Published February 10, 2025 | Version v1
Dataset Open

Sensitivity of atmospheric carbon dioxide to dust iron solubility during the last glacial-interglacial cycle: simulation output data

  • 1. ROR icon Pontificia Universidad Católica de Chile
  • 2. ROR icon Consejo Nacional de Investigaciones Científicas y Técnicas
  • 3. ROR icon University of Bristol
  • 4. ROR icon University of California, Riverside

Description

This dataset, archived in Output_simulations.tar.gz, contains the output of model simulations from the study "Sensitivity of atmospheric carbon dioxide to dust iron solubility during the last glacial-interglacial cycle." It is structured to facilitate access to regional (Regional) and global (Global) simulation outputs and associated data derived from various sources of aeolian dust deposition fields.

Organizational Structure:

Global Simulations: Files in this directory are derived from global models and are organized by the source of the dust deposition fields used to force the cGENIE model. The sources include:

  • Albani (Albani et al. (2014))
  • Lambert ( Lambert et al. (2015))
  • Takemura (Takemura et al. (2009))
  • Ohgaito (Ohgaito et al. (2018))
  • MIROC-ESM (Sueyoshi et al. (2013))
  • MRI-CGCM3 (Yukimoto et al. (2012))

Each sub-directory contains simulation outputs for different scaling factors (0.33, 0.67, 1.00, 2.00, 3.00) reflecting variations in dust iron solubility.

Regional Simulations: These directories are structured similarly to the global simulations but are further organized by High Nutrient, Low Chlorophyll (HNLC) regions, which include:

  • SA (South Atlantic)
  • SP (South Pacific)
  • NP (North Pacific)
  • CP (Central East Pacific)
  • NA (North Atlantic)


Files in these sub-directories detail the outcomes from simulations that apply the same scaling factors as the global simulations but focused on specific oceanic regions noted for their unique biogeochemical characteristics.

Included Files:

fields_biogem_2d.nc: Contains two-dimensional fields of ocean and atmospheric properties, formatted as NetCDF.
fields_biogem_3d.nc: Includes three-dimensional fields of ocean properties at multiple depth levels, provided as NetCDF.
biogem_series_atm_pCO2.res: Outputs the atmospheric concentration of pCO2 from each simulation, crucial for understanding the impacts of varied iron solubility on atmospheric carbon dioxide levels.

Files

Output_simulations.zip

Files (860.1 MB)

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md5:c433218f87b9b54bf269e08d3e62720a
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Additional details

Funding

Fondo Nacional de Desarrollo Científico y Tecnológico
1231682

Software

Development Status
Active

References

  • Albani, S., Mahowald, N. M., Perry, A. T., Scanza, R. A., Zender, C. S., Heavens, N. G., et al. (2014). Improved dust representation in the Community Atmosphere Model. Journal of Advances in Modeling Earth Systems, 6(3), 541–570. https://doi.org/10.1002/2013MS000279
  • Lambert, F., Tagliabue, A., Shaffer, G., Lamy, F., Winckler, G., Farias, L., et al. (2015). Dust fluxes and iron fertilization in Holocene and Last Glacial Maximum climates. Geophysical Research Letters, 42(14), 6014–6023. https://doi.org/10.1002/2015GL064250
  • Takemura, T., Egashira, M., Matsuzawa, K., Ichijo, H., O'ishi, R., & Abe-Ouchi, A. (2009). A simulation of the global distribution and radiative forcing of soil dust aerosols at the Last Glacial Maximum. Atmospheric Chemistry and Physics, 9(9), 3061-3071. https://doi.org/10.5194/acp-9-3061-2009
  • Ohgaito, R., Abe-Ouchi, A., O'ishi, R., Takemura, T., Ito, A., Hajima, T., et al. (2018). Effect of high dust amount on surface temperature during the Last Glacial Maximum: A modelling study using MIROC-ESM. Climate of the Past, 14(11), 1565-1581. https://doi.org/10.5194/cp-14-1565-2018
  • Sueyoshi, T., Ohgaito, R., Yamamoto, A., Chikamoto, M. O., Hajima, T., Okajima, H., et al. (2013). Set-up od the PMIP3 paleoclimate experiments conducted using an Earth system model, MIROC-ESM. Geoscientific Model Development, 6(3), 819-836. https://doi.org/10.5194/gmd-6-819-2013
  • Yukimoto, S., Adachi, Y., Hosaka, M., Sakami, T., Yoshimura, H., Hirabara, M., et al. (2012). A new global climate model of the Meteorological Research Institute: MRI-CGCM3 - Model description and basic performance. Journal of the Meteorological Society of Japan, 90A, 23-64. https://doi.org/10.2151/jmsj.2012-A02