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1. Introduction The majority of strong tornadoes [rated as category 2 or above on the enhanced Fujita scale (EF2+)] are produced within the mesocyclone region of supercell thunderstorms (e.g., Markowski and Richardson 2010 ). In these instances, it is not clear whether or not the mesocyclone may be masking the presence of a developing tornado until the tornado is strong enough to become obvious in the Doppler velocity measurements. This is likely the situation at distances from a radar where
1. Introduction The majority of strong tornadoes [rated as category 2 or above on the enhanced Fujita scale (EF2+)] are produced within the mesocyclone region of supercell thunderstorms (e.g., Markowski and Richardson 2010 ). In these instances, it is not clear whether or not the mesocyclone may be masking the presence of a developing tornado until the tornado is strong enough to become obvious in the Doppler velocity measurements. This is likely the situation at distances from a radar where
1. Introduction A defining characteristic of supercell thunderstorms is their mesocyclone, a quasi-steady region of vertical vorticity within the storm’s updraft. This persistent feature contributes to the supercell’s ability to produce a host of severe weather threats, including damaging nontornadic winds ( Smith et al. 2012 ), flash flooding ( Nielsen and Schumacher 2020 ), large individual hail stones ( Blair et al. 2017 ) and/or large accumulations of small hail ( Kumjian et al. 2019
1. Introduction A defining characteristic of supercell thunderstorms is their mesocyclone, a quasi-steady region of vertical vorticity within the storm’s updraft. This persistent feature contributes to the supercell’s ability to produce a host of severe weather threats, including damaging nontornadic winds ( Smith et al. 2012 ), flash flooding ( Nielsen and Schumacher 2020 ), large individual hail stones ( Blair et al. 2017 ) and/or large accumulations of small hail ( Kumjian et al. 2019
1. Introduction Examination of Doppler radar data from several thunderstorms containing mesocyclones has revealed an intriguing pattern, in which one or more relatively narrow bands of radar reflectivity approach the storm from its right flank (generally from a southerly direction). Then, upon interaction with the storm, there is an intensification of the mesocyclone and sometimes tornadogenesis. The reflectivity bands in these cases, however, cannot be attributed to density currents or outflow
1. Introduction Examination of Doppler radar data from several thunderstorms containing mesocyclones has revealed an intriguing pattern, in which one or more relatively narrow bands of radar reflectivity approach the storm from its right flank (generally from a southerly direction). Then, upon interaction with the storm, there is an intensification of the mesocyclone and sometimes tornadogenesis. The reflectivity bands in these cases, however, cannot be attributed to density currents or outflow
reviewed by Davies-Jones and Brooks (1993) , Rotunno (1993) , and Davies-Jones et al. (2001) . [Herein, “low level” refers to altitudes nominally ≤1000 m AGL. Davies-Jones et al. (2001) referred to these altitudes as “near ground.” The distinction between low-level and midlevel mesocyclones is discussed further in section 4 .] Midlevel vertical vorticity having relatively high correlation with vertical velocity (negative correlation, in the case of a “left-moving” storm)—what most would probably
reviewed by Davies-Jones and Brooks (1993) , Rotunno (1993) , and Davies-Jones et al. (2001) . [Herein, “low level” refers to altitudes nominally ≤1000 m AGL. Davies-Jones et al. (2001) referred to these altitudes as “near ground.” The distinction between low-level and midlevel mesocyclones is discussed further in section 4 .] Midlevel vertical vorticity having relatively high correlation with vertical velocity (negative correlation, in the case of a “left-moving” storm)—what most would probably
1. Introduction Analyses of tornado occurrence show that strong to violent tornadoes cause a disproportionate amount of damage and fatalities ( Ashley 2007 ). This is mainly due to the tendency for strong to violent tornadoes to have the widest and longest damage paths ( Brooks 2004 ). In an attempt to explain this relationship, Trapp et al. (2017 , hereafter T17 ) posed the simple hypothesis that wide, intense tornadoes should form more readily from a contraction of wide mesocyclones or
1. Introduction Analyses of tornado occurrence show that strong to violent tornadoes cause a disproportionate amount of damage and fatalities ( Ashley 2007 ). This is mainly due to the tendency for strong to violent tornadoes to have the widest and longest damage paths ( Brooks 2004 ). In an attempt to explain this relationship, Trapp et al. (2017 , hereafter T17 ) posed the simple hypothesis that wide, intense tornadoes should form more readily from a contraction of wide mesocyclones or
