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Observed Temperature and Moisture Advection Characteristics in the Southern Great Plains
Until recently, advection profiles in the planetary boundary layer have been difficult to quantify from observations. As a result, not much is known about its basic characteristics, like magnitude and diurnal cycles, or how these differ as a function of large-scale environments. Here, to provide insight into advective characteristics, a Green’s Theorem–based method for calculating profiles of advection in the lowest 3 km from an array of ground-based thermodynamic and kinematic profiling instruments has been applied to 2 years of observations from the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) observing site. Since advection largely depends on synoptic-scale forcing, a self-organizing map (SOM) was used to classify days based on mean sea level pressure analyses; from that, the diurnal evolution of vertical profiles of advection for different synoptic environments was quantified. The overall mean magnitude of the potential temperature advection is approximately ±3 K h −1 , while the moisture advection is approximately ±1.5 g kg −1 h −1 , with substantial variability in the sign and magnitude of the advective tendencies at different heights and throughout the diurnal cycle. Advection magnitude is strongly connected to the strength of synoptic-scale forcing, which varies depending on the time of year. Variability in advection is larger for potential temperature than it is for moisture, and strongly forced environments, like midlatitude cyclones, feature greater variability in the advection magnitude than weakly forced or quiescent environments.
An Optimized Parameterization of Sub‐Grid Scale Advection for Convection Permitting Models
Convection‐permitting models (CPMs) explicitly resolve deep convection yet under‐resolve the organized lateral exchanges among drafts and their environment that control entrainment/detrainment, precipitation efficiency, and mesoscale structure. In this work, we introduce the Optimized Advection Scheme (OAS), which introduces a small rotation of the Cartesian frame of reference for the horizontal winds relative to other variables used in advection that induces cross‐gradient transport to mimic under‐resolved convective mixing. The rotation angle is selected to minimize the Kullback–Leibler divergence between the simulated and satellite observed precipitation intensity distributions, yielding a physically consistent perturbation that is computationally inexpensive and portable. Optimized Advection Scheme is implemented in WRF and evaluated over Amazon (April 2014). It shifts precipitation–precipitable‐water joint distributions toward lighter rain, reduces overly intense rates, and improves mesoscale convective system (MCS) lifetime and propagation. Mechanistically, the added cross‐gradient transport promotes convective detrainment and environmental mixing, which cools and moistens the mid‐troposphere, weakens downward momentum transport, alleviates excessive downwelling shortwave biases, and warms the surface temperature. The optimized rotation angle yields comparable improvements at 4‐km and 1‐km grid spacing, demonstrating resolution‐independent benefits across the CPM gray zone. By targeting the dynamical root of under‐mixed convective circulations, rather than tuning model microphysics or closures, OAS delivers robust, scale‐aware improvements in precipitation statistics, cloud vertical structure, and characteristics of MCS (MCSs), offering a practical pathway to more reliable CPM simulations for weather and climate applications.
Propagating information content: an example with advection
The mathematical algorithm to derive geophysical information from remote sensing observations is called a retrieval. The mathematics of many retrieval problems are ill-posed, and thus a priori information is used to help constrain the derived geophysical variable to realistic values. One quantity of interest, therefore, is the information content of the observation. Perfect information content in the observation would be achieved if the retrieval were able to capture any perturbation in the desired geophysical variable with the proper magnitude. Many new data products can be derived by combining geophysical variables retrieved from multiple different remote sensors. This paper explores, for the first time, how to derive the information content of these derived products. The approach uses traditional error propagation techniques to derive the uncertainty of the derived field twice, both when the observations are used in the retrieval and also when only the a priori information from each remote sensor is propagated. These two uncertainties are then used to provide an estimate of the information content of the derived geophysical variable. This study demonstrates how to propagate the uncertainties from six different instruments to provide the information content for water vapor and temperature advection. A multi-month analysis demonstrates that, in a mean sense, the information content for temperature advection is nearly unity for all heights below 700 m while, the information content for water vapor advection is somewhat more variable but still larger than 0.6 in the convective boundary layer.
