Analyzing Flux Algorithms used in FVCOM for each of the Great Lakes

Session: Physical Processes in Lakes (3)

Lindsay Fitzpatrick, Cooperative Institute for Great Lakes Research, [email protected]
Eric Anderson, NOAA/GLERL, [email protected]
Ayumi Fujisaki-Manome, University of Michigan, [email protected]
Philip Chu, NOAA/GLERL, [email protected]

Abstract

The NOAA Great Lakes Operational Forecasting System (GLOFS) is a set of hydrodynamic computer models used to provide real-time forecasts of water level fluctuations, currents, water temperatures, and ice for the Great Lakes. The initial implementation of GLOFS was based on the Princeton Ocean Model (POM), but GLOFS is transitioning to the Finite-Volume Community Ocean Model (FVCOM; Anderson et al., 2018). A recent study evaluated FVCOM’s available flux algorithms with in situ measurements from the Great Lakes (Charusombat et al., 2018). It found that the Coupled Ocean-Air Response Experiment (COARE) was most successful at recreating turbulent heat fluxes compared to point-based observations at eddy-covariance flux towers. In this study, we explore GLOFS model skill in simulating hydrodynamic conditions using two different FVCOM flux algorithms. Simulations were carried out for 2015-2017 for each of the Great Lakes (with the exception of Ontario).  Several model runs were conducted for each of the three years using COARE and the Lui and Schwab (1987) scheme known as SOLAR. During evaluation, it was found that the SOLAR algorithm showed better simulation of water temperature for Lake Erie and Lake Superior, whereas COARE was better in Lake Michigan and Lake Huron.