Precipitation and Evolution Sensitivity in Simulated Deep Convective Storms: Comparisons between Liquid-Only and Simple Ice and Liquid Phase Microphysics*

By M. Gilmore, Jerry M. Straka, E. Rasmussen. 2004

208 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/3bd7470de388a0a0e9d714fb4019f1459cea3795

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In Atmospheric Science

Citations in the corpus

Assimilation of Reflectivity Data in a Convective-Scale, Cycled 3DVAR Framework with Hydrometeor Classification (2012, methodology): “(5) For hail, the reflectivity formulation based on Lin et al. (1983) and Gilmore et al. (2004) is used, with Z(qh) 5 4:33 3 10 10(rqh) 1:75.”
Sensitivity of WRF cloud microphysics to simulations of a severe thunderstorm event over Southeast India (2010, methodology): “(1983) and its icephase behaviour is much different due to the changes of Hong et al. (2004). In the Purdue Lin scheme, six classes of hydrometeors (water vapour, cloud water, rain, cloud ice, snow and graupel) are considered. All parameterization production terms are based on Lin et al. (1983) and ”
The Impact of Raindrop Collisional Processes on the Polarimetric Radar Variables (2014, background): “…for understanding the evolution of raindrop size spectra is that storm dynamics can be strongly inﬂuenced by precipitation microphysics (Srivastava 1985, 1987; Markowski et al. 2002; Gilmore et al. 2004; Dawson et al. 2010; Van Weverberg et al. 2011; Bryan and Morrison 2012; Morrison et al. 2012).”
Additive Noise for Storm-Scale Ensemble Data Assimilation (2009, methodology): “For this study, we use the Gilmore et al. (2004) version of the Lin et al.”
Direct Assimilation of Radar Reflectivity without Tangent Linear and Adjoint of the Nonlinear Observation Operator in the GSI-Based EnVar System: Methodology and Experiment with the 8 May 2003 Oklahoma City Tornadic Supercell (2017, methodology): “To illustrate these methods, the radar reflectivity observation operator consistent with the WSM6 microphysics scheme (Hong and Lim 2006) is used following Lin et al. (1983), Gilmore et al. (2004), Tong and Xue (2005), Dowell et al. (2011), and Johnson et al. (2015).”
Resolution Requirements for the Simulation of Deep Moist Convection (2003, methodology): “The main reference used to justify this design appears to be Klemp and Wilhelmson (1978). Several arguments were put forth by Klemp and Wilhelmson in support of this strategy, although they acknowledged that it may not be entirely appropriate to do so.”
Tornadogenesis: Our current understanding, forecasting considerations, and questions to guide future research (2009, background): “, vorticity redistribution versus vorticity generation within the RFD), the importance of microphysical differences among supercells and how those microphysical differences arise (Tartaglione et al., 1996; Gilmore et al., 2004; van den Heever and Cotton, 2004), the thermodynamic characteristics of s”
Effects of Upper-Level Shear on the Structure and Maintenance of Strong Quasi-Linear Mesoscale Convective Systems (2006, background): “In addition to liquid water processes, ice processes are represented with a three-class (ice, snow, graupel/hail) scheme (see Gilmore et al. 2004a).”
Assimilation of Simulated Polarimetric Radar Data for a Convective Storm Using the Ensemble Kalman Filter. Part I: Observation Operators for Reflectivity and Polarimetric Variables (2008, methodology): “Raindrops are normally modeled as oblate spheroids and the oblateness, r, is represented by the axis ratio between minor to major axis, which is related to the equivalent diameter D given by Green (1975) in an equilibrium model.”
Inverted-polarity electrical structures in thunderstorms in the Severe Thunderstorm Electrification and Precipitation Study (STEPS) (2005, methodology): “…numerical studies show great sensitivity in resultant convective structure, evolution, and precipitation output to relatively minor differences in microphysical schemes, casting much doubt on our current ability to forecast convective precipitation in operational models (e.g., Gilmore et al. 2003).”