Sound velocity profile data from an AML Oceanographic MVP30 and Minos X collected in Cape Cod Bay, Massachusetts during USGS Field Activity 2019-002-FA (PNG images, SVP text, and point shapefile, GCS WGS 84)

Sound velocity profiles were collected approximately every 1-4 hours using an AML MVP30. A computer controlled smart winch and deployment system allowed the free fall MVP profiler to be deployed while the vessel was underway at a user specified time interval. Data from the sound velocity profiler were written to a Kongsberg SIS format ASCII file (.asvp). The MVP was set to only collect data on the down-cast. Beginning on Friday August 2 at 1655 UTC, the MVP30 was replaced by an AML Minos X SVTP hand-deployed sound velocity profiler. The Minos X was deployed every 1-3 hours to collect sound velocity, pressure, and temperature profiles in the water column though the remainder of the survey. AML SeaCast software (v. 4.4) was used to read the profile data from the Minos X, export all raw cast data to an AML SeaCast (.csv) formatted file, then edit the sound velocity profile to preserve only the downcast portion of the deployment and export it to a Kongsberg SIS ASCII (.asvp) formatted file.

A Python script (plotMVPsql_2019_002_py3.py run from the shell script do_MVPplots) was used to read the ASVP data, filter outlier data, and reformat all of the parsed ASVP data into a final sound velocity file in CARIS SVP format that is ready for import into CARIS HIPS. The contact person for this and all subsequent processing steps below is Seth Ackerman.

After additional editing of the sound velocity data in CARIS HIPS (version 11.3), the final profiles were exported to two separate CARIS HIPS (.svp) files (one each for legs 1 and 2 of the survey). These corrected CARIS SVP files were then split into individual files for each sound velocity cast using the terminal 'csplit' command. >> csplit -f Leg1_ -n3 -k Leg1_SVP_Master.svp '/^Section/' '{300}' >> csplit -f Leg2_ -n3 -k Leg2_SVP_Master.svp '/^Section/' '{300}' Then the Python script MVP_plot_intoSQL_5May2021.py was used to create a plot for each sound velocity cast as a PNG image graph with speed of sound (meter/second) versus depth (meters). Position, Date, Time, and Profile ID were pulled from the SVP header line and written into the image for reference. The image files are named based on the date and time each sound velocity cast was collected. The same script parses the position, Julian Day, time, and Profile ID and entered it into a geospatial SQLite (version 3.36) database using the pyspatialite interface. The geographic positions were used to create point geometries for the station locations, and additional fields indicating survey ID, vessel ID, and device ID were added within the Python script. The individual .svp files (created by the csplit commands above) were then renamed to match the file names of the PNG files (based on the day and time of collection) using the following script: >> for f in Leg*.svp; do x=`awk 'NR==1{print "cast_"substr($2,1,4)substr($2,6,3)"_"substr($3,1,2)substr($3,4,2)substr($3,7,2)".svp"}' $f`; echo mv -v $f $x | sh; done And finally the CARIS SVP header was restored using the following command line scripts: >> for f in *.svp; do x=`echo "$f" ; cat $f`; echo "$x" > $f; done >> for f in *.svp; do x=`echo "[SVP_VERSION_2]" ; cat $f`; echo "$x" > $f; done

The sound velocity cast locations were exported from the SQLite database as Geographic Coordinate System (GCS, latitude and longitude) WGS 84 point features in ESRI Shapefile format using Spatialite-tools (version 5.0.1) using the spatialite_tool command in Terminal: >> spatialite_tool -e -shp 2019-002-FA_MVPSVP_data -d ./2019-002-FA-SQLdb_NEWSVP.sqlite -t MVPNav_pt -g geom_MVPnav -c CP1252 -s 4326 --type POINT