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Data Brief
Data Brief
Data in Brief
2352-3409
Elsevier

S2352-3409(24)00831-X
10.1016/j.dib.2024.110867
110867
Data Article
Infrared radiative transfer dataset: Comparisons of HITRAN2020, HITRAN2016, and MT_CKD versions 3.2 & 4.1.1 across five model atmospheres
Gava Maria Lívia L.M. maria.gava@inpe.br
⁎
Costa Simone M.S.
Sena Caio Atila P.
Satellite and Meteorological Sensors Division (DISSM), National Institute for Space Research, Rodovia Presidente Dutra, Km 40, Cachoeira Paulista, 12630-000 SP, Brazil
⁎ Corresponding author. maria.gava@inpe.br
24 8 2024
12 2024
24 8 2024
57 1108678 5 2024
25 7 2024
19 8 2024
© 2024 The Author(s)
2024
https://creativecommons.org/licenses/by-nc/4.0/ This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
This dataset presents the outputs of a series of experiments conducted varying combinations of two versions of the High Resolution Transmission (HITRAN) database (2016 and 2020) and two versions of the MT_CKD water vapor (WV) continuum model (3.2 and 4.1.1) across five distinct model atmospheres. The primary objective of compiling this dataset was to assess the impacts of updated spectroscopic parameters and water vapor continuum models on atmospheric radiative transfer calculations. The line-by-line calculations were performed by the Reference Foward Model (RFM). Key atmospheric gases, namely H2O, CO2, O3, CH4, CO, N2O, and O2, are prescribed at each atmospheric model. The dataset includes calculations with all gases present as well as experiments removing individual gases (specifically, CO2, O3, and H2O). It gathers upward and downward radiation fluxes, and cooling rates. The dataset is available in a compressed .tar file format, where each file contains 880 individual text files representing specific atmospheric heights. This collection is designed to facilitate further research in atmospheric science, particularly for validating other radiative transfer models and improving the understanding of atmospheric energy dynamics.

Keywords

Downward fluxes
Upward fluxes
Cooling rates
Line-by-line calculations
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pmcSpecifications TableSubject	Atmospheric science, Radiation,	
Specific subject area	Radiative transfer calculations	
Type of data	Raw data: Outputs from RFM in plain text format.	
Data collection	The atmospheric profiles used as input for the RFM calculations are from [6], and were made available at https://github.com/livialmg/HITRAN_MT_CKD_IR_calculations/. HITRAN 2020 is available at https://hitran.org/lbl/, and HITRAN 2016 is from https://www.spectralcalc.com/spectral_browser/db_intensity.php.	
Data source location	National Institute for Space Research
Cachoeira Paulista, São Paulo
Brazil	
Data accessibility	Repository name: Zenodo.
Data identification number: 10.5281/zenodo.11122536
Direct URL to data: https://zenodo.org/records/11122536 [1]	
Related research article	[2] Gava, M. L. L.M.; Costa, S. M. S.; Sena, C. A. P. The effects of changes in HITRAN and the water vapor continuum model on infrared radiative transfer calculations and remote sensing applications. J Quant Spectrosc Radiat Transfer, 322(2024), Article 109025.	

1 Value of the Data

• Line-by-line calculations serve as a benchmark for evaluating the performance of other radiative transfer models and approximations. By comparing model results against line-by-line simulations provided in this dataset, researchers can assess the accuracy and reliability of alternative methods and identify areas for improvement.

• The utilization of various atmospheric models within this database facilitates a comprehensive exploration of the impacts of different spectroscopic parameters and water vapor continuum models across diverse atmospheric conditions.

• The dataset includes experiments conducted with and without the approximation of Planck function (B) varying linearly through the layer with optical depth, providing an opportunity to evaluate the impact of this consideration on atmospheric fluxes. By comparing results from experiments with and without this approximation, researchers can assess how the treatment of B linearization affects radiative fluxes at various levels of the atmosphere, including the top of the atmosphere (TOA) and the surface.

• This dataset presents outputs from experiments performed removing a key gas at the time, which offers the opportunity to evaluate greenhouse effects under the new spectroscopic parameters. The high spectral resolution of the outputs allows this analysis to be performed concerning specific spectral areas of interest.

