1. Quality Assurance Procedures for CORIE Data Realtime QA Timeseries Diagram of Slopes Sequential Likelihood Ratio Archival QA Time Pressure Temperature Salinity Velocity Meteorology Database Web Visualization Field Staff Near Real-time Quality Assessment Instrument Network Archival Quality Assessment Ascii Public Data Archive Field Notes Quality Flags Metadata

2. Real-time Quality Assurance Visual evaluation of data quality 4 times a week Automated testing for biofouling, checked by operator Real-time checks result in notification of field staff No database storage of notification No incorporation of assessment into database quality flags Non-automated use of assessment to deactivate web display of real-time data

3. Archival quality assurance CTD and ADP data quality assessment on a monthly basis. 1 month lag in assessment (January data tested at the end of February) CTD QA dependent on subsequent data ADP QA not dependent on subsequent data Data which passes QA is stored in ascii public archive QA not used to generate Quality flags in database FebMarApr CTD QA ADP QA

4. Timeseries Timeseries of Depth, Salinity, Temperature displayed on website Inspected for instrument failure or biofouling

5. Cross-estuary slope diagram S-T plot of all stations Almost all stations should produce the same s-t line Chnke, ogi01, and ogi02 are exceptions Mottb possibly biofouledExtensive biofouling

6. Sequential Likelihood Ratio Based on linear S-T relationship across estuary Accounts for local variation from linear relationship Depends on S and T at daily maximum S at each station, river T and Ocean T Modeled S clean and S biofouled based on T, T R, and T O compared to measured S Station specific ratio cutoff, trained on known biofouled data Used to generate a visual display Currently trained for lower estuary stations Extension of method to lateral bays under development Could be used for archival QA TRTR 34 TOTO 0 SMSM TMTM S cl S bf

7. CTD: time Radio network can produce data with bunched time values Expected timestep between data points is determined from data (median timestep) If timesteps are shorter than median time step, with a gap preceding bunch that has correct length, then data are reassigned times evenly spaced over gap If gap is longer than data clump, then data clump is discarded

8. CTD: Salinity Main concern is biofouling, but Conductivity sensors can also fail Sensor failure is detected by range check (S 35) and by visual inspection Biofouling is tested by using cross estuary s-t relationship Determine median s-t slope for each tidal period

9. CTD: Salinity Compare each instrument’s s-t slope for that tidal period to median Cutoff: abs(local slope) – abs(median slope) > 0.2 => biofouled When an instrument is considered biofouled, preceding data is considered biofouled until a clean cutoff is exceeded Clean cutoff: abs(local slope) – abs(median slope) < 0 When median slope approaches 0, method fails If instrument is biofouled after period of near-zero slope, then entire period of near-sero slope is considered biofouled

10. CTD: Salinity Automated assessment produces both false positives and false negatives Results are manually checked False positiveFalse negative Transient Biofouling

11. Storage of Quality Assessment Data records which do not meet minimal quality standards are stored in the raw data files, but do not enter the database Notices of observer suspicion of data quality are not currently stored in a formal manner, and are not entered into the database Archival quality assurance procedures currently generate public archive files which contain only data which has passed the quality assurance testspublic archive files The quality assurance flagging is not currently stored in the database

12. Models A model of the clean signal –Temperature and salinity variation are correlated. Model daily maximum salinity and corresponding temperature are jointly Gaussian. –The probability density for observing the sequence of salinity measurements {s n }, given the sequence of recorded mixing coefficients {T n }  and a clean sensor p({s n } | {  n }  clean ) A model of the biofouled signal –Allows for different degradation rates m for each biofouling episode, and arbitrary onset time  with these parameters fit to incoming data. p({s n } | {  n }  m  biofouled ) = p ({s n } | {  n }  biofouled ) –m and  are unknown –These parameters are fit to the data sequence by maximum likelihood.

13. Regression Model: Mixture of Experts The correlation between salinity and temperatures is not stationary. –The detector system needs to switch between seasons. –A mixture of local models can cover different behaviors. Both of experts and gating network receive same input vector. Each expert network tackles each of the different seasons. The gating network decides which of the experts should be used. Regression output Expert Network 1 Expert Network 2 Expert Network n  Gating Network Input vector T Output nn   g1g1 gngn g2g2  Ref.

