The computation of turbulent fluxes of heat, momentum, and greenhouse gases requires measurements taken at high sampling frequencies. An important step in this process involves the detection and removal of sudden, short-lived variations that do not represent physical processes and that contaminate the data (i.e., spikes). The objective of this study is to assess the performance of several noteworthy despiking methodologies in order to provide a benchmark assessment and to provide a recommendation that is most applicable to high-frequency micrometeorological data in terms of efficiency and simplicity. The performance of a statistical time window–based algorithm widely used in micrometeorology is compared to three other methodologies (phase space, wavelet based, and median filter). These algorithms are first applied to a synthetic signal (a clean reference version and then one with spikes) in order to assess general performance. Afterward, testing is done on a time series of actual CO2 concentrations that contains extreme systematic spikes every hour owing to instrument interference, as well as several smaller random spike points. The study finds that the median filter and wavelet threshold methods are most reliable, and that their performance by far exceeds statistical time window–based methodologies that use the median or arithmetic mean operator (−34% and −71% reduced root-mean-square deviation, respectively). Overall, the median filter is recommended, as it is most easily automatable for a variety of micrometeorological data types, including data with missing points and low-frequency coherent turbulence.

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[1] Accelerations in the flow over forests generate coherent structures which locally enhance updrafts and downdrafts, forcing rapid exchanges of energy and matter. Here, observations of the turbulent flow are made in a highly heterogeneous black spruce boreal forest in Fairbanks, Alaska at~2.6 h (12 m) and~0.6 h (3 m), where h is the mean canopy height of 4.7 m. Wavelet analysis is used to detect coherent structures. The sonic temperature and wind data cover 864 half-hour periods spanning winter, spring, and summer. When mean global statistics of structures are analyzed at the two levels independently, results are similar to other studies. Specifically, an average of eight structures occurs per period, their mean duration is 85 s, and their mean heat flux contribution is 48%. However, this analysis suggests that 31% of the structures detected at 2.6 h, and 13% at 0.6 h, may be influenced by wave-like flow organization. Remarkably, less than 25% of the structures detected occur synchronously in the subcanopy and above canopy levels, which speaks robustly to the lack of flow interaction within only nine vertical meters of the forest.

We evaluate local differences in thermal regimes and turbulent heat fluxes across the heterogeneous canopy of a black spruce boreal forest on discontinuous permafrost in interior Alaska. The data were taken during an intensive observing period in the summer of 2013 from two micrometeorological towers 600 m apart in a central section of boreal forest, one in a denser canopy (DC) and the other in a sparser canopy, but under approximately similar atmospheric boundary layer (ABL) flow conditions. Results suggest that on average 34% of the half-hourly periods in a day are nonstationary, primarily during night and during ABL transitions. Also, thermal regimes differ between the two towers; specifically between midnight and 0500 Alaska Standard Time (AKST) it is about 3°C warmer at DC. On average, the sensible heat flux at DC was greater. For midday periods, the difference between those fluxes exceeded 30% of the measured flux and over 30 W m À2 in magnitude more than 60% of the time. These differences are due to higher mechanical mixing as a result of the increased density of roughness elements at DC. Finally, the vertical distribution of turbulent heat fluxes verifies a maximum atop the canopy crown (2.6 h) when compared with the subcanopy (0.6 h) and above canopy (5.1 h), where h is the mean canopy height. We argue that these spatial and vertical variations of sensible heat fluxes result from the complex scale aggregation of energy fluxes over a heterogeneous canopy.