MARFA

Table of Contents

• Overview
• Features
• Usage scenarious and limitations
• Prerequisites
• Quick Start Instructions
• Command Line Parameters
• Atmospheric Profile File Structure
• Output PT-table structure
• Spectral Databases
• χ-factors
• Other spectroscopic data
  • TIPS
  • Molar masses
• Performance Estimations
• Introducing Custom Features
  • Custom χ-factors
  • Custom line shapes
• Troubleshooting
• License
• References

Overview

MARFA (Molecular atmospheric Absorption with Rapid and Flexible Analysis) is a versatile tool designed to calculate volume absorption coefficients or monochromatic absorption cross-sections using initial spectroscopic data from spectral lines databases and atmospheric data from an external file. With MARFA, users can generate absorption PT-tables (look-up tables) for each atmospheric level simultaneously in seconds time. These PT-tables are produced in a binary format (unformatted files), making them easily integrable into radiative transfer codes. Users have a high degree of control, with the ability to set line cut-off parameter and introduce custom spectroscopic features. Originally developed to facilitate the modeling of radiative transfer in Venus's atmosphere, MARFA's flexible design allows it to be adapted to a wide range of spectroscopic and atmospheric scenarios.

In addition to using and contributing to the source code, it is recommended to interact with the web interface of the tool to better understand its capabilities. The web interface can be accessed at:

Features

• Spectral coverage: Applicable for high-resolution line-by-line calculations in far-, mid-, near-IR and visible spectral regions. It roughly covers 10-20000 cm^-1 range.

• Efficient Line-by-Line Technique: Utilizes an effective interpolation method [Fomin, 1995] with nine grids to accelerate the summation of contributions from a large number of spectral lines. Nine grids are optimal for handling large cut-off conditions.

• Atmospheric Profile Handling: Computes output absorption spectra for all atmospheric levels in a single runtime.

• Line Databases Support: Includes adapted HITRAN-2016 databases for CO₂ and H₂O within the source code. Other spectral databases can be incorporated manually by processing them into the required format.

• Line Shapes Support: Supports standard line shapes, including Doppler, Lorentz, and Voigt (default). Additional line shapes can be manually added by following given instructions.

• Line Wings Corrections: Implements various χ-factors to accommodate sub-Lorentzian behavior of spectral line wings of CO₂. Custom χ-factors can be manually added.

• PT-Tables Generation: Produces spectra as unformatted files in PT-format, directly integrable into radiative transfer schemes.

• Additional Tools: Provides various scripts for plotting and data processing, facilitating validation and the integration of new data.

Usage Scenarios and Limitations

The codes are well-suited for calculating absorption features in scenarios where spectral and atmospheric data are uncertain, such as for terrestrial planets of Solar System (excluding Earth) or exoplanets. They can efficiently handle long cut-off conditions without a significant increase in computational time. Additionally, the codes are designed to allow users to introduce their own functionality. Therefore, if you have your own functions but lack a computational core, you can use these codes to calculate absorption features over a wide range of input values.

Important notes:

• Calculations are performed for one molecular species across all atmospheric levels in a single runtime.

• The current resolution at which PT tables are calculated is fixed and determined by the Doppler half-width in the far-IR. The resolution is deltaWV/NT = 10/20480 ≈ 5 * 10^-4cm^-1. Such resolution is excessive for calculations in the near-IR. A dynamic resolution based on the inspected spectral interval will soon be implemented, allowing it to be set as user input.

• Continuum absorption is not accounted for in this project. This functionality may be added later with contributions from new collaborators.

• The microwave region can also be considered, but certain adjustments must be made, including applying the Van-Vleck-Weisskopf correction and addressing the issue of "negative wavenumbers" in the line-by-line algorithm.

Prerequisites

To build and run the source code on your machine, you need to have GFortran (GNU Fortran compiler) and the Fortran Package Manager (fpm) installed. The tool is compatible with macOS, Linux and Windows operating systems. However, installation might be challenging for Windows unexperienced users.

