Articles | Volume 20, issue 4
https://doi.org/10.5194/acp-20-2201-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-20-2201-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
26 Feb 2020
Research article |
| 26 Feb 2020
| 26 Feb 2020
Comparing the impact of environmental conditions and microphysics on the forecast uncertainty of deep convective clouds and hail
Constanze Wellmann
CORRESPONDING AUTHOR
Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology, Karlsruhe, Germany
Andrew I. Barrett
Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology, Karlsruhe, Germany
Jill S. Johnson
Institute for Climate and Atmospheric Science, School of Earth and Environment, University of Leeds, Leeds, UK
Michael Kunz
Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology, Karlsruhe, Germany
Bernhard Vogel
Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology, Karlsruhe, Germany
Ken S. Carslaw
Institute for Climate and Atmospheric Science, School of Earth and Environment, University of Leeds, Leeds, UK
Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology, Karlsruhe, Germany
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Cited
17 citations as recorded by crossref.
- The effects of climate change on hailstorms T. Raupach et al. 10.1038/s43017-020-00133-9
- Importance of aerosols and shape of the cloud droplet size distribution for convective clouds and precipitation C. Barthlott et al. 10.5194/acp-22-2153-2022
- Influence of the terminal velocity of graupel on the simulation of a convective system over Beijing Y. Li et al. 10.1016/j.atmosres.2022.106181
- Impacts of combined microphysical and land-surface uncertainties on convective clouds and precipitation in different weather regimes C. Barthlott et al. 10.5194/acp-22-10841-2022
- Model emulation to understand the joint effects of ice-nucleating particles and secondary ice production on deep convective anvil cirrus R. Hawker et al. 10.5194/acp-21-17315-2021
- Notable Contributions of Aerosols to the Predictability of Hail Precipitation X. Li et al. 10.1029/2020GL091712
- Quantifying uncertainty in simulations of the West African monsoon with the use of surrogate models M. Fischer et al. 10.5194/wcd-5-511-2024
- Model Predictability of Hail Precipitation with a Moderate Hailstorm Case. Part I: Impact of Improved Initial Conditions by Assimilating High-Density Observations R. Li et al. 10.1175/MWR-D-21-0329.1
- Characteristics of hail hazard in South Africa based on satellite detection of convective storms H. Punge et al. 10.5194/nhess-23-1549-2023
- Swabian MOSES 2021: An interdisciplinary field campaign for investigating convective storms and their event chains M. Kunz et al. 10.3389/feart.2022.999593
- Representation of the autoconversion from cloud to rain using a weighted ensemble approach: a case study using WRF v4.1.3 J. Yin et al. 10.5194/gmd-15-771-2022
- Assessing the potential for simplification in global climate model cloud microphysics U. Proske et al. 10.5194/acp-22-4737-2022
- Sensitivity of mixed-phase moderately deep convective clouds to parameterizations of ice formation – an ensemble perspective A. Miltenberger & P. Field 10.5194/acp-21-3627-2021
- The impact of microphysical uncertainty conditional on initial and boundary condition uncertainty under varying synoptic control T. Matsunobu et al. 10.5194/wcd-3-1273-2022
- A ten-year statistical radar analysis of an operational hail suppression program in Alberta F. Pirani et al. 10.1016/j.atmosres.2023.107035
- Weakening of tropical sea breeze convective systems through interactions of aerosol, radiation, and soil moisture J. Park & S. van den Heever 10.5194/acp-22-10527-2022
- Influence of the Terminal Velocity of Graupel on the Simulation of a Convective System Over Beijing Y. Li et al. 10.2139/ssrn.3995974
17 citations as recorded by crossref.
- The effects of climate change on hailstorms T. Raupach et al. 10.1038/s43017-020-00133-9
- Importance of aerosols and shape of the cloud droplet size distribution for convective clouds and precipitation C. Barthlott et al. 10.5194/acp-22-2153-2022
- Influence of the terminal velocity of graupel on the simulation of a convective system over Beijing Y. Li et al. 10.1016/j.atmosres.2022.106181
- Impacts of combined microphysical and land-surface uncertainties on convective clouds and precipitation in different weather regimes C. Barthlott et al. 10.5194/acp-22-10841-2022
- Model emulation to understand the joint effects of ice-nucleating particles and secondary ice production on deep convective anvil cirrus R. Hawker et al. 10.5194/acp-21-17315-2021
- Notable Contributions of Aerosols to the Predictability of Hail Precipitation X. Li et al. 10.1029/2020GL091712
- Quantifying uncertainty in simulations of the West African monsoon with the use of surrogate models M. Fischer et al. 10.5194/wcd-5-511-2024
- Model Predictability of Hail Precipitation with a Moderate Hailstorm Case. Part I: Impact of Improved Initial Conditions by Assimilating High-Density Observations R. Li et al. 10.1175/MWR-D-21-0329.1
- Characteristics of hail hazard in South Africa based on satellite detection of convective storms H. Punge et al. 10.5194/nhess-23-1549-2023
- Swabian MOSES 2021: An interdisciplinary field campaign for investigating convective storms and their event chains M. Kunz et al. 10.3389/feart.2022.999593
- Representation of the autoconversion from cloud to rain using a weighted ensemble approach: a case study using WRF v4.1.3 J. Yin et al. 10.5194/gmd-15-771-2022
- Assessing the potential for simplification in global climate model cloud microphysics U. Proske et al. 10.5194/acp-22-4737-2022
- Sensitivity of mixed-phase moderately deep convective clouds to parameterizations of ice formation – an ensemble perspective A. Miltenberger & P. Field 10.5194/acp-21-3627-2021
- The impact of microphysical uncertainty conditional on initial and boundary condition uncertainty under varying synoptic control T. Matsunobu et al. 10.5194/wcd-3-1273-2022
- A ten-year statistical radar analysis of an operational hail suppression program in Alberta F. Pirani et al. 10.1016/j.atmosres.2023.107035
- Weakening of tropical sea breeze convective systems through interactions of aerosol, radiation, and soil moisture J. Park & S. van den Heever 10.5194/acp-22-10527-2022
- Influence of the Terminal Velocity of Graupel on the Simulation of a Convective System Over Beijing Y. Li et al. 10.2139/ssrn.3995974
Latest update: 23 Apr 2024
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.
Severe hailstorms may cause damage to buildings and crops. Thus, the forecast of numerical...
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