2 Background

For an accurate representation of atmospheric radiative transfer, precise spectroscopic parameters are of utmost importance. Equally critical is the correct representation of atmospheric opacity attributed to the WV continuum. The HITRAN and MT_CKD WV continuum models have been the primary sources for these aspects within the atmospheric research community [3]. These tools are frequently updated in response to theoretical advancements and new experimental measurements [4]. The latest versions of HITRAN and MT_CKD are respectively the 2020 and 4.1.1 versions.

In light of these updates, this dataset was compiled to evaluate the impacts of the latest versions of HITRAN and MT_CKD on radiative transfer calculations. By systematically comparing results obtained using different versions of these tools, researchers can assess how updates in spectroscopic parameters and WV continuum representations influence radiative transfer processes. This dataset adds value by providing a comprehensive assessment of the implications of updated sources on atmospheric radiative transfer, thus informing future model developments and enhancing our understanding of Earth's atmospheric radiation budget.

3 Data Description

The dataset consists of upward and downward radiation fluxes in units of W.m−2.(cm-1)−1 and cooling rates in units of K.day−1.(cm−1)−1. It is structured according to similar experiments set up, which are compressed into a single .tar file. The filename convention is as follows:var_profile_HITRAN_lev_LLLLL_mtckd{_woflag}.tar

where var corresponds to the variable output and flag relates to the experiment set up. The possible inputs to the tar filenames are given in Table 1.Table 1 Description of the possible inputs to tar file names.

Table 1:var (3 digits)	flag (3 digits)	
“olr”: upward radiation flux	“H2O”: experiment removing water vapor.	
“dlr”: downward radiation flux	“CO2”: experiment removing carbon dioxide.	
“coo”: cooling rates	“O3”: experiment removing ozone.	
	“BFX”: experiment without the “B linear to optical depth” approximation.	
	None: experiment with the “B linear to optical depth” approximation.	

Each tar file consists of 880 plain text files, which corresponds to RFM outputs to specific atmospheric height. The text files name convention is as follows:var_profile_HITRAN_lev_LLLLL_mtckd{_woflag}.txt

Where profile corresponds to the atmospheric model, HITRAN and mtckd are the HITRAN and MT_CKD versions used (i.e. 2016 or 2020 and v3.2 or v4.1.1), respectively, and LLLLL is the height of the output. var and flag are the same as in the tar files. The possible inputs to the text filenames are given in Table 2.Table 2 Description of possible inputs to text file names.

Table 2:profile (3 digits)	HITRAN (4 digits)	LLLLL (5 digits)	mtckd (3 digits)	
“tro”: Tropical	2016	Output height in meters. 5 digits. Ranging from the surface (i.e. Surface (“00000”) to 95 km (i.e. “95000”)	“3.2”: v3.2	
“mls”: Mid Latitude Summer	2020		“4.1”: v4.1.1	
“mlw”: Mid Latitude Winter				
“sas”: Sub Artic Summer				
“saw”: Sub Artic Winter				

The text files can be open in any text editor. It consists of five lines. The first three lines are the header. The fourth line indicates the number of points of the output, the lower wavenumber limit, the resolution, the upper wavenumber limit, all in cm−1, and the RFM label. Fig. 1 gives an example of the text file “olr_mls_2016_lev_00000_3.2.txt”.Fig. 1 Example of visualization of file “olr_mls_2016_lev_00000_3.2.txt” in a text editor.

Fig 1

RFM website provides a Python script to read the data (http://eodg.atm.ox.ac.uk/RFM/sum/rfm_spectra.html, last access: 05 May 2024).

4 Experimental Design, Materials and Methods

The presented dataset consists of a series of clear-sky radiative transfer calculations varying the spectroscopic database and the water vapor continuum model. In order to perform line-by-line calculations the RFM was employed [5]. Its accuracy, efficiency, and thorough validation make it a well-suited suite for this application. It computes molecular absorption cross-sections by employing the Voigt lineshape for all transitions within a range of ±25 cm−1 from the line center. Hemispheric integrations are performed with the gaussian quadrature method. Cooling rates are obtained with the following equation:(1) R=1Cp×ρd(Fu−Fd)dz×86400

Where Fu and Fd are upward and downward spectral radiance fluxes, respectively, z is the altitude, Cp is the molar heat capacity and ρ is the molar density of air molecules.

