Deployment 2009 to 2010:
Arctic Winch (AW)

final data



Deployment summary:
Duration: Aug 4, 2009 to June 17, 2010
Location: BS3 mooring site
Variables measured: pressure, temperature, conductivity, fluorescence, turbidity
Sensor information: The Arctic Winch is a WHOI-developed instrument platform. For this
    deployment, it was equipped with an RBR CTD.
Instrument settings: output 6 Hz data
Calibration: comparison to nearby calibrated SEaBird SBE37 microcat
Processed data: contained in the matlab files aw_bs3_200910_final.mat. The file format is described here.


Data processing:

Processing steps include:
- raw time series de-spiking;
- conversion of temperature/conductivity to salinity and density;
- lagging of T/C relation to reduce spiking and inversions
- pressure binning into standard profiles.
- removal of remaining density inversions
- conductivity calibration
- A/D sensor voltage -> engineering data conversion


Raw Data De-spiking

Working on previous year's data, I spent some effort on de-spiking algorithms,
eventually settling on acomparison of consecutive time series segments to a
second-order fit. Outliers were identified as exceeding n standard deviations.
A minimum outlier size was set to avoid editing of good points during very low
variability segments. After some experimenting, I selected a subset size of 50 points,
and a spike threshold of 2 std. I set a minimum spike size of 1 dbar, 0.1 deg C,
and 0.5 conductivity units. Lateron, I found that basic range editing worked well as a
first step, excluding points beyond simple limits of -10 to 200 dbar, -5 to 15 deg C,
and 15 to 50 conductivity units, respectively. As it turned out, spiking was not much
of an issue; it was mainly observed in one of the early datasets I had worked with.


Salinity Derivation

The Arctic winch CTD rests at depth, then ascents to the surface once a day. I split
the daily profile into up (ascent) and down (descent) profiles, with the latter
quite clearly providing more realistic data. The physical reason is presumably
the CTD location below the float.

Salinity and density were derived for several lags of temperature versus conductivity
(-3 to +2 scans). A best lag was selected based on visual inspection of the down profiles.
For BS3 2009-2010, it was -2 scans; it had been 0 for earlier RBR datasets or +1 for earlier
FSI CTD datasets.)


Pressure Binning

The down cast was pressure binned using a bin size of 0.5 decibar. The bin center depth
ranged from 0.25 to 79.75 dbar, though the deepest bin depth with good data was 39.75 dbar.


Editing of Pressure-binned Profiles

The binned profiles were examined for glitches, identified primarily by vertical
density inversions. A subset of profiles - I used 10 here - were displayed in various
forms: as profiles against a backdrop of the complete dataset, as TS diagrams, as
well as staggered profiles of the subset. With the unducted, unpumped RBR CTD,
a mismatch of temperature and conductivity to derive salinity and thus density
was the primary reason for significant density inversion. They occurred primarily
during the first 20% of the time series, and were manually edited out, thus leaving
the "holes" in the above pcolor plots of S and sigma but not T.


Conductivity Calibration

The conductivity sensor calibration was checked against the post-cruise calibrated
record of the microcat mounted onto the same top float of the mooring. Their
vertical separation was about 1m, as shown below.




Selecting only the "quiet" periods of the record, the lowest bins of the Arctic
Winch data indicated a small vertical conductivity gradient near the mooring float.
We constracted a deep Arctic Winch conductivity record by averaging the three deepest
bins with good data, centered on 38.25, 38.75, and 39.25 dbar, and projected it down
to the microcat depth using the average vertical conductivity gradient. Microcat
conductivity (black), the three deepest Arctic Winch bins, as well as the constructed
deep record (magenta) are shown below for the whole time series (left) as well as for
a detail from the "quiet" period (right).

Lastly, the microcat conductivity was interpolated onto Arctic Winch profile times,
and a linear fit of the difference between the two was calculated. For the fit, extreme
differences particularly from the early data were removed by considering only
points within +- 0.15 mS/cm of an initial guess (marked by * below).



The estimated conductivity correction of 0.0827 mS/cm corresponded to a salinity increase
of about 0.06 psu.


A/D sensor conversion

The Arctic winch sensor suite included a WetLabs FLNTU fluorescence / backscatter sensor.
Sensor voltages were converted to chlorophyll in micrograms/liter (ug/l) and backscatter
in nephelometric turbidity units (NTU) based on the manufacturer's "characterization
sheets" (calibration sheets). Unfortunately the serial number of the instrument used on this
deployment is not known. Instead, we rely on typical conversion numbers (e.g., see the
calibration sheets from FLTNU's # 2674 and 2688 that were part of the instrument pool used
for the Arctic Winches. The factory calibration coefficients differ little from instrument
to instrument. It is our understanding that a precise calibration depends more on local
species compositions than on variations amongst instrument components as reflected in
the calibration sheets. Since we do not have species compositions, our "generic" cal
coefficients seem sufficient here.

We used the following conversions:
      fluorescence [ug/l] = 10 * (fluorescence voltage - 0.08)
      turbidity [NTU] = 5 * (turbidity voltage - 0.056)



For completeness, I include my processing log here, though its details may be most valuable
as a reminder for myself.