Dataset: Seaglider observations at Station ALOHA in the North Pacific Subtropical Gyre

Name: Seaglider observations from Seagliders 146, 147, 148, 511, 512, and 626 at Station ALOHA in the North Pacific Subtropical Gyre from 2008-2023
Published: 2024-10-25
Keywords: North Pacific Subtropical Gyre, Gliders, ALOHA, oceans

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Cite This Dataset

Spatial Extent: N:23.78321667 E:-156.47122547 S:20.31742889 W:-160.55633364

Temporal Extent: 2008-08-14 - 2023-08-13

Project:

Oligotrophic ocean metabolism from underwater glider observations (Glider Ocean Metabolism)

Principal Investigator:

Sara Ferrón (University of Hawaiʻi at Mānoa)

David M. Karl (University of Hawaiʻi at Mānoa)

Co-Principal Investigator:

Benedetto Barone (University of Hawaiʻi at Mānoa)

Scientist:

Catherine Garcia (University of Hawaiʻi at Mānoa)

Technician:

Steve Poulos (University of Hawaiʻi at Mānoa)

BCO-DMO Data Manager:

Lynne M. Merchant (Woods Hole Oceanographic Institution, WHOI BCO-DMO)

Version:

Version Date:

2024-10-25

Restricted:

Validated:

Current State:

Preliminary and in progress

Seaglider observations from Seagliders 146, 147, 148, 511, 512, and 626 at Station ALOHA in the North Pacific Subtropical Gyre from 2008-2023

Abstract:

This dataset includes over 20,000 depth profiles collected with underwater gliders in a total of 18 missions between 2008 and 2023. The glider missions were centered at the long-term sampling site of the Hawaii Ocean Time-series (HOT) program, Station ALOHA (22°45′N, 158°W), within the North Pacific Subtropical Gyre. The gliders were equipped with sensors to measure temperature, salinity, pressure, dissolved oxygen concentration, chlorophyll a concentration from fluorescence (excitation/emission lambda = 470/695 nm), and the particulate backscattering coefficient at three wavelengths (lambda = 470 nm, 700 nm, and either 650 or 660 nm depending upon mission). Vertical profiles down to at least 200 m were collected for all sensors over periods of several months per mission. Chlorophyll a and oxygen concentrations are calibrated with discrete observations. Particulate backscattering coefficients are corrected with an additional dark subtraction. This dataset differs from the raw data files in that it is quality controlled, calibrated, and corrected. Raw data files can be found at https://hahana.soest.hawaii.edu/seagliders/index.php. The glider observations were collected over the years by Dr. Karl, with different funding sources (including NSF) to investigate carbon cycle processes in the oligotrophic North Pacific Subtropical Gyre. Dr. Ferron and Dr. Barone received NSF funding to conduct a re-analysis of this comprehensive dataset in order to characterize metabolic rates and understand their patterns of variability. Dr. Garcia conducted the data processing that resulted in this curated dataset. Steve Poulos operated the Seagliders in all missions.

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Methods & Sampling

Vertically resolved data were collected by underwater Seagliders, which are guided autonomous underwater vehicles developed at the University of Washington’s Applied Physics lab (Eriksen et al., 2001). The Seagliders were piloted either in a circular or 'bowtie' pattern for several months in each mission around Station ALOHA.

Gliders were equipped with the sensors to measure temperature and salinity (Seabird CT Sail), pressure (Paine Electronics 211-75-710-05 and Kistler 4260M00), dissolved oxygen (Aandera models 5013 and 4330), chlorophyll fluorescence and optical backscatter at three wavelengths: 470 nm, 700 nm, and either 650 or 660 nm (WET Labs ECO Triplet ).

Data Processing Description

The raw observations were quality-controlled, accounting for known sensor responses and deviations from factory calibrations. Detailed descriptions of the data processing, quality control metrics, and calibration methods are provided by Garcia et al. (2023; https://doi.org/10.5281/zenodo.10247019). Quality control steps included a pitch angle test (to detect density inversions), global and regional range tests, stuck value test, biofouling evidence test, and visual inspection. If a test passed, the data were assigned a QC value of 1 (‘good data’). If a test failed (e.g. out of range or density inversion tests), data were flagged, either as ‘questionable data’ (QC = 3) or as ‘bad data’ (QC = 4). All quality control flags and adjustments (i.e. calibration and correction parameters) are preserved in each mission’s file. Code for all processing steps is available on GitHub: https://github.com/cathygarcia/SeagliderDataprocessing.