Immersive Particle Advection: Through the Scales of Renewable Energy: Preprint
We describe the benefits of immersive flow analysis for three large-scale computational science studies in the field of renewable energy. The studies encompass a range of scales, spanning from the large atmospheric scale of a wind farm to the human scale of an electric vehicle cabin down to the microscopic scale of battery material science. In these studies, users explored the flow patterns and dynamics through immersive particle advection. The integration of high-performance computing with immersive analysis provided a deeper understanding of these systems, helping develop more effective solutions for a sustainable energy future.
Experimental investigations of ablation stream interaction dynamics in tungsten wire arrays: Interpenetration, magnetic field advection, and ion deflection
Experiments have been carried out to investigate the collisional dynamics of ablation streams produced by cylindrical wire array z-pinches. A combination of laser interferometric imaging, Thomson scattering, and Faraday rotation imaging has been used to make a range of measurements of the temporal evolution of various plasma and flow parameters. This paper presents a summary of previously published data, drawing together a range of different measurements in order to give an overview of the key results. The paper focuses mainly on the results of experiments with tungsten wire arrays. Early interferometric imaging measurements are reviewed, then more recent Thomson scattering measurements are discussed; these measurements provided the first direct evidence of ablation stream interpenetration in a wire array experiment. Combining the data from these experiments gives a view of the temporal evolution of the tungsten stream collisional dynamics. In the final part of the paper, we present new experimental measurements made using an imaging Faraday rotation diagnostic. These experiments investigated the structure of magnetic fields near the array axis directly; the presence of a magnetic field has previously been inferred based on Thomson scattering measurements of ion deflection near the array axis. Although the Thomson and Faraday measurements are not in full quantitative agreement, the Faraday data do qualitatively supports the conjecture that the observed deflections are induced by a static toroidal magnetic field, which has been advected to the array axis by the ablation streams. It is likely that detailed modeling will be needed in order to fully understand the dynamics observed in the experiment.
Conservative and bounded volume-of-fluid advection on unstructured grids
Not Available
The rigorous upscaling of advection-dominated transport in heterogeneous porous media via the Method of Finite Averages
Systems involving advection-dominated transport through heterogeneous porous and fractured media are ubiquitous in subsurface engineering applications. However, upscaling such systems continues to challenge rigorous modeling efforts, particularly when advection is stronger than diffusion at fine spatial scales (i.e., when the Péclet number is greater than one at length scales that characterize a system’s unit-cells, representative elementary volumes, or averaging regions). Here, in this work, we propose and validate a strategy for extending the Method of Finite Averages (MoFA), a rigorous upscaling methodology for heterogeneous porous media, to upscale transport systems experiencing stronger advection than diffusion at fine scales (i.e., fine-scale Péclet numbers greater than one). We detail the strategy, the physical conditions under which it can be applied while retaining a priori modeling error guarantees, and implement the strategy to obtain a MoFA model for advective-diffusive transport that accommodates advective physics at fine spatial scales. We then perform two numerical experiments considering systems with system-scale Péclet numbers of 300 and 1000 — which correspond to fine-scale Péclet numbers of 30 and 100, respectively — to verify that the error guarantees are met under the strategy. After, we conduct a numerical study to demonstrate the strategy’s advantages over the original MoFA methodology. The results suggest that rigorously-upscaled transport models for heterogeneous porous media experiencing advective physics at finer spatial scales can be derived through MoFA and resolved orders of magnitude faster than their pore-scale counterparts. The results also suggest that the presented strategy is limited to modeling shallow concentration gradients when there are large differences between the time scales related to advection and a system’s temporally-varying boundary conditions. This limitation hinders the strategy’s practicality in modeling more advective systems, and as such, opportunity exists for developing additional strategies that accommodate rapidly-varying boundary conditions — and consequentially, steeper concentration gradients — while modeling advective systems with MoFA.
