Introduction EU-Norsewind
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1 Satellite winds in EU-Norsewind Charlotte Bay Hasager, Risø DTU, Denmark Alexis Mouche, CLS, France Merete Badger, Poul Astrup & Morten Nielsen, Risø DTU, Denmark Romain Husson, ESA
2 Introduction EU-Norsewind EU-Norsewind project ( ) with the aim to produce a wind atlas for the Northern European Seas including the Baltic, Irish and North Seas. Ground-based using 15 lidars and some masts. Satellite-based wind mapping. Atmospheric modeling. Testning for location offshore Portugal. 2 Risø DTU, Technical University of Denmark
3 EU-Norsewind team Coordinator: Andy Oldroyd of Oldbaum Services in Glasgow. Web 3 Risø DTU, Technical University of Denmark
4 Content SAR wind mapping from Risø DTU and CLS Aim Challenges Scatterometer wind maps Norsewind integration 4 Risø DTU, Technical University of Denmark
5 Norsewind: nominal remote sensing sites 5 Risø DTU, Technical University of Denmark
6 Satellite SAR wind map Wind map covering Danish and southern Norwegian Seas based on Envisat ASAR WSM from 2006/09/16 at 20:56:41 UTC from Risø DTU/ JHU APL. 400 km wide swath See dtu.dk/business_r elations/products_ Services/Software/ VEA_windmaps.as px 6 Risø DTU, Technical University of Denmark
7 Satellite SAR wind map 400 km wide swath Wind map covering the North Sea based on Envisat ASAR WSM from 2009/02/19 at 21:19:18 UTC from CLS using the SOPRANO. See 7 Risø DTU, Technical University of Denmark
8 8 Risø DTU, Technical University of Denmark
9 Project aim is to estimate Wind statistics: Weibull A Weibull k Mean wind speed U Energy density E..and the uncertainties. 9 Risø DTU, Technical University of Denmark
10 Number of samples Weibull fitting at conditional data Diurnal variation 10 m versus hub-height SAR-wind processing, in particular wind direction 10 Risø DTU, Technical University of Denmark
11 How many satellite wind maps? Random sampling (Barthelmie & Pryor 2003: J. Applied Meteorology 42, 83-94) - 70 scenes for mean wind speed within 10% at 90% confidence interval scenes for energy density within 10% at 90% confidence interval Weighting according to wind sectors -measurements -models Image selection according to wind classes - definition of ~200 typical wind situations from e.g. NCEP/NCAR data 11 Risø DTU, Technical University of Denmark
12 Envisat ASAR WSM CLS 1300, Risø 600, ESA 6000, ~ 1000/year 12 Risø DTU, Technical University of Denmark
13 Envisat ASAR WSM: CLS archive coverage 13 Risø DTU, Technical University of Denmark
14 Risø archive coverage and mean wind 14 Risø DTU, Technical University of Denmark
15 Weibull fitting conditional data Weibull fit example from Horns Rev using 92 SAR wind maps b. 16 U = 7.3 m/s E = 421 W/m 2 Compare to mast with same 92 data U = 7.6 m/s E = 422 W/m 2 Compare to Horns Rev light ship ( ), European Wind Atlas U = 7.3 m/s E = 456 W/m 2 Frequency [%] Wind speed [m s -1 ] Christiansen et al. (2006): Remote Sens. Env. 15 Risø DTU, Technical University of Denmark
16 Diurnal wind speed variation at Vindeby in Baltic Sea and Horns Rev in the North Sea. The vertical lines indicate sampling times for SAR at the sites. Normalised wind speed Vindeby Horns Rev Hour (Barthelmie & Pryor 2003: J. Applied Meteorology 42, 83-94) 16 Risø DTU, Technical University of Denmark
17 Wind direction Satellite winds are valid at 10 m From Alfredo Peña 17 Risø DTU, Technical University of Denmark
18 Wind direction and Normalized Radar Cross Section (NRCS) 18 Risø DTU, Technical University of Denmark
19 Scatterometer winds: ASCAT Image of ASCAT from ESA 19 Risø DTU, Technical University of Denmark
20 Scatterometer winds: ASCAT Copyright (2009) EUMETSAT 20 Risø DTU, Technical University of Denmark
21 Scatterometer winds: ASCAT Copyright (2009) EUMETSAT 21 Risø DTU, Technical University of Denmark
22 ASCAT 550 km swath Near-global coverage each 5 days Since October km resolution C-band Available ~300 Available later ~900 Copyright (2009) EUMETSAT 22 Risø DTU, Technical University of Denmark
23 Scatterometer winds: QuikSCAT 23 Risø DTU, Technical University of Denmark
24 Scatterometer winds (QuikSCAT) 24 Risø DTU, Technical University of Denmark
25 Scatterometer winds (ASCAT) 25 Risø DTU, Technical University of Denmark
26 Scatterometer: QuikSCAT 1800 km swath Near-global coverage daily Since July km resolution Available ~7000 Available later ~ Risø DTU, Technical University of Denmark
27 Number of samples (NO) Weibull fitting at conditional data (YES) Diurnal variation (YES) 10 m versus hub-height (YES) SAR-wind processing, in particular wind direction (NO) 27 Risø DTU, Technical University of Denmark
28 Example QuikSCAT mean wind 28 Risø DTU, Technical University of Denmark
29 Example mast and QuikSCAT at Horns Rev Mast (courtesy DONG energy) 29 Risø DTU, Technical University of Denmark QuikSCAT
30 Norsewind integration SAR- stand-alone map Scatterometer stand-alone map Coastal focus: SAR versus scatterometer SAR wind direction from models, lidar and masts integration Comparison: satellite winds versus ground-based winds Mesoscale (WRF) model results versus satellite-based - cases Mesoscale (WRF) model results versus satellite-based entire Norsewind Testing offshore area in Portugal 30 Risø DTU, Technical University of Denmark
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