined three-dimensional grid box (WM3D), while the second variant considers explicitly the vertical coordinate of the SIPs, reducing the well-mixed assumption to a two-dimensional, horizontal plane (WM2D). Since the number of calculations in AON depends quadratically on the number of SIPs, an approach is tested that reduces the number of calculations to a linear dependence (so-called linear sampling). All variants are compared to established Eulerian bin model solutions. Generally, all methods approach the same solutions, and agree well if the methods are applied with sufficiently high accuracy (foremost the number of SIPs, timestep, vertical grid spacing). However, it is found that the rate of convergence depends on the applied model variant. The dependence on the vertical grid spacing can be reduced if AON WM2D is applied. The study also shows that the AON simulations with linear sampling, a common speed-up measure, converges slower, as smaller timesteps are required to reach convergence compared to simulations with a quadratic dependence on the number of SIPs. Most importantly, the study highlights that results generally require a smaller number of SIPs per grid box for convergence than previous box simulations indicated. The reason is the ability of sedimenting SIPs to interact with an effectively larger ensemble of particles when they are not restricted to a single grid box. Since sedimentation is considered in most commonly applied three-dimensional models, the results indicate smaller computational requirements for successful simulations than previously assumed, encouraging a wider use of LCMs in the future.

Simon Unterstrasser et al.

Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement

Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement

Simon Unterstrasser et al.

Data sets

Simulation/Plot Data of Coalescence/aggregation column model Simon Unterstrasser https://doi.org/10.5281/zenodo.3547341

Model code and software

ColumnModel: GMDD release Simon Unterstrasser https://doi.org/10.5281/zenodo.3547539

Simon Unterstrasser et al.

Viewed

Total article views: 361 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
231 101 29 361 30 26
  • HTML: 231
  • PDF: 101
  • XML: 29
  • Total: 361
  • BibTeX: 30
  • EndNote: 26
Views and downloads (calculated since 11 Feb 2020)
Cumulative views and downloads (calculated since 11 Feb 2020)

Viewed (geographical distribution)

Total article views: 274 (including HTML, PDF, and XML) Thereof 274 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Saved

No saved metrics found.

Discussed

No discussed metrics found.
Latest update: 23 Sep 2020
Publications Copernicus
Download
Short summary
Lagrangian cloud models use simulation particles for the representation of cloud particles like droplets or ice crystals. The collision and merging of cloud particles (called collection in case of cloud droplets and aggregation in case of ice crystals) was found to be numerically challenging process in Lagrangian models. The study presents verification exercises in a 1D column model, where sedimentation and collection are the only active processes.
Lagrangian cloud models use simulation particles for the representation of cloud particles like...
Citation