Onset of kinetic effects on Rayleigh–Taylor instability: Advective–diffusive asymmetry
In nature and engineering applications, the Rayleigh–Taylor instability (RTI) occurs over a wide range of Atwood, Reynolds, Mach, and Knudsen numbers. At low Atwood, Mach, and Knudsen numbers, the classic advective instability causes quasi-symmetric bubble and spike growth on the two sides of the interface. However, recent findings suggest that at high degrees of rarefaction, advective effects are suppressed and molecular diffusion leads to planar growth of the density fronts on either side of the interface. This study aims to investigate the flow physics of the transition from advective to diffusive behavior, focusing on the onset of the kinetic effects. Using the gas kinetic methodology, RTI is simulated over a range of Knudsen and Mach numbers in the transition regime. The simulation results reveal the various stages of transformation from advective instability to diffusive transport. For the first time, the study demonstrates the existence of a Knudsen–Mach parameter regime where the bubble side exhibits advective instability, while the other side shows a planar density front due to molecular diffusion, rather than the canonical advective spike shape. The dominance of different mechanisms on the two sides of the interface leads to the advective–diffusive asymmetry. In conclusion, the findings of this study can lead to a more comprehensive understanding of RTI over a wide range of Mach and Knudsen numbers.
A dynamic likelihood approach to filtering transport processes: advection-diffusion dynamics
A Bayesian data assimilation scheme is formulated for advection-dominated advective and diffusive evolutionary problems, based upon the Dynamic Likelihood (DLF) approach to filtering. The DLF was developed specifically for hyperbolic problems –waves–, and in this paper, it is extended via a split step formulation, to handle advection-diffusion problems. In the dynamic likelihood approach, observations and their statistics are used to propagate probabilities along characteristics, evolving the likelihood in time. The estimate posterior thus inherits phase information. For advection-diffusion the advective part of the time evolution is handled on the basis of observations alone, while the diffusive part is informed through the model as well as observations. We expect, and indeed show here, that in advection-dominated problems, the DLF approach produces better estimates than other assimilation approaches, particularly when the observations are sparse and have low uncertainty. The added computational expense of the method is cubic in the total number of observations over time, which is on the same order of magnitude as a standard Kalman filter and can be mitigated by bounding the number of forward propagated observations, discarding the least informative data.
Surface‐Atmosphere Decoupling Prolongs Cloud Lifetime Under Warm Advection Due To Reduced Entrainment Drying
Abstract An initially well‐mixed stratocumulus deck can remain overcast for several tens of hours under warm‐advection conditions, although moisture supply is cut off from the ocean due to surface‐atmosphere decoupling (stabilization of the surface‐atmosphere interface). In this study, a set of idealized large‐eddy simulations were performed to investigate the physical mechanism of how warm‐air advection impacts the evolution of a pre‐existing stratocumulus deck. To mimic warm‐air advection, we decrease the sea surface temperature linearly over time in a doubly periodic domain. Given the same initial conditions, the stratocumulus deck is more persistent when experiencing warm‐air advection than cold‐air advection. This persistence is caused by reduced cloud‐top entrainment drying due to decoupling, a process more influential than the decoupling‐induced cutoff of moisture supply. This mechanism is more notable when the free troposphere becomes more humid. The relevance of the mechanism to previous observations of less low‐level cloudiness under warm‐advection conditions is discussed.
AIR Algebraic Multigrid for a Space-Time Hybridizable Discontinuous Galerkin Discretization of Advection(-Diffusion)
This article investigates the efficiency, robustness, and scalability of approximate ideal restriction (AIR) algebraic multigrid as a preconditioner in the all-at-once solution of a space-time hybridizable discontinuous Galerkin discretization of advection-dominated flows. The motivation for this study is that the time-dependent advection-diffusion equation can be seen as a “steady” advection-diffusion problem in $(d+1)$-dimensions and AIR has been shown to be a robust solver for steady advection-dominated problems. Numerical examples demonstrate the effectiveness of AIR as a preconditioner for advection-diffusion problems on fixed and time-dependent domains, using both slab-by-slab and all-at-once space-time discretizations, and in the context of uniform and space-time adaptive mesh refinement. A closer look at the geometric coarsening structure that arises in AIR also explains why AIR can provide robust, scalable, space-time convergence on advective and hyperbolic problems, while most multilevel parallel-in-time schemes struggle with such problems.