1. Introduction Maritime polar mesocyclones are mesoscale cyclonic vortices that develop poleward of the main polar front ( Rasmussen and Turner 2003 ). They form and develop over high-latitude oceans during marine cold air outbreaks over a relatively warm sea ( Kolstad 2011 ). These areas are characterized by large sensible and latent heat fluxes from the sea surface, active cumulus convection, and a shallow baroclinic zone. Note that intense polar mesocyclones are known as polar lows, and
1. Introduction Maritime polar mesocyclones are mesoscale cyclonic vortices that develop poleward of the main polar front ( Rasmussen and Turner 2003 ). They form and develop over high-latitude oceans during marine cold air outbreaks over a relatively warm sea ( Kolstad 2011 ). These areas are characterized by large sensible and latent heat fluxes from the sea surface, active cumulus convection, and a shallow baroclinic zone. Note that intense polar mesocyclones are known as polar lows, and
are available for other phenomena or use by other neighboring radars). As a first step toward addressing this and related challenges, the goal of the present study is to use pseudo-observations of an idealized vertical vortex to evaluate a variety of sampling strategies for CASA radars in order to determine which might be most effective for real tornadoes and mesocyclones. Here, effectiveness is defined as the best fit of the pseudo-observations to an analytic model of tornadoes and mesocyclones
are available for other phenomena or use by other neighboring radars). As a first step toward addressing this and related challenges, the goal of the present study is to use pseudo-observations of an idealized vertical vortex to evaluate a variety of sampling strategies for CASA radars in order to determine which might be most effective for real tornadoes and mesocyclones. Here, effectiveness is defined as the best fit of the pseudo-observations to an analytic model of tornadoes and mesocyclones
; Wurman et al. 2013 ), while others occurred in large circulations that may have been tornadoes or other submesocyclone-scale structures ( Agee et al. 1976 , hereafter A76 ; Agee and Jones 2009 , hereafter AJ09 ; Rasmussen and Straka 2007 ; Potts and Agee 2002 , hereafter PA02 ). This motivates the documentation and classification of the spectrum of vortical structures smaller than, or within, mesocyclones, 3 influenced by finescale radar observations of their kinematic structure. 2. Different
; Wurman et al. 2013 ), while others occurred in large circulations that may have been tornadoes or other submesocyclone-scale structures ( Agee et al. 1976 , hereafter A76 ; Agee and Jones 2009 , hereafter AJ09 ; Rasmussen and Straka 2007 ; Potts and Agee 2002 , hereafter PA02 ). This motivates the documentation and classification of the spectrum of vortical structures smaller than, or within, mesocyclones, 3 influenced by finescale radar observations of their kinematic structure. 2. Different
1. Introduction Essential to the understanding and prediction of supercell tornadoes is a fundamental understanding of the processes that regulate their parent low-level mesocyclone. 1 This is because the pressure perturbations within supercell mesocyclones result in strong near-surface vertical accelerations (e.g., Rotunno and Klemp 1985 ), which vertically stretch near-ground vertical vorticity contributing to tornadogenesis (e.g., Doswell and Burgess 1993 ; Wicker and Wilhelmson
1. Introduction Essential to the understanding and prediction of supercell tornadoes is a fundamental understanding of the processes that regulate their parent low-level mesocyclone. 1 This is because the pressure perturbations within supercell mesocyclones result in strong near-surface vertical accelerations (e.g., Rotunno and Klemp 1985 ), which vertically stretch near-ground vertical vorticity contributing to tornadogenesis (e.g., Doswell and Burgess 1993 ; Wicker and Wilhelmson
A Three-Step Method for Estimating Vortex Center Locations in Four-Dimensional Space from Radar-Observed Tornadic Mesocycloneslimitation caused by the use of isotropic background error covariance. To overcome the abovementioned limitation and to improve the mesocyclone wind analyses beyond the capabilities of the 3DVar and RWAS, a two-dimensional variational method was developed by formulating the background covariance with the desired vortex-flow dependences in a moving frame following the observed mesocyclone on each selected tilt of the radar scans ( Xu et al. 2015b , hereinafter X15b ). In X15b , the mesocyclone vortex
limitation caused by the use of isotropic background error covariance. To overcome the abovementioned limitation and to improve the mesocyclone wind analyses beyond the capabilities of the 3DVar and RWAS, a two-dimensional variational method was developed by formulating the background covariance with the desired vortex-flow dependences in a moving frame following the observed mesocyclone on each selected tilt of the radar scans ( Xu et al. 2015b , hereinafter X15b ). In X15b , the mesocyclone vortex