Data processing steps for each variable are summarized below:

Temperature, Conductivity, Salinity, and Potential Density Anomaly

- Both temperature and conductivity profiles were lag corrected.
- Practical salinity was calculated using the Gibbs Seawater Toolbox, McDougall et al., 2011 (gsw_SP_from_C.m), and then converted to absolute salinity (gsw_SA_from_SP.m).
- Potential density anomaly was calculated with respect to a reference water pressure of 0 db using the Gibbs Seawater Toolbox (gsw_sigma0.m).

Dissolved oxygen concentrations

- Raw optode phase values proceeded through a series of corrections to account for the effects of temperature, salinity, pressure, and time response in addition to sensor drift (Bittig et al., 2018, Barone et al., 2019).
- Optode phase values were converted to dissolved oxygen concentrations, and re-calibrated using discrete Winkler measurements.

Chlorophyll a

- Factory-calibrated chlorophyll a observations were re-calibrated using discrete measurements of either HPLC chlorophyll a (16 missions) or fluorometric chlorophyll a (2 missions).
- Daytime chlorophyll a values are not quench corrected, and may be lower than actual values. It is recommended to use nighttime profiles near the surface.
- Additionally, a spike flag is included based on published protocol (Briggs et al., 2011).

Backscattering coefficient due to particles (bbp)

- Factory-calibrated bbp values could have a large offset, that was not expected based on natural variability.
- A mission-specific deep dark correction (1st percentile of bbp at 190-200 m) was subtracted for each bbp dataset. Both the uncorrected and corrected data are available.
- Additionally, a spike flag is included based on published protocol (Briggs et al., 2011).

BCO-DMO Processing

Submitted files processed with the BCO-DMO tool Laminar.
Submitted files named:
sg146_4_qc_pass.xlsx, sg146_6_qc_pass.xlsx, sg146_9_qc_pass.xlsx
sg146_5_qc_pass.xlsx, sg146_7_qc_pass.xlsx sg147_4_qc_pass.xlsx
sg148_11_qc_pass.xlsx sg148_16_qc_pass.xlsx sg148_8_qc_pass.xlsx
sg148_12_qc_pass.xlsx sg148_6_qc_pass.xlsx sg148_9_qc_pass.xlsx
sg511_21_qc_pass.xlsx
sg512_1_qc_pass.xlsx sg512_3_qc_pass.xlsx sg512_4_qc_pass.xlsx
sg626_1_qc_pass.xlsx, sg626_4_qc_pass.xlsx

In Laminar, all the submitted files were concatenated into one file.
Three identifying columns were added: seaglider_id, seaglider_platform, seaglider_mission.
The parameter time was renamed ISO_DateTime_UTC due to time being in the format %Y-%m-%dT%H:%M:%SZ and UTC.
The latitude and longitude values were rounded to 8 digit precision which represents a precision of approximately 1.11mm.
The processed table of concatenated submitted files was named 928732_v1_seaglider_observations_at_station_aloha.csv.

