Hydrographic data from the CTD mounted on the trace metal rosette (TMR) aboard R/V Falkor cruise (160115) during the ProteOMZ expedition in the Central Pacific in 2016.

Website: https://www.bco-dmo.org/dataset/734608
Data Type: Cruise Results
Version: 1
Version Date: 2018-05-01

Project
» The ProteOMZ Expedition: Investigating Life Without Oxygen in the Pacific Ocean (ProteOMZ (Proteomics in an Oxygen Minimum Zone))
ContributorsAffiliationRole
Saito, Mak A.Woods Hole Oceanographic Institution (WHOI)Principal Investigator, Contact
Santoro, Alyson E.University of California-Santa Barbara (UCSB-LifeSci)Co-Principal Investigator
Ake, HannahWoods Hole Oceanographic Institution (WHOI BCO-DMO)BCO-DMO Data Manager


Coverage

Spatial Extent: N:10.544984 E:-158.320979 S:-26.364655 W:-179.289931
Temporal Extent: 2016-01-16 - 2016-02-11

Dataset Description

Hydrographic data files from the SeaBird SBE19 CTD mounted on the trace metal rosette (TMR).


Acquisition Description

Data were collected using the Trace Metal Rosette (TMR, Sea-Bird SEACAT 19+), equipped standard conductivity, temperature and pressure sensors, as well as an added optional SBE 43 dissolved oxygen sensor. All four sensors were factory refurbished/calibrated immediately prior to the expedition in November of 2015 by Sea-Bird Electronics (Bellevue WA).

Notes on CTD/O2 data acquisition and processing using Sea-Bird hardware and software. The GO-SHIP Repeat Hydrography Manual: A Collection of Expert Reports and Guidelines. IOCCP Perort No. 14, ICPO Publication Series No. 134, v. 1. 2010.

Location: Tropical/equatorial Pacific along 150º W; Honolulu, Hawai’i to Pape'ete, French Polynesia


Processing Description

Data from the SBE19Plus were processed using Sea-Bird's SBE Data Processing software, v. 7.23.2.

SBE processing modules were applied in the following order: Data Conversion, Filter, Align CTD, Cell Thermal Mass, and Loop Edit were applied to the input variables using the parameters identified in the .cnv file header shown below. Oxygen data were first processed using the raw sensor voltage, then converted to units of umol/kg using the Derive module. Finally, Wild Edit was used to remove extraneous values and data were binned by depth into 1 m bins using Bin Average and converted to ASCII format using ASCII Out.

Sea state during the cruise and issues with the block used to deploy the TMR did not allow full in-water equilibration of the CTD sensors and pumping system prior to each cast. As a result, we recommend using data from the upcasts (designated with the prefix 'u' in the filename).

# datcnv_date = May 19 2016 15:57:33, 7.23.2 [datcnv_vars = 5]
# datcnv_in = C:\Users\Santoro\Desktop\Falkor_2016\TMR\160131TMR21CTDdata.hex C:\Users\Santoro\Desktop\Falkor_2016\TMR\SBE19plusV2_6801.xmlcon
# datcnv_skipover = 0
# datcnv_ox_hysteresis_correction = yes
# filter_date = May 19 2016 15:58:16, 7.23.2
# filter_in = C:\Users\Santoro\Desktop\Falkor_2016\tmr_process\160131TMR21CTDdata.cnv
# filter_low_pass_tc_A = 0.500
# filter_low_pass_tc_B = 0.150
# filter_low_pass_A_vars = depSM tv290C c0mS/cm sbeox0V
# filter_low_pass_B_vars = prdM
# alignctd_date = May 19 2016 15:58:49, 7.23.2
# alignctd_in = C:\Users\Santoro\Desktop\Falkor_2016\tmr_process\160131TMR21CTDdata.cnv
# alignctd_adv = c0mS/cm 0.073 # celltm_date = May 19 2016 15:59:14, 7.23.2
# celltm_in = C:\Users\Santoro\Desktop\Falkor_2016\tmr_process\160131TMR21CTDdata.cnv
# celltm_alpha = 0.0300, 0.0000
# celltm_tau = 7.0000, 0.0000
# celltm_temp_sensor_use_for_cond = primary, 
# loopedit_date = May 19 2016 16:00:13, 7.23.2
# loopedit_in = C:\Users\Santoro\Desktop\Falkor_2016\tmr_process\160131TMR21CTDdata.cnv
# loopedit_minVelocity = 0.250                                                                                            
# loopedit_surfaceSoak: minDepth = 5.0, maxDepth = 20, useDeckPress = 1                                                   
# loopedit_excl_bad_scans = yes
# Derive_date = May 19 2016 16:03:09, 7.23.2 [derive_vars = 5]
# Derive_in = C:\Users\Santoro\Desktop\Falkor_2016\tmr_process\160131TMR21CTDdata.cnv C:\Users\Santoro\Desktop\Falkor_2016\TMR\SBE19plusV2_6801.xmlcon
# derive_time_window_docdt = seconds: 2
# derive_ox_tau_correction = yes
# wildedit_date = May 19 2016 16:03:51, 7.23.2
# wildedit_in = C:\Users\Santoro\Desktop\Falkor_2016\tmr_process\160131TMR21CTDdata.cnv
# wildedit_pass1_nstd = 2.0
# wildedit_pass2_nstd = 20.0
# wildedit_pass2_mindelta = 0.000e+000
# wildedit_npoint = 100
# wildedit_vars = prdM depSM tv290C c0mS/cm sbeox0V sal00 potemp090C density00 sigma-È00 sbeox0Mm/Kg
# wildedit_excl_bad_scans = yes
# file_type = ascii

