September 26, 2019
Data Assimilation Impact of In Situ and Remote Sensing Meteorological Observations on Wind Power Forecasts during the First Wind Forecast Improvement Project (WFIP)
AbstractDuring the first Wind Forecast Improvement Project (WFIP) new meteorological observations were collected from a large suite of instruments, including wind velocities measured on networks of tall towers provided by wind industry partners, wind speeds measured by cup anemometers mounted on the nacelles of wind turbines, and by networks of Doppler sodars and radar wind profilers. Previous data denial studies found a significant improvement of up to 6% RMSE reduction for short-term wind power forecasts due to the assimilation of all of these observations into the NOAA Rapid Refresh (RAP) forecast model using a 3dvar GSI data assimilation scheme. As a follow-on study, we now investigate the impacts of assimilating into the RAP model either the additional remote sensing observations (sodars and wind profiling radars) alone, or assimilating the industry provided in situ observations (tall towers and nacelle anemometers) alone, in addition to the standard meteorological data sets that are routinely available. The more numerous tall tower/nacelle observations provide a relatively large improvement through the first 3-4 hours of the forecasts, which however decays to a negligible impact by forecast hour 6. In comparison the less numerous vertical profiling sodars/radars provide an initially smaller impact that decays at a much slower rate, with a positive impact present through the first 12 hours of the forecast. Large positive assimilation impacts for both sets of instruments are found during daytime hours, while small or even negative impacts are found during nighttime hours.
Revised: September 26, 2019 | Published: July 1, 2019