Abstract
Abstract. Herein, we present a description of the Mechanism of Intermediate complexity for Modelling Iron (MIMI v1.0). 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 parameterized by an acidic interstitial aerosol reaction and a separate in-cloud aerosol 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 (iron solubility) for which observations are much more variable in space and time. Comparing model and observational data is sensitive to the definition of the average as well as 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. The iron solubility calculated at each model time step versus that calculated based on a ratio of the monthly mean values, which is routinely presented in aerosol studies and used in ocean biogeochemistry models, is on average globally one-third (34 %) higher. 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 2 to 4 compared with the previous version, which has implications for our understanding of the ocean biogeochemistry of these predominantly iron-limited ocean regions.
Highlights
Iron is an essential micronutrient for ocean primary productivity (Martin et al, 1991; Martin, 1990)
The present study improves upon the previous atmospheric iron cycle module developed for the Community Atmosphere Model (CAM) version 4 (CAM4) embedded in the Community Earth System Model (CESM); we will refer to this version as Bulk Aerosol Module (BAM)-Fe (Scanza et al, 2015, 2018)
We find that the ratio of online and offline solubility is > 1 for most of the cases when the ratio of the relative standard deviations of soluble and total iron is < 1 (Fig. S2), indicating that the differences in both methods of iron solubility calculation are sensitive to the differences in the relative size of the tails of the distribution
Summary
Iron is an essential micronutrient for ocean primary productivity (Martin et al, 1991; Martin, 1990). To incorporate the processes currently thought to be the most significant (Journet et al, 2008; Meskhidze et al, 2005; Paris et al, 2011; Shi et al, 2012) and improve model-to-observation comparisons of the soluble iron fraction, in remote ocean regions (Baker et al, 2006b; Ito, 2015; Mahowald et al, 2018; Matsui et al, 2018; Sholkovitz et al, 2012), model development has been focused on refining the atmospheric iron emission sources and subsequent atmospheric processing (Ito, 2015; Ito and Xu, 2014; Johnson and Meskhidze, 2013; Luo et al, 2008; Meskhidze et al, 2005; Myriokefalitakis et al, 2015; Scanza et al, 2018). We suggest further developments for atmospheric iron modelling and for comparing model results with sporadic observations (Sect. 5)
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