Time spectra and cross‐spectra of kinetic energy in the planetary boundary layer

Hess, Glenn; Clarke, R. H.

doi:10.1002/qj.49709941912

Cited by 20 publications

(9 citation statements)

References 27 publications

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“…Since then, several investigators have confirmed the existence of a spectral gap in the spectra of horizontal wind velocity over land. Hess and Clarke [1973] also showed a tendency for a gap in the spectra of wind velocity measured at different heights between the surface layer and free atmosphere.…”

Section: Introductionmentioning

confidence: 85%

On the influence of gravel bed dynamics on velocity power spectra

Singh

Porté‐Agel

Foufoula‐Georgiou

2010

Water Resources Research

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[1] A series of flume experiments were conducted to study the effect of bed form dynamics on the flow over a gravel bed comprising a wide distribution of grain sizes. Instantaneous high-frequency streamwise flow velocities were sampled using an acoustic Doppler velocimeter at a frequency of 200 Hz, while the simultaneous bed elevations were sampled using sonar transducers at a frequency of 0.2 Hz for a duration of 20 h. Spectral analysis of the measured velocity fluctuations reveals the existence of two distinct power law scaling regimes. At high frequencies, an inertial subrange of turbulence with ∼−5/3 Kolmogorov scaling is observed. At low frequencies, another scaling regime with spectral slope of about −1.1 is found. We interpret this range as the signature of the evolving multiscale bed topography on the near-bed velocity fluctuations. The two scaling ranges are separated by a spectral gap, i.e., a range of intermediate scales with no additional energy contribution. The high-frequency limit of the spectral gap corresponds to the integral scale of turbulence. The low-frequency end of the gap corresponds to the scale of the smallest bed forms identified by the velocity sensor, which depends on the position of the sensor. Our results also show that the temporal scales of the largest bed forms can be potentially identified from spectral analysis of low-resolution velocity measurements collected near the channel bed.

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Section: Introductionmentioning

confidence: 85%

On the influence of gravel bed dynamics on velocity power spectra

Singh

Porté‐Agel

Foufoula‐Georgiou

2010

Water Resources Research

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“…of this gap have been over land (Van der Hoven, 1957;Vinnichenko, 1970;Hess and Clarke, 1973;Smedman-Hogstrom and Hogstrom, 1975;Thomson, 1979). Theoretical arguments in support of the spectral gap over land are found in Fiedler and Panofsky (1970) and Weinstock (1980).…”

Section: Buoy Observations and Intercomparison Of The Data From The Bmentioning

confidence: 99%

Mesoscale spatial and temporal variability of meteorological observations from an array of buoys in JASIN-1978

Ishida

1986

Boundary-Layer Meteorol

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Observations of wind speed and direction, air and sea temperatures and solar radiation were obtained from an array of buoys in JASIN-1978 conducted in the area northwest of Scotland in the summer of 1978. The observations were analyzed to show spatial and temporal variability in the mesoscale fields. Spectra of wind speed and air and sea temperatures were computed to illustrate the distribution of variance over periods ranging from 3.5 min to 40 days. When plotted on log-log graphs, the spectral estimates generally decreased with slopes between -$ and -2 with increasing frequency. Spectra of air and sea temperatures had a peak at the diurnal period but not the wind speed spectrum.When plotted in variance-preserving form, the spectrum of wind speed was consistent with a spectral gap and was qualitatively similar to other observations of low-frequency spectra. On the basis of auto-and crosscorrelation analyses, it appeared that mesoscale eddies propagated through the array ofbuoys with the mean wind speed except during times of frontal passages. The cross-correlation between wind speed and air temperature showed evidence of horizontal roll vortices or some other forms of organized convection.

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“…Analysis of the data shows that the mesoscale disturbances contributed to the downward flux of westerly momentum, but only slightly (Clarke, 1972;Hess and Clarke, 1973). At 1 km altitude the mesoscale flux of momentum was only 4% of the surface value.…”

Section: Implicationsforglobalmodelingmentioning

confidence: 99%

The impact of the Wangara experiment

Hess

Hicks

Yamada

1981

Boundary-Layer Meteorol

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Our understanding of the structure and dynamics of the atmospheric boundary layer (ABL) is often limited by a lack of experimental data. The voluminous amount of high quality data obtained from the Wangara Experiment (Clarke et al., 1971) has contributed greatly to meeting a long-standing need, particularly for data describing the ABL in middle latitudes over land.In the surface layer the measurements provided the basis for determination of the stability dependence of the dimensionless gradients d,+, and dH arising out of Monin-Obukhov similarity theory (Hicks, 1976). In the outer layer where the choice of scaling parameters is not unique, the data have been used to determine the stability dependence of the similarity functions A, B, and C, and the most appropriate choices of scaling parameters (e.g., Yamada, 1976). In addition, the experimental data give determinations of some of the fundamental constants of turbulent flow in the ABL, such as the Von Kdrmin constant k = 0.40-0.41 (Hicks, 1969), and the neutral barotropic ABL similarity constants A,, = 1.1 and & = 4.3 (Clarke and Hess, 1974), where the subscript 0 indicates that the surface geostrophic wind was used as reference.Perhaps the greatest impact of the Wangara Experiment has been to provide a data bank which could be used to test numerical simulations of the ABL. This has been useful not only for the newly developed higher-order closure models, but also for one-layer integral models predicting the height of the mixed layer and the height of the nocturnal surface inversion layer.Lastly, the Wangara Experiment has pointed out some of the limitations and difficulties of obtaining accurate measurements of thermal winds, vertical velocity, acceleration terms, and representative spatially averaged fluxes. Microscale turbulence measurements outside the surface layer were not included in the Wangara Experiment and further experiments are needed to determine these statistics.

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Time spectra and cross‐spectra of kinetic energy in the planetary boundary layer

Cited by 20 publications

References 27 publications

On the influence of gravel bed dynamics on velocity power spectra

On the influence of gravel bed dynamics on velocity power spectra

Mesoscale spatial and temporal variability of meteorological observations from an array of buoys in JASIN-1978

The impact of the Wangara experiment

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