US IOOS coastal and ocean modeling testbed: Inter-model evaluation of tides, waves, and hurricane surge in the Gulf of Mexico

Kerr, PC; Donahue, AS; Westerliink, JJ; Luettich, RA; Zheng, LY; Weisberg, RH; Huang, Y; Wang, Harry V.; Teng, Y; Forrest, David R.

Publication

US IOOS coastal and ocean modeling testbed: Inter-model evaluation of tides, waves, and hurricane surge in the Gulf of Mexico

Kerr, PC
;
Donahue, AS
;
Westerliink, JJ
;
Luettich, RA
;
Zheng, LY
;
Weisberg, RH
;
Huang, Y
;
Wang, Harry V.
;
Teng, Y
;
Forrest, David R.

Abstract

A Gulf of Mexico performance evaluation and comparison of coastal circulation and wave models was executed through harmonic analyses of tidal simulations, hindcasts of Hurricane Ike (2008) and Rita (2005), and a benchmarking study. Three unstructured coastal circulation models (ADCIRC, FVCOM, and SELFE) validated with similar skill on a new common Gulf scale mesh (ULLR) with identical frictional parameterization and forcing for the tidal validation and hurricane hindcasts. Coupled circulation and wave models, SWAN+ADCIRC and WWMII+SELFE, along with FVCOM loosely coupled with SWAN, also validated with similar skill. NOAA's official operational forecast storm surge model (SLOSH) was implemented on local and Gulf scale meshes with the same wind stress and pressure forcing used by the unstructured models for hindcasts of Ike and Rita. SLOSH's local meshes failed to capture regional processes such as Ike's forerunner and the results from the Gulf scale mesh further suggest shortcomings may be due to a combination of poor mesh resolution, missing internal physics such as tides and nonlinear advection, and SLOSH's internal frictional parameterization. In addition, these models were benchmarked to assess and compare execution speed and scalability for a prototypical operational simulation. It was apparent that a higher number of computational cores are needed for the unstructured models to meet similar operational implementation requirements to SLOSH, and that some of them could benefit from improved parallelization and faster execution speed.