12 research outputs found
Circling in on convective organization
Get PDFCold pools (CPs) contribute to convective organization. However, it is unclear by which mechanisms organization occurs. By using a particle method to track CP gust fronts in large eddy simulations, we characterize the basic collision modes between CPs. Our results show that CP interactions, where three expanding gust fronts force an updraft, are key at triggering new convection. Using this, we conceptualize CP dynamics into a parameterâfree mathematical model: circles expand from initially random points in space. Where two expanding circles collide, a stationary front is formed. However, where three expanding circles enclose a single point, a new expanding circle is seeded. This simple model supports three fundamental features of CP dynamics: precipitation cells constitute a spatially interacting system; CPs come in generations; and scales steadily increase throughout the diurnal cycle. Finally, this model provides a framework for how CPs act to cause convective selfâorganization, clustering, and extremes
Can Recurrence Quantification Analysis Be Useful in the Interpretation of Airborne Turbulence Measurements?
Get PDFIn airborne data or model outputs, clouds are often defined using information about Liquid Water Content (LWC). Unfortunately LWC is not enough to retrieve information about the dynamical boundary of the cloud, that is, volume of turbulent air around the cloud. In this work, we propose an algorithmic approach to this problem based on a method used in time series analysis of dynamical systems, namely Recurrence Plot (RP) and Recurrence Quantification Analysis (RQA). We construct RPs using time series of turbulence kinetic energy, vertical velocity and temperature fluctuations as variables important for cloud dynamics. Then, by studying time series of laminarity (LAM), a variable which is calculated using RPs, we distinguish between turbulent and non-turbulent segments along a horizontal flight leg. By selecting a single threshold of this quantity, we are able to reduce the number of subjective variables and their thresholds used in the definition of the dynamical cloud boundary
Idealized large-eddy and convection-resolving simulations of moist convection over mountainous terrain
Get PDFOn summertime fair-weather days, thermally driven wind systems play an important role in determining the initiation of convection and the occurrence of localized precipitation episodes over mountainous terrain. This study compares the mechanisms of convection initiation and precipitation development within a thermally driven flow over an idealized double-ridge system in large-eddy (LESs) and convection-resolving (CRM) simulations. First, LES at a horizontal grid spacing of 200 m is employed to analyze the developing circulations and associated clouds and precipitation. Second, CRM simulations at horizontal grid length of 1 km are conducted to evaluate the performance of a kilometer-scale model in reproducing the discussed mechanisms.
Mass convergence and a weaker inhibition over the two ridges flanking the valley combine with water vapor advection by upslope winds to initiate deep convection. In the CRM simulations, the spatial distribution of clouds and precipitation is generally well captured. However, if the mountains are high enough to force the thermally driven flow into an elevated mixed layer, the transition to deep convection occurs faster, precipitation is generated earlier, and surface rainfall rates are higher compared to the LES. Vertical turbulent fluxes remain largely unresolved in the CRM simulations and are underestimated by the model, leading to stronger upslope winds and increased horizontal moisture advection toward the mountain summits. The choice of the turbulence scheme and the employment of a shallow convection parameterization in the CRM simulations change the strength of the upslope winds, thereby influencing the simulated timing and intensity of convective precipitation
The 3D Elliptical Parcel-In-Cell (EPIC) method
Get PDFWe present the three-dimensional version of the Elliptical Parcel-In-Cell (EPIC) method for the simulation of fluid flows and analogous continuum systems. The method represents a flow using a space-filling set of ellipsoidal parcels, which move, rotate and deform in the flow field. Additionally, parcels may carry any number of attributes, such as vorticity, density, temperature, etc, which generally evolve in time on the moving parcels. An underlying grid is used for efficiency in computing the velocity field from the interpolated vorticity field, and in obtaining parcel attribute tendencies. Mixing is enabled by permitting parcels to split when excessively deformed, and by merging very small parcels with the nearest other parcel. Several tests are provided which illustrate the behaviour of the method and demonstrate its effectiveness in modelling complex, buoyancy-driven turbulent fluid flows. The results are compared with a large eddy simulation (LES) and a direct numerical simulation (DNS) model
