1222 Developing the RAP/HRRR Physics Suite to Improve Tropical Shallow-Cumuli Structures across the Gray Zone

Wednesday, 15 January 2020
Hall B (Boston Convention and Exhibition Center)
J. Olson, NOAA, Boulder, CO; and J. Kenyon, J. Brown, W. M. Angevine, H. Vagasky, and G. Grell

The 13-km Rapid Refresh (RAP) and 3-km convection-allowing High-Resolution Rapid Refresh (HRRR) are hourly-updating operational forecast models that support short-range forecasting interests within the contiguous United States. The physics suite used in the RAP/HRRR is currently being tested within the global framework, so some model development effort has shifted to the proper representation of tropical shallow-convection and the boundary layer structure. The RAP/HRRR uses a modified form of the Mellor–Yamada–Nakanishi–Niino (MYNN) Eddy Diffusivity-Mass Flux (EDMF) planetary boundary layer (PBL) scheme, which is the primary model component investigated, but other aspects like cloud-radiative interactions and numerical filters will also be investigated.

The National Oceanic and Atmospheric Administration (NOAA) plans to participate in the PAN-GASS Grey Zone model comparison activities by performing and contributing simulations of the boundary layer and cloud structures observed in EUREC4A. This poster presents results of tropical boundary layer simulations using the MYNN-EDMF (within the context of the RAP/HRRR physics suite) to investigate the sensitivity of the morphology of shallow cumuli. Sensitivity tests are performed by activating/deactivating certain components, such as the momentum transport, cloud-radiative feedbacks, etc. Sensitivities, successes and remaining challenges are identified for further research. This poster is meant to instigate interesting conversation on the important processes involved in evolving fields of shallow-cumuli and their representation within the model physics, which are important for regulating the structure of the tropical boundary layer.

- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner