Splitting horizontal and vertical polynomial order in a compatible finite element discretisation for numerical weather prediction
Daniel Witt, Thomas Bendall, Jemma Shipton

TL;DR
This paper introduces a novel compatible finite element discretisation for atmospheric equations that independently treats horizontal and vertical polynomial orders, improving accuracy and efficiency in numerical weather prediction.
Contribution
It presents a split-order tensor-product finite element scheme that preserves key properties and analyzes its wave propagation and accuracy, offering a new approach for atmospheric modeling.
Findings
Increasing horizontal polynomial order enhances gravity wave representation.
Vertical order increase can degrade dispersion accuracy near the grid scale.
Horizontal order increase yields significant accuracy improvements in atmospheric simulations.
Abstract
The accurate and efficient representation of atmospheric dynamics remains a central challenge in numerical weather prediction. A particular difficulty arises from the strong anisotropy of the atmosphere, in which horizontal and vertical motions occur on very different length scales, motivating numerical discretisations that can reflect this structure. In this study, we introduce a compatible finite element discretisation of the compressible Boussinesq and compressible Euler equations in which the horizontal and vertical polynomial orders are treated independently. The split-order discretisation is constructed using a tensor-product framework that preserves the discrete de Rham complex and associated mimetic properties. Its wave-propagation characteristics are examined through a discrete dispersion analysis that extends previous analyses to configurations with differing horizontal and…
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Taxonomy
TopicsMeteorological Phenomena and Simulations · Wind and Air Flow Studies · Tropical and Extratropical Cyclones Research