BCO-DMO Data Processing Notes:

- Files were originally grouped in separate zip files, but were compressed into one to serve.


[ table of contents | back to top ]

Related Datasets

IsRelatedTo
Saito, M. A., Saunders, J. (2022) Relative protein abundance from scaled and corrected exclusive peptide spectral counts from the ProteOMZ R/V Falkor expedition cruise FK160115 in the Pelagic central Pacific Ocean in 2016. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2022-01-13 doi:10.26008/1912/bco-dmo.868030.1 [view at BCO-DMO]
Relationship Description: This dataset was collected asynchronously using another instrument at the same stations during the expedition.

[ table of contents | back to top ]

Parameters

ParameterDescriptionUnits
PrdMPressure, Strain Gauge db
DepSMDepth of salt water meters
Tv290CTemperature [ITS-90] Celsius
C0mS/cmConductivity mS per cm
Sal00Salinity Practical Salinity Units
Potemp090CPotential Temperature [ITS-90] Celsius
Density00Density kilogram per meter cubed
Sigma-E00Density [sigma-theta] kilogram per meter cubed
Sbeox0Mm/KgOxygen, SBE 43 umol per kilogram
FlagFlag unitless


[ table of contents | back to top ]

Instruments

Dataset-specific Instrument Name
Trace metal rosette
Generic Instrument Name
Trace Metal Bottle
Dataset-specific Description
Used to collect samples
Generic Instrument Description
Trace metal (TM) clean rosette bottle used for collecting trace metal clean seawater samples.


[ table of contents | back to top ]

Deployments

FK160115

Website
Platform
R/V Falkor
Start Date
2016-01-16
End Date
2016-02-11
Description
Project: Using Proteomics to Understand Oxygen Minimum Zones (ProteOMZ) More information is available from the ship operator at https://schmidtocean.org/cruise/investigating-life-without-oxygen-in-the... Additional cruis information is available from the Rolling Deck to Repository (R2R): https://www.rvdata.us/search/cruise/FK160115


[ table of contents | back to top ]

Project Information

The ProteOMZ Expedition: Investigating Life Without Oxygen in the Pacific Ocean (ProteOMZ (Proteomics in an Oxygen Minimum Zone))


Coverage: Central Pacific Ocean (Hawaii to Tahiti)


From Schmidt Ocean Institute's ProteOMZ Project page:

Rising temperatures, ocean acidification, and overfishing have now gained widespread notoriety as human-caused phenomena that are changing our seas. In recent years, scientists have increasingly recognized that there is yet another ingredient in that deleterious mix: a process called deoxygenation that results in less oxygen available in our seas.

Large-scale ocean circulation naturally results in low-oxygen areas of the ocean called oxygen deficient zones (ODZs). The cycling of carbon and nutrients – the foundation of marine life, called biogeochemistry – is fundamentally different in ODZs than in oxygen-rich areas. Because researchers think deoxygenation will greatly expand the total area of ODZs over the next 100 years, studying how these areas function now is important in predicting and understanding the oceans of the future. This first expedition of 2016 led by Dr. Mak Saito from the Woods Hole Oceanographic Institution (WHOI) along with scientists from University of Maryland Center for Environmental Science, University of California Santa Cruz, and University of Washington aimed to do just that, investigate ODZs.

During the 28 day voyage named “ProteOMZ,” researchers aboard R/V Falkor traveled from Honolulu, Hawaii to Tahiti to describe the biogeochemical processes that occur within this particular swath of the ocean’s ODZs. By doing so, they contributed to our greater understanding of ODZs, gathered a database of baseline measurements to which future measurements can be compared, and established a new methodology that could be used in future research on these expanding ODZs.



[ table of contents | back to top ]

Funding

Funding SourceAward
Gordon and Betty Moore Foundation: Marine Microbiology Initiative (MMI)
Alfred P. Sloan Foundation (Sloan)
Schmidt Ocean Institute (SOI)

[ table of contents | back to top ]