Fortran compiler: Gfortran

For installing the gfortran you can use GNU Fortran website or use your system's package manager.

Other compilers:

Other fortran compilers were not tested and checked.

fpm

Installation instructions ara available on the official website or on the fpm github page.

Python3

Python3 is mainly needed for running the plotting scripts and converting binary files to a human readable format.

Quick start instructions

Clone the repository and navigate to the project directory:

git clone https://github.com/Razumovskyy/MARFA
cd MARFA

Build the project

fpm build

Install python packages

In python virtual environment (recommended) run:

pip install -r requirements.txt

Choose the atmospheric file

For a quick start you can choose one of the default atmospheric profiles located in the data/Atmospheres folder. For example data/Atmospheres/VenusCO2.dat which reflects the carbon dioxide profile in the Venus nightside atmosphere.

Run the project with some command line parameters

For example, to calculate absorption coefficient of carbon dioxide in typical Venus's nightside atmosphere in 4000-4100 cm^-1:

fpm run marfa -- CO2 4000 4100 H16 125 tonkov VAC VenusCO2.dat

Here is a breakdown of the command-line arguments (for more detailed explanation of parameters see this section):

• CO2: The input molecule
• 4000 and 4100: The boundaries of the spectral interval of interest (in cm^-1)
• H16: basefilename for the spectral database
• 125: The line cut-off condition (in cm^-1)
• tonkov: The name of the chi-factor correction used for CO₂.
• VAC Specifies the target calculated value as volume absorption coefficient.
• VenusCO2.dat The atmospheric profile file to read pressure, tempareature and molecular density data from.

After running this command, the PT-tables for each level from the VenusCO2.dat file will be generated in the output/ptTables folder. The output files are created in a binary format (unformatted files or so called direct access files) to facilitate faster integration with radiative transfer models.

Converting to a human-readable output and plotting

To convert a specific PT-table file to a human-readable format and plot the spectra, use the Python script located in the scripts directory. Execute the following command:

python scripts/postprocess.py --v1 4000 --v2 4100 --level 40 --resolution medium --plot

You can find the file containing human-readable data in the processedData folder, named according to the corresponding format, e.g., output/processedData/CO2_40_VAC_4000-4100.dat. Below is an example of the file’s content, which includes log information and data: the first column represents wavenumbers [cm^-1], and the second column shows the log₁₀ of the volume absorption coefficient (or cross-section if targetValue is set to VAC).

# Input Molecule: CO2
# Cut Off: 125
# Chi Factor Function Name: tonkov
# Target Value: VAC
# Atmospheric Profile File: VenusCO2.dat
# V1: 4000.0 cm-1
# V2: 4100.0 cm-1
# Resolution: medium
# Level Number: 40
               1       20470
     4000.00000        -1.4572563
     4000.00488        -1.4536923
     4000.00977        -1.4693524
     4000.01465        -1.4902035
      ...
     4099.98535        -5.6071868
     4099.99023        -5.5950541

If the --plot flag is enabled, a plot of the data set is generated and saved to the plots directory with the same name, for example: output/plots/CO2_40_VAC_4000-4100.png. Here’s an example:

The V1 and V2 values do not necessarily need to match the initial boundaries Vstart and Vend used to calculate the PT-table. Instead, you can examine a narrower interval with higher resolution to gain more detailed insights:

python scripts/postprocess.py --v1 4020 --v2 4022 --level 40 --resolution high --plot

