This paper describes the development and evaluation of a new nonhydrostatic dynamical framework for global and regional atmospheric modeling, with an emphasis on the numerical performance of dry dynamics. The model is formulated in a layer‐averaged manner using a generalized hybrid sigma‐mass vertical coordinate and an unstructured mesh. The mass‐based equations allow a flexible and effective switch between the hydrostatic and nonhydrostatic solvers. The unstructured mesh treats the conventional icosahedral grid and the more general Voronoi polygon in a consistent manner, allowing a flexible switch between quasi‐uniform and variable‐resolution modeling. The horizontal discretization and vertical discretization are formulated in an explicit Eulerian approach, while those terms describing the vertically propagating fast waves are solved implicitly. The model is equipped with physically based Smagorinsky diffusion as a tuning tool. A suite of multiscale test cases from hydrostatic to nonhydrostatic regimes is used to assess the model performance. The general strategies for evaluation focus on two aspects: (i) the nonhydrostatic solver should behave similarly to its hydrostatic counterpart under the hydrostatic regime and (ii) the nonhydrostatic solver should produce unique nonhydrostatic responses under the nonhydrostatic regime. In the context of model evaluation, model sensitivity to numerical configurations is further explored to understand the impact of isolated components, helping to identify appropriate configurations for realistic modeling applications. The present framework is a prototype toward a Global‐Regional Integrated forecast SysTem (GRIST).

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Accurate estimates of the state-of-health (SOH) for rechargeable batteries provide a significant value to the management of any operation involving electrical systems. This is especially important for transportation systems, where unexpected battery performance may lead to catastrophic failures. This paper performs experiments aiming at analyzing Lithium-ion battery performances with aging due to different temperatures and charging-discharging rates, and the optimum working areas of temperature and charging-discharging current are determined. In addition, the cycle life tests of battery are launched based on the simulations of battery performances under typical urban driving cycles using ADVISOR, and after the inspection of the results, a new SOH prediction model is proposed. Finally, in comparison with the experimental results, it is shown that the proposed method could be valid and effective in estimating battery SOH.

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