There is no pressure variable in the .nc files. This should be a coordinate.

By Lori Garzio, on 7/11/19

56% of the optical_absorption values for this deployment are nans, fill values, outside of global ranges, or outliers (+/- 5 SD).

By Lori Garzio, on 6/28/19

There is no pressure variable in the .nc files. This should be a coordinate.

By Lori Garzio, on 6/28/19

According to Roesler and Barnard (Optical proxy for phytoplankton biomass in the absence of photophysiology: Rethinking the absorption line height, Methods in Oceanography, 2013), “absorption meters are highly prone to biofouling, particularly biofilms which not only attenuate the collimated beam but also impact the scattering properties of the optical surfaces and tubes. In productive coastal waters biofouling can have significant impacts (i.e. 10% of the signal) within one to two weeks”.

By Lori Garzio, on 6/28/19

Data gaps should be annotated.

By Lori Garzio, on 7/3/19

total_volume_scattering_coefficient data show a repetitive pattern of increasing to the upper detection limit of the instrument and dropping to zero. A similar issue has been seen on CE06ISSM-RID16-02-FLORTD000 (see annotation ID 97). chl-a and CDOM data are also suspect. This dataset should be annotated.

By Lori Garzio, on 7/3/19

Suspect data at the end of the deployment - negative chl-a and CDOM values, total_volume_scattering_coefficient maxes out.

By Lori Garzio, on 7/3/19

The variable pressure_depth (dbar) is an array of all fill values for every deployment. This should contain valid pressure data.

By Lori Garzio, on 7/3/19

The missing data for deployment 5 should be annotated.

By Lori Garzio, on 3/26/19

Deployment 7 data gaps should be annotated: [['2018-04-20T18:48:18', '2018-05-18T21:30:23'], ['2018-05-23T16:48:11', '2018-05-25T17:30:24'], ['2018-05-30T15:18:11', '2018-06-01T19:30:22']]

By Lori Garzio, on 3/26/19

Deployment 6 should be annotated to indicate why recovered_inst data aren't available.

By Lori Garzio, on 3/26/19

A substantial percentage of data for all deployments is outside of global ranges. It looks like the instruments biofouled shortly after each deployment (1-2 months) - the suspect data should be annotated for all deployments, and further analysis should be done using shipboard bottle data (which is outside the scope of this project).

By Lori Garzio, on 3/26/19

Suspect data at the beginning of the deployment.

By Lori Garzio, on 8/14/19

The range of upward_velocity values for this deployment is substantially higher compared to the range for other deployments.

By Lori Garzio, on 8/14/19

Suspect data towards the end of the deployment. Something happened in early Aug 2018 that caused the CT sensor stopped working temporarily. Issue should be investigated and annotated. A similar issue is seen in the data from CE04OSSM-SBD11-06-METBKA000, CE07SHSM-SBD11-06-METBKA000 and CE09OSSM-SBD11-06-METBKA000 from the same time period.

By Lori Garzio, on 4/8/19

Downwelling Shortwave Irradiance (shortwave_irradiance) and Net Shortwave Irradiance (met_netsirr) minimum values jump to ~10 W m-2 shortly after deployment (should be around 0 W m-2). A similar issue was seen on GS01SUMO-SBD11-06-METBKA000 (see annotation ID 1522 and Redmine 12543). This should be investigated and annotated.

By Lori Garzio, on 4/8/19

Data gap should be annotated.

By Lori Garzio, on 4/8/19

There are telemetered data at the beginning of the deployment, and no recovered_host data for the same time period. These data should be available in the recovered_host data stream.

By Lori Garzio, on 4/8/19

According to annotation IDs 1430-1431, no CT data are expected. However, sea_surface_temperature values are -5, sea_surface_conductivity values are 0.0, and met_salsurf values are 0.0. It looks like other variables are using these data in their calculations, which is creating bad data products. Excluding from summary data ranges

By Lori Garzio, on 4/8/19

Data gaps should be annotated: [['2017-01-02T10:59:17', '2017-01-03T23:08:12'], ['2017-01-26T12:11:28', '2017-01-29T14:44:28'], ['2017-01-29T14:44:28', '2017-01-31T18:27:25'], ['2017-01-31T18:45:15', '2017-02-05T13:46:10'], ['2017-02-05T21:34:14', '2017-02-08T19:43:18'], ['2017-02-08T19:57:53', '2017-02-11T13:14:58']]

By Lori Garzio, on 4/8/19