Dataset: Elemental and isotopic noble gas ratios and N2/Ar from the North Atlantic: model simulations

Name: Model simulations of elemental and isotopic heavy noble gas ratios using the Transport Matrix Method (TMM)
Published: 2023-02-21
Keywords: noble gas, North Atlantic, nitrogen, gas exchange, oceans

Cite This Dataset

DOI:10.26008/1912/bco-dmo.890293.1

Project:

Collaborative Research: Novel constraints on air-sea gas exchange and deep ocean ventilation from high-precision noble gas isotope measurements in seawater (HPNGI)

Collaborative Research: Probing the Ventilation Efficiency of the Deep Ocean with Conservative Dissolved Gas Tracers in Archived Samples (TTO NGs and O2)

Principal Investigator:

Alan M. Seltzer (Woods Hole Oceanographic Institution, WHOI)

Co-Principal Investigator:

Peter Barry (Woods Hole Oceanographic Institution, WHOI)

William J. Jenkins (Woods Hole Oceanographic Institution, WHOI)

Samar Khatiwala (University of Oxford, Oxford)

David P. Nicholson (Woods Hole Oceanographic Institution, WHOI)

William M. Smethie Jr. (Lamont-Doherty Earth Observatory, LDEO)

Rachel Stanley (Wellesley College)

Martin Stute (Lamont-Doherty Earth Observatory, LDEO)

BCO-DMO Data Manager:

Shannon Rauch (Woods Hole Oceanographic Institution, WHOI BCO-DMO)

Version:

Version Date:

2023-02-21

Restricted:

Validated:

Yes

Current State:

Final no updates expected

Model simulations of elemental and isotopic heavy noble gas ratios using the Transport Matrix Method (TMM)

Abstract:

This dataset includes model simulations of the following tracers using the Transport Matrix Method (TMM): (i) new observations of heavy noble gas ratios (elemental and isotopic ratios) from the Bermuda Atlantic Time-series (BATS) on cruise 10391 (30 April 2022 - 05 May 2022), and (ii) measurements of Kr/Ar and N2/Ar ratios in stored dissolved gas samples collected in 1981 through the Transient Tracers in the Ocean (TTO) program. Together these measurements and model simulations provide insight into physical processes governing gas exchange in the high-latitude regions of North Atlantic Deep Water formation, and a comparison of physical simulations of N2/Ar ratios to observations in TTO samples reveals excess N2 that arises from benthic denitrification in the deep North Atlantic.

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Archival Copy

Version Date	Archive	Persistent Identifier	Date Assigned
2023-02-21	Marine Biological Laboratory/Woods Hole Oceanographic Institution Library (MBLWHOI DLA)	10.26008/1912/bco-dmo.890293.1	2023-02-24

Methods & Sampling

Note: all methods are described in detail in the accompanying publication currently in final review at Proceedings of the National Academy of Sciences.

All model simulations were carried out using the University of Victoria Earth System Climate Model (UVic ESCM) via the Transport Matrix Method (TMM), using an updated version of the gas exchange model of Nicholson et al. (2016) to include noble gas isotopes, N2, and different gas exchange parameterizations. A full description is included in the accompanying paper (Seltzer et al., 2023).

The BATS data and TTO data are available as related datasets at BCO-DMO. See the following:
BATS - https://www.bco-dmo.org/dataset/890342
TTO - https://www.bco-dmo.org/dataset/890427

Data Processing Description

Data Processing:
All data were processed using MATLAB. Codes are available upon request.

The data are provided here in both NetCDF (.nc) and MATLAB (.mat).

Data Files

File

UVic_TMM_output.nc

(NetCDF, 109.94 MB)
MD5:382713b172d61b0486dd2549b279cc54

Primary data file for dataset ID 890293. Data are the sam as UVic_TMM_output.mat but in NetCDF format.

netcdf UVic_TMM_output {

dimensions:

        lon = 100 ;

        lat = 100 ;

        depth = 19 ;

        month = 12 ;

        mon = 12 ;

variables:

        double D136Xe_model(month, depth, lat, lon) ;

        double D40Ar_model(month, depth, lat, lon) ;

        double D86Kr_model(month, depth, lat, lon) ;

        double DKrAr_model(month, depth, lat, lon) ;

        double DN2Ar_model(month, depth, lat, lon) ;

        double DXeAr_model(month, depth, lat, lon) ;

        double month(mon) ;

        double x(lon) ;

        double y(lat) ;

        double z(depth) ;

}

Variable descriptions: 

D136Xe_model: monthly climatologies of simulated 136Xe/129Xe solublity anomaly (in per mil; lon x lat x depth x month)

