Articles | Volume 20, issue 4
Atmos. Chem. Phys., 20, 2201–2219, 2020
Atmos. Chem. Phys., 20, 2201–2219, 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.

Related authors

Evaluation of natural aerosols in CRESCENDO Earth system models (ESMs): mineral dust
Ramiro Checa-Garcia, Yves Balkanski, Samuel Albani, Tommi Bergman, Ken Carslaw, Anne Cozic, Chris Dearden, Beatrice Marticorena, Martine Michou, Twan van Noije, Pierre Nabat, Fiona M. O'Connor, Dirk Olivié, Joseph M. Prospero, Philippe Le Sager, Michael Schulz, and Catherine Scott
Atmos. Chem. Phys., 21, 10295–10335,,, 2021
Short summary
Model emulation to understand the joint effects of ice-nucleating particles and secondary ice production on deep convective anvil cirrus
Rachel E. Hawker, Annette K. Miltenberger, Jill S. Johnson, Jonathan M. Wilkinson, Adrian A. Hill, Ben J. Shipway, Paul R. Field, Benjamin J. Murray, and Ken S. Carslaw
Atmos. Chem. Phys. Discuss.,,, 2021
Preprint under review for ACP
Short summary
Controls on surface aerosol number concentrations and aerosol-limited cloud regimes over the central Greenland Ice Sheet
Heather Guy, Ian M. Brooks, Ken S. Carslaw, Benjamin J. Murray, Von P. Walden, Matthew D. Shupe, Claire Pettersen, David D. Turner, Christopher J. Cox, William D. Neff, Ralf Bennartz, and Ryan R. Neely III
Atmos. Chem. Phys. Discuss.,,, 2021
Revised manuscript accepted for ACP
Short summary
Online treatment of eruption dynamics improves the volcanic ash and SO2 dispersion forecast: case of the Raikoke 2019 eruption
Julia Bruckert, Gholam Ali Hoshyaripour, Ákos Horváth, Lukas Muser, Fred J. Prata, Corinna Hoose, and Bernhard Vogel
Atmos. Chem. Phys. Discuss.,,, 2021
Preprint under review for ACP
Short summary
The temperature dependence of ice-nucleating particle concentrations affects the radiative properties of tropical convective cloud systems
Rachel E. Hawker, Annette K. Miltenberger, Jonathan M. Wilkinson, Adrian A. Hill, Ben J. Shipway, Zhiqiang Cui, Richard J. Cotton, Ken S. Carslaw, Paul R. Field, and Benjamin J. Murray
Atmos. Chem. Phys., 21, 5439–5461,,, 2021
Short summary

Related subject area

Subject: Clouds and Precipitation | Research Activity: Atmospheric Modelling | Altitude Range: Troposphere | Science Focus: Physics (physical properties and processes)
Statistical properties of a stochastic model of eddy hopping
Izumi Saito, Takeshi Watanabe, and Toshiyuki Gotoh
Atmos. Chem. Phys., 21, 13119–13130,,, 2021
Short summary
Understanding the model representation of clouds based on visible and infrared satellite observations
Stefan Geiss, Leonhard Scheck, Alberto de Lozar, and Martin Weissmann
Atmos. Chem. Phys., 21, 12273–12290,,, 2021
Short summary
Impact of high- and low-vorticity turbulence on cloud–environment mixing and cloud microphysics processes
Bipin Kumar, Rahul Ranjan, Man-Kong Yau, Sudarsan Bera, and Suryachandra A. Rao
Atmos. Chem. Phys., 21, 12317–12329,,, 2021
Short summary
Preconditioning of overcast-to-broken cloud transitions by riming in marine cold air outbreaks
Florian Tornow, Andrew S. Ackerman, and Ann M. Fridlind
Atmos. Chem. Phys., 21, 12049–12067,,, 2021
Short summary
Aitken mode particles as CCN in aerosol- and updraft-sensitive regimes of cloud droplet formation
Mira L. Pöhlker, Minghui Zhang, Ramon Campos Braga, Ovid O. Krüger, Ulrich Pöschl, and Barbara Ervens
Atmos. Chem. Phys., 21, 11723–11740,,, 2021
Short summary

Cited articles

Adams-Selin, R. D., van den Heever, S. C., and Johnson, R. H.: Impact of Graupel Parameterization Schemes on Idealized Bow Echo Simulations, Mon. Weather Rev., 141, 1241–1262,, 2013. a
Baldauf, M., Seifert, A., Förstner, J., Majewski, D., Raschendorfer, M., and Reinhardt, T.: Operational Convective-Scale Numerical Weather Prediction with the COSMO Model: Description and Sensitivities, Mon. Weather Rev., 139, 3887–3905,, 2011. a
Barrett, A. I., Wellmann, C., Seifert, A., Hoose, C., Vogel, B., and Kunz, M.: One Step at a Time: How Model Time Step Significantly Affects Convection-Permitting Simulations, J. Adv. Model. Earth Sy., 11, 641–658,, 2019. a, b
Bastos, L. S. and O'Hagan, A.: Diagnostics for Gaussian Process Emulators, Technometrics, 51, 425–438,, 2009. a
Bigg, E. K.: The formation of atmospheric ice crystals by the freezing of droplets, Q. J. Roy. Meteor. Soc., 79, 510–519,, 1953. a
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.
Final-revised paper