Search Results
develop broad stratiform regions beyond the mature phase ( Romatschke and Houze 2010 ; Rasmussen and Houze 2011 , 2016 ; Rasmussen et al. 2016 ). This convection life cycle was examined for a case in SSA using available satellite observations and a WRF model simulation that confirmed this life cycle evolution ( Rasmussen and Houze 2016 ), which aligns well with that of other global convective hotspots featuring frequent upscale growth into MCSs over both land and ocean regions ( Houze 2004
develop broad stratiform regions beyond the mature phase ( Romatschke and Houze 2010 ; Rasmussen and Houze 2011 , 2016 ; Rasmussen et al. 2016 ). This convection life cycle was examined for a case in SSA using available satellite observations and a WRF model simulation that confirmed this life cycle evolution ( Rasmussen and Houze 2016 ), which aligns well with that of other global convective hotspots featuring frequent upscale growth into MCSs over both land and ocean regions ( Houze 2004
between ENSO phases. The TRMM PR rainfall algorithm is known to underestimate precipitation produced by deep convection over land ( Iguchi et al. 2009 ; Rasmussen et al. 2013 ). Therefore, rainfall was instead estimated with the Z – R relationship used by Rasmussen et al. (2013) , Z = aR b , where Z is the radar reflectivity factor (mm 6 m −3 ) and R is the corrected rain rate (mm h −1 ). The parameters a and b are constants based on rain type. The values used to calculate rainfall in
between ENSO phases. The TRMM PR rainfall algorithm is known to underestimate precipitation produced by deep convection over land ( Iguchi et al. 2009 ; Rasmussen et al. 2013 ). Therefore, rainfall was instead estimated with the Z – R relationship used by Rasmussen et al. (2013) , Z = aR b , where Z is the radar reflectivity factor (mm 6 m −3 ) and R is the corrected rain rate (mm h −1 ). The parameters a and b are constants based on rain type. The values used to calculate rainfall in
distribution, relation to diurnal and seasonal cycles, and associated synoptic conditions) have also been studied over different regions using different datasets and detection criteria. Usually, a conservative moisture variable is utilized to identify the dryline—either specific humidity or mixing ratio—although some works use near-surface dewpoint temperature. In addition, conditions over the temperature field are often included to eliminate surface fronts, and on occasions, a wind shift across the
distribution, relation to diurnal and seasonal cycles, and associated synoptic conditions) have also been studied over different regions using different datasets and detection criteria. Usually, a conservative moisture variable is utilized to identify the dryline—either specific humidity or mixing ratio—although some works use near-surface dewpoint temperature. In addition, conditions over the temperature field are often included to eliminate surface fronts, and on occasions, a wind shift across the
the U.S. operational National Weather Service radiosonde network (horizontal spacing ~300 km). Studies using data from these and other sources have illustrated significant environmental variability surrounding focal areas of CI owing to: intersections between air masses (e.g., Wilson and Mueller 1993 ; Kingsmill 1995 ; Ziegler and Rasmussen 1998 ; Markowski et al. 2006 ; Arnott et al. 2006 ; Buban et al. 2007 ; Wakimoto and Murphey 2009 ), complex terrain (e.g., Banta and Schaaf 1987
the U.S. operational National Weather Service radiosonde network (horizontal spacing ~300 km). Studies using data from these and other sources have illustrated significant environmental variability surrounding focal areas of CI owing to: intersections between air masses (e.g., Wilson and Mueller 1993 ; Kingsmill 1995 ; Ziegler and Rasmussen 1998 ; Markowski et al. 2006 ; Arnott et al. 2006 ; Buban et al. 2007 ; Wakimoto and Murphey 2009 ), complex terrain (e.g., Banta and Schaaf 1987
( Morrison 2017 ); thus, initial updraft width could be one factor governing CI. Numerical representation of updraft size and vertical mass flux is sensitive to the model grid resolution (e.g., Bryan et al. 2003 ; Varble et al. 2014 ; Varble et al. 2020 ; Hirt et al. 2020 ), as well as other physical parameterizations, limiting what can be ascertained about updraft-environment interactions using convection-allowing mesoscale models. A more complete understanding of CI requires synchronized
( Morrison 2017 ); thus, initial updraft width could be one factor governing CI. Numerical representation of updraft size and vertical mass flux is sensitive to the model grid resolution (e.g., Bryan et al. 2003 ; Varble et al. 2014 ; Varble et al. 2020 ; Hirt et al. 2020 ), as well as other physical parameterizations, limiting what can be ascertained about updraft-environment interactions using convection-allowing mesoscale models. A more complete understanding of CI requires synchronized
-to-bowing MCS transition has been documented before in the USA by Moller et al. (1990) , Conway et al. (1996) , Finley et al. (2001) , Klimowski et al. (2004) , among others, although not explicitly orographic supercell-to-bowing MCS transitions. Finley et al. (2001) used a numerical modeling approach to analyze a supercell-to-bowing MCS transition, determining that just prior to UCG, the low-level cold pool deepened and intensified, which resulted in a strong low-level horizontal pressure gradient
-to-bowing MCS transition has been documented before in the USA by Moller et al. (1990) , Conway et al. (1996) , Finley et al. (2001) , Klimowski et al. (2004) , among others, although not explicitly orographic supercell-to-bowing MCS transitions. Finley et al. (2001) used a numerical modeling approach to analyze a supercell-to-bowing MCS transition, determining that just prior to UCG, the low-level cold pool deepened and intensified, which resulted in a strong low-level horizontal pressure gradient
