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  • Author or Editor: Dean Vickers x
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Dean Vickers
and
L. Mahrt

Abstract

A series of automated tests is developed for tower and aircraft time series to identify instrumentation problems, flux sampling problems, and physically plausible but unusual situations. The automated procedures serve as a safety net for quality controlling data. A number of special flags are developed representing a variety of potential problems such as inconsistencies between different tower levels and the flux error due to fluctuations of aircraft height.

The tests are implemented by specifying critical values for parameters representing each specific error. The critical values are developed empirically from experience of applying the tests to real turbulent time series. When these values are exceeded, the record is flagged for further inspection and comparison with the rest of the concurrent data. The inspection step is necessary to either verify an instrumentation problem or identify physically plausible behavior. The set of tests is applied to tower data from the Risø Air Sea Experiment and Microfronts95 and aircraft data from the Boreal Ecosystem–Atmosphere Study.

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Dean Vickers
and
L. Mahrt

Abstract

An alternative method to Fourier analysis is discussed for studying the scale dependence of variances and covariances in atmospheric boundary layer time series. Unlike Fourier decomposition, the scale dependence based on multiresolution decomposition depends on the scale of the fluctuations and not the periodicity. An example calculation is presented in detail.

Multiresolution decomposition is applied to tower datasets to study the cospectral gap scale, which is the timescale that separates turbulent and mesoscale fluxes of heat, moisture, and momentum between the atmosphere and the surface. It is desirable to partition the flux because turbulent fluxes are related to the local wind shear and temperature stratification through similarity theory, while mesoscale fluxes are not. Use of the gap timescale to calculate the eddy correlation flux removes contamination by mesoscale motions, and therefore improves similarity relationships compared to the usual approach of using a constant averaging timescale.

A simple model is developed to predict the gap scale. The goal here is to develop a practical formulation based on readily available variables rather than a theory for the transporting eddy scales. The gap scale increases with height, increases with instability, and decreases sharply with increasing stability. With strong stratification and weak winds, the gap scale is on the order of a few minutes or less. Implementation of the gap approach involves calculating an eddy correlation flux using the modeled gap timescale to define the turbulent fluctuations (e.g., w′ and T′). The turbulent fluxes (e.g., wT′) are then averaged over 1 h to reduce random sampling errors.

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L. Mahrt
,
Dean Vickers
,
William M. Drennan
,
Hans C. Graber
, and
Timothy L. Crawford

Abstract

Errors in eddy correlation measurements from moving platforms (aircraft, ships, buoys, blimps, tethered balloons, and kites) include contamination of the measured fluctuations by superficial fluctuations associated with vertical movement of the platform in the presence of mean vertical gradients. Such errors occur even with perfect removal of the motion of the platform. These errors are investigated here from eddy correlation data collected from the LongEZ research aircraft and the air–sea interaction spar (ASIS) buoy during the Shoaling Waves Experiment (SHOWEX).

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