Application of A Subgrid-scale Cloud Parameterization To Improve RAP and HRRR Cloud Ceiling Forecasts

Abstract

The 13-km Rapid Refresh (RAP) and 3-km convection-allowing High-Resolution Rapid Refresh (HRRR) are hourly-updating forecast models that support operational aviation weather forecasting and other short-range forecasting interests within the contiguous United States. The current operational versions of these models have shown superior forecast skill over predecessor versions, in part due to improved representation of shallow cumulus clouds. However, continued advances in RAP and HRRR cloud ceiling forecast skill, in particular, will likely depend on the implementation of a fully generalized subgrid-scale cloud parameterization that can also represent low-level stratus clouds. To better represent partial cloudiness in subsaturated grid volumes under a variety of conditions, an upgraded statistical cloud parameterization within the Mellor?Yamada?Nakanishi?Niino (MYNN) planetary boundary layer (PBL) scheme has been tested. This scheme is generally found to ?activate? more robustly in areas of small cloud fraction, including subgrid stratus, and is able to realistically produce continuously varying (i.e., non-binary) cloud fractions. Importantly, this upgraded cloud scheme is fully coupled to the radiation parameterization, thereby providing a conduit for cloud?radiative interaction in the absence of resolved-scale clouds or parameterized convective clouds. Finally, use of this upgraded cloud scheme in the RAP and HRRR may permit the implementation of a cloud-ceiling diagnostic based solely on the model cloud fraction, allowing for a simplified postprocessing algorithm and more accurate ceiling forecasts. Model verification results from retrospective simulations and selected case studies will be shown to illustrate these performance improvements in the RAP and HRRR for low cloud ceilings forecasts relevant to aviation operations.