Original paper
Improved near surface wind speed predictions using Gaussian process regression combined with numerical weather predictions and observed meteorological data
Abstract
This study presents a hybrid numerical weather prediction model (NWP) and a Gaussian process regression (GPR) model for near surface wind speed prediction up to 72 h ahead using data partitioned on atmospheric stability class to improve model performance. NWP wind speed data from the UK meteorological office was corrected using a GPR model, where the data was subdivided using the atmospheric stability class calculated using the...
Paper Details
Title
Improved near surface wind speed predictions using Gaussian process regression combined with numerical weather predictions and observed meteorological data
Published Date
Oct 1, 2018
Journal
Volume
126
Pages
1043 - 1054
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Notes
History