A generalized approach to parameterizing convection combining ensemble and data assimilation techniques

By G. Grell, D. Dévényi. 2002

2,200 citations recorded by the source corpus.

Subfields: Atmospheric Science, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/8d2bcd7beda972b262b89390607069c6c6bf9932

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Atmospheric Science

1. Fuqing Zhang
2. Z. Meng
3. Joseph B. Klemp
4. Q. Xiao
5. William C. Skamarock
6. D. Barker
7. Jimy Dudhia
8. E. Bou‐Zeid

In Global and Planetary Change

1. Fuqing Zhang
2. Z. Meng
3. Q. Xiao
4. Jimy Dudhia
5. Joseph B. Klemp
6. D. Barker
7. E. Bou‐Zeid
8. C. Melhauser

Citations in the corpus

• Sensitivity of Numerical Simulation of Early Rapid Intensification of Hurricane Emily (2005) to Cloud Microphysical and Planetary Boundary Layer Parameterizations (2008, methodology): “The Grell-Devenyi ensemble cumulus scheme (Grell and Devenyi 2002), which has a better performance in the simulation of Hurricane Emily in the previous study (Li and Pu 2006), is used for the 27 km and 9 km grid spacings.”
• The Kain–Fritsch Convective Parameterization: An Update (2004, background): “…1985; Betts 1986; Frank and Cohen 1987; Tiedtke 1989; Gregory and Rowntree 1990; Emanuel 1991; Grell 1993), and many of these schemes continue to be used and modified (e.g., Janjic´ 1994; Cheng and Arakawa 1997; Emanuel and Zivkovic-Rothman 1999; Gregory et al. 2000; Grell and Devenyi 2002).”
• Coupled weather research and forecasting–stochastic time-inverted lagrangian transport (WRF–STILT) model (2010, methodology): “In the WRF model, the Grell–Devenyi scheme ( Grell and Devenyi 2002 ) at the time was implemented for deep moist convection only (shallow, non-precipitating convection was not yet implemented).”
• WRF Model Sensitivity to Choice of Parameterization over South America: Validation against Surface Variables (2010, background): “The Grell–Devenyi (GRELL) that includes convective effects from ensembles generated with different closure assumptions (Grell and Devenyi 2002).”
• Regional climate modelling of the 2006 West African monsoon: sensitivity to convection and planetary boundary layer parameterisation using WRF (2011, methodology): “The Grell ensemble (GR) scheme and the Grell 3D ensemble (GR3D) scheme (Grell 1993; Grell and Devenyi 2002) have a rather simple approach of convective clouds.”
• Tests of an Ensemble Kalman Filter for Mesoscale and Regional-Scale Data Assimilation. Part III: Comparison with 3DVAR in a Real-Data Case Study (2008, methodology): “Unless otherwise specified, the physical parameterization schemes include the Grell–Devenyi cumulus scheme (Grell and Devenyi 2002), the WRF Single Moment (WSM) sixclass microphysics with graupel (Hong et al.”
• Nested Mesoscale Large-Eddy Simulations with WRF: Performance in Real Test Cases (2012, methodology): “The cumulus parameterization is present only in the coarsest mesoscale simulation of 12.15-km resolution and relies on the Grell scheme (Grell and Devenyi 2002).”
• Severe haze in northern China: A synergy of anthropogenic emissions and atmospheric processes (2019, methodology): “Cumulus scheme Grell-Devenyi ensemble scheme (24) Boundary layer scheme MYJ TKE scheme (15)”
• Four-Dimensional Variational Data Assimilation for WRF : Formulation and Preliminary Results (2009, methodology): “The ARW model used in the forecast employs the WRF Single-Moment 5-class (WSM5) microphysics scheme (Hong et al. 2004), Grell–Devenyi ensemble cumulus scheme ( Grell and Devenyi 2002 ), and the Yonsei University (YSU) boundary layer scheme.”
• A mass-flux cumulus parameterization scheme for large-scale models: description and test with observations (2012, background): “Many of these schemes continue to be improved (e.g., Janjic 1994; Cheng and Arakawa 1997; Emanuel and Zivkovic-Rothman 1999; Gregory et al. 2000; Grell and Devenyi 2002).”
• A Description of the Advanced Research WRF Version 3 (2008, methodology): “3 Grell-Devenyi ensemble scheme Grell and Devenyi (2002) introduced an ensemble cumulus scheme in which effectively multiple cumulus schemes and variants are run within each grid box and then the results are averaged to give the feedback to the model.”
• Engineering Notes Probabilistic Weather Forecasting Analysis for Unmanned Aerial Vehicle Path Planning (2014, background): “The recent development in numerical weather prediction [12–15] makes possible the high-resolution ensemble forecasting [16,17].”