2017 Atlantic Hurricane Forecasts from a High-Resolution Version of the GFDL fvGFS Model: Evaluation of Track, Intensity, and Structure

Abstract

AbstractThe 2017 Atlantic hurricane season had several high-impact tropical cyclones (TCs), including multiple cases of rapid intensification (RI). A high-resolution nested version of the GFDL finite-volume dynamical core (FV3) with GFS physics (fvGFS) model (HifvGFS) was used to conduct hindcasts of all Atlantic TCs between 7 August and 15 October. HifvGFS showed promising track forecast performance, with similar error patterns and skill compared to the operational GFS and HWRF models. Some of the larger track forecast errors were associated with the erratic tracks of TCs Jose and Lee. A case study of Hurricane Maria found that although the track forecasts were generally skillful, a right-of-track bias was noted in some cases associated with initialization and prediction of ridging north of the storm. The intensity forecasts showed large improvement over the GFS and global fvGFS models but were somewhat less skillful than HWRF. The largest negative intensity forecast errors were associated with the RI of TCs Irma, Lee, and Maria, while the largest positive errors were found with recurving cases that were generally weakening. The structure forecasts were also compared with observations, and HifvGFS was found to generally have wind radii larger than the observations. Detailed examination of the forecasts of Hurricanes Harvey and Maria showed that HifvGFS was able to predict the structural evolution leading to RI in some cases but was not as skillful with other RI cases. One case study of Maria suggested that the inclusion of ocean coupling could significantly reduce the positive bias seen during and after recurvature.