analysis.aerosol_gas_tables module

scripts.analysis.aerosol_gas_tables.Get_files(adfobj, data_dir, start_year, end_year, h_case, **kwargs)

This function retrieves the files, latitude, and longitude information in all the directories within the chosen dates.

scripts.analysis.aerosol_gas_tables.SEbudget(adfobj, dic_SE, data_dir, files, var, ext1_SE, **kwargs)

Function used for getting the data for the budget calculation. This is the chunk of code that takes the longest by far.

Example: ~70/75 mins per case for 9 years ** This is for both chemistry and aeorosl calculations

dic_SE: dictionary specyfing what variables to get. For example,

for precipitation you can define SE as:

dic_SE[‘PRECT’]={‘PRECC’+ext1_SE:8.64e7,’PRECL’+ext1_SE:8.64e7} - It means to sum the file variables “PRECC” and “PRECL”

for my arbitrary desired variable named “PRECT”

• It also has the option to apply conversion factors.

  For instance, PRECL and PRECC are in m/s. 8.64e7 is used to convernt m/s to mm/day

data_dir: string of the directory that contains the files. always end with ‘/’

files: list of the files to be read

var: string showing the variable to be extracted.

-> this will be the individual componnent, ie O3_CHMP, SOA_WDF, etc.

scripts.analysis.aerosol_gas_tables.aerosol_gas_tables(adfobj)

Calculate aerosol and gaseous budget tables

Default set of variables: change in lib/adf_variable_defaults.yaml

GAS_VARIABLES: [‘CH4’,’CH3CCL3’, ‘CO’, ‘O3’, ‘ISOP’, ‘MTERP’, ‘CH3OH’, ‘CH3COCH3’] AEROSOL_VARIABLES: [‘AOD’,’SOA’, ‘SALT’, ‘DUST’, ‘POM’, ‘BC’, ‘SO4’]

Default output for tables:

Gases:

CH4_BURDEN (Tg), CH4_CHEM_LOSS (Tg/yr), CH4_LIFETIME (years)

CH3CCL3_BURDEN (Tg), CH3CCL3_CHEM_LOSS (Tg/yr), CH3CCL3_LIFETIME (days)

CO_EMIS (Tg/yr), CO_BURDEN (Tg), CO_CHEM_LOSS (Tg/yr), CO_CHEM_PROD (Tg/yr), CO_DRYDEP (Tg/yr) CO_TDEP (Tg/yr), CO_LIFETIME (days), CO_TEND (Tg/yr)

O3_BURDEN (Tg), O3_CHEM_LOSS (Tg/yr), O3_CHEM_PROD (Tg/yr), O3_DRYDEP (Tg/yr), O3_TDEP (Tg/yr) O3_LIFETIME (days), O3_TEND (Tg/yr), O3_STE (Tg/yr)

LNOx_PROD (Tg N/yr)

ISOP_EMIS (Tg/yr), ISOP_BURDEN (Tg)

Monoterpene_EMIS (Tg/yr), Monoterpene_BURDEN (Tg)

Methanol_EMIS (Tg/yr), Methanol_BURDEN (Tg), Methanol_DRYDEP (Tg/yr), Methanol_WETDEP (Tg/yr), Methanol_TDEP (Tg/yr)

Acetone_EMIS (Tg/yr), Acetone_BURDEN (Tg), Acetone_DRYDEP (Tg/yr), Acetone_WETDEP (Tg/yr), Acetone_TDEP (Tg/yr)

Aerosols:

AOD_mean

SOA_BURDEN (Tg), SOA_CHEM_LOSS (Tg/yr), SOA_DRYDEP (Tg/yr), SOA_WETDEP (Tg/yr), SOA_GAEX (Tg/yr), SOA_LIFETIME (days)

SALT_EMIS (Tg/yr), SALT_BURDEN (Tg), SALT_DRYDEP (Tg/yr), SALT_WETDEP (Tg/yr), SALT_LIFETIME (days)

DUST_EMIS (Tg/yr), DUST_BURDEN (Tg), DUST_DRYDEP (Tg/yr), DUST_WETDEP (Tg/yr), DUST_LIFETIME (days)

POM_EMIS (Tg/yr), POM_BURDEN (Tg), POM_DRYDEP (Tg/yr), POM_WETDEP (Tg/yr), POM_LIFETIME (days)

