Atmospheric tracer transport is a computationally demanding component of the atmospheric dynamical core of weather and climate simulations. Simulations typically have tens to hundreds of tracers. A tracer field is required to preserve several properties, including mass, shape, and tracer consistency. To improve computational efficiency, it is common to apply different spatial and temporal discretizations to the tracer transport equations than to the dynamical equations. Using different discretizations increases the difficulty of preserving properties. This paper provides a unified framework to analyze the property preservation problem and classes of algorithms to solve it. We examine the primary problem and a safety problem; describe three classes of algorithms to solve these; introduce new algorithms in two of these classes; make connections among the algorithms; analyze each algorithm in terms of correctness, bound on its solution magnitude, and its communication efficiency; and study numerical results. A new algorithm, QLT, has the smallest communication volume, and in an important case it redistributes mass approximately locally. These algorithms are only very loosely coupled to the underlying discretizations of the dynamical and tracer transport equations and thus are broadly and efficiently applicable. In addition, they may be applied to remap problems in applications other than tracer transport.
Herrington, Adam R.; Lauritzen, Peter H.; Taylor, Mark A.; Goldhaber, Steve; Eaton, Brian E.; Bacmeister, Julio T.; Reed, Kevin A.; Ullrich, Paul A.
Atmospheric modeling with element-based high-order Galerkin methods presents a unique challenge to the conventional physics-dynamics coupling paradigm, due to the highly irregular distribution of nodes within an element and the distinct numerical characteristics of the Galerkin method. The conventional coupling procedure is to evaluate the physical parameterizations (physics) on the dynamical core grid. Evaluating the physics at the nodal points exacerbates numerical noise from the Galerkin method, enabling and amplifying local extrema at element boundaries. Grid imprinting may be substantially reduced through the introduction of an entirely separate, approximately isotropic finite-volume grid for evaluating the physics forcing. Integration of the spectral basis over the control volumes provides an area-average state to the physics, which is more representative of the state in the vicinity of the nodal points rather than the nodal point itself and is more consistent with the notion of a ''large-scale state'' required by conventional physics packages. This study documents the implementation of a quasi-equal-area physics grid into NCAR's Community Atmosphere Model Spectral Element and is shown to be effective at mitigating grid imprinting in the solution. The physics grid is also appropriate for coupling to other components within the Community Earth System Model, since the coupler requires component fluxes to be defined on a finite-volume grid, and one can be certain that the fluxes on the physics grid are, indeed, volume averaged.
A set of algorithms based on characteristic discontinuous Galerkin methods is presented for tracer transport on the sphere. The algorithms are designed to reduce message passing interface communication volume per unit of simulated time relative to current methods generally, and to the spectral element scheme employed by the U.S. Department of Energy's Exascale Earth System Model (E3SM) specifically. Two methods are developed to enforce discrete mass conservation when the transport schemes are coupled to a separate dynamics solver; constrained transport and Jacobian-combined transport. A communication-efficient method is introduced to enforce tracer consistency between the transport scheme and dynamics solver; this method also provides the transport scheme's shape preservation capability. A subset of the algorithms derived here is implemented in E3SM and shown to improve transport performance by a factor of 2.2 for the model's standard configuration with 40 tracers at the strong scaling limit of one element per core.
Concern over Arctic methane (CH 4 ) emissions has increased following recent discoveries of poorly understood sources and predictions that methane emissions from known sources will grow as Arctic temperatures increase. New efforts are required to detect increases and explain sources without being confounded by the multiple sources. Methods for distinguishing different sources are critical. We conducted measurements of atmospheric methane and source tracers and performed baseline global atmospheric modeling to begin assessing the climate impact of changes in atmospheric methane. The goal of this project was to address uncertainties in Arctic methane sources and their potential impact on climate by (1) deploying newly developed trace-gas analyzers for measurements of methane, methane isotopologues, ethane, and other tracers of methane sources in the Barrow, AK, (2) characterizing methane sources using high-resolution atmospheric chemical transport models and tracer measurements, and (3) modeling Arctic climate using the state-of-the-art high- resolution Spectral Element Community Atmosphere Model (CAM-SE).
This article discusses the problem of identifying extreme climate events such as intense storms within large climate data sets. The basic storm detection algorithm is reviewed, which splits the problem into two parts: a spatial search followed by a temporal correlation problem. Two specific implementations of the spatial search algorithm are compared: the commonly used grid point search algorithm is reviewed, and a new algorithm called Stride Search is introduced. The Stride Search algorithm is defined independently of the spatial discretization associated with a particular data set. Results from the two algorithms are compared for the application of tropical cyclone detection, and shown to produce similar results for the same set of storm identification criteria. Differences between the two algorithms arise for some storms due to their different definition of search regions in physical space. The physical space associated with each Stride Search region is constant, regardless of data resolution or latitude, and Stride Search is therefore capable of searching all regions of the globe in the same manner. Stride Search's ability to search high latitudes is demonstrated for the case of polar low detection. Wall clock time required for Stride Search is shown to be smaller than a grid point search of the same data, and the relative speed up associated with Stride Search increases as resolution increases.
The Department of Energy’s (DOE) Biological and Environmental Research project, “Water Cycle and Climate Extremes Modeling” is improving our understanding and modeling of regional details of the Earth’s water cycle. Sandia is using high resolution model behavior to investigate storms in the Arctic.