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Abstract. Aliasing errors arise in the multiplication of partial sums, such as those encountered when numerically solving the Navier–Stokes equations, and can be detrimental to the accuracy of a numerical solution. In this work, a performance and cost analysis is proposed for widely used dealiasing schemes in large-eddy simulation, focusing on a neutrally stratified, pressure-driven atmospheric boundary-layer flow. Specifically, the exact 3∕2 rule, the Fourier truncation method, and a high-order Fourier smoothing method are intercompared. Tests are performed within a newly developed mixed pseudo-spectral finite differences large-eddy simulation code, parallelized using a two-dimensional pencil decomposition. A series of simulations are performed at varying resolution, and key flow statistics are intercompared among the considered runs and dealiasing schemes. The three dealiasing methods compare well in terms of first- and second-order statistics for the considered cases, with modest local departures that decrease as the grid stencil is reduced. Computed velocity spectra using the 3∕2 rule and the FS method are in good agreement, whereas the FT method yields a spurious energy redistribution across wavenumbers that compromises both the energy-containing and inertial sublayer trends. The main advantage of the FS and FT methods when compared to the 3∕2 rule is a notable reduction in computational cost, with larger savings as the resolution is increased (15 % for a resolution of 1283, up to a theoretical 30 % for a resolution of 20483).

Monitoring airborne inoculum is gaining interest as a potential means of The use of airborne inoculum monitoring is becoming of more interest in hopes of giving growers an earlier warning of disease risk in a management unit or region. This information is sought by growers to aid in adapting to changes in the management tools at their disposal and the market driven need to reduce the use of fungicides and cost of production. To effectively use inoculum monitoring as a decision aide, there is an increasing need to understand the physics of particle transport in managed and natural ecosystem s plant canopies to effectively deploy and use near-ground aerial inoculum data. This understanding, combined with the nuances of pathogen- specific biology and disease epidemiology, can serve as a guide to designing improved monitoring approaches. The complexity of any pathosystem and local environment are such that there is not a generalized approach to near-ground air sampler placement, but there is a conceptual framework to arrive at a “semi-optimal” solution based on available resources. This review is intended as a brief synopsis of the linkages among pathogen biology, disease epidemiology, and the physics of the aerial dispersion of pathogen inoculum and what to consider when deciding where to locate ground-based air samplers. We leverage prior work in developing airborne monitoring tools for hops, grapes, spinach, and turf, and research into the fluid mechanics governing particle transport in sparse canopies and urban and forest environments. We present simulation studies to guide readers in their understanding ofdemonstrate how particles move in the complex environments of agricultural fields and to illustrate the limited sampling area of common air samplers.