Energy | 2021

Scaling behavior of wind speed in the coast of Brazil and the South Atlantic Ocean: The crossover phenomenon

 
 
 
 
 

Abstract


Abstract Meteorological data collected using ocean buoys are very important for weather forecasting. In addition, they provide valuable information on ocean–atmosphere interaction processes that have not yet been explored. Accordingly, data collection using ocean buoys is well established around the world. In Brazil, ocean buoy data are obtained by the Brazilian Navy through a monitoring network on the Brazilian coast, which has high potential for wind power generation. In this context, the present study aimed to analyze the scaling behavior of wind speed on the Brazilian coast (continental shelf), South Atlantic Ocean and coast of Africa in order to determine long-range correlations and acquire more information on the crossover phenomenon at various scales. For this purpose, the detrended fluctuation analysis technique and numerical simulation with the Weather Research and Forecasting mesoscale model were used. The results from buoys show that wind speed exhibits a scaling behavior, but without the crossover phenomenon in the Brazilian coast, South Atlantic Ocean and coast of Africa, indicating the dependence of the phenomenon by the terrestrial surface, suggesting influence on the wind power generation. Buoy data from the South Atlantic Ocean and coast Africa showed a subdiffusive behavior ( α ≥ 1 ), whereas those from the Brazilian coast indicated persistence ( 0.5 α 1 ), except for the confluence region of Porto Seguro, which indicated anti-persistence ( α = 0.48 ). The numerical simulations using the WRF mesoscale model showed a subdiffusive behavior on the Brazilian coast, and no persistence was reproduced in most coastal buoys. The findings support deeper understanding of the wind regime and its associated properties, with particular attention to the Brazilian continental shelf, suggesting that the methodology is useful for assessing the potential of offshore wind power generation.

Volume 217
Pages 119413
DOI 10.1016/j.energy.2020.119413
Language English
Journal Energy

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