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<p>This study proposes a framework that improves the precision of offshore wind resource assessment. Built on the theory of statistical downscaling and multi-criteria techniques, this framework allows to downscale available Global Climate Model (GCM) data using various statistical-downscaling techniques that help improve the granularity of assessments. Secondly, as per the proposed algorithm, the study area is split into four quadrants and weights for each considered GCM in all the quadrants are evaluated following which weighted ensembles and mosaics are created. Subsequently, best mosaic ensemble is identified using the proposed framework and is further used to estimate harnessable wind power. The proposed framework is demonstrated considering the data of 13 GCMs of the CMIP6 archive with an extent of the Indian offshore region. Spatial findings providing actionable insights into harnessable offshore wind energy in India suggest that the southeast (SE) quadrant with a high median WPD (247.39 W/m<sup>2</sup>) is a plausible region for installations.</p>

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Split quadrant mosaic algorithm: a novel approach to develop multi-model ensemble for wind resource assessment

  • 期刊论文

  • 发表日期：

    2025年10月13日

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  • Garlapati Nagababu,
  • Preksha Patwa,
  • Harish Puppala,
  • V. V. Arun Kumar Surisetty,
  • Surendra Singh Kachhwaha,
  • Rashmi Sharma

摘要

This study proposes a framework that improves the precision of offshore wind resource assessment. Built on the theory of statistical downscaling and multi-criteria techniques, this framework allows to downscale available Global Climate Model (GCM) data using various statistical-downscaling techniques that help improve the granularity of assessments. Secondly, as per the proposed algorithm, the study area is split into four quadrants and weights for each considered GCM in all the quadrants are evaluated following which weighted ensembles and mosaics are created. Subsequently, best mosaic ensemble is identified using the proposed framework and is further used to estimate harnessable wind power. The proposed framework is demonstrated considering the data of 13 GCMs of the CMIP6 archive with an extent of the Indian offshore region. Spatial findings providing actionable insights into harnessable offshore wind energy in India suggest that the southeast (SE) quadrant with a high median WPD (247.39 W/m2) is a plausible region for installations.