Articles | Volume 20, issue 4
Atmos. Chem. Phys., 20, 2201–2219, 2020
https://doi.org/10.5194/acp-20-2201-2020
Atmos. Chem. Phys., 20, 2201–2219, 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 et al.

Download

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

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Constanze Wellmann on behalf of the Authors (12 Nov 2019)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (15 Nov 2019) by Barbara Ervens
RR by Anonymous Referee #1 (15 Nov 2019)
RR by Anonymous Referee #3 (28 Nov 2019)
ED: Publish subject to minor revisions (review by editor) (30 Nov 2019) by Barbara Ervens
AR by Corinna Hoose on behalf of the Authors (10 Dec 2019)  Author's response    Manuscript
ED: Publish as is (04 Jan 2020) by Barbara Ervens
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