Analysis of Long Time Series of Coastal Wind

Heggem, Tore; Lende, Rune; Løvseth, Jørgen

doi:10.1175/1520-0469(1998)055<2907:aoltso>2.0.co;2

Cited by 16 publications

(13 citation statements)

References 14 publications

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“…Consequently the wind fluctuations are transformed to very large power fluctuations. Vincent and Hahmann (2011), Heggem et al (1998) and others showed that a typical weather situation, which enhances mesoscale wind variability, are cold air outbreaks on the rear of low pressure systems. When the cold air is advected over warm water, cellular clouds develop.…”

Section: Introductionsupporting

confidence: 72%

On the correlation of spatial wind speed and solar irradiance variability above the North Sea

Mehrens

Bremen

2016

Adv. Sci. Res.

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Abstract. Mesoscale wind fluctuations on a time scale of tens of minutes to several hours lead to high wind power fluctuations. Enhanced mesoscale wind variability emerges during cold air outbreaks and resulting cellular convection. The study investigates spatial wind and solar variability and their correlation during cellular convection. Cellular convection leads to simultaneous high solar and wind variability, but the highest solar or wind variability occurs due to other meteorological phenomena.

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Section: Introductionsupporting

confidence: 72%

On the correlation of spatial wind speed and solar irradiance variability above the North Sea

Mehrens

Bremen

2016

Adv. Sci. Res.

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“…In the full‐frequency range from 6 × 10 −9 (5 year) to 8 × 10 −3 Hz (2 min), we observed the most significant spectral peak at the daily cycle both at 100 and 10 m heights. This result differs from some previous studies [e.g., Van der Hoven , ; Troen and Petersen , ; Heggem et al , ; Larsén et al , ] that found no or insignificant diurnal peak in their full‐scale spectra of low‐level horizontal winds at either an offshore or a coastal site.…”

Section: Discussionmentioning

confidence: 99%

“…Some studies [e.g., Smedman‐Högström and Högström , ; Gomes and Vickery , ; Metzger and Holmes , ; Larsén et al , ] have confirmed its existence, although the gaps in their studies were not as pronounced as that of Van der Hoven []. However, other studies have discussed that the spectral gap is filled up with enhanced wind speed fluctuations, particularly when mesoscale structures, such as horizontal rolls, exist in the ABL [e.g., LeMone , ; Young , ; Gjerstad et al , ; Heggem et al , ; Lenschow and Sun , ; Vincent et al , ]. Recently, Larsén et al [] suggested that the horizontal wind variation from the mesoscale and microscale eddies yields the spectrum in the gap range.…”

Section: Introductionmentioning

confidence: 99%

Spectral structure of 5 year time series of horizontal wind speed at the Boulder Atmospheric Observatory

Kang

Won

2016

JGR Atmospheres

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We investigate the spectral structures of 5 year, 1 min time series of horizontal wind speeds at 100 and 10 m heights at the Boulder Atmospheric Observatory tower located in the eastern slope of the Rocky Mountains, USA. In the full‐scale spectra, the diurnal spectral peak, which is usually insignificant at a coastal or offshore site, is the most significant at both heights. The spectrum is enhanced on the low‐frequency side of the diurnal peak during winter, but on the high‐frequency side during summer, which indicates frequent synoptic weather events during winter supplanted by mesoscale events during summer. In terms of the spectral density in the spectral gap of Van der Hoven (1957), separating boundary layer turbulence from the synoptic‐scale fluctuations, at a frequency between 10−4 and 10−3 Hz, we rank the daily time series at 100 m height and sample the summer top and winter bottom 10 percentile cases. The winter cases of the reduced spectral density in the gap region present the f−3 spectrum (f is frequency) and negatively skewed velocity increment distributions, which are the signatures of enstrophy (the integral of squared vorticity) cascade of turbulent two‐dimensional (2‐D) flows. In contrast, the summer cases of the enhanced spectral density present the f−5/3 spectrum and positively skewed velocity increment distributions, which are the signatures of upscale energy cascade of 2‐D flows. In these mesoscale events that fill up the gap, the turbulence intensity‐wind speed relationship is very sensitive to the choice of the averaging period.

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“…The Fourier spectrum, which reflects the combined effects of all stability conditions, shows a slight minimum in variance for time scales of around 12 min. These values are within the range of frequencies for the spectral gap suggested by authors such as Petersen (1975), Courtney and Troen (1990), Gjerstad et al (1995), Heggem et al (1998), Yahaya et al (2003) and Metzger et al (2007). Previous analysis of the spectral gap has addressed a variety of flow conditions and surface types.…”

Section: Wind Variability As a Function Of Atmospheric Stabilitymentioning

confidence: 99%

Wind fluctuations over the North Sea

Vincent

Pinson

Giebel

2011

Intl Journal of Climatology

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Climatological patterns in wind speed fluctuations with periods of 1 min to 10 h are analysed using data from a meteorological mast in the Danish North Sea. Fluctuations on these time scales are of particular relevance to the effective management of the power supply from large wind farms. The Hilbert-Huang transform (HHT) is shown to be an effective tool for analysing long time series of wind speed observations, as it describes the time-evolving spectral information in the time series. By binning and averaging the time-evolving spectrum, the average spectral behaviour of the wind speed under a certain class of conditions can be found. Here, the HHT is applied to create conditional spectra which demonstrate patterns in the occurrence of severe wind variability. It is shown that wind fluctuations over the North Sea are more severe for westerly flow than for easterly flow, and that severe fluctuations are often observed in the vicinity of precipitation. The most severe wind fluctuations occur in the autumn and winter seasons, and are slightly more common when the pressure tendency is rising. Further, it is found that the wind is more variable for atmospherically unstable conditions than for stable conditions.

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Analysis of Long Time Series of Coastal Wind

Cited by 16 publications

References 14 publications

On the correlation of spatial wind speed and solar irradiance variability above the North Sea

On the correlation of spatial wind speed and solar irradiance variability above the North Sea

Spectral structure of 5 year time series of horizontal wind speed at the Boulder Atmospheric Observatory

Wind fluctuations over the North Sea

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