Command line parameters

Parameters for fpm run marfa command

Required syntax: fpm run marfa -- arg1 arg2 ... arg8 <arg9>

№	Argument	Description	Required	Allowed values
1	inputMolecule	Species to calculate absorption features of.	Yes	First 12 molecules from the HITRAN molecule metadata list. Molecule must be provided in a text form, e.g. CO2, CH4, O2
2	Vstart	Left boundary of the spectral interval	Yes	roughly 10-20000 cm-1, but should align with database you take data from
3	Vend	Right boundary of the spectral interval	Yes	roughly 10-20000 cm-1, but should align with database you take data from
4	databaseSlug	Title of the spectral database to be used. For more details see the spectral databases section	Yes	Base file names from the data/databases directory
5	cutOff	Distance from the center of the line from which absorption from this line is neglected	Yes	recommended values: 10-500 cm-1
6	χ-factor	χ-factor function name. Currently only CO2 corrections are available. For more details see χ-factors section	Yes	Titles of functions in the ChiFactors.f90 module. Provide none to avoid using correction
7	targetValue	Absorption feature to be written in the PT-table: volume absorption coefficient (km-1) or absorption cross-section (cm2/mol)	Yes	VAC (volume absorption coefficient), ACS (absorption cross-section)
8	Atmosphere file name	Atmospheric file name, located in the data/Atmospheres directory. For the format of the file see: Atmospheric Profile File Structure	Yes	file names from the data/Atmospheres directory
9	uuid	ID for user request	No	Optional and is needed for the web-version of the program

Examples:

fpm run marfa -- CO2 660 670 H16 25 tonkov ACS VenusCO2.dat
fpm run marfa -- H2O 10 3000 H16 250 none VAC VenusH2O.dat

Parameters for python scripts/postprocess.py command

Argument	Description	Required	Allowed values
subdirectory	Name of the PT-table directory	No, default value is where PT-tables from the latest run are stored. See the output/ptTables/latest_run.txt file	Any
v1	Start wavenumber from which you want to get processed data	Yes	Vstart < v1 < v2 < Vend
v2	End wavenumber to which you want to get processed data	Yes	Vstart < v1 < v2 < Vend
level	Atmospheric level at which you want to access data. Essentially means, that you access to the file <level>.ptbin	Yes	Normally from 1 to 100 (but see your atmospheric file)
resolution	Resolution at which you want to obtain the data. If you consider large intervals, it is not recommeded to use high resolution	Yes	high (4.8E-4cm-1), medium (4.8E-3cm-1), coarse(4.8E-2cm-1)
plot	Plot the data you postprocessed	No	Provide just a flag
uuid	Needed only for the web app. If set, subdirectory is ignored and data saved inside users folder	No	ID of a request

Examples:

python scripts/postprocess.py --v1 4032 --v2 4038 --level 40 --resolution high --plot
python scripts/posprocess.py --v1 10 --v2 3000 --level 50 --resolution coarse
python scripts/postprocess.py directory_name --v1 2500 --v2 --2550 --level 30 --resolution medium

Atmospheric profile file structure

To correctly run the MARFA code, the atmospheric file must adhere to a specific format and be placed in the data/Atmospheres/ directory. Below is an example of the required format:

# Atmospheric file example (Haus2015) CO2                                                                     
81
     0.000 0.90918E+02  733.00  0.8694E+26
     2.000 0.80059E+02  717.00  0.7851E+26
     4.000 0.70286E+02  701.00  0.7075E+26
     6.000 0.61599E+02  685.00  0.6366E+26

File Format Breakdown

1. Header (First Line):

   • Can be used for keeping infof about atmospheric characteristics, such as planet, authors of the source paper, and gas species. This header is ignored during runtime.
   • Example: # Atmospheric file example (VIRA2) CO2

2. Number of Levels (Second Line):

   • Contains a single number N representing the number of atmospheric levels.
   • Example: 81 (indicating 81 levels).

3. Atmospheric Data (Next N Lines):

   • Each line contains level-dependent data in four columns:

     • Column 1: Height [km]
     • Column 2: Total pressure [atm]
     • Column 3: Temperature [K]
     • Column 4: Number density [mol/(cm²*km)] of the given species

   • Example (Venus lower atmosphere):

      0.000 0.90918E+02  733.00  0.8694E+26
      2.000 0.80059E+02  717.00  0.7851E+26
      4.000 0.70286E+02  701.00  0.7075E+26
      6.000 0.61599E+02  685.00  0.6366E+26
     

Important Notes

• Number of levels: The recommended number of atmospheric levels is around 100. It is not advised to use atmospheres with more than 200 levels, as this will result in extended computational times, reducing the efficiency of the codes.

