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Time
Times are reported in Coordinated Universal Time (UTC), the successor to Greenwich Mean Time (GMT). Drift of instrument clocks is determined by comparing instrument times with accurate times (from the Global Positioning System [GPS] or clocks synchronized with the National Institute of Standards and Technology in Boulder, Colorado; [http://tf.nist.gov/]) before and after deployments. Ordinarily, the observed offsets were small compared to the sample intervals, typically a few seconds; therefore most instrument times in this dataset are not adjusted for clock drift.
Time is stored in the EPIC-compliant netCDF files as two variables named "time" and "time2." This technique avoided round-off error on older computers that did not have sufficient resolution when time is stored as an integer. "Time" is the time in whole Julian days, where midnight on May 23, 1968 = 2,440,000, and "time2" is the time in milliseconds since midnight. Thus, the time in Julian days is computed as
time + (time2 / (1,000 ms/s × 3,600 s/hr × 24 hr/d))
where the product in the denominator is the number of milliseconds in a day. In the CF-compliant netCDF files, time is stored as single variable "time" conforming to the CF conventions document, generally in the form “{units} since {datetime}”: for example, “seconds since 1992-10-8 15:15:42.5 +0:00.”
Burst and Wave Data
EPIC compliant burst and wave data files contain variables that are shaped differently than evenly spaced time-series data. Most of the files in this database have evenly spaced sample intervals, and the variables are vectors of the length of the time variable. Burst data are sampled rapidly at an even interval but have gaps between bursts; time is represented a matrix. For example, an ADV might be programmed to sample hourly bursts of 17.5 minutes, at 8 Hz, so there are 8,400 points per burst. Here, time variables are defined using two dimensions (time, sample), where time is the length of the number of bursts in the record (2,045) and sample is the number of samples in each burst (8,400). Consequently, the data variables in the time series also have that shape. The burst mean variables presented in the ADV statistics file for this example are vectors of length 2,045.
In CF-compliant burst files, time variables have only one dimension (time), where time is a representative time for the burst (for example, the beginning or middle of the burst). As in EPIC-compliant files, other burst data variables will have both time and sample dimensions, where sample is an integer representing the sample number within the burst. The exact time of each sample can be determined from the time variable and the interval of the samples within the burst data.
Wave data files from acoustic current meters contain power spectra and possibly directional spectra; these variables are dimensioned by time (as a vector), frequency, and possibly direction. Some of the pressure-based waves files will contain power spectra dimensioned by time and frequency. The manufacturer’s waves-processing software is used to generate the variables stored, so the contents will vary based on what the code computes. Units and computation techniques may be inconsistent between a “pspec” variable from an ADCP, an AWAC, and a Seagauge file. Evaluation of using DIWASP (Johnson, 2011) to process directional wave data in a consistent way is in process.
An objective in treating data from a wide variety of irregularly sampled data types (bursts, waves) is to have enough consistency in structure to allow use of existing tools to visualize the data.
Instrument Orientation
When interpreting the current meter data, processing software must consider two aspects of orientation: (1) whether the instrument orientation is face up or down, and (2) the orientation of the instrument's beams relative to the Cartesian coordinate system. Typically, acoustic current meters are equipped with internally mounted flux-gate compasses. These are calibrated prior to deployment according to manufacturer's recommendations. Velocity data from profiling instruments (for example, ADCPs) are recorded in raw beam coordinates by instrument firmware and are rotated to geographic coordinates (east, north, up) in postprocessing by using the internal compass and are corrected for local magnetic variation. Data from single point instruments (for example, ADVs) are often recorded in instrument coordinates (referred to as x, y, z coordinates here) and later rotated into geographic coordinates and corrected for local magnetic variation.
In cases where several current meters are mounted on the same tripod, possibly facing different directions, all data from the raw beam coordinate system are initially converted to the east-north-up coordinate system. Because the current is expected to be uniform over the spatial scale of the platform, the primary axes of data from similar sampling heights may be aligned and used to determine the actual instrument orientation.
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