Orbital Advection with Magnetohydrodynamics and Vector Potential
Orbital advection is a significant bottleneck in disk simulations, and a particularly tricky one when used in connection with magnetohydrodynamics. We have developed an orbital advection algorithm suitable for the induction equation with magnetic potential. The electromotive force is split into advection and shear terms, and we find that we do not need an advective gauge since solving the orbital advection implicitly precludes the shear term from canceling the advection term. We prove and demonstrate the third order in time accuracy of the scheme. The algorithm is also suited to non-magnetic problems. Benchmarked results of (hydrodynamical) planet–disk interaction and of the magnetorotational instability are reproduced. We include detailed descriptions of the construction and selection of stabilizing dissipations (or high-frequency filters) needed to generate practical results. The scheme is self-consistent, accurate, and elegant in its simplicity, making it particularly efficient for straightforward finite-difference methods. As a result of the work, the algorithm is incorporated in the public version of the Pencil Code, where it can be used by the community.
Evidence that Horizontal Moisture Advection Regulates the Ubiquitous Amplification of Rainfall Variability over Tropical Oceans
The column moist static energy (MSE) budget equation approximates the processes associated with column moistening and drying in the tropics, and is therefore predictive of precipitation amplification and decay. We use ERA-Interim (ERA-I) and TRMM 3B42 data to investigate day-to-day convective variability and distinguish the roles of horizontal MSE (or moisture) advection versus vertical advection, sources, and sinks. Over tropical convergence zones, results suggest that horizontal moisture advection is a primary driver of day-to-day precipitation fluctuations; when drying via horizontal moisture advection is smaller (greater) than Chikira’s “column process,” precipitation tends to amplify (decay). In the absence of horizontal moisture advection, precipitation tends to increase spontaneously almost universally through a positive column process feedback. This bulk positive feedback is characterized by negative effective gross moist stability (GMS), which is maintained throughout the tropical convergence zones. How this positive feedback is achieved varies geographically, depending on the shape of vertical velocity (omega) profiles. In regions where omega profiles are top-heavy, the effective GMS is negative primarily owing to strong feedbacks between convection and diabatic MSE sources (radiative and surface fluxes). In these regions, vertical MSE advection stabilizes the atmosphere (positive vertical GMS). Where omega profiles are bottom-heavy, by contrast, a positive feedback is primarily driven by import of MSE through a shallow circulation (negative vertical GMS). The diabatic feedback and vertical GMS are in a seesaw balance, offsetting one another. Our results suggest that ubiquitous convective variability is amplified by the same mechanism as moisture-mode instability.
Thermally driven advection for radioxenon transport from an underground nuclear explosion
Abstract Barometric pumping is a ubiquitous process resulting in migration of gases in the subsurface that has been studied as the primary mechanism for noble gas transport from an underground nuclear explosion (UNE). However, at early times following a UNE, advection driven by explosion residual heat is relevant to noble gas transport. A rigorous measure is needed for demonstrating how, when, and where advection is important. In this paper three physical processes of uncertain magnitude (oscillatory advection, matrix diffusion, and thermally driven advection) are parameterized by using boundary conditions, system properties, and source term strength. Sobol' sensitivity analysis is conducted to evaluate the importance of all physical processes influencing the xenon signals. This study indicates that thermally driven advection plays a more important role in producing xenon signals than oscillatory advection and matrix diffusion at early times following a UNE, and xenon isotopic ratios are observed to have both time and spatial dependence.