D40Ar_model: monthly climatologies of simulated 40Ar/36Ar solublity anomaly (in per mil; lon x lat x depth x month)

D86Kr_model: monthly climatologies of simulated 86Kr/82Kr solublity anomaly (in per mil; lon x lat x depth x month)

DKrAr_model: monthly climatologies of simulated Kr/Ar solublity anomaly (in per mil; lon x lat x depth x month)

DN2Ar_model: monthly climatologies of simulated N2/Ar solublity anomaly (in per mil; lon x lat x depth x month)

DXeAr_model: monthly climatologies of simulated Xe/Ar solublity anomaly (in per mil; lon x lat x depth x month)

month: month of year (1 to 12; Jan to Dec)

x: longitude (0 to 360 degrees)

y: latituide (-90 to 90 degrees)

z: depth (meters)

Supplemental Files

File

UVic_TMM_output.mat

(MATLAB Data (.mat), 43.39 MB)
MD5:02babd5f11474b62e1729a271121e2f7

Supplemental data file for dataset ID 890293. Data are the same as UVic_TMM_output.nc but in MATLAB Format.

Variable descriptions: 

D136Xe_model: monthly climatologies of simulated 136Xe/129Xe solublity anomaly (in per mil; lon x lat x depth x month)

D40Ar_model: monthly climatologies of simulated 40Ar/36Ar solublity anomaly (in per mil; lon x lat x depth x month)

D86Kr_model: monthly climatologies of simulated 86Kr/82Kr solublity anomaly (in per mil; lon x lat x depth x month)

DKrAr_model: monthly climatologies of simulated Kr/Ar solublity anomaly (in per mil; lon x lat x depth x month)

DN2Ar_model: monthly climatologies of simulated N2/Ar solublity anomaly (in per mil; lon x lat x depth x month)

DXeAr_model: monthly climatologies of simulated Xe/Ar solublity anomaly (in per mil; lon x lat x depth x month)

month: month of year (1 to 12; Jan to Dec)

x: longitude (0 to 360 degrees)

y: latituide (-90 to 90 degrees)

z: depth (meters)

More Information about this dataset

Funding Sources

Funding Source	Award Number
NSF Division of Ocean Sciences	OCE-1923915
NSF Division of Ocean Sciences	OCE-2122427

Deployments

None available yet

Instruments

High-Performance Computing Cluster

Supplied Name: NCAR Cheyenne supercomputer

Supplied Description:

The TMM infrastructure developed by S. Khatiwala and D. Nicholson was implemented on the NCAR Cheyenne supercomputer.

Cheyenne is a 5.34-petaflops, high-performance computer built for the National Center for Atmospheric Research (NCAR). The system was released for production work on January 12, 2017. The Cheyenne supercomputer features 145,152 Intel Xeon processor cores in 4,032 dual-socket nodes (36 cores/node) and 313 TB of total memory.

Instrument Type

Generic Name: High-Performance Computing Cluster

Acronym: HPC

Generic Description:

"High-Performance Computing" (HPC) refers to a class of evolving technologies that provide leading-edge computational capabilities, including scalable high-performance computers, high-end graphic systems, and high-speed networks. HPC may be used for molecular modeling, genome analysis, and image processing, among others.

Parameters

Date and time formats are described in python strftime() syntax.

Supplied Name	Supplied description	Supplied Units	Standard Name
D136Xe_model	monthly climatologies of simulated 136Xe/129Xe solublity anomaly (in per mil; lon x lat x depth x month)	per mil	no_bcodmo_term
D40Ar_model	monthly climatologies of simulated 40Ar/36Ar solublity anomaly (in per mil; lon x lat x depth x month)	per mil	no_bcodmo_term
D86Kr_model	monthly climatologies of simulated 86Kr/82Kr solublity anomaly (in per mil; lon x lat x depth x month)	per mil	no_bcodmo_term
DKrAr_model	monthly climatologies of simulated Kr/Ar solublity anomaly (in per mil; lon x lat x depth x month)	per mil	no_bcodmo_term
DN2Ar_model	monthly climatologies of simulated N2/Ar solublity anomaly (in per mil; lon x lat x depth x month)	per mil	no_bcodmo_term
DXeAr_model	monthly climatologies of simulated Xe/Ar solublity anomaly (in per mil; lon x lat x depth x month)	per mil	no_bcodmo_term
month	month of year (1 to 12; Jan to Dec)	unitless	month
x	longitude (0 to 360 degrees)	degrees	lon
y	latituide (-90 to 90 degrees)	degrees	lat
z	depth (meters)	meters	depth

Status message

Database

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Dataset: Elemental and isotopic noble gas ratios and N2/Ar from the North Atlantic: model simulations