@article{21013, abstract = {We have addressed convective self‐aggregation (CSA) in steady and oscillating sea surface temperature (SST) and solar radiation (SOLIN) cloud‐resolving model simulations in a non‐rotating radiative‐convective equilibrium (RCE) framework. Our experiment designs are motivated by land‐ocean heterogeneity of atmospheric convection. The steady and oscillating forcings are idealizations of ocean and land conditions, respectively, based on their differences in heat capacities. In both kinds of simulations, the diurnal mean SST and SOLIN are the same, and both SST and SOLIN are only varied in time (i.e., they are spatially homogeneous at any given time). We find that diurnally oscillating forcing accelerates CSA. Stronger long‐wave cooling in dry regions at night and during the warm SST phase (late afternoon) both allow the long‐wave feedback, known to favor aggregation, to intensify compared to steady forcing simulations. In addition to the long‐wave, reduced short‐wave warming in dry regions (during the day) further enhances radiative cooling there compared to moist regions. Overall, the radiative cooling is enhanced in dry regions compared to neighboring moist convective regions. A dry subsidence is driven by this net radiative (short‐wave plus long‐wave) cooling, consistent with earlier work on CSA. Stronger radiative cooling allows stronger subsidence which allows low‐level circulation to more efficiently transport moisture and energy up‐gradient, driving convection to aggregate faster. We also note a sensitivity of our experimental setup to initial conditions, more so at warmer SST. This stochastic behavior might be critical in reconciling the differences of opinion regarding the response of convection aggregation to oscillating SST forcing.}, author = {GOSWAMI, BIDYUT B and Lu, Ziyin and Muller, Caroline J}, issn = {1942-2466}, journal = {Journal of Advances in Modeling Earth Systems}, number = {1}, publisher = {Wiley}, title = {{Convective self‐aggregation in diurnally oscillating sea surface temperature and solar forcing experiments}}, doi = {10.1029/2024ms004576}, volume = {18}, year = {2026}, } @article{21657, abstract = {We compare three global kilometer-scale models (ICON, IFS and NICAM) to clarify the advantages and challenges of high-resolution global weather and climate modeling, using different approaches to represent convection, from fully parameterized to fully explicit. Our analysis focuses on tropical precipitation characteristics spanning a wide range of spatio-temporal scales—including the diurnal cycle, extreme precipitation, convective organization, and the Madden-Julian Oscillation (MJO)—along with interactions between convection and the thermodynamic environment. All three models commonly show weaker convective organization with smaller precipitation cells than observed, though the strength of the bias varies by model. This diversity is introduced by differences in the representation of (a) convective initiation affected by the convective sensitivity to moisture and (b) tropospheric moistening associated with deep convection. Models with stronger thermodynamic-convection coupling increase environmental moisture near convection, thereby enhancing convective organization. This has important upscale effects on the MJO; while IFS and NICAM capture its eastward propagation well, ICON has difficulty reproducing it. The amplitudes and phases of precipitation diurnal cycles over land show much greater disagreement among the models than over ocean, influenced by how convection is initiated. Biases in rain evaporation and cold pool formation hinder the propagation of mesoscale convection, leading to errors such as the misrepresentation of nocturnal convection moving off the coast of Sumatra in IFS and ICON. These results highlight the importance of thermodynamic-convection coupling in realistically simulating tropical convection across scales. To improve this coupling, kilometer-scale models require better representation of the interaction between resolved convection and three-dimensional turbulent mixing.}, author = {Takasuka, Daisuke and Becker, Tobias and Bao, Jiawei}, issn = {1942-2466}, journal = {Journal of Advances in Modeling Earth Systems}, number = {3}, publisher = {Wiley}, title = {{Precipitation characteristics and thermodynamic-convection coupling in global kilometer-scale simulations}}, doi = {10.1029/2025MS005343}, volume = {18}, year = {2026}, } @article{19416, abstract = {Recently, Biagioli and Tompkins (2023, https://doi.org/10.1029/2022ms003231) used a simple stochastic model to derive a dimensionless parameter to predict convective self aggregation (SA) development, which was based on the derivation of the maximum free convective distance ($d_{clr}$) expected in the pre-aggregated, random state. Our goal is to test and further investigate this hypothesis, namely that $d_{clr}$ can predict SA occurrence, using an ensemble of twenty-four distinct combinations of horizontal mixing, planetary boundary layer (PBL), and microphysical parameterizations. We conclude that the key