The calculations were performed in the 10–3000 cm−1 spectral region at 0.0005 cm−1 resolution. To ensure manageable file sizes, the results are spectrally averaged to 0.1 cm−1 resolution. The averaging is performed by convolving spectra calculated on a fine grid with a triangular function. The base of this triangular function is set to be twice the output resolution. This averaging process helps to reduce file size while still retaining essential information from atmospheric fine spectral structure.

The calculations are performed assuming plane-parallel geometry, the surface is treated as a blackbody and the surface temperature is regarded as the same of the first atmospheric layer. Line coupling was neglected. For characterizing different atmospheric conditions five profiles were selected, namely, tropical (TRO), mid-latitude summer (MLS), mid-latitude winter (MLW), sub-artic summer (SAS) and sub-artic winter (SAW) [6]. Vertical distribution of temperature, water vapor and ozone of these profiles are displayed in Fig. 2. The profiles consist of 50 levels, with vertical resolution of 1 km from 0 to 25 km, 2.5 km from 25 to 50 km and 5 km from 50 to 120 km (These profiles are available at https://github.com/livialmg/HITRAN_MT_CKD_IR_calculations/). Each atmospheric layer is considered as a homogeneous path in the calculations.Fig. 2 Input atmospheric vertical profiles.

Fig 2

For each atmospheric model, experiments were conducted, alternating between HITRAN database versions 2016 [7] and 2020 [8], as well as between versions 3.2 and the latest version 4.1.1 of the MT_CKD WV continuum model [3]. This resulted in four outputs for each variable for every combination of atmospheric model and experimental setup.

The first setup considers only radiatively active gases in the infrared longwave portion of the spectrum for computations: CO2, H2O, O3, CH4, N2O, CO, O2. It uses an approximation of Planck function varying linearly through the layer with optical depth, which considers that the effective emitting level moves towards the observer in optically thick layers. Cooling rates were calculated solely for this experimental setup.

The second experiment setup mirrors the first, except it does not utilize the approximation of the Planck function varying linearly through the layer with optical depth.

Additionally, three other experiments were conducted, each removing one key gas from the calculations, namely, CO2, H2O, and O3. All other parameters remained consistent with the first experiment.

The RFM code and driver tables used to generate the dataset are freely available in the following GitHub repository: https://github.com/livialmg/HITRAN_MT_CKD_IR_calculations/.

Limitations

Not applicable.

Ethics Statement

The authors confirm that they have read and adhered to the ethical requirements for publication in Data in Brief. Furthermore, the current work does not involve human subjects, animal experiments, nor does it include any data collected from social media platforms.

CRediT Author Statement

Maria Lívia L. M. Gava: Writing – original draft, Methodology, Conceptualization. Simone M. S. Costa: Conceptualization, Writing - Review & Editing. Caio Atila P. Sena: Conceptualization, Writing - Review & Editing.

Data Availability

Infrared Radiative Transfer Calculations Dataset (Original data) (Zenodo).

Acknowledgments

The authors express their gratitude to Dr. A Dudhia from the University of Oxford for providing the RFM source code, supported by funding from the UK National Centre for Earth Observation. We also extend our thanks to Dr. I. Gordon for his assistance in accessing HITRAN 2016.

Funding

This research has been supported by the 10.13039/501100002322 Coordenação de Aperfeiçoamento de Pessoal de Nível Superior – Brasil (CAPES finance code 001 ).

Declaration of Competing Interest

Authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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References

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2 Gava M.L.L. Costa S.M.S. Sena C.A.P. The effects of changes in HITRAN and the water vapor continuum model on infrared radiative transfer calculations and remote sensing applications J. Quant. Spectrosc. Radiat. Transfer 322 2024 Article 109025
3 Mlawer E. Cady-Pereira K. Mascio J. Gordon I. The inclusion of the MT_CKD water vapor continuum model in the HITRAN molecular spectroscopic database J. Quant. Spectrosc. Radiat. Transfer 306 2023 Article 108645
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6 Anderson G.P. AFGL Atmospheric Constituent Profiles (0-120 km): Tech. Rep. Air Force Geophys. Lab 1986 Hanscom Air Force Base Mass
7 Gordon I.E. Rothman L.S. The HITRAN2016 molecular spectroscopic database J. Quant. Spectrosc. Radiat. Transfer 203 2017 3 69
8 Gordon I.E. Rothman L.S. The HITRAN2020 molecular spectroscopic database J. Quant. Spectrosc. Radiat. Transfer 277 2022 Article 107949
