AbstractNorth Atlantic tropical cyclone (TC) forecasts from four ensemble prediction systems (EPS) are verified using the National Hurricane Center’s (NHC) best tracks for the 2008 through 2015 seasons. The one to five day forecasts are evaluated for the 21-member National Center for Environmental Prediction (NCEP) Global Ensemble Forecast System (GEFS), the 23-member UKMET ensemble, and the 51-member European Center for Medium Range Weather Forecast (ECMWF) ensemble, as well as a combination of these ensembles (Multi-Model Global; MMG). Several deterministic models are also evaluated, such as the Global Forecast System (GFSdet), Hurricane Weather Research and Forecasting (HWRF), deterministic ECMWF (ECdet), and Geophysical Fluids Dynamical Laboratory (GFDL) models. ECdet track errors are the smallest on average at all lead times, but are not significantly different from the GEFS and ECMWF ensemble means. All models have a slow bias (90 to 240 km) in the along-track direction by 120 h, while there is little bias in the cross-track direction. Much of this slow bias is attributed to TCs undergoing extratropical transition (ET). All EPSs are underdispersed in the along-track direction, while the ECMWF is slightly overdispersed in the cross-track direction. The MMG and ECMWF track forecasts have more probabilistic skill than the ECdet and comparable skill to the NHC climatology-based cone forecast. TC intensity errors for the HWRF and GFDL are lower than the coarser models within the first 24 h, but are comparable to the ECdet at longer lead times. The ECMWF and MMG have comparable or better probabilistic intensity forecasts than the ECdet, while the GEFS’s weak bias limits its skill.
Weather and Forecasting – American Meteorological Society
Published: Sep 29, 2017
It’s your single place to instantly
discover and read the research
that matters to you.
Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.
All for just $49/month
Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly
Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.
Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.
Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.
All the latest content is available, no embargo periods.
“Hi guys, I cannot tell you how much I love this resource. Incredible. I really believe you've hit the nail on the head with this site in regards to solving the research-purchase issue.”Daniel C.
“Whoa! It’s like Spotify but for academic articles.”@Phil_Robichaud
“I must say, @deepdyve is a fabulous solution to the independent researcher's problem of #access to #information.”@deepthiw
“My last article couldn't be possible without the platform @deepdyve that makes journal papers cheaper.”@JoseServera