Life cycle of midlatitude deep convective systems in a Lagrangian framework

The core information for this publication's citation.: 
Feng, Z., X. Dong, B. Xi, S. A. McFarlane, A. D. Kennedy, B. Lin, and P. Minnis (2012), Life cycle of midlatitude deep convective systems in a Lagrangian framework, J. Geophys. Res., 117, D23201, doi:10.1029/2012JD018362.
Abstract: 

Deep convective systems (DCSs) consist of intense convective cores (CC), large stratiform rain (SR) regions, and extensive nonprecipitating anvil clouds (AC). This study focuses on the evolution of these three components and the factors that affect system lifetime and AC production. An automated satellite tracking method is used in conjunction with a recently developed multisensor hybrid classification to analyze the evolution of DCS structure in a Lagrangian framework over the central United States. Composite analysis from 4221 tracked DCSs during two warm seasons (May–August, 2010–2011) shows that maximum system size correlates with lifetime, and longer-lived DCSs have more extensive SR and AC. For short to medium systems (lifetimes <6 h), the lifetime is mainly attributed to the intensity of the initial convection. Systems that last longer than 6 h are associated with up to 50% higher midtropospheric relative humidity and up to 40% stronger middle to upper tropospheric wind shear. Such environments allow continuous growth of detrained hydrometeors by deposition, supporting further development of the SR and AC region, as indicated by the increased staggered timing between stratiform clouds and peak convective intensity, thus prolonging the system lifetime beyond 6 h. Regression analysis shows that the areal coverage of thick AC is strongly correlated with the size of CC, updraft strength, and SR area. Ambient upper tropospheric wind speed and wind shear also play an important role for convective AC production, where for systems with large AC (radius >120 km) they are 24% and 20% higher, respectively, than those with small AC (radius = 20 km).

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Research Program: 
Modeling Analysis and Prediction Program (MAP)