AbstractThis paper presents a method to bias correct and downscale wind speed over water bodies that are unresolved by numerical weather prediction (NWP) models and analyses. The dependency of wind speeds over water bodies to fetch length is investigated as a predictor of model wind speed error. Because model bias is found to be related to the forecast wind direction, a statistical method that uses the forecast fetch to remove wind speed bias is developed and tested. The method estimates wind speed bias using recent forecast errors from similar stations (i.e., those with comparable fetch lengths). As a result, the bias correction is not tied to local observations but instead to locations with similar land–water characteristics. Thus, it can also be used to downscale wind fields over inland and coastal water bodies. The fetch method is compared to four reference bias correction methods using one year’s worth of wind speed output from three NWP analyses in Florida. The fetch method yields a bias error near zero and results in a reduction of the mean absolute error that is comparable to the reference methods. The fetch method is then used to bias correct and downscale a coarse analysis to 500-m grid spacing over a coastal estuary in central Florida.
Weather and Forecasting – American Meteorological Society
Published: Aug 16, 2017
It’s your single place to instantly
discover and read the research
that matters to you.
Enjoy affordable access to
over 12 million articles from more than
10,000 peer-reviewed journals.
All for just $49/month
Read as many articles as you need. Full articles with original layout, charts and figures. Read online, from anywhere.
Keep up with your field with Personalized Recommendations and Follow Journals to get automatic updates.
It’s easy to organize your research with our built-in tools.
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