Wind speeds at heights crucial for wind energy: Measurements and verification of forecasts

Journal of Applied Meteorology and Climatology

Volumn 51, Issue 9, 2012, Pages 1602-1617

  Drechsel, Susanne ^a   Mayr, Georg J ^a   Messner, Jakob W ^a   Stauffer, Reto ^a  

^a UNIVERSITY OF INNSBRUCK   (Austria)

Author keywords

Boundary layer; Forecast verification skill; Wind

Indexed keywords

DIURNAL VARIATION; FORECAST VERIFICATIONS; INTERPOLATION METHOD; LOW COSTS; LOW LEVEL; METEOROLOGICAL TOWER; MODEL CHANGE; MOUNTAINOUS REGIONS; NWP MODEL; RELATIVE CONTRIBUTION; SHORT-TERM FORECASTS; SITE CHARACTERISTICS; VERTICAL RESOLUTION; WIND CONDITIONS; WIND SPEED; WIND SPEED MEASUREMENT;

BOUNDARY LAYERS; EXTRAPOLATION; FORECASTING; METEOROLOGICAL INSTRUMENTS; WIND; WIND EFFECTS; WIND POWER;

URBAN GROWTH;

AMPLITUDE; BOUNDARY LAYER; DIURNAL VARIATION; HEIGHT; INTERPOLATION; MEASUREMENT METHOD; PERFORMANCE ASSESSMENT; WEATHER FORECASTING; WIND POWER; WIND VELOCITY;

EUROPE;

EID: 84866173180     PISSN: 15588424     EISSN: 15588432     Source Type: Journal    
DOI: 10.1175/JAMC-D-11-0247.1     Document Type: Article

References (24)

1. Baas, P., F. Bosveld, H. Klein Baltink, and A. Holtslag, 2009: A climatology of nocturnal low-level jets at Cabauw. J. Appl. Meteor. Climatol, 48, 1627-1642.
2. Champeaux, J., V. Masson, and F. Chauvin, 2005: ECOCLIMAP: A global database of land surface parameters at 1 km resolution. Meteor. Appl., 12, 29-32.
3. Dankert, H., and J. Horstmann, 2007: A marine radar wind sensor. J. Atmos. Oceanic Technol., 24, 1629-1642.
4. ECMWF, 2008: IFS documentation-Cy33r1. Part VI: Technical and computational procedures. ECMWF Tech. Rep., 237 pp.[Available online at http://www.ecmwf.int/research/ifsdocs/CY33r1/TECHNICAL/IFSPart6.pdf.
5. Elliot, D. L., C. G. Holladay, W. R. Barchet, H. P. Foote, and W. F. Sandusky, 1986: Wind energy resource atlas of theUnited States. U.S. Dept. of Energy Rep. DOE/CH 10093-4, 210 pp.
6. Frandsen, S., and Coauthors, 2007: Summary report: The shadow effect of large wind farms: Measurements, data analysis and modelling. Risø National Laboratory Tech. Rep. Risø-R-1615 (EN), 36 pp. Available online at http://www.risoe.dk/rispubl/reports/ris-r-1615.pdf
7. Giebel, G., R. Brownsword, G. Kariniotakis, M. Denhard, and C. Draxl, 2011: The state-of-the-art in short-term prediction of wind power: A literature overview. ANEMOS Project Deliv. Rep. D1.1, 36 pp. [Available online at http://www.risoe.dk/ rispubl/vea/veapdf/ANEMOS_giebel.pdf.]
8. Global Wind Energy Council, 2010: Global wind 2009 report. GWEC Annual Rep., 68 pp. [Available online at http://www.gwec.net/fileadmin/documents/Publications/Global_Wind_2007_report/GWEC_Global_Wind_2009_Report_LOWRES_15th.%20Apr.pdf
9. Görsdorf, U., F. Beyrich, H. Dier, and U. Leiterer, 2002: Composite wind and temperature profiles obtained from a complex of in-situ and remote sensing measurement systems for the forcing of a boundary layer model. Theor. Appl. Climatol., 73, 97-105.
10. Gryning, S., E. Batchvarova, B. Brümmer, H. Jørgensen, and S. Larsen, 2007: On the extension of the wind profile over homogeneous terrain beyond the surface boundary layer. Bound. Layer Meteor., 124, 251-268.
11. Jiménez, P. A., J. F. González-Rouco, J. Navarro, J. P. Montávez, and E. García-Bustamante, 2010: Quality assurance of surface wind observations from automated weather stations. J. Atmos. Oceanic Technol., 27, 1101-1122.
12. Kelly, M., and S.-E. Gryning, 2010: Long-term mean wind profiles based on similarity theory. Bound.-Layer Meteor., 136, 377-390.
13. Lapworth, A., 2003: Factors determining the decrease in surface wind speed following the evening transition. Quart. J. Roy. Meteor. Soc., 129, 1945-1968.
14. Liu, Y., and Coauthors, 2010: Improving short-term wind energy prediction with wind farm data using the NCAR WRFRTFDDA models. Abstracts, 10th European Conf. on Applications of Meteorology, Zürich, Switzerland, European Meteorological Society, EMS2010-390. [Available online at http://www.emetsoc.org/fileadmin/ems/dokumente/annual_meetings/2010/AW14_Liu.pdf
15. Méchali, M., R. Barthelmie, S. Frandsen, L. Jensen, and P.-E. Réthoré, 2006: Wake effects at Horns Rev and their influence on energy production. European Wind Energy Conf. (EWEC 2006), Athens, Greece, European Wind Energy Association, 10 pp. [Available online at http://johnstonanalytics.com/yahoo_site_admin/assets/docs/WakeEffectsWindTurbines.21172331.pdf
16. Motta, M., R. J. Barthelmie, and P. Vlund, 2005: The influence of non-logarithmic wind speed profiles on potential power output at Danish offshore sites. Wind Energy, 8, 219-236.
17. Petersen, E. L., N. G. Mortensen, L. Lars, J. Højstrup, and H. P. Frank, 1997: Wind power meteorology. Risø National Laboratory Tech. Rep. Risø-I-1206(EN), 46 pp. [Available online at http://citeseerx.ist.psu.edu/viewdoc/summary?doi510.1.1.123.5357
18. Peterson, E. W., and J. P. Hennessey, 1978: On the use of power laws for estimates of wind power potential. J. Appl. Meteor., 17, 390-394.
19. Petroliagis, T., M. Denhard, J. Tambke, R. Hagedorn, and D. Heinemann, Eds., 2010: How well we can forecast winds at different heights? An assessment of ECMWF IFS & EPS skill of forecasting wind fields at different model levels. Proc. EWEC 2010, Warsaw, Poland, European Wind Energy Association.
20. Pinson, P., and R. Hagedorn, 2012: Verification of the ECMWF ensemble forecasts of wind speed against observations. Meteor. Appl., doi:10.1002/met.283, in press.
21. Rife, D., C. Davis, Y. Liu, and T. Warner, 2004: Predictability of low-level winds by mesoscale meteorological models. Mon. Wea. Rev., 132, 2553-2569.
22. Stull, R. B., 2008: An Introduction to Boundary Layer Meteorology. Atmospheric and Oceanographic Sciences Library, Vol. 13, Springer, 670 pp.
23. Troen, I., and E. Petersen, 1989: European Wind Atlas. Risø National Laboratory, 656 pp.
24. Wenzel, A., N. Kalthoff, and V. Horlacher, 1997: On the profiles of wind velocity in the roughness sublayer above a coniferous forest. Bound.-Layer Meteor., 84, 219-230.