A Multiscale Dynamical Model in a Dry-Mass Coordinate for Weather and Climate Modeling: Moist Dynamics and Its Coupling to Physics

• Published in: Monthly weather review 2020-07, Vol.148 (7), p.2671-2699
• Main Authors: Zhang, Yi, Li, Jian, Yu, Rucong, Liu, Zhuang, Zhou, Yihui, Li, Xiaohan, Huang, Xiaomeng
• Format: Article
• Language: English
• Subjects: Climate; Climate models; Clouds; Components; Context; Continuity equation; Coupling; Dynamic models; Dynamics; Equations of motion; Finite element method; Fluxes; Intercomparison; Mass; Mass flux; Modelling; Performance evaluation; Physics; Tracer transport; Tracers; Transport; Weather forecasting; Workflow
• ISSN: 0027-0644; 1520-0493
• DOI: 10.1175/MWR-D-19-0305.1

A multiscale dynamical model for weather forecasting and climate modeling is developed and evaluated in this study. It extends a previously established layer-averaged, unstructured-mesh nonhydrostatic dynamical core (dycore) to moist dynamics and parameterized physics in a dry-mass vertical coordinate. The dycore and tracer transport components are coupled in a mass-consistent manner, with the dycore providing time-averaged horizontal mass fluxes to passive transport, and tracer transport feeding back to the dycore with updated moisture constraints. The vertical mass flux in the tracer transport is obtained by reevaluating the mass continuity equation to ensure compatibility. A general physics–dynamics coupling workflow is established, and a dycore–tracer–physics splitting strategy is designed to couple these components in a flexible and efficient manner. In this context, two major physics–dynamics coupling strategies are examined. Simple-physics packages from the 2016 Dynamical Core Model Intercomparison Project (DCMIP2016) experimental protocols are used to facilitate the investigation of the model behaviors in idealized moist-physics configurations, including cloud-scale modeling, weather forecasting, and climate modeling, and in a real-world test-case setup. Performance evaluation demonstrates that the model is able to produce reasonable sensitivity and variability at various spatiotemporal scales. The consideration and implications of different physics–dynamics coupling options are discussed within this context. The appendix provides discussion on the energetics in the continuous- and discrete-form equations of motion.