Query: hitran.org/api/v2/<api_key>/molecules?id=1

<figure><img src="image_42.png" /><figcaption>**Fig. 40.** Sample JSON response for the REST API query requesting molecule information, with an additional restriction imposed on the HITRAN ID value. The JSON fields contain the information on the molecule entry with the `id=1` (water vapor).</figcaption></figure>

<figure><img src="image_43.png" /><figcaption>**Fig. 41.** An API key is required to make use of the full querying capabilities of HAPI2. Users can generate a personal API key from their HITRANonline user profile at www.hitran.org by clicking "Generate API key". The resulting API key will be displayed in the location indicated in the screenshot.</figcaption></figure>

In addition, among the prominent features of HAPI2 is the ability to account for the full line-mixing. Following the work of Hashemi et al. [161], the latest versions (starting from v1.1) of HAPI [52] can account for line-mixing effects through the implementation of the first-order Rosenkranz line-mixing parameters Y [232] into the Hartmann-Tran profile for the CO₂ molecule. Despite the advantages of the first-order approach (e.g., reduced number of collisional quantities and fast computations of the profiles), it fails to model the absorption for regions where lines are dense and strongly affected by line-mixing, such as Q-branches of CO₂. The HAPI2 extension includes the Python version of the line-mixing code by Lamouroux et al. [166] with account of the corrections made by Hashemi et al. [161]. Despite the structure of the Python version, it has essentially the same structure as the FORTRAN version [166] (and references therein), the major difference is that the database files are no longer provided. They will be constructed

from the code locally by the users, as a preliminary step of the first CO₂ line-mixing calculation. If the files were already built, this step will not be executed by the code, except if it is explicitly asked by the user.

As was the case for HAPI [52], the HAPI2 extension stores the downloaded files locally. Thus, the final prominent feature of HAPI2 is the ability to make use of the fast and flexible relational database on these local files. This gives users the ability to perform data mining on the stored sets of molecules, references, line parameters, and cross-sections, including user-supplied data sets. The data scheme used in this relational engine is an extension of the relational scheme constructed by Hill et al. [50]. In the HAPI2 implementation, this scheme was created using the SQLAlchemy (https://www.sqlalchemy.org/) library which provides back-ends for many existing database management systems such as SQLite, MySQL, PostgreSQL, and more. HAPI2 uses SQLite as the default database back-end. The back-ends in HAPI2 use the Object Relational Mapping (ORM) technique to connect with the low-level database. Some of the data filtering is available through the REST API on the server side (e.g., setting the wavenumber range for transitions and specifying the set of isotopologues). Nevertheless, the full capability of the data filtering can be done locally by the means of the standard SQLAlchemy ORM methods.

The HAPI2 extension is currently available on the Github repository (https://github.com/hitranonline/hapi2) as well as in the Python Package Index. A more complete description of the HAPI2 extension library will be described in a separate paper.

## 6.3. HAPIEST

The HITRAN Application Programming Interface and Efficient Spectroscopic Tools (HAPIEST) is a joint project which started in the Fall of 2017 as a collaboration between the HITRAN team and the State University of New York at Oswego. The purpose of HAPIEST is to simplify usage of HAPI to work efficiently with HITRANonline and to allow users who are not familiar with Python to access the spectroscopic data offered by HITRAN.

HAPIEST provides a cross-platform graphical user interactive that gives access to the basic features of HAPI (such as data fetching and filtering), as well as calculating and plotting spectral functions (absorption coefficients, and transmittance, absorption, and radiance spectra). Moreover, HAPIEST provides access to most of the controls that are involved in spectral filtering and simulation, and is distributed both as binary and source code. The most recent version of the source code can be found on Github (https://github.com/hitranonline/hapiest), as well as the most recent binary versions (https://github.com/hitranonline/hapiest/releases).

