Articles | Volume 20, issue 4
https://doi.org/10.5194/acp-20-2201-2020
https://doi.org/10.5194/acp-20-2201-2020
Research article
 | 
26 Feb 2020
Research article |  | 26 Feb 2020

Comparing the impact of environmental conditions and microphysics on the forecast uncertainty of deep convective clouds and hail

Constanze Wellmann, Andrew I. Barrett, Jill S. Johnson, Michael Kunz, Bernhard Vogel, Ken S. Carslaw, and Corinna Hoose

Viewed

Total article views: 2,988 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
2,242 680 66 2,988 76 66
  • HTML: 2,242
  • PDF: 680
  • XML: 66
  • Total: 2,988
  • BibTeX: 76
  • EndNote: 66
Views and downloads (calculated since 25 Jul 2019)
Cumulative views and downloads (calculated since 25 Jul 2019)

Viewed (geographical distribution)

Total article views: 2,988 (including HTML, PDF, and XML) Thereof 2,841 with geography defined and 147 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 14 Dec 2024
Download
Short summary
Severe hailstorms may cause damage to buildings and crops. Thus, the forecast of numerical weather prediction (NWP) models should be as reliable as possible. Using statistical emulation, we identify those model input parameters describing environmental conditions and cloud microphysics which lead to large uncertainties in the prediction of deep convection. We find that the impact of the input parameters on the uncertainty depends on the considered output variable.
Altmetrics
Final-revised paper
Preprint