CASE-STUDY OF ERIN USING THE FSU NESTED REGIONAL SPECTRAL MODEL

Authors
Citation
S. Cocke, CASE-STUDY OF ERIN USING THE FSU NESTED REGIONAL SPECTRAL MODEL, Monthly weather review, 126(5), 1998, pp. 1337-1346
Citations number
19
Categorie Soggetti
Metereology & Atmospheric Sciences
Journal title
ISSN journal
00270644
Volume
126
Issue
5
Year of publication
1998
Pages
1337 - 1346
Database
ISI
SICI code
0027-0644(1998)126:5<1337:COEUTF>2.0.ZU;2-3
Abstract
A case study of Hurricane Erin of the 1995 storm season is presented u sing the recently developed Florida State University (FSU) Nested Regi onal Spectral Model. The nested regional spectral model uses a perturb ation technique similar to that used in the National Centers for Envir onmental Prediction and European Centre for Medium-Range Weather Forec asts regional spectral models, but with a number of differences such a s the use of a Mercator projection. The perturbations are deviations f rom the FSU Global Spectral Model (FSUGSM) results and are spectrally represented with pi-periodic trigonometric basis functions. The pertur bations are relaxed at the boundary to approach the global model resul ts. The perturbation time tendencies are solved using a semi implicit time integration scheme similar to that used in the FSUGSM. The region al model has the same sigma-coordinate vertical structure and physics as the FSUGSM. Implicit horizontal diffusion and time filtering of the perturbations is included. Erin made landfall on both the Atlantic co ast and gulf coast of Florida, each time with hurricane strength. A 4- day prediction is performed using a 0.5 degrees transform grid, which yields an equivalent resolution to a T240 global model. T106 and T126 global models were used to provide base fields for the regional model as well as control experiments. The intensity forecast of the regional model was superior to that of the global model and reasonably close t o the observed intensity. With physical initialization, the forecast t rack of the storm is improved in both the global and regional models. However, the regional model predicted the best track, showing both lan dfalls within 100 km of the observed landfalls.