The data were first converted from hexadecimal to ASCII format (as raw counts) and then converted to physical units.  Optical data were calibrated using the calibration factors provided by Satlantic, Inc.  Missing, saturated, and anomalous data were replaced with NaNs.   Repeated data were removed.  The data were then despiked as follows:

Despiking Method

The despiking method used was based on a combination of statistical and subjective criteria.

The input parameters and typical values used (in brackets) were as follows:

• numav : number of data points to average in a running average (30)

• n : least number of standard deviations from the mean that is acceptable (2)

• minstd : minimum standard deviation used (value varies)

• initav : estimated mean for the good data points in the first set of 30 data points (value varies)

The steps taken were as follows:

1. A running average and standard deviation is calculated in groups of 30 (numav) data points.

2. If the standard deviation is less than a guessed lower estimate for the standard deviation (minstd), the guessed estimate (minstd) is used instead (this prevents stds of zero).

3. For the first 30 points, if any of the points deviate from a guess for the initial mean (initav) by more than n minimum standard deviations (n*minstd), they are removed.

4. After the initial set of 30 points, the despiking method is as follows: Each data point is compared with the mean and standard deviation of the previous 30 points. If it differs from the mean by more than n standard deviations, it is removed.

5. After the initial despiking has been made, a second despiking is performed on data where any remaining spikes are obvious (such as latitude, longitude, and occasionally SST data). This second type of despiking is simply based on visual estimation of the maximum deviation that should occur between data points.

Optical despiking

Before applying the above method to radiance data, each set of radiance measurements was first divided by Ed490 to remove diurnal variations. Poor data points were then determined by recording the positions of spikes present in these ratios. The corresponding data points were removed from the radiance data. Poor data points in the Ed490 data set were assumed to correspond to the poor data points present in the ratio of Lu412 to Ed490. Note that this method also removes some good data points, since some of the data points removed from the radiance data may have been caused by poor Ed490 values, and vice versa.  To eliminate further anomalous data points, all Lu's at a given time stamp were assumed to be bad if any of the Lu's at that time stamp were bad.

Chlorophyll Concentration and Fluorescence Line Height calculations

chl = 0.56353 * [Lu(443)/Lu(555)]^-0.595

FLH = Lu(683) - Lu(670)*4/17 (assumes a linear baseline and that Lu(687) is 0)

Fouling

Please note that data after late September may be suspect because of biofouling.  Please use these data with caution.

Webpage by Jasmine S. Nahorniak, Oregon State University.