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 and DBI (Florida, USA).
The Technocean 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. GPS positions were sampled at hourly intervals. The DBI CODE drifters transmitted data to the Iridium global cellular telephone system. Their GPS positions were sampled every 15 min.
The drifters were released in the northwestern Mediterranean Sea on 2-4 September 2012 from NRV Alliance as part of the NOMR12 experiment.
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.
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 (both Argos and GPS, separately) and temperature data were edited through automatic and manual procedures (see also Gerin and Bussani, 2011). The automatic procedures for the position data recognize the GPS data before the deployment, the double GPS data (existing because of the repetition of the GPS message) and all the points responsible for speed higher than 150 cm/s and 300 cm/s for the Argos and GPS data, respectively. For this last step the deployment position is considered good (reference point) and the second point is considered as the point to check. If the second point passes the test, it becomes the reference point and the subsequent point bacomes the point to check, otherwise, the second point is flagged as NaN and the third point becomes the point to check. This procedure is iterated till the last position point. The longitude and latitude of the recognized points are flagged with NaN. Due to some problems with the GPS data (duplicated points at different times or good point but at wrong times) the latitude and longitude are checked separately for wrong positions. This additional step is performed by considering the deviation from the median value of 4 points at a time.
Thereafter, a manual procedure is performed to eliminate the remaining residual outliers. 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 temperature outliers.
Gerin R. and Bussani A. (2011). Nuova procedura di editing automatico dei dati drifter impiegata su oceano per MyOcean e prodotti web in near-real time e delay mode. REL. OGS 2011/55 OGA 20 SIRE, Trieste, Italy, 13 pp.
3. Data interpolation and filtering
The GPS edited data (or the Argos data in case of no/bad GPS data) were interpolated onto regular 1-hour intervals using an optimum analysis technique known as Kriging. The Kriging used here employ an analytic function fit to the empirical structure function computed from the entire despiked data set.
The interpolated positions and temperature were then subsampled at 2-hours intervals and 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.
More on data and
along with temperature