Articles | Volume 12, issue 10
https://doi.org/10.5194/acp-12-4555-2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/acp-12-4555-2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
24 May 2012
Research article |
| 24 May 2012
Ensemble forecasting with a stochastic convective parametrization based on equilibrium statistics
P. Groenemeijer
Ludwig-Maximilians-Universität, München, Germany
currently at: European Severe Storms Laboratory, Wessling, Germany
G. C. Craig
Ludwig-Maximilians-Universität, München, Germany
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Cited
19 citations as recorded by crossref.
- The Plant–Craig Stochastic Convection Scheme in ICON and Its Scale Adaptivity R. Keane et al. https://doi.org/10.1175/JAS-D-13-0331.1
- Stochastic Behavior of Tropical Convection in Observations and a Multicloud Model K. Peters et al. https://doi.org/10.1175/JAS-D-13-031.1
- Stochastic convective parameterization improving the simulation of tropical precipitation variability in the NCAR CAM5 Y. Wang et al. https://doi.org/10.1002/2016GL069818
- Simulation of upscale error growth with a stochastic convection scheme T. Selz & G. Craig https://doi.org/10.1002/2015GL063525
- Process‐oriented stochastic perturbations applied to the parametrization of turbulence and shallow convection for ensemble prediction A. Fleury et al. https://doi.org/10.1002/qj.4242
- Different Representation of Mesoscale Convective Systems in Convection-Permitting and Convection-Parameterizing NWP Models and Its Implications for Large-Scale Forecast Evolution K. Peters et al. https://doi.org/10.3390/atmos10090503
- Physically Based Stochastic Perturbations (PSP) in the Boundary Layer to Represent Uncertainty in Convective Initiation K. Kober & G. Craig https://doi.org/10.1175/JAS-D-15-0144.1
- Evaluation of the Plant–Craig stochastic convection scheme (v2.0) in the ensemble forecasting system MOGREPS-R (24 km) based on the Unified Model (v7.3) R. Keane et al. https://doi.org/10.5194/gmd-9-1921-2016
- Convective quasi‐equilibrium J. Yano & R. Plant https://doi.org/10.1029/2011RG000378
- Multiple‐Instance Superparameterization: 1. Concept, and Predictability of Precipitation T. Jones et al. https://doi.org/10.1029/2019MS001610
- Empirical values and assumptions in the convection schemes of numerical models A. Villalba-Pradas & F. Tapiador https://doi.org/10.5194/gmd-15-3447-2022
- A stochastic parametrization for deep convection using cellular automata L. Bengtsson et al. https://doi.org/10.1002/qj.2108
- Examination of a Stochastic and Deterministic Convection Parameterization in the COSMO Model K. Kober et al. https://doi.org/10.1175/MWR-D-15-0012.1
- Global climate impacts of stochastic deep convection parameterization in the NCARCAM5 Y. Wang & G. Zhang https://doi.org/10.1002/2016MS000756
- Downstream influence of mesoscale convective systems. Part 2: Influence on ensemble forecast skill and spread S. Clarke et al. https://doi.org/10.1002/qj.3613
- Impact of a stochastic parametrization of cumulus convection, using cellular automata, in a mesoscale ensemble prediction system L. Bengtsson & H. Körnich https://doi.org/10.1002/qj.2720
- Predicting convective rainfall over tropical oceans from environmental conditions D. Raymond & M. Flores https://doi.org/10.1002/2015MS000595
- Performance evaluation of a high‐resolution regional model over West Africa for operational use: A case study of August 2017 E. Olaniyan et al. https://doi.org/10.1002/met.2080
- Effects of coupling a stochastic convective parameterization with the Zhang–McFarlane scheme on precipitation simulation in the DOE E3SMv1.0 atmosphere model Y. Wang et al. https://doi.org/10.5194/gmd-14-1575-2021
19 citations as recorded by crossref.
- The Plant–Craig Stochastic Convection Scheme in ICON and Its Scale Adaptivity R. Keane et al. https://doi.org/10.1175/JAS-D-13-0331.1
- Stochastic Behavior of Tropical Convection in Observations and a Multicloud Model K. Peters et al. https://doi.org/10.1175/JAS-D-13-031.1
- Stochastic convective parameterization improving the simulation of tropical precipitation variability in the NCAR CAM5 Y. Wang et al. https://doi.org/10.1002/2016GL069818
- Simulation of upscale error growth with a stochastic convection scheme T. Selz & G. Craig https://doi.org/10.1002/2015GL063525
- Process‐oriented stochastic perturbations applied to the parametrization of turbulence and shallow convection for ensemble prediction A. Fleury et al. https://doi.org/10.1002/qj.4242
- Different Representation of Mesoscale Convective Systems in Convection-Permitting and Convection-Parameterizing NWP Models and Its Implications for Large-Scale Forecast Evolution K. Peters et al. https://doi.org/10.3390/atmos10090503
- Physically Based Stochastic Perturbations (PSP) in the Boundary Layer to Represent Uncertainty in Convective Initiation K. Kober & G. Craig https://doi.org/10.1175/JAS-D-15-0144.1
- Evaluation of the Plant–Craig stochastic convection scheme (v2.0) in the ensemble forecasting system MOGREPS-R (24 km) based on the Unified Model (v7.3) R. Keane et al. https://doi.org/10.5194/gmd-9-1921-2016
- Convective quasi‐equilibrium J. Yano & R. Plant https://doi.org/10.1029/2011RG000378
- Multiple‐Instance Superparameterization: 1. Concept, and Predictability of Precipitation T. Jones et al. https://doi.org/10.1029/2019MS001610
- Empirical values and assumptions in the convection schemes of numerical models A. Villalba-Pradas & F. Tapiador https://doi.org/10.5194/gmd-15-3447-2022
- A stochastic parametrization for deep convection using cellular automata L. Bengtsson et al. https://doi.org/10.1002/qj.2108
- Examination of a Stochastic and Deterministic Convection Parameterization in the COSMO Model K. Kober et al. https://doi.org/10.1175/MWR-D-15-0012.1
- Global climate impacts of stochastic deep convection parameterization in the NCARCAM5 Y. Wang & G. Zhang https://doi.org/10.1002/2016MS000756
- Downstream influence of mesoscale convective systems. Part 2: Influence on ensemble forecast skill and spread S. Clarke et al. https://doi.org/10.1002/qj.3613
- Impact of a stochastic parametrization of cumulus convection, using cellular automata, in a mesoscale ensemble prediction system L. Bengtsson & H. Körnich https://doi.org/10.1002/qj.2720
- Predicting convective rainfall over tropical oceans from environmental conditions D. Raymond & M. Flores https://doi.org/10.1002/2015MS000595
- Performance evaluation of a high‐resolution regional model over West Africa for operational use: A case study of August 2017 E. Olaniyan et al. https://doi.org/10.1002/met.2080
- Effects of coupling a stochastic convective parameterization with the Zhang–McFarlane scheme on precipitation simulation in the DOE E3SMv1.0 atmosphere model Y. Wang et al. https://doi.org/10.5194/gmd-14-1575-2021
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