• Units:

  • The data uses [km] for height to ensure the total absorption coefficient is in [km^-1].

• Density Calculation:

  • It is recommended to provide the number density in [mol/(cm²*km)] rather than [mol/cm³]. This is because the density is also used in calculating the partial pressure of species (for Lorentz HWHM), where the units are fixed. Refer to the pSelf calculation in the app/main.f90 file for more details.

• Directory Placement:

  • Ensure the atmospheric file is stored in the data/Atmospheres/ directory to be recognized by the MARFA code.

Output PT-table file

General information

• PT-table files are generated and placed somwhere inside output/ptTables directory.
• One PT-table file corresponds to one atmospheric level.
• Name of the PT-table file contains only level number, e.g. 1__.ptbin, 65_.ptbin.
• PT-table file has an extention .ptbin.

PT-file structure

The file consists of records with data, which could be directly accessed.

• Each record contains an array RK of high-resolution absorption data: either cross-section or absorption coefficient
• Each record contains data about 10cm^-1 interval (deltaWV parameter in the code).
• Resolution of the data is defined by: deltaWV/NT = 10/20480 ≈ 4.8828×10^-4cm^-1.
• Relation between wavenumber of interest and record number: record_number = int(WV/10). For example, if you want to know the value of absorption at 7560 cm^-1, than you need to access the 756 record.
• Each record is of length NT * 4 = 20481 * 4 bytes = 81924 bytes = 81,924 kilobytes

Schematic python code snippet for accessing data from this file:

            import numpy as np

            # assuming you need to know absorption in 756 cm^-1
            V1 = 756

            # determining record number where this data stored
            recrod_number = int(V1 / 10.0)

            # number of values in one record
            NT = 20481

            # record length in bytes
            record_length = NT * 4

            with open('1__.ptbin', 'rb') as f:
              # start reading from record with record number "record_number"
              seek_position = (record_number-1) * record_length
              f.seek(seek_position)
  
              # read one record
              record_bytes = f.read(record_length)
  
              # Unpack an array of data using little-endian
              RK = np.frombuffer(record_bytes, dtype='<f4')
  
              # Converting data to float32 format (optional)
              RK = RK.astype(np.float32)

Note

There is a current minor vulnerabilty in the code regarding record numbers, which result in excess of PT-files size with increasing wavenumber. For example, you calculated PT-table for 6500-7000 cm^-1 spectral interval. First non-zero data will populate 650th record, leaving 1-649 records unpopulated. This excess of records may require additional and unnecessary storage. This issue would be resolved soon. But because of it, PT-table caculated for 100-110 cm^-1 will be much smaller in size than one calculated for 6500-6510 cm^-1. There is currently an open issue on it.

Spectral databases

To calculate absorption cross-sections, line-by-line approach is used which requires a presence of spectral database files. These files must match a specific format, follow a naming rule and be placed in the data/databases directory. Normally, bank of spectral parameters is compiled in a .par by means of HITRAN web site or from other sources.

Before running marfa, to speed up reading operations, .par file must be preprocessed into unformatted file (direct access file). The source code provides built-in functionality for users to perform this preprocessing.

Additionaly, the codebase contains three files already preprocessed to the required format: H16.01, H16.02 and H16.09. These files are direct access files with all necessary spectral data for three molecules (according to HITRAN convention, also see get_species_code subroutine in main.f90 file): 01 - H₂O, 02 - CO₂, 09 - SO₂. These files are produced from initial .par files generated from the HITRAN 2016 database.

When running marfa, database slug (base filename) must be provided as a command line argument, so to make the executable aware of where to access line-by-line data from. For example:

fpm run marfa -- H2O 1200 1600 H16 <other parameters>

This command implies that the executable will try to access spectral data for the file: /data/databases/H16.01.

