Improving Lake-Effect Snowfall Forecast through a Coupled FV3GFS-FVCOM Modeling System

Session: Poster Session

David Wright, Cooperative Institute for Great Lakes Research, [email protected]
Philip Chu, NOAA/GLERL, [email protected]
Christiane Jablonowski, University of Michigan, [email protected]
Ayumi Fujisaki-Manome, University of Michigan, [email protected]
Brent Lofgren, NOAA/GLERL, [email protected]
Greg Mann, National Weather Service, [email protected]
Eric Anderson, NOAA/GLERL, [email protected]

Abstract

During the late fall and winter seasons, numerical weather predictions (NWP) are often challenged by lake-effect snowfall (LES) events generated by the Great Lakes.  To correctly forecast the intensity and placement of these mesoscale weather events, accurate representation is needed of local and synoptic scale atmospheric features as well as lake surface characteristics.  In this study, we will discuss preliminary findings from coupling two models (FV3GFS and FVCOM) to better represent the snowfall placement and intensity of LES events.  FV3GFS, developed by NCEP’s Environmental Modeling Center as part of NOAA’s Next-Generation Global Prediction System (NGGPS), is the latest global atmospheric model which uses a variable resolution grid to achieve horizontal grid spacings of 3km.  FVCOM is a hydrodynamic model that is part of NOAA’s next-generation Great Lakes Operational Forecast System (GLOFS) and is used to provide the more accurate lake surface characteristics as lower boundary conditions for the atmospheric model.  These two models are coupled using a “loosely” coupled system where models are run alternatingly until a stable solution is reached.  Case studies from around the Great Lakes are used to test the feasibility of this system.