Japan Geoscience Union Meeting 2023

Presentation information

[E] Oral

A (Atmospheric and Hydrospheric Sciences ) » A-AS Atmospheric Sciences, Meteorology & Atmospheric Environment

[A-AS05] Large-scale moisture and organized cloud systems

Fri. May 26, 2023 1:45 PM - 3:15 PM 201A (International Conference Hall, Makuhari Messe)

convener:Daisuke Takasuka(Atmosphere and Ocean Research Institute, The University of Tokyo), Satoru Yokoi(Japan Agency for Marine-Earth Science and Technology), Hiroaki Miura(The University of Tokyo), Atsushi Hamada(University of Toyama), Chairperson:Daisuke Takasuka(Atmosphere and Ocean Research Institute, The University of Tokyo), Atsushi Hamada(University of Toyama)

1:45 PM - 2:00 PM

[AAS05-01] Coupling Momentum and Variance in a MMF with a 2D CRM

★Invited Papers

*Walter Michael Hannah1, Kyle Pressel2, Mikhail Ovchinnikov2, Qiu Yang2, Ruby Leung2, Gregory Elsaesser3, Matthew Norman4, Ben Hillman5 (1.Lawrence Livermore National Laboratory, 2.Pacific Northwest National Laboratory, 3.NASA, 4.Oak Ridge Leadership Computing Facility, 5.SNL)

Keywords:atmospheric modelling, multiscale modelling framework, convective momentum transport, GPU acceleration, tropical variability

An atmospheric multiscale modeling framework (MMF) allows an explicit representation of convection by coupling a cloud resolving model (CRM) with a general circulation model (GCM). This avoids the need for conventional parameterizations of clouds and turbulence. Traditional MMF implementations often use a 2D CRM with periodic boundary conditions to constrain the computational cost, but some consequences of this approach are that convective momentum transport cannot be explicitly represented and small-scale fluctuations within the CRM cannot be transported by the large-scale flow. These limitations can be problematic because they force the model to ignore key atmospheric processes. Two enhancements have been implemented in the E3SM-MMF to address these deficiencies. The first is the momentum transport scheme of Tulich (2015) in which the large-scale momentum field is represented in the CRM by two scalars, which allows the 3D momentum transport to be approximated by a 2D CRM. The second feature is a scheme that allows small scale fluctuations within the CRM to be transported between CRM instances on the global grid.