%0 Journal Article %1 Balog2016Numerical %A Balog, Irena %A Ruti, Paolo M. %A Tobin, Isabelle %A Armenio, Vincenzo %A Vautard, Robert %D 2016 %J Renewable Energy %K wind climate climatology energy renewables %P 395--405 %R 10.1016/j.renene.2015.06.038 %T A numerical approach for planning offshore wind farms from regional to local scales over the Mediterranean %U http://dx.doi.org/10.1016/j.renene.2015.06.038 %V 85 %X QuikSCAT satellite data are introduced as observational fields of wind speed over Mediterranean. The simulations of present climate are attained with two Regional Climate Models. The models reliability in re-producing the wind field is verified against QuikSCAT observations. We presented estimations of wind resource atlas over the Mediterranean Sea and determine a threshold in localizing potential sub-areas for future wind farms. Additional analysis for selected sub-areas are performed to assess how close simulated are to observational field. Renewable energy resources, such as wind, are available worldwide. Locating areas with high and continual wind sources are crucial in pre-planning of wind farms. Vast offshore areas are characterized by higher and more reliable wind resources in comparison with continental areas. However, offshore wind energy production is in a quite preliminary phase. Elaborating the potential productivity of wind farms over such areas is challenging due to sparse in situ observations. The Mediterranean basin is not an exception. In this study we are proposing numerical simulations of near-surface wind fields from regional climate models (RCMs) in order to obtain and fill the gaps in observations over the Mediterranean basin. Four simulations produced with two regional climate models are examined here. Remote sensing observations (QuikSCAT satellite) are used to assess the skill of the simulated fields. A technique for estimating the potential energy from the wind fields over the region is introduced. The wind energy potential atlas and the map of a wind turbine's functional range are presented, locating the potentially interesting sub-regions for wind farms. The ability of models to reproduce the annual cycle and the probability density function of wind speed anomalies are detailed for specified sub-regions.

@article{Balog2016Numerical, abstract = { QuikSCAT satellite data are introduced as observational fields of wind speed over Mediterranean. The simulations of present climate are attained with two Regional Climate Models. The models reliability in re-producing the wind field is verified against QuikSCAT observations. We presented estimations of wind resource atlas over the Mediterranean Sea and determine a threshold in localizing potential sub-areas for future wind farms. Additional analysis for selected sub-areas are performed to assess how close simulated are to observational field. Renewable energy resources, such as wind, are available worldwide. Locating areas with high and continual wind sources are crucial in pre-planning of wind farms. Vast offshore areas are characterized by higher and more reliable wind resources in comparison with continental areas. However, offshore wind energy production is in a quite preliminary phase. Elaborating the potential productivity of wind farms over such areas is challenging due to sparse in situ observations. The Mediterranean basin is not an exception. In this study we are proposing numerical simulations of near-surface wind fields from regional climate models (RCMs) in order to obtain and fill the gaps in observations over the Mediterranean basin. Four simulations produced with two regional climate models are examined here. Remote sensing observations (QuikSCAT satellite) are used to assess the skill of the simulated fields. A technique for estimating the potential energy from the wind fields over the region is introduced. The wind energy potential atlas and the map of a wind turbine's functional range are presented, locating the potentially interesting sub-regions for wind farms. The ability of models to reproduce the annual cycle and the probability density function of wind speed anomalies are detailed for specified sub-regions.}, added-at = {2018-06-18T21:23:34.000+0200}, author = {Balog, Irena and Ruti, Paolo M. and Tobin, Isabelle and Armenio, Vincenzo and Vautard, Robert}, biburl = {https://www.bibsonomy.org/bibtex/24c6dda3512a1d38a87cf5b07d5c5761d/pbett}, citeulike-article-id = {14013818}, citeulike-attachment-1 = {Balog_etal_2016.pdf; /pdf/user/pbett/article/14013818/1064070/Balog_etal_2016.pdf; 4e8c12730402e82ffd88252f195aaaa3b4e133b5}, citeulike-linkout-0 = {http://dx.doi.org/10.1016/j.renene.2015.06.038}, doi = {10.1016/j.renene.2015.06.038}, file = {Balog_etal_2016.pdf}, interhash = {6462f3c873265bac62e11fab22b97c5e}, intrahash = {4c6dda3512a1d38a87cf5b07d5c5761d}, issn = {09601481}, journal = {Renewable Energy}, keywords = {wind climate climatology energy renewables}, month = jan, pages = {395--405}, posted-at = {2016-04-16 11:14:06}, priority = {2}, timestamp = {2018-06-22T18:36:14.000+0200}, title = {A numerical approach for planning offshore wind farms from regional to local scales over the Mediterranean}, url = {http://dx.doi.org/10.1016/j.renene.2015.06.038}, volume = 85, year = 2016 }