Required parameters

The titles are taken from HITRAN web site for clarity and compatiblity. In brackets the variable name in the codebase:

• (lineWV) The wavenumber of the spectral line transition (cm^-1) in vacuum
• (refLineIntensity) The spectral line intensity (cm^-1/(molecule * cm^-2)) at reference temperature T = 296 K
• (gammaForeign) The air-broadened half width at half maximum (HWHM) (cm⁻¹/atm) at reference temperature T = 296K and reference pressure p = 1 atm.
• (gammaSelf) The self-broadened half width at half maximum (HWHM) (cm⁻¹/atm) at reference temperature T = 296K and reference pressure p = 1 atm.
• (lineLowerState) The lower-state energy of the transition (cm^-1)
• (foreignTempCoeff) The coefficient of the temperature dependence of the air-broadened half width
• (jointMolIso) CUSTOM: Integer number containing information about both Mol (The molecular species identification (ID) number) and Iso (The isotopologue ID number).
• (deltaForeign) The pressure shift (cm^-1/atm) at reference temperature T = 296 K and pressure p = 1 atm of the line position with respect to the vacuum transition wavenumber.

Note: jointMolIso is customized because of linear structure of the files with TIPS and molecular mass data (linear on isotope numbers). In the app/processParFile.f90 file there is an N_MOL_ISO array which is needed for smooth access to the isotope by one number. I address you to check this implementation there and in those parts of code where TIPS and molecular masses are accessed.

Preprocessing user's .par file

For that you can use app/processParFile.f90 program, for example:

fpm run processParFile -- HNO3 HITRAN2020 path/to/file.par

After running this command HITRAN2020.12 file will be saved in the data/databases directory and could be accessed when running the main program:

fpm run marfa -- HNO3 <VStart> <VEnd> HITRAN2020 <other parameters>

Structure of the database files

Each direct access file in the data/databases folder has the following structure:

• File consists of records, each record contains data related to one spectral line
• Each record contains required parameters from the above section.
• Parameter LineWV is stored in double precision, 8 bytes are required for it. For other 7 parameters, 4 bytes are allocated apiece. Thus, the total length of a record is 36 bytes.

χ-factors

There is an indication that the far wings of spectral lines tend to diverge from expected Lorentzian or Voigt behavior. To address that χ‌-factor could be applied.

In MARFA code currently there are several χ‌-factors implemented, which describe sub-Lorentzian behavior of CO₂ rotational lines. They could be found in the ChiFactors.f90 module. These corrections are primarilly used for Venus atmosphere conditions. Below is a reference to the scientific papers from which the analytical expressions were derived (see References section for more details):

χ-factor	Reference
tonkov	Tonkov et al. (1996)
pollack	Pollack et al. (1993)
perrin	Perrin and Hartmann (1989)

The χ-factors dataset is intended to be expanded through the effort from other contributors.

Other spectral or molecular data

TIPS

Total internal partition sums (TIPS) are needed for obtaining temperature-dependent spectral intensities. How the TIPS are implemented in MARFA:

• TIPS values could be found in the file inside data/TIPS/ directory
• TIPS data are taken from Gamache work (Gamache 2017, see References)
• Data are available for first 74 isotopologues (first 12 molecules: H2O, CO2, O3, N2O, CO, CH4, O2, NO, SO2, NO2, NH3, HNO3)
• Covered temperature range is 20 - 1000 K
• For chosen isotope number TIPS as function of temperature can be accessed through the function: TIPSofT located in the Spectroscopy.f90 module.

Outlook

• I plan to add recent TIPS (Gamache et al. 2021, see References)
• It might be better to organize input TIPS as en external subroutine based on Gamache's code Fortran or Python: TIPS_2021_v1p0.for, BD_TIPS_2021_v1p0.for or TIPS_2021_v1p0.py. I will soon return to it.

Molecluar weights

Molecular weights are available in the MolarMasses.f90 module. WISO array contains weights data for 124 isotopolouges of first 42 molecules according to HITRAN molecules numbering system.

