Relation of the atmospheric potential gradient with meteorological elements-cross power spectral analysis

Bhartendu,

doi:10.1007/bf00877906

Cited by 11 publications

(2 citation statements)

References 9 publications

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“…The terdiurnal and quartodiurnal maximums of the potential gradient for Dusheti are likely to be due to corresponding maximums of the conductivities, but the terdiurnal maximum ot the potential gradient for Irkutsk could not be explained in this way. It could be of a meteorological nature like that for Toronto [Bhartendu, 1969b[Bhartendu, , 1971c, where the potential gradient terd•urnal component is found to be related to the rate of change of temperature and relative humidity.…”

Section: Tential Gradient Dourbes-balshaja Elan Formentioning

confidence: 99%

Electric potential gradient and conductivity power and cross power spectra at land stations

Bhartendu¹

1972

J. Geophys. Res.

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Electrical potential gradient and positive and negative conductivity power spectra for five stations and coherence coefficient and cross spectral phase spectra for seven station pairs are computed. The potential gradient spectra exhibit maximums at the diurnal and semidiurnal frequencies for all five stations, at the terdiurnal for two stations, and at the quartodiurnal for one station. The positive and negative conductivity power spectra are similar and exhibit maximum at the diurnal frequency for two stations, at the semidiurnal for three, at terdiurnal for one, and at the quartodiurnal frequency for two. The cross power spectra are complicated. There is no definite frequency for which high coherence is found for all cases, but in some cases high coherence is observed at one or more frequencies of diurnal, semidiurnal, terdiurnal, or quartodiurnal components. Phase relationship of these components is variable. The inadequacy of the correlation coefficient is indicated, and the significance of the results is discussed.

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Section: Tential Gradient Dourbes-balshaja Elan Formentioning

confidence: 99%

Electric potential gradient and conductivity power and cross power spectra at land stations

Bhartendu¹

1972

J. Geophys. Res.

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“…The correspondence in variation and correlation between the two variables at different timescales can then be evaluated by comparing the variance spectra (or power spectra) and examining the covariance spectra (or cospectra), respectively [e.g., Allen, 1968; Rodriguez-lturbe and Nordin, 1969]. Such technique has been used by Bhartendu [1971Bhartendu [ , 1977 to study the relationships between the atmospheric electrical conductivity and meteorological parameters, where significant correspondence at diurnal, semidiurnal, and terdiurnal scales has been identified. However, much remains to be done for the timescale dependent relationships between the atmospheric electrical conductivity and concentrations of important air pollutants.…”

Section: Introductionmentioning

confidence: 99%

The spectral relationships between atmospheric electrical conductivity and air pollution in urban conditions

Guo¹,

Barthakur²,

Bhartendu³

1996

J. Geophys. Res.

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The timescale dependent relationships between the atmospheric electrical conductivity and concentrations of aerosol particles, carbon monoxide, sulfur dioxide, and nitrogen dioxide in downtown Toronto were examined by spectral analyses based on a year of hourly averaged observations at a single site during 1973–1974. The highlights of the relationships were found as follows: (1) The variance spectra (or power spectra) of both electrical conductivity and pollutant concentrations obeyed the −5/3 power law of spectral decay, suggesting that the air in the city of Toronto during the experiment was severely polluted. (2) The variation of the electrical conductivity corresponded significantly to those of pollutant concentrations for most timescales, characterized by a common variance‐contributing scale range from a few hours to a few weeks in the variance spectra. (3) The variations of both electrical conductivity and pollutant concentrations were contributed mainly by daily changes of hourly averaged values and weekly changes of daily averaged values, coinciding with the daily and weekly cycles in the city's traffic and industrial activities. (4) The electrical conductivity correlated negatively with pollutant concentrations for most timescales. However, the correlations were contributed mainly by weekly changes of daily averaged values, different from the variation contributions of these variables. This suggests that the electrical conductivity is poorly synchronized with pollutant concentrations for the timescales smaller than diurnal component, which could be expected to introduce noises if the correlations between the electrical conductivity and pollutant concentrations at the scales smaller than diurnal component are pursued.

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Relationship of the Ohm’s Law Electrical Parameters with Meteorological Elements

Bhartendu¹

1976

Electrical Processes in Atmospheres

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Relation of the atmospheric potential gradient with meteorological elements-cross power spectral analysis

Cited by 11 publications

References 9 publications

Electric potential gradient and conductivity power and cross power spectra at land stations

Electric potential gradient and conductivity power and cross power spectra at land stations

The spectral relationships between atmospheric electrical conductivity and air pollution in urban conditions

Relationship of the Ohm’s Law Electrical Parameters with Meteorological Elements

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