6th International Conference Energy & Meteorology: Abstract Submission

Using bias-correction to improve offshore wind energy resource assessment on the west coast of the Iberian Peninsula (649)

Xurxo Costoya 1 2 , Alfredo Rocha 2 , David Carvalho 3
  1. Environmental PHYsics LABoratory (EPHYSLAB), Facultade de Ciencias, Universidade de Vigo, Ourense, Spain, España
  2. CESAM – Department of Physics, University of Aveiro, Campus Universitário de Santiago, Aveiro, Portugal
  3. Global Modeling and Assimilation Office (GMAO), NASA Goddard Space Flight Center, Greenbelt, MD , Columbia, USA

Offshore wind energy assessment has become an interesting topic along the Atlantic coast of the Iberian Peninsula due to the favorable characteristics and the installation of the first offshore wind farms in this area. Wind future projections analysis are important to ensure the viability of future offshore wind projects. Climate models are the only tool to analyze the influence of climatic variations on wind patterns. However, these models may be affected by systematic errors, mainly in near-shore areas, due to thermal gradients (land-sea temperature differences) and also due to local topography. These biases can be potentially reduced by statistical post-processing techniques called bias-correction or bias adjustment. It is important to take into account that the energetic production depends on the wind speed cubed, therefore, bias-corrected data can improve its estimation.

The main purpose of the present study will be that of correcting wind speed series derived from the Coordinated Regional climate Downscaling Experiment (CORDEX). With this aim, six regional climate models driven by fourteen global climate models under the RCP4.5 and RCP8.5 scenarios will be evaluated. The methodology described in Miao et al., (2016) will be followed to carry out the wind speed bias correction. In-situ observations from different buoys located along the Western Iberian Peninsula, as well as, data from the Cross-Calibrated Multi-Platform Ocean Surface Wind Vectors (CCMP) will be used to bias correct wind speed series. Finally, bias-corrected data will be used to analyze wind power flux on the Iberian west coast.

Reference:

  • Miao, C., Su, L., Sun, Q., & Duan, Q. (2016). A nonstationary bias‐correction technique to remove bias in GCM simulations. Journal of Geophysical Research: Atmospheres, 121(10), 5718-5735.