@article{14453,
  abstract     = {Squall lines are substantially influenced by the interaction of low-level shear with cold pools associated with convective downdrafts. Beyond an optimal shear amplitude, squall lines tend to orient themselves at an angle with respect to the low-level shear. While the mechanisms behind squall line orientation seem to be increasingly well understood, uncertainties remain on the implications of this orientation. Roca and Fiolleau (2020, https://doi.org/10.1038/s43247-020-00015-4) show that long lived mesoscale convective systems, including squall lines, are disproportionately involved in rainfall extremes in the tropics. This article investigates the influence of the interaction between low-level shear and squall line outflow on squall line generated precipitation extrema in the tropics. Using a cloud resolving model, simulated squall lines in radiative convective equilibrium amid a shear-dominated regime (super optimal), a balanced regime (optimal), and an outflow dominated regime (suboptimal). Our results show that precipitation extremes in squall lines are 40% more intense in the case of optimal shear and remain 30% superior in the superoptimal regime relative to a disorganized case. With a theoretical scaling of precipitation extremes (C. Muller & Takayabu, 2020, https://doi.org/10.1088/1748-9326/ab7130), we show that the condensation rates control the amplification of precipitation extremes in tropical squall lines, mainly due to its change in vertical mass flux (dynamic component). The reduction of dilution by entrainment explains half of this change, consistent with Mulholland et al. (2021, https://doi.org/10.1175/jas-d-20-0299.1). The other half is explained by increased cloud-base velocity intensity in optimal and superoptimal squall lines.},
  author       = {Abramian, Sophie and Muller, Caroline J and Risi, Camille},
  issn         = {1942-2466},
  journal      = {Journal of Advances in Modeling Earth Systems},
  number       = {10},
  publisher    = {Wiley},
  title        = {{Extreme precipitation in tropical squall lines}},
  doi          = {10.1029/2022MS003477},
  volume       = {15},
  year         = {2023},
}

@article{14564,
  abstract     = {Cumulus parameterization (CP) in state‐of‐the‐art global climate models is based on the quasi‐equilibrium assumption (QEA), which views convection as the action of an ensemble of cumulus clouds, in a state of equilibrium with respect to a slowly varying atmospheric state. This view is not compatible with the organization and dynamical interactions across multiple scales of cloud systems in the tropics and progress in this research area was slow over decades despite the widely recognized major shortcomings. Novel ideas on how to represent key physical processes of moist convection‐large‐scale interaction to overcome the QEA have surged recently. The stochastic multicloud model (SMCM) CP in particular mimics the dynamical interactions of multiple cloud types that characterize organized tropical convection. Here, the SMCM is used to modify the Zhang‐McFarlane (ZM) CP by changing the way in which the bulk mass flux and bulk entrainment and detrainment rates are calculated. This is done by introducing a stochastic ensemble of plumes characterized by randomly varying detrainment level distributions based on the cloud area fraction of the SMCM. The SMCM is here extended to include shallow cumulus clouds resulting in a unified shallow‐deep CP. The new stochastic multicloud plume CP is validated against the control ZM scheme in the context of the single column Community Climate Model of the National Center for Atmospheric Research using data from both tropical ocean and midlatitude land convection. Some key features of the SMCM CP such as it capability to represent the tri‐modal nature of organized convection are emphasized.},
  author       = {Khouider, B. and GOSWAMI, BIDYUT B and Phani, R. and Majda, A. J.},
  issn         = {1942-2466},
  journal      = {Journal of Advances in Modeling Earth Systems},
  keywords     = {General Earth and Planetary Sciences, Environmental Chemistry, Global and Planetary Change},
  number       = {11},
  publisher    = {American Geophysical Union},
  title        = {{A shallow‐deep unified stochastic mass flux cumulus parameterization in the single column community climate model}},
  doi          = {10.1029/2022ms003391},
  volume       = {15},
  year         = {2023},
}

@article{14654,
  abstract     = {Two assumptions commonly applied in convection schemes—the diagnostic and quasi-equilibrium assumptions—imply that convective activity (e.g., convective precipitation) is controlled only by the large-scale (macrostate) environment at the time. In contrast, numerical experiments indicate a “memory” or dependence of convection also on its own previous activity whereby subgrid-scale (microstate) structures boost but are also boosted by convection. In this study we investigated this memory by comparing single-column model behavior in two idealized tests previously executed by a cloud-resolving model (CRM). Conventional convection schemes that employ the diagnostic assumption fail to reproduce the CRM behavior. The memory-capable org and Laboratoire de Météorologie Dynamique Zoom cold pool schemes partially capture the behavior, but fail to fully exhibit the strong reinforcing feedbacks implied by the CRM. Analysis of this failure suggests that it is because the CRM supports a linear (or superlinear) dependence of the subgrid structure growth rate on the precipitation rate, while the org scheme assumes a sublinear dependence. Among varying versions of the org scheme, the growth rate of the org variable representing subgrid structure is strongly associated with memory strength. These results demonstrate the importance of parameterizing convective memory, and the ability of idealized tests to reveal shortcomings of convection schemes and constrain model structural assumptions.},
  author       = {Hwong, Yi-Ling and Colin, M. and Aglas, Philipp and Muller, Caroline J and Sherwood, S. C.},
  issn         = {1942-2466},
  journal      = {Journal of Advances in Modeling Earth Systems},
  number       = {12},
  publisher    = {Wiley},
  title        = {{Assessing memory in convection schemes using idealized tests}},
  doi          = {10.1029/2023MS003726},
  volume       = {15},
  year         = {2023},
}