14. Approach and Results Parameterized novelty detectors embedded in a sequential likelihood ratio test –SLR at current time N is compared to a threshold to identify biofouling events. Results –Automated biofouling detectors deployed throughout the estuary. Monitored by observer, and used to send out notices of biofouling events, but not incorporated directly in to data flagging.detectors Ref.

15. Criteria for rejecting data before it enters the database rserial2db rejects data lines based on failed checksum or garbled line Short input line: [RE^M], skipping. Skipping unknown data line: [abedCT 0000 00 00 00 00 00 1516D +20.856, +07.947, +19.0889*6F] Checksum failed for data line: W,üR'¢í?»TW%X¯»U»PT$CRdsdmaRV0CTDd00730R seabedCT 0000 00 00 00 00 00 1516D +09.502, +08.366, +08.0447*60 Short input line: [], skipping. Skipping unknown data line: [W,ýS'¢è¾?»T W%Y­»S»UT10394A141322 1316:0 746:1 :2 :3 :4 532:5 -1806:6 :7] Line length = 162, must be 81 to 83 chars long, skipping data line: 10395A138173 1193:0 770:1 :2 :3 :4 282:5 :6 10395A138177 1192:0 770:1 :2 :3 :4 278:5 :6 :7 Most data is not subjected to sanity check (e.g salinity 35) Certain stations are handled as special cases and are subject to sanity checks (ogi02 is checked for negative sal, temp, and cond)

16. Metadata for Operational Resources Partners –Name –Abbreviation –Adminstrative contact –Scientific contact –Technical contact <- when things go wrong. Sensor inventory –Owner, Type, Manufacturer, Serial number, Deployment –Station ID, lat/lon, depth, Metadata

17. Operational metadata (cont.) Models –Owner, developer, version, domain Output formats –Native binary? –NetCDF (need CDL descriptions) –OPeNDAP URLs or LAS if deployed All operational metadata into Postgres with a web interface for modifications (this has been done, grab schema from SEACOOS or GoMOOS?) Metadata

18. CORIE Data Management Data Flow

19. CORIE Data Management Base Station Processes Rserialv2db 1.Raw input from serial port timestamped and written to disk. 2.Metadata, timestamp added to data line (config.txt). 3.Some processing (Coastal Leasing) and quality control (checksums). 4.Pre-processed data line written to disk. 5.Raw and pre-processed data lines written to transfer table in a local relational database. Pusher 1.Reads records from local DB on base station, FIFO. 2.Writes records to remote DB on ambts01. 3.Deletes records from local DB on base station.

20. CORIE Data Management At OGI Telemetry server - ambts01 –Rack mounted, 1GB memory, 2.4Ghz single CPU, 32GB mirrored disk, RHE Linux. –PostgreSQL parsedb2.pl –Reads records from transfer table. –Parses record, processes data, and deposits to proper tables in telemetry database on ambts01. –Replicates to production databases on amb104, amb105. –Sets a flag in the transfer table to indicate record was processed and replicated. –Data ready for applications from production database servers on amb104 and amb105.

21. CORIE Data Management Monitoring and Alerting Monitoring –Monitor incoming data stream –Observation networkObservation network –Monitor individual instrumentsMonitor individual instruments Alerting –E-Mail –Pager Oncall, troubleshooting. –CORIE Base Station Operations ManualCORIE Base Station Operations Manual –CORIE Serial Port Reader ManualCORIE Serial Port Reader Manual –Telemetry ONCALL Information

22. CORIE Data Management Maintenance on Base Station System –OS updates –Hardware failures –Security issues Weekly data files –Rserialv2 signals HUP – Re-read configuration file, instrument changes USR1 – Rotates the raw and partially processed data files Database –Vacuum, analyze, log file rotation and cleanup –Database table used for data transfer is usually empty

23. CORIE Data Management Real Time Data Transfer Currently – –$CRjettaRV1CTDd00640R seabedCT 2005 03 27 10 06 06 1454D 15.605 09.238 13.4218 Going forward, XML for RT xfer –MarineXML standardMarineXML standard –Upload to web application, FTP, SOAP, or direct to DB –Sample CTD record.Sample CTD record. –Downside is XML bloat Metadata web forms –Station name, location, instrument –Event logging