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Multi-decadal variability in a centennial reconstruction of daily wind

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Kirchner Bossi, N. and Prieto, L. and García Herrera, Ricardo and Carro Calvo, L. and Salcedo Sanz, S. (2013) Multi-decadal variability in a centennial reconstruction of daily wind. Applied energy, 105 . pp. 30-46. ISSN 0306-2619

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Official URL: http://dx.doi.org/10.1016/j.apenergy.2012.11.072


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Abstract

A wind clustering methodology capable of dynamically characterizing and long-term reconstructing daily surface wind series is introduced and tested for six meteorological towers at different wind farms in Spain, for the period 1871–2009. On this basis this paper provides for the first time a centennial surface wind reconstruction with a daily resolution without the need of numerical simulations. Thus, several soft-computing algorithms are developed, with public domain Sea Level Pressure (SLP) Reanalysis data as the only input. These algorithms are constructed by tackling an Euclidean distances’ problem at the geostrophic speeds’ space. Once the wind-independent classifications are obtained, the methodology is calibrated by linking the obtained classifications with observed wind data, thus allowing to estimate and characterize the daily surface wind speed and direction. A cross-validation is then performed in order to obtain several measures of goodness of the method, such as its wind speed estimation uncertainty in terms of Mean Absolute Error (MAE) and Pearson correlation (r) for both the wind module and vectorial values. Regarding previous approaches, this statistic downscaling shows an outstanding performance: Wind speed module estimates produce a MAE of 1.12 m/s (0.32 m/s) in some towers for a daily (monthly) scale, as r reaches values of 0.78 (daily scale) and 0.91 (monthly scale). The wind-independent classifications allowed to perform daily surface wind speed and rose reconstructions in time periods when no wind data are available, which constitutes the main goal of this work. Thus, a 140 year daily wind reconstruction is performed and analyzed for one tower located at central Iberia. There, significant low frequency variations are detected, as well as wind speed oscillations in the 20 y band. Remarkable changes are also identified over reconstructed decadal wind speed frequency distributions and wind rose. Since long-term wind measurements are rarely available at modern wind farm sites, such an analysis on centennial reconstructed wind series can represent an appropriate tool that places the last years of observed wind speed in a climatological perspective.


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Additional Information:

© 2012 Elsevier Ltd. All rights reserved. This work has been partially supported by the Spanish Ministry of Education through Project ECO2010-22065-C03-02, and by Iberdrola Renovables Energía S.A. Special thanks are given to Prof. Emiliano Hernández Martín from Universidad Complutense de Madrid and to Prof. Ricardo Trigo from Universidade de Lisboa.

Uncontrolled Keywords:Circulation weather types; Cluster-analysis; Neural-networks; Evolutionary algorithms; Classification scheme; Southern California; Reanalysis project; Speed prediction; Daily rainfall; Patterns
Subjects:Sciences > Physics > Atmospheric physics
ID Code:61650
Deposited On:28 Jul 2020 11:45
Last Modified:28 Jul 2020 11:54

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