Data and code for publication: "Spatially and temporally dense measurements reveal meteorological driver of atmospheric mercury variability"

This repository includes all data required to reproduce key figures from Roy et al.: Spatially and temporally dense measurements reveal meteorological driver of atmospheric mercury variability. Subdirectories are organized as follows: data Organized into four subdirectories containing all data required for reproducing results from this manuscript NADP Location of Raw NADP data. Files for four main sites (NJ30,NY06,NY20,VT99) and one supplemental site (NJ54) should be downloaded at AMNet website (https://nadp.slh.wisc.edu/networks/atmospheric-mercury-network/) The combined file required for all analysis (AMNET-NE-h.csv) is created by running site_contact.py. GCdata Contains subdirectories with output from each GEOS-Chem simulation (GC_output) and processed subsets of data (GC_processed). Additionally, Global Mercury Assessment (2018) emissions are included in this directory pblh Location of observationally derived and MERRA2 pblh data. Raw, observationally derived met data described by Zhang et al. (2020) (https://doi.org/10.1029/2020JD032803) can be downloaded at https://doi.org/10.5281/zenodo.3934378. Profiles for EWR, BDL, and MHT required for reproducing analysis. File names will be {site prefix}_20m_interp_profiles.nc In order for profiles to be readable by xarray, the following command should be executed for each site immediately after download: ncrename -v height,h_magl -v time,datetime {site prefix}_20m_interp_profiles.nc {site prefix}_20m_interp_profiles_xr.nc MERRA2 contains meteorological reanalysis data for base and nested runs. Processing scripts used to generate these files are also included in this directory (.sh) boxmod_opt Location of solution space arrays for figures 3 and 4 of main text and S5-S8 of supplemental. Scripts for generating these arrays are located at scripts/preprocess/BulkFlux.py and scripts/preprocess/BulkFlux_June_supplemental.py. scripts Organized into two subdirectories containing scripts for preprocessing data inputs and plotting/analyzing data. preprocess BulkFlux.py: Generates optimal solution space for the selected year and month. Note - will only work if data is available! BulkFlux_June_Supplemental: Generates optimal solution space for supplemental figures S5-S8 for selected year and month. Note - will only work if data is available in pointer directories. function.py: identical to function.py in figures (soft link in original directory). gc_preprocess.sh: Used to select, concatenate files from raw GC output that are then directed to data/GC_output/ gc_preprocess_STND.sh: Same as gc_preprocess.sh, except for STND simulation (needed to read parameters for hybrid sigma vertical coordinates used by GEOS-Chem) GC_UW_FT.py: script for subsampling raw GEOS-Chem output to compile concentrations within the pbl (C_PBL), upwind (C_UW), and the free troposphere (C_FT) figures function.py: Important functions required for processing data prior to plotting EST_figures.ipynb: Plots all figures in main text, along with any percentages discussed therein. EST_supplement.ipynb: Plots all supplemental figures. EST_graphabstract.ipynb: Plots map required for background of graphical abstract figure. results Destination for all figures produced for the main text and supplemental. Note: For simplicity, we have uploaded preprocessed GEOS-Chem output required to reproduce the manuscript and supplemental. Raw GEOS-Chem output is available upon request. Please reach out if you have any questions about the scripts or workflow! Eric Roy - Email: emroy (at) mit (dot) edu