More Information about this dataset

Funding Sources

Funding Source	Award Number
NSF Division of Ocean Sciences	OCE-2048435

Deployments

Deployment	Synonyms	Start Date	Platform	Investigator
SG146_4_station_ALOHA	SG146_4	2009-05-12	Seaglider 146	David M. Karl (Principal Investigator)	data info
SG146_5_station_ALOHA	SG146_5	2010-08-13	Seaglider 146	David M. Karl (Principal Investigator)	data info
SG146_6_station_ALOHA	SG146_6	2011-05-10	Seaglider 146	David M. Karl (Principal Investigator)	data info
SG146_7_station_ALOHA	SG146_7	2012-05-23	Seaglider 146	David M. Karl (Principal Investigator)	data info
SG146_9_station_ALOHA	SG146_9	2014-03-13	Seaglider 146	David M. Karl (Principal Investigator)	data info
SG147_4_station_ALOHA	SG147_4	2009-07-24	Seaglider 147	David M. Karl (Principal Investigator)	data info
SG148_11_station_ALOHA	SG148_11	2012-05-24	Seaglider 148	David M. Karl (Principal Investigator)	data info
SG148_12_station_ALOHA	SG148_12	2013-05-23	Seaglider 148	David M. Karl (Principal Investigator)	data info
SG148_16_station_ALOHA	SG148_16	2020-09-02	Seaglider 148	David M. Karl (Principal Investigator)	data info
SG148_6_station_ALOHA	SG148_6	2008-08-14	Seaglider 148	David M. Karl (Principal Investigator)	data info
SG148_8_station_ALOHA	SG148_8	2009-05-12	Seaglider 148	David M. Karl (Principal Investigator)	data info
SG148_9_station_ALOHA	SG148_9	2010-11-09	Seaglider 148	David M. Karl (Principal Investigator)	data info
SG511_21_station_ALOHA	SG511_21	2023-03-28	Seaglider 511	David M. Karl (Principal Investigator)	data info
SG512_1_station_ALOHA	SG512_1	2010-12-14	Seaglider 512	David M. Karl (Principal Investigator)	data info
SG512_3_station_ALOHA	SG512_3	2012-08-06	Seaglider 512	David M. Karl (Principal Investigator)	data info
SG512_4_station_ALOHA	SG512_4	2013-09-19	Seaglider 512	David M. Karl (Principal Investigator)	data info
SG626_1_station_ALOHA	SG626_1	2017-01-25	Seaglider 626	David M. Karl (Principal Investigator)	data info
SG626_4_station_ALOHA	SG626_4	2023-05-25	Seaglider 626	David M. Karl (Principal Investigator)	data info

Instruments

Aanderaa Oxygen Optodes

Supplied Name: Aandera oxygen optode models 5013 and 4330

Supplied Description:

Instrument Type

Generic Name: Aanderaa Oxygen Optodes

Acronym: AOO

Community Identifier: http://vocab.nerc.ac.uk/collection/L05/current/351/

Generic Description:

Aanderaa Oxygen Optodes are instrument for monitoring oxygen in the environment. For instrument information see the Aanderaa Oxygen Optodes Product Brochure.

Autonomous Underwater Vehicle

Supplied Name: Underwater Seagliders

Supplied Description:

Underwater Seagliders are guided autonomous underwater vehicles developed at the University of Washington’s Applied Physics lab (Eriksen et al., 2001).

Eriksen, C. C., Osse, T. J., Light, R. D., Wen, T., Lehman, T. W., Sabin, P. L., Ballard, J. W., & Chiodi, A. M. (2001). Seaglider: a long-range autonomous underwater vehicle for oceanographic research. IEEE Journal of Oceanic Engineering, 26(4), 424–436. https://doi.org/10.1109/48.972073

Instrument Type

Generic Name: Autonomous Underwater Vehicle

Acronym: AUV

Generic Description:

An Autonomous Underwater Vehicle (AUV) is a free-roving platform operating in the water column with propulsion but no human operator on board (e.g. Autosub, Gavia).

Wet Labs ECO Triplet

Supplied Name:

Supplied Description:

Instrument Type

Generic Name: Wet Labs ECO Triplet

Acronym: Triplet

Generic Description:

The Wet Labs ECO Triplet is a special-order, three-optical-sensor instrument available from WET Labs (wetlabs.com) in a user-defined configuration. The Triplet addresses the need for multiple simultaneous scattering and fluorescence sensors for autonomous vehicles and unattended measurement platforms. For example, possible configurations include any combination of three of the following: Blue scattering, Green scattering, Red scattering, Chlorophyll fluorescence, CDOM fluorescence, Phycoerythrin fluorescence, Phycocyanin fluorescence, Rhodamine fluorescence, or Uranine (fluorescein) fluorescence.

Parameters

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Dataset: Seaglider observations at Station ALOHA in the North Pacific Subtropical Gyre