High quality observations for improved seasonal predictions. Implications for the wind energy sector

• Autores: Jaume Ramon Gamon
• Directores de la Tesis: Llorenç Lledó (dir. tes.), Albert Soret (codir. tes.), Joan Bech Rustullet (tut. tes.)
• Lectura: En la Universitat de Barcelona ( España ) en 2022
• Idioma: inglés
• Tribunal Calificador de la Tesis: César Azorín Molina (presid.), Raül Marcos Matamoros (secret.), Hiba Omrani (voc.)
• Programa de doctorado: Programa Oficial de Doctorado en Física
• Materias:
  • Ciencias de la tierra y del espacio
    • Climatología
      • Climatología aplicada
      • Climatología física
  • Ciencias tecnológicas
    • Tecnología energética
      • Generación de energía
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• Resumen

  • Seasonal climate predictions appear extremely helpful in anticipating climate variations and taking timely action to manage their possible effects better. The wind power industry is a potential user of those predictions: the amount of future renewable production highly depends on wind speed anomalies. Regrettably, current seasonal predictions suffer from insufficient skill levels, and their probabilistic nature makes them harsh to understand for non-experienced users. This PhD thesis aims at improving the quality of seasonal predictions for wind speed, targeting specific needs and gaps reported by the wind energy industry. The main goal is achieved by employing high-quality wind observations. Adequate use of reanalyses or station data can enhance seasonal predictions, provided that sound methods and practical tools are defined.