Ergodicity test of the eddy-covariance technique

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Abstract

The ergodic hypothesis is a basic hypothesis typically invoked in atmospheric surface layer (ASL) experiments. The ergodic theorem of stationary random processes is introduced to analyse and verify the ergodicity of atmospheric turbulence measured using the eddy-covariance technique with two sets of field observational data. The results show that the ergodicity of atmospheric turbulence in atmospheric boundary layer (ABL) is relative not only to the atmospheric stratification but also to the eddy scale of atmospheric turbulence. The eddies of atmospheric turbulence, of which the scale is smaller than the scale of the ABL (i.e. the spatial scale is less than 1000 m and temporal scale is shorter than 10 min), effectively satisfy the ergodic theorems. Under these restrictions, a finite time average can be used as a substitute for the ensemble average of atmospheric turbulence, whereas eddies that are larger than ABL scale dissatisfy the mean ergodic theorem. Consequently, when a finite time average is used to substitute for the ensemble average, the eddy-covariance technique incurs large errors due to the loss of low-frequency information associated with larger eddies. A multi-station observation is compared with a single-station observation, and then the scope that satisfies the ergodic theorem is extended from scales smaller than the ABL, approximately 1000 m to scales greater than about 2000 m. Therefore, substituting the finite time average for the ensemble average of atmospheric turbulence is more faithfully approximate the actual values. Regardless of vertical velocity or temperature, the variance of eddies at different scales follows Monin-Obukhov similarity theory (MOST) better if the ergodic theorem can be satisfied; if not it deviates from MOST. The exploration of ergodicity in atmospheric turbulence is doubtlessly helpful in understanding the issues in atmospheric turbulent observations and provides a theoretical basis for overcoming related difficulties.

Figures

  • Table 1. Local stability parameter (z− d)/Lc of the eddies in different temporal scales on 25 August.
  • Figure 1. Variation of mean ergodic function Ero(w) of vertical velocity measured at the height 3.08 m in NSPCE with relaxation time for the different scale eddies after band-pass filtering. (a), (b) and (c) are the respective results of the three time frames. If their mean ergodic function is more approximate to 0, then eddies in the corresponding temporal scale will more closely satisfy the ergodic conditions.
  • Figure 2. Variation of mean ergodic function Ero(T ) of the different scale eddies of temperature with relaxation time (other conditions are as some as Fig. 2, and the same applies to the following figures).
  • Figure 3. Variation of mean ergodic function Ero(q) of the different scale eddies of humidity with relaxation time.
  • Figure 4. Variation of mean ergodic function Ero(w) of the vertical velocity (a), temperature (b) and specific humidity (c) before filtering at 14:00–15:00 (CST) during midday in NSPCE with relaxation time τ .
  • Figure 5. Variation of the autocorrelation ergodic function of vertical velocity with relaxation time for different scale eddies.
  • Figure 6. Variation of mean ergodic function (a) and autocorrelation ergodic function (b) of the vertical velocity with relaxation time for the different scale eddies in the seven stations of CASES-99.
  • Figure 7. Variation of ogive functions of w′2 and −u′w′ with frequency at height 3.08 m for the three time frames in NSPCE.

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APA

Chen, J., Hu, Y., Yu, Y., & Lü, S. (2015). Ergodicity test of the eddy-covariance technique. Atmospheric Chemistry and Physics, 15(17), 9929–9944. https://doi.org/10.5194/acp-15-9929-2015

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