2015 | OriginalPaper | Chapter
Hint
Swipe to navigate through the chapters of this book
Published in:
Progress in Clean Energy, Volume 2
The onsite measurement periods, typically ranging from 1 to 5 years, are short when compared with the standard period for average climate definition of 20–30 years and the lifetime of a wind farm. The annual variability of the wind regime, if not accounted for, adds to the uncertainty of the site’s resource assessment and can lead to serious misevaluations. The use of long-term wind data is an old issue in wind resource assessment. The typical methods of eliminating the annual variations of the wind regime from the average are correlations like the measure–correlate–predict (MCP) technique. However, the availability of such long periods of wind data is not as frequent as desired. At the end of 2009 a new reanalysis dataset named MERRA (Modern Era Retrospective analysis for Research and Applications) was published by NASA’s Global Modeling and Assimilation Office/Goddard Space Flight Center. The MERRA analysis is being conducted with the GEOS-5 Atmospheric Data Assimilation System (ADAS). The model grid is 0.5° latitude and 2/3° longitude and temporal resolution of 1 h. The MERRA data considers the orography and roughness of the site, and has a high availability.
In this work, the author analyzes the MERRA data for the level of 50 m above ground level (agl), period 1979–2013, in the wider area of Western Coast (Aegean Sea) of Turkey (17 grid points from the area of Enez to Antalya cities, 26.0°E–30.67°E and 40.50°N–36.0°N) and studies the yearly variability. Also, a correlation study (using MCP techniques) is done between the different grid points of MERRA reanalysis project and their combinations should also be evaluated. Possible relationships between terrain characteristics, local wind systems, and correlation values should also be investigated. The establishment of the existence of a predominant periodicity in the long-term wind variation could provide valuable information on the behavior of the wind climate for the upcoming years.
Please log in to get access to this content
To get access to this content you need the following product:
Advertisement
1.
go back to reference Lileo S, Petrik O (2012) Investigation on the use of NCEP/NCAR, MERRA and NCEP/CFSR reanalysis data in the wind resource analysis. Proceedings EWEA 2012, Copenhagen Lileo S, Petrik O (2012) Investigation on the use of NCEP/NCAR, MERRA and NCEP/CFSR reanalysis data in the wind resource analysis. Proceedings EWEA 2012, Copenhagen
2.
go back to reference Thøgersen ML et al (2010) WindPRO/ONLINE – Remote sending data and other data for download in WindPro, August 2010, EMD A/S: 5.1–5.4 Thøgersen ML et al (2010) WindPRO/ONLINE – Remote sending data and other data for download in WindPro, August 2010, EMD A/S: 5.1–5.4
3.
go back to reference Rienecker MM, Suarez MJ, Gelaro R, Todling R, Bacmeister J, Liu E, Bosilovich MG, Schubert SD, Takacs L, Kim GK, Bloom S, Chen J, Collins D, Conaty A, da Silva A et al (2011) MERRA - NASA’s modern-era retrospective analysis for research and applications. J Clim 24(14):3624–3648. doi: 10.1175/JCLI-D-11-00015.1 CrossRef Rienecker MM, Suarez MJ, Gelaro R, Todling R, Bacmeister J, Liu E, Bosilovich MG, Schubert SD, Takacs L, Kim GK, Bloom S, Chen J, Collins D, Conaty A, da Silva A et al (2011) MERRA - NASA’s modern-era retrospective analysis for research and applications. J Clim 24(14):3624–3648. doi:
10.1175/JCLI-D-11-00015.1
CrossRef
4.
go back to reference Thøgersen ML et al (2010) WindPRO/MCP, June 2010, EMD A/S: 1.4, 6.1–6.2 Thøgersen ML et al (2010) WindPRO/MCP, June 2010, EMD A/S: 1.4, 6.1–6.2
5.
go back to reference Thøgersen ML et al (2007) Measure-Correlate-Predict Methods: case studies and software implementation. Proceedings EWEC 2007, Milan Thøgersen ML et al (2007) Measure-Correlate-Predict Methods: case studies and software implementation. Proceedings EWEC 2007, Milan
- Title
- Investigation of the Long-Term Resource Variation in Western Coast (Aegean Sea) of Turkey Through Use of MERRA Reanalysis Data
- DOI
- https://doi.org/10.1007/978-3-319-17031-2_68
- Author:
-
Konstantinos C. Gkarakis
- Publisher
- Springer International Publishing
- Sequence number
- 68
- Chapter number
- Chapter 68