Adapting the MPAS Dynamical Core for Applications Extending Into the Thermosphere. (31st August 2021)

• Record Type: Journal Article
• Authors: Klemp, J. B.; Skamarock, W. C.
• Is Part Of: Journal of advances in modeling earth systems. Volume 13:Number 9(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-08-31
• Subjects: idealized model -- modeling -- model verification and validation -- numerical solutions -- numerical approximations and analyses; Geological modeling -- Periodicals; Climatology -- Periodicals; Geochemical modeling -- Periodicals; 551.5011
• DOI: 10.1029/2021MS002499
• Languages: English
• ISSNs: 1942-2466

Abstract

Abstract: To extend the nonhydrostatic global Model for Prediction Across Scales (MPAS) for deep‐atmosphere (geospace) applications, we have modified the model equations and numerics to include variable atmospheric composition and (potentially large) molecular viscosity and thermal conductivity. The split‐explicit numerical integration techniques in MPAS remain stable in idealized test cases for atmospheric domains extending into the upper thermosphere and continue to provide an efficient numerical framework for nonhydrostatic simulations. Variations in the atmospheric constituents influence the dynamical equations by altering the heat capacity and ideal gas constants. These feedbacks require little alteration of the dynamical equations although our testing reveals that the amplitude of disturbances may be sensitive to even small variations in the thermodynamic coefficients. Although the potential temperature is no longer formally conserved for adiabatic flow, it remains effective as a prognostic thermodynamic variable in the model equations. Molecular viscosity and thermal conductivity are dominant influences in the upper thermosphere and are represented implicitly in the model numerics. Because of the large magnitude of these terms, their treatment, though stable, may significantly under represent the true magnitude of their damping effects. Further consideration of these deep‐atmosphere extensions to MPAS will be explored in more realistic simulations of thermospheric dynamics. Plain Language Summary: Typically weather and climate models focus on simulating the atmosphere throughout the troposphere and stratosphere. However, atmospheric disturbances in these regions can also impact important physical processes at much higher altitudes, even extending into the upper thermosphere (∼500 km). The Model for Prediction Across Scales (MPAS) was designed to simulate a broad range of atmospheric phenomena, from cloud scale up to global scale. Here, we modify the model and test its viability for deep‐atmosphere applications that include the thermosphere. This raises new challenges for the model numerics due to the extreme variation in the atmospheric parameters, such as density, for example, that deceases by ∼ 12 orders of magnitude between the surface and the upper thermosphere. The variability of the constituents of the atmosphere must now be included in the model as well as influences such as molecular viscosity and thermal conductivity, which are negligible in the lower atmosphere. In simulating idealized test cases in a simplified version of MPAS, we demonstrate that numerical integration of the model equations continues to provide a stable and efficient framework for applications in the thermospheric environment that include small scale atmospheric processes. Key Points: The dynamical equations and numerics for the nonhydrostatic Model for Prediction Across Scale (MPAS) have been modified to be suitable for atmospheric applications extending into the upper thermosphere Principal additions to the model equations include variable atmospheric constituents and molecular viscosity and thermal conductivity, which become dominant in the upper thermosphere Idealized test cases with a 2‐D slab version of MPAS that includes the thermosphere confirm that the split explicit numerical integration techniques in MPAS continue to provide an efficient numerical framework for nonhydrostatic simulations