Performance estimations

Execution time at one atmospheric level largerly depends on number of spectral lines and line cut-off condition. Here are some benchmarks for Apple M1 chip:

species	spectral interval (cm-1)	number of lines	cut off condition (cm-1)	execution time (s)
CO2	4000 - 4100		25	0.06
CO2	4000 - 4100		250	0.24
CO2	10 - 3000		25	4.08
CO2	10 - 3000		250	25.2

Loop over atmospheric levels is currently not parallelized but I plan to do it with OpenMP in near time. Thus, currently the time of processing a full atmospheric profile is linear to number of levels.

Additional room for optimization might be organized with increasing effectiveness of Voigt function estimation algorithm and lastly negliecting weak lines.

Introducing custom features

Custom χ-factors

To add custom χ-factor function follow the steps:

1. Write a fortran function with χ-factor. Optionally it might be pressure or tempreature dependent. You can use pressure and temperature parameters inside a function.
2. Put this function at the end of the chiFactors module
3. Add new case to the select-case clause in the fetchChiFactorFunction() in the ChiFactors.f90 module.
4. Check that in the LBL.f90 module chiCorrectedLorentz line shape function is used for the line wing description. There must be a line, like: shapeFuncPtr => chiCorrectedLorentz.

Note: Your χ-factor function must match the abstract interface for the χ-factor function: chiFactorFuncPtr (see ShapeFuncInterface module). Normally, it means that the function takes only one argument - distance from the line center in wavenumber in double precision and return only one value of real type. Check how the inputs and outputs are organized in predefined χ-factors functions and adjust accordingly.

Example:

    real function myChiFactor(X)
    real(kind=DP), intent(in) :: X
        
        myChiFactor = 1. ! default value of the chi-factor
        if (abs(X) > 4.) then
            if (abs(X) <= 125.) then
                myChiFactor = 1.24 * exp(-0.017*abs(X))
            else
                myChiFactor = 0.31 * exp(-0.036*abs(X))
            end if
        end if
        return
    end function myChiFactor

    subroutine fetchChiFactorFunction()
        select case(trim(adjustl(chiFactorFuncName)))
        case ('none')
            chiFactorFuncPtr => noneChi
        case ('tonkov')
            chiFactorFuncPtr => tonkov
        case ('pollack')
            chiFactorFuncPtr => pollack
        case ('perrin')
            chiFactorFuncPtr => perrin
        ! ADD YOUR CHI-FACTOR HERE:
        case ('myChiFactor')
            chiFactorFuncPtr => myChiFactor
        end select
    end subroutine fetchChiFactorFunction

Custom line shapes (for advanced usage)

Currently in the Shapes module only standard line shapes are introduced: lorentz, doppler, voigt, chiCorrectedLorentz (Lorentz shape with wings corrected with χ-factor) and correctedDoppler (auxillary function, used only in Voigt shape calculation). To add your own line shape, you need to:

1. Provide a Fortran function of a custom line shape to the Shapes module.
2. Go to the LBL module and assign shapeFuncPtr pointer to your line shape instead of the predefined shape.
3. Adjust the logic of the choice of line shape accordingly. This is required only for introducing "non-standard" (not Voigt, Lorentz or Doppler) line shapes.

Note 1: Essentialy, line shape function in Shapes module returns individual cross-section, because multiplication of line profile function to line intensity is included inside the function. Thus, multiplication on the temperature-dependent intensity must be provided. You can use predefined line intensity function intensityOfT in Spectroscopy module. Example:

    real function myLineShape(X)
        real(kind=DP), intent(in) :: X

        ! ... YOUR LOGIC HERE

        myLineShape = myLineShape * intensityOfT(temperature) ! THIS LINE MUST BE PROVIDED
    end function myLineShape

If you want to use your own intensities, you must add new intensity function to the Spectroscopy module and refer to it.

Note 2: Your function must match the abstract interface for the line shape (see ShapeFuncInterface module). Normally, it means that the function takes only one argument - distance from the line center in wavenumber in double precision and return only one value of real type. Check how the inputs and outputs are organized in predefined line shape functions and adjust accordingly.

