Abstract
A comprehensive database with ocean wind fields has been built up at the Technical University of Denmark (DTU) through consistent processing of Synthetic Aperture Radar (SAR) observations from Envisat (2002-12) and Sentinel-1 (2014-present). The archived wind fields cover the European seas up to 100 km from the coastline. They can be seen as a series of snapshots showing the instantaneous wind conditions for the areas most relevant for offshore wind power generation. Through statistical processing, these instantaneous snapshots are combined to give maps of the offshore wind resources for the standard output level of 10 m above the sea surface. This presentation demonstrates the effects of two recent improvements related to satellite-based wind resource mapping:
1) The number of satellite samples has increased dramatically since the launch of Sentinel-1A/B
2) A new method looks promising for routine extrapolation of wind fields to the height of modern wind turbines
At DTU, wind maps are retrieved in near-real-time from ESA’s L1 SAR products using the SAROPS processing tool developed by the US National Oceanic and Atmospheric Administration (NOAA). The geophysical model function CMOD5.N is used to obtain the equivalent neutral wind speed. A correction is applied to compensate for lower radar backscatter at HH polarization compared to VV polarization. Ancillary data used for the SAR-wind processing include wind directions from the Global Forecast System (GFS) and ice mask data from the US National Ice Center.
Once the instantaneous wind maps are stored in our database, they can be organized as time series in order to calculate wind resources for any point location or area. Since the time series comprises data from both Envisat and Sentinel-1, a check of the data calibration against one or more independent data sources is needed. Based on the calibrated time series, a Weibull fit is made to calculate the mean wind speed, Weibull scale and shape parameters, and the wind power density. The spatial grid of the output wind resource maps is 0.02 degrees in latitude and longitude. To extrapolate the 10-m wind resource maps from SAR to higher levels within the atmospheric boundary layer, we estimate a wind profile for each grid cell in the maps. Simulations from the Weather Research and Forecasting (WRF) model are used to correct this profile for long-term atmospheric stability effects. Accounting for atmospheric stability allows us to estimate the wind speed at different levels with greater accuracy compared to methods that assume a neutral atmospheric boundary layer. For the Northern European seas, the inclusion of atmospheric stability increases the mean wind speed at 100 m on the order of 0.5m/s.
The SAR-based wind resource maps are used in the New European Wind Atlas – an EU-funded project where European nations work together to produce an updated and validated wind atlas for Europe
1) The number of satellite samples has increased dramatically since the launch of Sentinel-1A/B
2) A new method looks promising for routine extrapolation of wind fields to the height of modern wind turbines
At DTU, wind maps are retrieved in near-real-time from ESA’s L1 SAR products using the SAROPS processing tool developed by the US National Oceanic and Atmospheric Administration (NOAA). The geophysical model function CMOD5.N is used to obtain the equivalent neutral wind speed. A correction is applied to compensate for lower radar backscatter at HH polarization compared to VV polarization. Ancillary data used for the SAR-wind processing include wind directions from the Global Forecast System (GFS) and ice mask data from the US National Ice Center.
Once the instantaneous wind maps are stored in our database, they can be organized as time series in order to calculate wind resources for any point location or area. Since the time series comprises data from both Envisat and Sentinel-1, a check of the data calibration against one or more independent data sources is needed. Based on the calibrated time series, a Weibull fit is made to calculate the mean wind speed, Weibull scale and shape parameters, and the wind power density. The spatial grid of the output wind resource maps is 0.02 degrees in latitude and longitude. To extrapolate the 10-m wind resource maps from SAR to higher levels within the atmospheric boundary layer, we estimate a wind profile for each grid cell in the maps. Simulations from the Weather Research and Forecasting (WRF) model are used to correct this profile for long-term atmospheric stability effects. Accounting for atmospheric stability allows us to estimate the wind speed at different levels with greater accuracy compared to methods that assume a neutral atmospheric boundary layer. For the Northern European seas, the inclusion of atmospheric stability increases the mean wind speed at 100 m on the order of 0.5m/s.
The SAR-based wind resource maps are used in the New European Wind Atlas – an EU-funded project where European nations work together to produce an updated and validated wind atlas for Europe
| Original language | English |
|---|---|
| Publication date | 2016 |
| Number of pages | 1 |
| Publication status | Published - 2016 |
| Event | ESA Living Planet Symposium 2016 - Prague, Czech Republic Duration: 9 May 2016 → 13 May 2016 http://lps16.esa.int/ |
Conference
| Conference | ESA Living Planet Symposium 2016 |
|---|---|
| Country/Territory | Czech Republic |
| City | Prague |
| Period | 09/05/2016 → 13/05/2016 |
| Internet address |