US East Coast synthetic aperture radar wind atlas for offshore wind energy

Abstract

Abstract. We present the first synthetic aperture radar (SAR)-based offshore wind atlas of the US East Coast from Georgia to the Canadian border. Images from Radarsat-1, Envisat, Sentinel-1A, and Sentinel-1B are processed to wind maps using the Geophysical Model Function (GMF) CMOD5.N. Extensive comparisons with 6,008 collocated buoy observations revealed that biases of the individual system range from −0.8 to 0.6 m/s. Unbiased wind retrievals are crucial for producing an accurate wind atlas and intercalibration for correcting these biases by adjusting the normalized radar cross section is applied. The intercalibrated SAR observations show biases in the range of to −0.2 to 0.0 m/s, while at the same time improving the root mean squared error from 1.67 to 1.46 m/s. These intercalibrated SAR observations are, for the first time, aggregated to create a wind atlas. Monthly averages are used to correct artefacts from seasonal biases. The SAR wind atlas is used as a reference to study wind resources derived from the Weather Research and Forecasting (WRF) model. Comparisons focus on the spatial variation of wind resources and show that model results estimate lower coastal wind speed gradients than those from SAR. At sites designated for offshore wind development by the Bureau of Ocean Energy Management, mean wind speeds typically vary between 0.3 and 0.5 m/s for SAR and less than 0.2 m/s for the WRF model within each site. Findings indicate that wind speed gradients and variation might be underestimated in mesoscale model outputs along US East Coast.

Europe's offshore winds assessed with synthetic aperture radar, ASCAT and WRF

“…Methods to deal with few satellite samples include the hybrid method (Badger et al, 2010) and the gap-filling method during periods with a lack of data due to sea ice (Doubrawa et al, 2015). The adjustment for few samples and for uneven diurnal or seasonal sampling only makes sense to perform for local sites or regions (Ahsbahs et al, 2019) rather than for all the European seas.…”

“…Satellite SAR was used for resource assessment for the North Sea (Hasager et al, 2005(Hasager et al, , 2015bChristiansen et al, 2016;Badger et al, 2010) and the Baltic Sea (Hasager et al, 2011;Badger et al, 2016) and was compared to meteorological mast data. Coastal mast data and mesoscale model results were compared to SAR-based wind resource estimates for the Icelandic waters (Hasager et al, 2015a).…”

Europe’s offshore winds assessed from SAR, ASCAT and WRF

“…Methods to deal with few satellite samples include the hybrid method (Badger et al, 2010) and the gap-filling method during periods with lack of data due to sea ice (Doubrawa et al, 2015). The adjustment for few samples and for uneven diurnal or seasonal sampling only makes sense to perform for local sites or regions (Ahsbahs et al, 2019) rather than for the entire European Seas. In case meteorological observations are accessible, these can be useful for comparison and adjustment.…”

“…At the European scale, the SAR wind speed archive may be improved for future analysis, using the novel inter-calibration method proposed by Badger et al (2019) and applied for SAR-based wind resource assessment along the US East Coast (Ahsbahs et al, 2019). The tendency in this inter-calibration is to decrease the SAR wind speeds.…”

“…SAR only provides observations of wind speed, and for direction based upon the interpolated wind directions from global models (e.g. Badger et al, 2010;Ahsbahs et al, 2019). Thus, wind roses from SAR are mixed from satellite data and modelling.…”