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Semi-Lagrangian Advection of Stratospheric Ozone on a YinYang Grid System

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  • 1 Air Quality Research Division, Environment Canada, Dorval, Quebec, Canada
  • | 2 Meteorological Research Division, Environment Canada, Dorval, Quebec, Canada
  • | 3 Met Office, Exeter, United Kingdom
  • | 4 Air Quality Research Division, Environment Canada, Toronto, Ontario, Canada
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Abstract

The lack of formal mass conservation that is inherent to the standard semi-Lagrangian transport scheme represents a significant model limitation that needs to be addressed. The magnitude of this impact depends on the nature of the advected quantity and particularly on the strength of species spatiotemporal variability. In this study, this issue is examined in the context of two configurations of the Environment Canada Global Environmental Multiscale (GEM) model. The first configuration (GEM Lat–Lon) is based on a global latitude–longitude grid system with the Arakawa C grid in the horizontal. The second configuration (GEM Yin–Yang) uses the overset Yin–Yang grid, which is singularity free and has quasi-uniform resolution. Both model versions have been used for studying the mass conservation property of passive and nonpassive tracers such as stratospheric ozone using different shape-preserving schemes and a global mass fixer. Experiments with idealized tracers indicate that the implementation of a global mass fixer and a conservative shape-preserving scheme reduces the error field in both 2D and 3D configurations. In the case of stratospheric ozone, the study demonstrates that the mass conservation error is significantly reduced with the use of the Yin–Yang grid. This is attributed to the quasi-uniform nature of the grid that contributes to improve the accuracy of the computation particularly in high-latitude regions where most of the ozone mass resides. The study demonstrates the potential benefits of using a quasi-uniform Yin–Yang grid system and shows that chemical constituents can serve as a useful diagnostic for the evaluation of numerical weather prediction (NWP) models.

Corresponding author address: Jean de Grandpré, Environment Canada, 2121 Trans-Canada Highway, Dorval QC H9P 1J3, Canada. E-mail: jean.degrandpre@ec.gc.ca

Abstract

The lack of formal mass conservation that is inherent to the standard semi-Lagrangian transport scheme represents a significant model limitation that needs to be addressed. The magnitude of this impact depends on the nature of the advected quantity and particularly on the strength of species spatiotemporal variability. In this study, this issue is examined in the context of two configurations of the Environment Canada Global Environmental Multiscale (GEM) model. The first configuration (GEM Lat–Lon) is based on a global latitude–longitude grid system with the Arakawa C grid in the horizontal. The second configuration (GEM Yin–Yang) uses the overset Yin–Yang grid, which is singularity free and has quasi-uniform resolution. Both model versions have been used for studying the mass conservation property of passive and nonpassive tracers such as stratospheric ozone using different shape-preserving schemes and a global mass fixer. Experiments with idealized tracers indicate that the implementation of a global mass fixer and a conservative shape-preserving scheme reduces the error field in both 2D and 3D configurations. In the case of stratospheric ozone, the study demonstrates that the mass conservation error is significantly reduced with the use of the Yin–Yang grid. This is attributed to the quasi-uniform nature of the grid that contributes to improve the accuracy of the computation particularly in high-latitude regions where most of the ozone mass resides. The study demonstrates the potential benefits of using a quasi-uniform Yin–Yang grid system and shows that chemical constituents can serve as a useful diagnostic for the evaluation of numerical weather prediction (NWP) models.

Corresponding author address: Jean de Grandpré, Environment Canada, 2121 Trans-Canada Highway, Dorval QC H9P 1J3, Canada. E-mail: jean.degrandpre@ec.gc.ca
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