1. WinRiver MOVING ADCP DATA PROCESSING

2. 1. Average data to a greater interval Use raw data Decreases errors and increases data quality

13. 2. Convert to ASCII format Files found at: http://users.coastal.ufl.edu/~arnoldo/eoc6934/ponce/adcphttp://users.coastal.ufl.edu/~arnoldo/eoc6934/ponce/adcp/

18. depth cell length (cm)blank after transmit (cm)ADCP depth# of pings per ensemble# of depth cells time per ensemble (hundredths of s) Profiling mode Date and timeEnsemble ## of ensembles in segmentpitchrollcorrected headingtemperature Bottom track vel (east in cm/s) Bottom track vel (north in cm/s)Bottom track vel (vertical in cm/s) Bottom track vel (error in cm/s)Water layer velDepth Reading (m) Total elapsed distance (m)Total elapsed time (s)Distance traveled north (m)Distance traveled east (m)Course made good (m) Lat & LonShip velocity north (cm/s)Ship velocity east (cm/s)Total distance traveled (m) Discharge Values # of bins to follow and units of measurementVelocity reference (BT, layer, none) and intensity units (dB or COUNTS)Intensity scale factor (dB/count) Sound absorption factor (in dB/m) Bin depth Velocity Magnitude Velocity Direction East Component North Component VerticalError Echo Intensity % good Discharge

19. 3. Depurate data with the following criteria (for Lily Springs): % good > 20% |error| < 10 cm/s

20. 3. Depurate data with the following criteria (for other data): % good > 80% |error| < 10 cm/s discharge < 100 m 3 /s ship speed or bottom track speed > 0.15 m/s

21. 4. Calibrate Compass Method of Joyce (1989, Journal of Atmospheric and Oceanic Technology, 6, 169-172 ) and Method of Pollard & Reid (1989) tan  = / 1 +  = [ / ] 1/2 u corr = [1 +  ] [u cos  - v sin  ] v corr = [1 +  ] [u sin  + v cos  ] where u bt is the East component of the bottom track velocity u sh is the East component of the navigation velocity (from GPS) u is the East component of the current velocity measured by the ADCP u corr is the corrected East component of velocity indicates average throughout one transect repetition Carry out the correction for each transect repetition

22. 5. Generate a regular matrix for u, v, and t corresponding to each transect repetition Identify each transect repetition according to the time of beginning and end of each repetition

23. Draw each repetition placing the data (u, v, and t) on a regular grid (distance vs. depth) The origin of the matrix (zero distance) is arbitrary (e.g. a point at the coast) Calculate the distance from that origin to the location of each profile in order to generate the regular grid The end result is a group of N regular grids, where N is the number of transect repetitions. Each grid point has a time series of N values for u, v, t, and backscatter.