Example 1

If you want to provide your own Voigt line shape, then it is the most straightforward.

1. Add your function to the Shapes module.
2. Go to src/LBL.f90 module and substitute code lines with shapeFuncPtr => voigt with e.g. shapeFuncPtr => myVoigt.

Example 2

If you want to introduce non-standard (not Voigt, Loretntz, Doppler) line shapes, then you additionally need to adjust the logic in LBL module yourself. In the current state, line shape function for calculation is a specific spectral point depends on how far this point from the center of the spectral line. If it is far enough, the lorentz or chiCorrectedLorentz, in the middle region voigt is applied and in the close vicinity of the line center doppler is used. If you want to introduce your own line shape you need to specify where it will be estimated, so adjust this pice of code in LBL module:

if (shapePrevailFactor > BOUNDL) then
                ! Region utilizing Lorentz or chiCorrectedLorentz shape
                if (shiftedLineWV < startDeltaWV) then
                    shapeFuncPtr => Lorentz
                    call leftLBL(startDeltaWV, shiftedLineWV, shapeFuncPtr) 
                ! rest of the logic ...
else
                if (shapePrevailFactor > BOUNDD) then
                ! Region utilizing Voigt shape
                    if (shiftedLineWV < startDeltaWV) then
                        shapeFuncPtr => voigt
                        call leftLBL(startDeltaWV, shiftedLineWV, shapeFuncPtr)
                    ! rest of the logic ... 
                else
                ! Region utilizing Doppler shape
                    if (shiftedLineWV < startDeltaWV ) then
                        shapeFuncPtr => doppler
                        call leftLBL(startDeltaWV, shiftedLineWV, shapeFuncPtr)
                        ! rest of the logic ...
                end if
end if

Troubleshooting

Feedback is awaited to populate this section. Most potential issues, such as invalid user inputs, in the Fortran source code and Python scripts are handled with clear error messages to facilitate troubleshooting.

If you refer to the χ-factor function which doesn't exist, then the Segmentation Fault error will be raised during runtime. This would be fixed later.

How to cite this work

License

This project is licensed under the MIT License. See the LICENSE file for more details.

References

• Fomin, B. A. Effective interpolation technique for line-by-line calculations of radiation absorption in gases. Journal of Quantitative Spectroscopy and Radiative Transfer 53.6 (1995): 663-669.
• Tonkov, M. V., et al. Measurements and empirical modeling of pure CO₂ absorption in the 2.3-μm region at room temperature: far wings, allowed and collision-induced bands. Applied optics 35.24 (1996): 4863-4870.
• Pollack, James B., et al. Near-infrared light from Venus' nightside: A spectroscopic analysis. Icarus 103.1 (1993): 1-42.
• Perrin, M. Y., and J. M. Hartmann. Temperature-dependent measurements and modeling of absorption by CO₂-N₂ mixtures in the far line-wings of the 4.3 μm CO₂ band. Journal of Quantitative Spectroscopy and Radiative Transfer 42.4 (1989): 311-317.
• Gamache, Robert R., et al. Total internal partition sums for 166 isotopologues of 51 molecules important in planetary atmospheres: Application to HITRAN2016 and beyond.
• Gamache, Robert R., et al. Total internal partition sums for the HITRAN2020 database. Journal of Quantitative Spectroscopy and Radiative Transfer 271 (2021): 107713.
• Gordon, Iouli E., et al. The HITRAN2016 molecular spectroscopic database. Journal of quantitative spectroscopy and radiative transfer 203 (2017): 3-69. Journal of Quantitative Spectroscopy and Radiative Transfer 203 (2017): 70-87.
• I. E. Gordon, L. S. Rothman, R. J. Hargreaves, R. Hashemi, E. V. Karlovets, F. M. Skinner, et al., The HITRAN2020 molecular spectroscopic database, J. Quant. Spectrosc. Radiat. Transfer 277, 107949 (2022). [doi:10.1016/j.jqsrt.2021.107949]