Discontinuities in the data are detected using the Haar transform (Mahrt 1991). The Haar transform calculates the difference in some quantity over two half-window means. Large values of the transform identify changes that are coherent on the scale of the window. The goal is to detect discontinuities that lead to semipermanent changes as opposed to sharp changes associated with smaller-scale fluctuations. The transform is computed for a series of moving windows of width L1and then normalized by the smaller of the standard deviation for the entire record and one-fourth the range for the entire record. The record is hard flagged if the absolute value of any single normalized transform exceeds 3 and soft flagged at 2.
To identify coherent changes over the window width L1 in the intensity of the fluctuations, we compute the variance for each half-window and then compute the difference normalized by the variance over the entire record. The record is hard flagged if the absolute value of any single normalized transform exceeds 3 and soft flagged at 2.
For the RASEX record in Fig. 3c, the Haar transform of the mean virtual temperature is hard flagged. There is no evidence in the winds or turbulence intensity to support a sharp increase in virtual temperature of this magnitude, nor is there any supporting evidence from the other sonic anemometer and the hard flag is verified as an instrument problem.
Figure 4 shows three of the RASEX 10-m sonic records hard flagged by Haar criteria but classified as physical after further analysis. Figure 4a shows a RASEX vertical velocity record hard flagged for kurtosis and the Haar variance during a transition from near laminar flow to strong turbulence. The horizontal wind components and the virtual temperature from the sonic anemometer support this transition and the cup anemometers measured an eightfold increase in the variance of the wind speed. Figure 4b shows a possible gravity wave train that was hard flagged for the Haar mean and variance of virtual temperature. The crosswind component and the virtual temperature are correlated (R = −0.70) consistent with a gravity wave train. The 32-m sonic also shows this behavior. Figure 4c shows an intermittent turbulence case hard flagged for the Haar variance of the vertical velocity. Changes in the local variances of the horizontal wind components and virtual temperature are positively correlated with the changes in the vertical velocity variance and appear to be related to intermittent turbulence.
Figure 5a shows a BOREAS example of a land-based, warm, and dry turbulent boundary layer that is advected over Candle Lake during strong (8 m s−1) winds. The aircraft intersects a cool, moist, and less turbulent internal boundary layer approximately 8 km downwind from the upwind edge of the
Figure 3b shows a BOREAS vertical velocity record hard flagged for exceeding the absolute limits, skewness, kurtosis, dropouts, and Haar variance (see next section) thresholds. Near the 5-km mark into the record, the measured alongwind component, vertical velocity, static pressure, and the aircraft airspeed are all affected by the same electronic problem.