BC_EMIS (Tg/yr), BC_BURDEN (Tg), BC_DRYDEP (Tg/yr), BC_WETDEP (Tg/yr), BC_LIFETIME (days)

SO4_EMIS_elevated (Tg S/yr), SO4_BURDEN (Tg S), SO4_DRYDEP (Tg S/yr), SO4_WETDEP (Tg S/yr), SO4_GAEX (Tg S/yr) SO4_LIFETIME (days), SO4_AQUEOUS (Tg S/yr), SO4_NUCLEATION (Tg S/yr)

List of variable names and descriptions for clarity

• ListVars: list of all available variables from given history file

• GAS_VARIABLES: list fo necessary CAM gaseous variables

• AEROSOL_VARIABLES: list fo necessary CAM aerosol variables

• AEROSOLS: list of necessary aerosols for computations

MODIFICATION HISTORY:

Behrooz Roozitalab, 02, NOV, 2022: VERSION 1.00 - Initial version

Justin Richling, 27 Nov, 2023 - updated to fit to ADF and check with old AMWG chem/aerosol tables - fixed:

• added difference bewtween cases column to tables

Behrooz Roozitalab, 8 Aug, 2024 - fixed:

• lifetime inconsitencies

• Removed redundant calculations to improve the speed

• Verified the results against the NCL script.

scripts.analysis.aerosol_gas_tables.calc_budget_data(current_var, Dic_scn_var_comp, area, trop, inside, num_yrs, duration, AEROSOLS)

Function to run through desired table values for calculations for the table entries

scripts.analysis.aerosol_gas_tables.fill_dic_SE(adfobj, dic_SE, variables, ListVars, ext1_SE, AEROSOLS, MW, AVO, gr, Mwair)

Function for dealing with conversion factors for different components and filling the main data dictionary ‘dic_SE’

Input dictionary and return updated dictionary ‘dic_SE’

Parameters:

• variables (list) –

  • list of main variables?

• ListVars (list) –

  • list of ???????

Returns:

• dic_SEdict

  • full dictionary of derived variables

• Some conversion factors need density or Layer’s pressure, that will be accounted for when reading the files.

• We convert everying to kg/m2/s or kg/m2 or kg/s, so that final Tg/yr or Tg results are consistent

scripts.analysis.aerosol_gas_tables.list_files(adfobj, directory, start_year, end_year, h_case)

This function extracts the files in the directory that are within the chosen dates and history number.

scripts.analysis.aerosol_gas_tables.make_Dic_scn_var_comp(adfobj, variables, current_dir, dic_SE, current_files, ext1_SE, AEROSOLS)

This function retrieves the files, latitude, and longitude information in all the directories within the chosen dates.

current_dir: list

• showing the directories to look for files. always end with ‘/’

current_files: list

• List of CAM history files

start_year: string

• Starting year

end_year: string

• Ending year

kwargs

ext1_SE: string

• specify if the files are for only a region, which changes to variable names. ex: if you saved files for a only a box region ($LL_lat$,$LL_lon$,$UR_lat$,$UR_lon$),

  the ‘lat’ variable will be saved as: ‘lat_$LL_lon$e_to_$UR_lon$e_$LL_lat$n_to_$UR_lat$n’ for instance: ‘lat_65e_to_91e_20n_to_32n’

returns:

• Dic_crit:

  • dictionary for critical values for current case

  Dic_scn_var_comp:

  • full dictionary of all variables and components for current case

• NOTE (The LNO is lightning NOx, which should be reported explicitly rather as CO_LNO, O3_LNO, …)

scripts.analysis.aerosol_gas_tables.make_table(adfobj, vars, chem_type, Dic_scn_var_comp, areas, trops, case_names, nicknames, durations, insides, num_yrs, AEROSOLS)

Create CSV table for aeorosols and gases, if applicable

Table includes column values of variable, case(s), difference (if applicable)

If this is a single model vs model run: 4 columns

first column: variables names, second column: test case variable values third column: baseline case variable values final column: difference of test and baseline.

If this is a model vs obs run: 2 columns

first column: variables names, second column: test case variable values

scripts.analysis.aerosol_gas_tables.set_dic_SE(ListVars, ext1_SE)

Initialize dictionary to house all the relevant tabel data