# Last Glacial Maximum and Preindustrial Iron Flux Global Ocean Model Results
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#               World Data Service for Paleoclimatology, Boulder
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#                      NOAA Paleoclimatology Program
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# NOTE: Please cite original publication, online resource and date accessed when using this data.
# If there is no publication information, please cite Investigator, title, online resource and date accessed.
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# Description/Documentation lines begin with #
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# Online_Resource: https://www.ncdc.noaa.gov/paleo/study/21331
# Online_Resource: http://www1.ncdc.noaa.gov/pub/data/paleo/gcmoutput/muglia2017
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# Archive: Paleoclimatic Modeling
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# Parameter_Keywords: ocean model
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# Contribution_Date
#    Date: 2017-02-01
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# Title
#    Study_Name: Last Glacial Maximum and Preindustrial Iron Flux Global Ocean Model Results
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# Investigators
#      Investigators: Muglia, Juan; Somes, Christopher; Nickelsen, Levin; Schmittner, Andreas
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# Description and Notes
#        Description: Study contains data from LGM and Preindustrial model runs. The data folders contain output files, which are tavg and tsi netcdf files. The rest of the files are necessary to run the model, if more experiments are going to be carried out.
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# Publication
# Authors: Muglia, Juan, Christopher Somes, Levin Nickelsen, and Andreas Schmittner
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# Published_Title: Combined effects of atmospheric and seafloor iron fluxes to the glacial ocean
# Journal_Name: Paleoceanography
# Volume: submitted
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# Abstract: Changes in the ocean iron cycle during the Last Glacial Maximum (LGM) have been proposed to help explain the low atmospheric CO2 from this period. Previous global modeling studies, however, have only considered changes in aeolian iron fluxes, although it is known that sedimentary and hydrothermal fluxes are important iron sources for today's ocean. Here we evaluate the effect of preindustrial-to-LGM changes in atmospheric dust, sedimentary, and hydrothermal fluxes on the ocean's iron and carbon cycles in a global coupled biogeochemical circulation model. Considering variable iron solubility we find that higher dust fluxes into the ocean in the LGM increase productivity and enhance the biological pump, sequestering carbon in deep waters and lowering CO2 by 4 ppm. The effect is countered by a decrease in sedimentary release of iron due to lower sea level, which increases CO2 by 15 ppm. In an upper-limit estimation of Southern Ocean surface iron fertilization, assuming a 10 times higher solubility for this region, combined with changes in sedimentary release we find an increase in deep dissolved inorganic carbon concentrations, that could potentially reduce atmospheric CO2 by 13 ppm. A five-fold increase in hydrothermal sources of iron during the LGM may have decreased atmospheric CO2 by an additional 6 ppm. We conclude that when addressing LGM-preindustrial changes in the ocean iron cycle, not only surface but also sedimentary and hydrothermal fluxes have to be taken into account.
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# Funding_Agency
#    Funding_Agency_Name: US National Science Foundation
#    Grant: OCE-1131834, OCE-1235544
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# Site Information
# Site_Name: Global Ocean
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# Country: 
# Northernmost_Latitude: 90
# Southernmost_Latitude: -90
# Easternmost_Longitude: 180
# Westernmost_Longitude: -180
# Elevation: 
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# Data_Collection
#   Collection_Name: global ocean model Muglia17
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# Chronology_Information 
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# Variables
# Data variables follow that are preceded by "##" in columns one and two.
# Variables list, one per line, shortname-tab-longname components (9 components: what, material, error, units, seasonality, archive, detail, method, C or N for Character or Numeric data)
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# Data
# Data lines follow (have no #)
# Data line format - tab-delimited text, variable short name as header
# Missing Value: 
All data as well as supporting code and files is contained in this folder:
https://www1.ncdc.noaa.gov/pub/data/paleo/gcmoutput/muglia2017