Distributions and Correlation Properties of Offshore Wind Speeds and Wind Speed Increments

Abstract We determine distributions and correlation properties of offshore wind speeds and wind speed increments by analyzing wind data sampled with a resolution of one second for 20 months at different heights above sea level in the North Sea. Distributions of horizontal wind speeds can be fitted to Weibull distributions with shape and scale parameters varying weakly with the vertical height separation. Kullback–Leibler divergences between distributions at different heights change with the squared logarithm of the height ratio. Cross-correlations between time derivatives of wind speeds are long-term anticorrelated, and the even parts of their correlation functions satisfy sum rules. Distributions of horizontal wind speed increments change from a tent-like shape to a Gaussian with rising increment lag. A surprising peak occurs in the left tail of the increment distributions for lags in a range $$10-200\,{km}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mn>10</mml:mn> <mml:mo>-</mml:mo> <mml:mn>200</mml:mn> <mml:mspace/> <mml:mrow> <mml:mi>km</mml:mi> </mml:mrow> </mml:mrow> </mml:math> after applying the Taylor’s hypothesis locally to transform time lags into distances. The peak is decisive in order to obtain an expected and observed linear scaling of third-order structure functions with distance. This suggests that it is an intrinsic feature of atmospheric turbulence.

Authors

Institutions

Publication Details

Journal
Boundary-Layer Meteorology
Published
2024-11-01
DOI
https://doi.org/10.1007/s10546-024-00889-3
Citations
4
Primary Topic
Wind Energy Research and Development
Type
article
Field-Weighted Citation Impact
5.20

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Distributions and Correlation Properties of Offshore Wind Speeds and Wind Speed Increments

H. Eduardo Roman, Philipp Maass, So-Kumneth Sim
4 citations
Boundary-Layer Meteorology
Wind Energy Research and Development
5.20
article

Distributions and Correlation Properties of Offshore Wind Speeds and Wind Speed Increments

H. Eduardo Roman, Philipp Maass, So-Kumneth Sim
article en
4 citations

Abstract

Abstract We determine distributions and correlation properties of offshore wind speeds and wind speed increments by analyzing wind data sampled with a resolution of one second for 20 months at different heights above sea level in the North Sea. Distributions of horizontal wind speeds can be fitted to Weibull distributions with shape and scale parameters varying weakly with the vertical height separation. Kullback–Leibler divergences between distributions at different heights change with the squared logarithm of the height ratio. Cross-correlations between time derivatives of wind speeds are long-term anticorrelated, and the even parts of their correlation functions satisfy sum rules. Distributions of horizontal wind speed increments change from a tent-like shape to a Gaussian with rising increment lag. A surprising peak occurs in the left tail of the increment distributions for lags in a range $$10-200\,{km}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mn>10</mml:mn> <mml:mo>-</mml:mo> <mml:mn>200</mml:mn> <mml:mspace/> <mml:mrow> <mml:mi>km</mml:mi> </mml:mrow> </mml:mrow> </mml:math> after applying the Taylor’s hypothesis locally to transform time lags into distances. The peak is decisive in order to obtain an expected and observed linear scaling of third-order structure functions with distance. This suggests that it is an intrinsic feature of atmospheric turbulence.

Boundary-Layer MeteorologyVol. 190(11)
Osnabrück University (DE), University of Milano-Bicocca (IT)
Deutsche Forschungsgemeinschaft, Bundesministerium für Wirtschaft und Energie, Universität Osnabrück, Projektträger Jülich
Openalex Percentile: Top 5%
Wind Energy Research and Development
5.20
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.