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

Santos, José Vicente Cardoso; Perini, Noéle Bissoli; Moret, Marcelo A.; Nascimento, Erick Giovani Sperandio; Moreira, Davidson Martins

doi:10.1016/j.energy.2020.119413

Cited by 4 publications

(5 citation statements)

References 26 publications

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“…This identifies, therefore, a possible relationship between the presence and intensity of the crossover with factors and characteristics of the local terrain, such as roughness, distance from the sea, elevation, orography and even urbanization, in addition to the fact that these data under analysis confirm results of previous works [13,14,15] which allows the generalization of the phenomenological explanations put forward by them.…”

Section: Discussionsupporting

confidence: 72%

“…Regarding data from other stations, these are controlled and made publicly available by the NDBC (National Data Buoy Center). Thus, the existence of different power laws for the analyzed cases is observed, detecting, in some of them, the crossover phenomenon, that is, a change in the behavior of the time series identified by the presence of correlations with power laws in two regions of distinct scales (subdiffusive and persistent) for the time series [13,14,15].…”

Section: Resultsmentioning

confidence: 94%

“…The analyzed data referring to the ocean buoys found in the Atlantic Ocean were taken from the PIRATA (Prediction and Research Moored Array in the Tropical Atlantic) project database, while those referring to the buoys located in the Indian and Pacific oceans belong, respectively, to the RAMA (Research Moored Array for African-Asian-Australian Monsoon Analysis and Prediction) and TAO (Tropical Atmosphere Ocean) projects. The data from the station located in Ondina, in the city of Salvador, BA, in turn, were taken from the meteorological station of this location [12,13]. Regarding data from other stations, these are controlled and made publicly available by the NDBC (National Data Buoy Center).…”

Section: Resultsmentioning

confidence: 99%

“…The periodicity of data collection from these anemometers, in turn, was standardized for all analyzed stations, being collected once every hour. In relation to the chronological horizon observed in each season, this was variable, being no longer than two years nor shorter than approximately two months, between the years 2014 and 2017 [13,14,15].…”

Section: The Use Of the Dfa Technique In Wind Speed Analysismentioning

confidence: 99%

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Long Range Correlations of Offshore Wind Speed on Continental Platforms in the Americas

Mattos¹,

Santos²

2021

Blucher Engineering Proceedings

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Time series records of wind speeds are considered and the general objective is their non-classical statistical analysis on the continental shelf in various locations on the American continent (north, central and south) with the purpose of prospecting the existence of associated power laws as well as long-range correlations and as specific objectives the record of feasibility of local wind generation and description of its behavior. A methodology based on literature review and the use of the DFA (Detrended Fluctuation Analysis) technique is adopted. Data from meteorological stations (onshore and offshore) are used. Finally, preliminary, robust and continuous results show promising aspects and registration of the crossover phenomenon in some situations.

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Section: Discussionsupporting

confidence: 72%

Section: Resultsmentioning

confidence: 94%

Section: Resultsmentioning

confidence: 99%

Section: The Use Of the Dfa Technique In Wind Speed Analysismentioning

confidence: 99%

See 2 more Smart Citations

Long Range Correlations of Offshore Wind Speed on Continental Platforms in the Americas

Mattos¹,

Santos²

2021

Blucher Engineering Proceedings

Self Cite

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“…For the analysis of temperature, the DFA technique was then used on data taken from anemometers located in different locations in the Americas and the oceans, and found at different altitudes, although most of them are located at levels close to the level of the sea [13][14][15].…”

Section: The Use Of the Dfa Technique In Temperature Analysismentioning

confidence: 99%

Fractal Effects of Temperature (Onshore-Offshore): Power Laws, Crossover Phenomenon and Long-Range Correlations and Wind Potential Developments.

Cruz¹,

Santos²

2022

Blucher Engineering Proceedings

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With the intense demand for alternative energy matrices in the world and with regard to wind energy, the study has the objective of analyzing the time series of temperature in different regions, through the use of the DFA (Detrended Fluctuation Analysis) to verify the existence of power laws to analyze the temperature persistence of the studied regions. Thus, it is necessary to evaluate the temperature behavior in the wind speed, identify the existence of the offshore/onshore crossover phenomenon, propose temperature influences on the wind potential and, identify impacts of the proposed research on the circular economy. Preliminary results indicate the fractalized behavior of temperature in the prospected regions as well as the existence of the crossover phenomenon, which corroborates the existence of local wind potential.

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Long-range correlations of the wind speed in a northeast region of Brazil

Souza

Santos

Nascimento

et al. 2022

Energy

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

Cited by 4 publications

References 26 publications

Long Range Correlations of Offshore Wind Speed on Continental Platforms in the Americas

Long Range Correlations of Offshore Wind Speed on Continental Platforms in the Americas

Fractal Effects of Temperature (Onshore-Offshore): Power Laws, Crossover Phenomenon and Long-Range Correlations and Wind Potential Developments.

Long-range correlations of the wind speed in a northeast region of Brazil

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