Tropical cyclogenesis sensitivity to environmental parameters in radiative–convective equilibrium

By D. Nolan, E. Rappin, Kerry A. Emanuel. 2007

188 citations recorded by the source corpus.

In this study, the relationship between the likelihood of tropical cyclogenesis and external environmental forcings is explored in the simplest idealized modelling framework possible: radiative‐convective equilibrium on a doubly periodic f‐plane. In such an environment, control of the equilibrium environmental sounding is reduced to three parameters: the sea‐surface temperature, the Coriolis parameter, and the imposed background surface wind speed. Cloud‐resolving mesoscale model simulations are used to generate environments of radiative‐convective equilibrium determined by these three factors. The favourability of these environments for tropical cyclogenesis is measured in three ways: in terms of the maximum potential intensity (MPI) of the sounding, based on the thermodynamic theory of Emanuel; in terms of the ‘genesis potential’ determined by an empirical genesis parameter; and in terms of the propensity of weak initial vortices in these environments to form into tropical cyclones.

Subfields: Atmospheric Science, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/b5fb98382ea82a849fad25ff3a5abc0a0ea2c5ec

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Citations in the corpus

Observational Evidence for Relationships between the Degree of Aggregation of Deep Convection, Water Vapor, Surface Fluxes, and Radiation (2012, unknown): “In particular, when deep convection is ‘‘localized’’ (Held et al. 1993), ‘‘aggregated’’ (Bretherton et al. 2005; Nolan et al. 2007; Khairoutdinov and Emanuel 2010), or ‘‘organized into bands’’ (Tompkins 2001), the large-scale atmosphere is found to be much drier than when convection is scattered.”
A Poisson Regression Index for Tropical Cyclone Genesis and the Role of Large-Scale Vorticity in Genesis (2011, methodology): “The GPI has been applied widely and successfully to study variations of genesis frequency on various time scales in reanalysis and models (e.g, Camargo et al. 2007a,b; Vecchi and Soden 2007b; Nolan et al. 2007; Camargo et al. 2009; Lyon and Camargo 2009; Yokoi et al. 2009; Yokoi and Takayuba 2009).”
Physical mechanisms controlling self‐aggregation of convection in idealized numerical modeling simulations (2013, background): “However, when certain conditions are met, the convection becomes organized into a single, intensely convecting moist cluster surrounded by a broad region of dry subsiding air [Bretherton et al., 2005; Nolan et al., 2007].”
Convective Self-Aggregation in Numerical Simulations: A Review (2017, background): “Given that aggregation physics may be important for such phenomena as tropical cyclones (Bretherton et al. 2005; Nolan et al. 2007; Davis 2015; Wing et al. 2016) and the MaddenJulian Oscillation (Bretherton et al.”
Radiative‐convective instability (2014, background): “Reevaporation of cloud water, resulting from entrainment of dry air, drives penetrative downdrafts within the clouds.”