The statistical variation of wind with distance

Durst, Carolin

doi:10.1002/qj.49708637012

Cited by 8 publications

(7 citation statements)

References 2 publications

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“…value. This may account for the Atlantic maximum of E since use of a value closer to Durst's (1954) value of in this region would have resulted in smaller values of E. Despite this, we still cling to the belief that oceanic maxima in e are real.…”

Section: Itmentioning

confidence: 83%

“…This value was used for all latitudes and altitudes in the absence of better estimates of T~. Durst (1954) and Charles (1959) did not indicate significant variation of T~ with altitude.…”

Section: Data and Resultsmentioning

confidence: 99%

“…In the atmosphere the microscale, I, ranges from a few millimeters near the surface to tens of meters near the jet stream and the macroscale, L, from a few meters to hundreds of kilometers (MacCready, 1953;Obukhov and Iaglom, 1959;Durst, 1954). By Taylor's (1938) Since meteorological wind observations are rarely resolved into components along and perpendicular to the mean vector wind, it is convenient to combine (4) vectorially to obtain (qt)2=7C(eGt)2'3/3.…”

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confidence: 99%

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A Climatology of Epsilon (Atmospheric Dissipation)

Ellsaesser¹

1969

Mon. Wea. Rev.

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Kolmogorov's structure functions for the longitudinal and transverse components of locally homogeneous isotropic turbulence are combined vectorially to obtain an expression which permits the evaluation of E (atmospheric dissipation rate) from climatological data. This is used to derive climatological patterns of e in the free atmosphere from Crutcher's upper wind statistics of the Northern Hemisphere. The latter are combined with Kung's boundarylayer values to estimate the distribution of total atmospheric dissipation over the Northern Hemisphere. I. EPSILON AS A FUNCTION OF CLIMATOLOGICAL PARAMETERS In a recent review of the methods of evaluating e (the rate of kinetic energy dissipation in the atmosphere), it appeared that it could be determined from wind variability data. The theory for such an eva1.uation is provided by Kolmogorov's (1941a) second hypothesis of similarity of locally homogeneous isotropic turbulence. In such a field of turbulence and with the z axis along the mean vector wind, this gives for the wind components a t points 1 and 2 a distance x apart U,(X)~= (U~-U~)~=~(U,)~[~-~,(X)]=C(~X)~~~ (1) and U~(X)~= (~~-~~) 2 = 2 (~,)~[ 1-r , (z) J = 4 5 C (~X)~/~, i.e., the space variance or structure function (square of the Eulerian space variability, a,($), which in turn is a function of the standard deviation, u,, and the Eulerian space correlation, ru(z)) is a function only of the separation distance and the intensity of, the turbulence. The latter, by Eolmogorov's hypothesis, is determined by e. Aside from the effect of orientation, equation (1) can be written by dimensional analysis. It can also be derived leading to theoretical as well as empirical values for..&e.constant C. Values assigned Cin the literature include 34 (Kolmogorov, 1941b), 22/a (Obukhov and Iaglom, 1951)) $5 (MacCready, 1953), and approximately 2 (Hinze, 1959; Pond et al., 1963). In this study we use C=2 primarily because this yields the lowest estimates. forE. The x-range of validity of (1) is presumed to be

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Section: Itmentioning

confidence: 83%

“…This value was used for all latitudes and altitudes in the absence of better estimates of T~. Durst (1954) and Charles (1959) did not indicate significant variation of T~ with altitude.…”

Section: Data and Resultsmentioning

confidence: 99%

mentioning

confidence: 99%

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A Climatology of Epsilon (Atmospheric Dissipation)

Ellsaesser¹

1969

Mon. Wea. Rev.

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“…In general <TT/<T 0.9476 The statistical forecasts index is included for comparison. These forecasts would be made following Durst [3] from a regression equation of the form Va -V = rr(Vz> -V) where VA is the wind at verification time and Vz> that at datum time.…”

Section: 72mentioning

confidence: 99%

Reviews

1958

Bulletin of the American Meteorological Society

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“…The values supplied permit some estimate to be made of the skill over climatology demonstrated by JNWP forecasts. Durst [3] has shown that stretch vector correlation coefficients, rr, vary with time and suggests that they follow the law rr = e~a T where a = 6.9 X 10~6 when T is measured in seconds. Crossley [4] shows that <rT2 = 2<t 2 (1 -rT) hence <rT/<r = [2(1 -e~a T )J.…”

Section: July 1957mentioning

confidence: 99%

Correspondence

1958

Bulletin of the American Meteorological Society

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The statistical variation of wind with distance

Cited by 8 publications

References 2 publications

A Climatology of Epsilon (Atmospheric Dissipation)

A Climatology of Epsilon (Atmospheric Dissipation)

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