The 3D Elliptical Parcel-In-Cell (EPIC) method
No full textWe present the three-dimensional version of the Elliptical Parcel-In-Cell (EPIC) method for the simulation of fluid flows and analogous continuum systems. The method represents a flow using a space-filling set of ellipsoidal parcels, which move, rotate and deform in the flow field. Additionally, parcels may carry any number of attributes, such as vorticity, density, temperature, etc, which generally evolve in time on the moving parcels. An underlying grid is used for efficiency in computing the velocity field from the interpolated vorticity field, and in obtaining parcel attribute tendencies. Mixing is enabled by permitting parcels to split when excessively deformed, and by merging very small parcels with the nearest other parcel. Several tests are provided which illustrate the behaviour of the method and demonstrate its effectiveness in modelling complex, buoyancy-driven turbulent fluid flows. The results are compared with a large eddy simulation (LES) and a direct numerical simulation (DNS) model
MONC and PMPIC comparison code for EPIC
No full textMONC, PMPIC and plotting source codes for the comparison with EPIC. The MONC code is a modified version of https://github.com/Leeds-MONC/monc. Please check the correct MONC and PMPIC citation if you use them in your work
The moist parcelâinâcell method for modelling moist convection
Get PDFHerein we describe a promising alternative approach to modelling moist convection and cloud development in the atmosphere. Rather than using a conventional gridâbased approach, we use Lagrangian âparcelsâ to represent key dynamical and thermodynamical variables. In the prototype model considered, parcels carry vorticity, mass, specific humidity, and liquidâwater potential temperature. In this first study, we ignore precipitation, and many of these parcel âattributesâ remain unchanged (i.e. are materially conserved). While the vorticity does change following the parcel motion, the vorticity tendency is readily computed and, crucially, unwanted numerical diffusion can be avoided. The model, called âMoist ParcelâInâCellâ (MPIC), is a hybrid approach which uses both parcels and a fixed underlying grid for efficiency: advection (here moving parcels) is Lagrangian whereas inversion (determining the velocity field) is Eulerian. The parcelâbased representation of key variables has several advantages: (1) it allows an explicit subgrid representation; (2) it provides a velocity field which is undamped by numerical diffusion all the way down to the grid scale; (3) it does away with the need for eddy viscosity parametrisations and, in their place, it provides for a natural subgrid parcel mixing; (4) it is exactly conservative (i.e. there can be no net loss or gain of any theoretically conserved attribute); and (5) it dispenses with the need to have separate equations for each conserved parcel attribute â attributes are simply labels carried by each parcel. Moreover, the latter advantage increases as more attributes are added, such as the distributions of microphysical properties, chemical composition and aerosol loading
Influence of the subcloud layer on the development of a deep convective ensemble
No full textThe rapid transition from shallow to deep convection is investigated using large-eddy simulations. The role of cold pools, which occur due to the evaporation of rainfall, is explored using a series of experiments in which their formation is suppressed.A positive feedback occurs: the presence of cold pools promotes deeper, wider, and more buoyant clouds with higher precipitation rates, which in turn lead to stronger cold pools. To assess the influence of the subcloud layer on the development of deep convection, the coupling between the cloud layer and the subcloud layer is explored using Lagrangian particle trajectories. As shown in previous studies, particles that enter clouds have properties that deviate significantly from the mean state. However, the differences between particles that enter shallow and deep clouds are remarkably small in the subcloud layer, and become larger in the cloud layer, indicating different entrainment rates. The particles that enter the deepest clouds also correspond to the widest cloud bases, which points to the importance of convective organization within the subcloud layer.Geoscience and Remote SensingCivil Engineering and Geoscience
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Proceedings from the 9th annual conference on the science of dissemination and implementation: Washington, DC, USA. 14-15 December 2016
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