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In their 2015 Current Biology paper, Streby et al. [1] reported that Golden-winged Warblers (Vermivora chrysoptera), which had just migrated to their breeding location in eastern Tennessee, performed a facultative and up to “>1,500 km roundtrip” to the Gulf of Mexico to avoid a severe tornadic storm. From light-level geolocator data, wherein geographical locations are estimated via the timing of sunrise and sunset, Streby et al. [1] concluded that the warblers had evacuated their breeding area approximately 24 hours before the storm and returned about five days later. The authors presented this finding as evidence that migratory birds avoid severe storms by temporarily moving long-distances. However, the tracking method employed by Streby et al. [1] is prone to considerable error and uncertainty. Here, we argue that this interpretation of the data oversteps the limits of the used tracking technique. By calculating the expected geographical error range for the tracked birds, we demonstrate that the hypothesized movements fell well within the geolocators’ inherent error range for this species and that such deviations in latitude occur frequently even if individuals remain stationary

We derive an implicit-explicit (IMEX) formalism for the three-dimensional Euler equations that allow a unified representation of various nonhydrostatic flow regimes, including cloud-resolving and mesoscale (flow in a 3D Cartesian domain) as well as global regimes (flow in spherical geometries). This general IMEX formalism admits numerous types of methods including single-stage multi-step methods (e.g., Adams methods and backward difference formulas) and multi-stage single-step methods (e.g., additive Runge-Kutta methods). The significance of this result is that it allows a numerical model to reuse the same machinery for all classes of time-integration methods described in this work. We also derive two classes of IMEX methods, 1D and 3D, and show that they achieve their expected theoretical rates of convergence regardless of the geometry (e.g., 3D box or sphere) and introduce a new second-order IMEX Runge-Kutta method that performs better than the other second order methods considered. We then compare all the IMEX methods in terms of accuracy and efficiency for two types of geophysical fluid dynamics problems: buoyant convection and inertia-gravity waves. These results show that the high-order time-integration methods yield better efficiency particularly when high levels of accuracy are desired.

This paper describes a unified, element based Galerkin (EBG) framework for a three-dimen- sional, nonhydrostatic model for the atmosphere. In general, EBG methods possess high- order accuracy, geometric flexibility, excellent dispersion properties and good scalability. Our nonhydrostatic model, based on the compressible Euler equations, is appropriate for both limited-area and global atmospheric simulations. Both a continuous Galerkin (CG), or spectral element, and discontinuous Galerkin (DG) model are considered using hexahe- dral elements. The formulation is suitable for both global and limited-area atmospheric modeling, although we restrict our attention to 3D limited-area phenomena in this study; global atmospheric simulations will be presented in a follow-up paper. Domain decompo- sition and communication algorithms used by both our CG and DG models are presented. The communication volume and exchange algorithms for CG and DG are compared and contrasted. Numerical verification of the model was performed using two test cases: flow past a 3D mountain and buoyant convection of a bubble in a neutral atmosphere; these tests indicate that both CG and DG can simulate the necessary physics of dry atmospheric dynamics. Scalability of both methods is shown up to 8192 CPU cores, with near ideal scal- ing for DG up to 32,768 cores.