MREA08 DRIFTER DATABASE
Scientific
document
1.
Buoy systems, positioning and data telemetry
The surface drifter data contained in this database come from CODE drifters equipped with GPS receivers and SST sensors, and manufactured by Technocean). All drifters measure Sea Surface Temperature (SST) at 15-min intervals. They also report battery voltage and tether strain (drogue presence) at hourly and 30-min intervals, respectively.
The drifters were released in the central Ligurian Sea between 1 and 21 October 2008 in small clusters of 3 to 5 units from ITN Magnaghi.
All drifters were tracked by, and transmitted data to, the Argos Data Collection and Location System (DCLS) onboard the NOAA polar-orbiting satellites. Transmissions were programmed every 90 seconds.
2.
Data Reduction and editing
2.1 Drifter Data
reduction
The data for each
drifter
were read, reduced and written into individual files. The
sensor
data were processed and reduced in the following way. The sensor data
(i.e.,
time, voltage and temperature) records telemetered during a single
satellite
overpass were decompressed, that is, each record was repeated by a
number
of times equal to a given compression index and the repeated records
were
shifted back in time by successive 90 s increments. The data were then
sorted in increasing sequential order and the median values were
estimated.
These median statistics were assigned to the drifter location and were
written into the output raw file. For the passes with good sensor data
but for which no
drifter
location was provided, the output raw latitude and
longitude
were assigned with the NaN default value.
During the
reading
and reduction process, the times were converted into MATLAB time (serial days
where 1 corresponds
to 01-Jan-0000. The deployment
coordinates
(time, latitude and longitude) were added to the drifter
time
series as the initial record. A location class from 1 to 3 correspond
to Argos position, while location class 4 (bad) or 5 (good) correspond to GPS position.
2.2
Determination
of time of last good fix and type of death
The type of
dysfunction
or the circumstances of the termination receipt of good quality
oceanographic
data have been carefully investigated by examining the suspect records
in the context of their proximity to the coast line, the values and the
probability that they were picked up by seafarers. Thus, the time for
the
last good fix was determined and the type of death was classified into
one of five categories: Recovered (intentionally), Grounded; Picked-up;
Battery
failure; Unknown.
2.3 Data
editing
The position and
temperature data
were edited through automatic and manual procedures. The
criteria utilized in the automatic procedure for the position data are
based on
a maximum distance of 1000 m, a maximum speed of 50 cm/s and a maximum
angle of
45 degrees, between successive points. This means that the longitude
and
latitude of a point are flagged with NaN if (i) the distances
with
the previous
and successive points are greater than the limit; (ii) the
previous or the
successive velocities are greater than the limit and (iii) the angles
formed
with the previous and successive points are both within 180+/-45
degrees
. This procedure
is iterated twice. Thereafter, a manual procedure is performed to
eliminate the remaining residual outliers visualized on the drifter
tracks.
The temperature
data
were edited using the following conditions: the temperatures are
flagged
with NaN if (i) the temperature gradient between successive points
exceeds
1/8 degrees/hour
and (ii) the temperature difference
with respect to a blackman
running mean exceeds 5, 4, 3, 2 and 1 degree (in iterative successive
runs). The
editing based on the maximum
gradient is then repeated. Finally the manual procedure is performed
to remove remaining outliers appearing in time series plots.
3. Data
interpolation and filtering
The despiked data
were
interpolated onto regular 2-hour intervals using an optimum analysis
technique
known as Kriging.
The
Kriging used here employed an analytic function fit to the empirical
structure
function
computed from the entire despiked data set. Both the interpolated
value and an estimate of its accuracy were
computed.
The interpolated
positions and temperature were then low-pass filtered with a Hamming
filter
with cut-off period at 36 hours
in
order to remove high frequency current components, especially the
strong
tidal and inertial currents. The low-pass time series were finally
subsampled
every 6 hours and the velocity was computed by finite centered
differencing
the 6-hourly interpolated/filtered position data. The processed data
files
contain 6-hourly values of position, velocity and
temperature.
The velocity for the first and last records of each drifter, the
temperature
after failure of the SST sensor, and all the variables during temporary
grounding, were assigned the NaN default value. If the time
difference
between the interpolated point and the closest edited observation is
larger
than 3 days, the corresponding velocity was assigned NaN in order
to
avoid meaningless interpolated velocity estimates in large data gaps.