impact of parameterization schemes on SA is through their control of the number of convective cores and their relative spacing, $d_{clr}$, which itself is impacted by cold-pool (CP) properties and mean updraft core size. SA is more likely when the convective core count is small, while CPs modify convective spacing via suppression in their interiors and triggering by gust-front convergence and collisions. Each parameterization scheme emphasizes a different mechanism. Subgrid-scale horizontal turbulent mixing mainly affects SA through the determination of convective core size and thus spacing. The sensitivity to the microphysics is mainly through rain evaporation and the subsequent impact on CPs, while perturbations to the ice cloud microphysics have a limited effect. Non-local PBL mixing schemes promote SA primarily by increasing convective inhibition through inversion entrainment and altering low cloud amounts, leading to fewer convective cores and larger $d_{clr}$. }, author = {Casallas Garcia, Alejandro and Tompkins, A.M. and Muller, Caroline J and Thompson, G.}, issn = {1942-2466}, journal = {Journal of Advances in Modeling Earth Systems}, number = {3}, publisher = {Wiley}, title = {{Sensitivity of self-aggregation and the key role of the free convection distance}}, doi = {10.1029/2024MS004791}, volume = {17}, year = {2025}, } @article{19672, abstract = {Some of the classical models of tropical cyclone intensification predict tropical cyclones to intensify up to a steady intensity, which depends on surface fluxes only, without any relevant role played by convective motions in the troposphere, typically assumed to have a moist adiabatic lapse rate. Simulations performed using the non-hydrostatic, high-resolution model System for Atmosphere Modeling in idealized settings (rotating radiative-convective equilibrium on a doubly periodic domain) show early intensification consistent with these theoretical expectations, but different intensity evolution, with the cyclone undergoing an oscillation in wind speed. This oscillation can be linked to feedbacks between the cyclone intensity and air buoyancy: convective heating, radiative heating, and mixing with warm low stratospheric air warm the mid and upper troposphere of the cyclone stabilizing the air column and thus reducing its intensity. After the intensity decay phase, mid and upper tropospheric cooling, mostly through cold advection from the surroundings, cooled by radiation, rebuilds Convective Available Potential Energy, that peaks just before a new intensification phase. These idealized simulations thus highlight the potentially important interactions between a tropical cyclone, its environment and radiation.}, author = {Polesello, Andrea and Charinti, Giousef Alexandros and Meroni, Agostino Niyonkuru and Muller, Caroline J and Pasquero, Claudia}, issn = {1942-2466}, journal = {Journal of Advances in Modeling Earth Systems}, number = {4}, publisher = {Wiley}, title = {{Intensity oscillations of tropical cyclones: Surface versus mid and upper tropospheric processes}}, doi = {10.1029/2024MS004613}, volume = {17}, year = {2025}, } @article{20319, abstract = {The time needed by deep convection to bring the atmosphere back to equilibrium is called convective adjustment timescale or simply adjustment timescale, typically denoted by . In the Community Atmospheric Model|Community Atmosphere Model (CAM), is the convective available potential energy (CAPE) relaxation timescale and is 1 hr, worldwide. Observational evidence suggests that is generally longer than 1 hr. Further, continental and oceanic convection are different in terms of the vigor of updrafts and can have different longevities. So using hour worldwide in CAM has two potential caveats. A longer improves the simulation of the mean climate. However, it does not address the land‐ocean heterogeneity of atmospheric deep convection. We investigate the prescription of two different CAPE relaxation timescales for land ( hr) and ocean ( to 4 hr). It is arguably an extremely crude parameterization of boundary layer control on atmospheric convection. We contrast a suite of 5‐year‐long simulations with two different for land and ocean to having one globally. The choice of longer over ocean is guided by previous studies and inspired by observational pieces of evidence. Nonetheless, to complement our variable experiments, we perform a simulation with  hr and  hrs. Most importantly, our key findings are immune to the exact values of prescribed and . The CAM model, with two values , improves convective‐stratiform rainfall partitioning and the Madden–Julian oscillation propagation characteristics.}, author = {GOSWAMI, BIDYUT B and Polesello, Andrea and Muller, Caroline J}, issn = {1942-2466}, journal = {Journal of Advances in Modeling Earth Systems}, number = {9}, publisher = {Wiley}, title = {{An assessment of representing land‐ocean heterogeneity via CAPE relaxation timescale in the Community Atmospheric Model 6 (CAM6)}}, doi = {10.1029/2025ms005035}, volume = {17}, year = {2025}, } @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}, }