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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/gmd-2019-84
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-2019-84
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Development and technical paper 06 May 2019

Development and technical paper | 06 May 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Geoscientific Model Development (GMD).

Improved methodologies for Earth system modelling of atmospheric soluble iron and observation comparisons using the Mechanism of Intermediate complexity for Modelling Iron (MIMI v.1.0)

Douglas S. Hamilton1, Rachel A. Scanza2, Yan Feng3, Joe Guinness4, Jasper F. Kok5, Longlei Li1, Xiaohong Liu6, Sagar D. Rathod7, Jessica S. Wan1, Mingxuan Wu6, and Natalie M. Mahowald1 Douglas S. Hamilton et al.
  • 1Department of Earth and Atmospheric Science, Cornell University, Ithaca, NY, USA
  • 2Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland, Washington, USA
  • 3Environmental Science Division, Argonne National Laboratory, Argonne, IL, USA
  • 4Department of Statistics and Data Science, Cornell University, Ithaca, NY, USA
  • 5Department of Atmospheric and Oceanic Sciences, University of California, Los Angeles, CA 90095, USA
  • 6Department of Atmospheric Science, University of Wyoming, Laramie, WY, USA
  • 7Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA

Abstract. Herein, we present the description of the Mechanism of Intermediate complexity for Modelling Iron (MIMI). This iron processing module was developed for use within Earth system models and has been updated within a modal aerosol framework from the original implementation in a bulk aerosol model. MIMI simulates the emission and atmospheric processing of two main sources of iron in aerosol prior to deposition: mineral dust and combustion processes. Atmospheric dissolution of insoluble to soluble iron is parametrized by an acidic interstitial reaction and a separate in-cloud reaction scheme based on observations of enhanced aerosol iron solubility in the presence of oxalate. Updates include a more comprehensive treatment of combustion iron emissions, improvements to the iron dissolution scheme, and an improved physical dust mobilization scheme. An extensive dataset consisting predominantly of cruise-based observations was compiled to compare to the model. The annual mean modelled concentration of surface-level total iron compared well with observations, but less so in the soluble fraction where observations are much more variable in space and time. Comparing model and observational data is sensitive to the definition of the average and the temporal and spatial range over which it is calculated. Through statistical analysis and examples, we show that a median or log-normal distribution is preferred when comparing with soluble iron observations. We redefined ocean deposition regions based on dominant iron emission sources and found that the daily variability in soluble iron simulated by MIMI was larger than that of previous model simulations. MIMI simulated a general increase in soluble iron deposition to Southern Hemisphere oceans by a factor of two to four compared with the previous version, which has implications for our understanding of the ocean biogeochemistry of these predominantly iron limited ocean regions.

Douglas S. Hamilton et al.
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Short summary
MIMI 1.0 has been designed for use within Earth System Models to simulate the emission, atmospheric processing and deposition of iron and its soluble fraction. Understanding the iron cycle is important due to its role as an essential micro-nutrient for ocean phytoplankton and its supply limits primary productivity in many of the worlds oceans. Human activity has perturbed the iron cycle and MIMI is capable of diagnosing many of these impacts, and hence is important for future climate studies.
MIMI 1.0 has been designed for use within Earth System Models to simulate the emission,...
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