Using the HAPI and HAPI2 libraries, HAPIEST can retrieve the spectroscopic line-by-line data for any molecule or isotopologue in HITRAN. There are currently three functionalities provided in HAPIEST for line-by-line data: viewing, graphing, and data selection. The "view" feature allows line-by-line data to be viewed in a spreadsheet-like widget. This feature automatically paginates tables to save on system resources, but this page-length can be changed in the user-configurable settings. One major feature of HAPIEST is the graphing capability. HAPIEST is able to display the line-by-line data in graphical form by calculating absorption coefficients, as well as absorption, transmittance, and radiance spectra, with a variety of instrumental functions and line profiles. As part of the HAPIEST functionality, users are able to filter (e.g., by vibrational band) and plot results separately. When bands are plotted, HAPIEST creates a legend for band graphs which will display upper- and lower-quanta of each band. In addition, the absorption cross-section data can also be downloaded from the HITRANonline web server and plotted by HAPIEST. Multiple absorp-
<figure><img src="image_46.png" /></figure>

<figure><img src="image_47.png" /><figcaption>**Fig. 42.** Screenshots of the graphical user interface of HAPIEST. The upper window displays the tab where absorption cross-section spectra from HITRANonline can be queried and filtered, then downloaded using the "Fetch cross-section" button (circled orange). In this example, three absorption cross-sections of CFC-11 (CCl₃F) with different pressures have been selected by filtering the available CFC-11 absorption cross-sections between 800–900 cm⁻¹ and 200–300 K. Clicking the "Graphing" tab (circled green) allows users to create a plot of their chosen cross-section spectra. The same three CFC-11 cross-sections have been plotted in the lower window using the graphing functionality of HAPIEST. Here, users are able to adjust their plot using the tools on the lower left of the window (such as by zooming to compare spectral regions) and the results can be saved.</figcaption></figure>

tion cross-sections can be plotted on the same axes and compared, as shown in Fig. 42 for three different temperature-pressure sets of CFC-11.

## 6.4. Total internal partition sums (TIPS)

New total internal partition sums (TIPS) were calculated or recalculated for many HITRAN molecules and their isotopologues [417]. Naturally, TIPS were calculated for all new isotopologues (³³S¹⁶O₂, ¹⁶O³²S¹⁸O, ¹⁵N¹⁶O₂, ¹⁶O¹³C³⁴S, ¹²C₂H₅D) and molecules (SO, CH₃F, GeH₄, CS₂, CH₃I, NF₃) that have been introduced to the database for HITRAN2020 and were not included as part of TIPS2017 [178]. Also, partition sums were revised for a number of molecules and isotopologues. In particular, TIPS of ozone have been recalculated to eliminate discrepancies noted in Ref. [200]. The TIPS are calculated in one-degree intervals from 1 K until the convergence of each partition sum (which is different for each molecule) and will be provided as an update to TIPS2017, which was used for all isotopologues in the previous edition of HITRAN [16]. The full TIPS for each new isotopologue and molecule will be made available through the HITRANonline website (https://hitran.org/docs/iso-meta/) where the corresponding partition sum, Q(296 K), is provided at 296 K.

<caption>**Table 13**</caption>

A list of the 24 coefficients that define the DPL parametrization for all the six line-shape parameters: pressure broadening and shift (γ₀ and δ₀), speed dependence of pressure broadening and shift (γ₂ and δ₂), real and imaginary parts of the complex Dicke parameter ($\tilde{v}_{opt}^{rf}$ and $\tilde{v}_{opt}^{i}$).

<table><thead><tr><th></th><th>Coefficient 1</th><th>Coefficient 2</th><th>Exponent 1</th><th>Exponent 2</th></tr></thead><tbody><tr><td>γ₀(T)</td><td>g₀</td><td>g'<sub>0</sub></td><td>n</td><td>n'</td></tr><tr><td>δ₀(T)</td><td>d₀</td><td>d'<sub>0</sub></td><td>m</td><td>m'</td></tr><tr><td>γ₂(T)</td><td>g₂</td><td>g'<sub>2</sub></td><td>j</td><td>j'</td></tr><tr><td>δ₂(T)</td><td>d₂</td><td>d'<sub>2</sub></td><td>k</td><td>k'</td></tr><tr><td>γ<sup>rf</sup><sub>opt</sub>(T)</td><td>r</td><td>r'</td><td>p</td><td>p'</td></tr><tr><td>γ<sup>i</sup><sub>opt</sub>(T)</td><td>i</td><td>i'</td><td>q</td><td>q'</td></tr></tbody></table>

## 7. Conclusions and future work

This article introduces and details the improvements and expansion of the new HITRAN2020 database release with respect to its predecessor, HITRAN2016 [16]. These improvements include the increased quality of reference spectral parameters, expansions of spectral and dynamic ranges, and new parametrizations and capabilities. The addition of new molecules and isotopologues or new collisional complexes is justified and explained. Non-Voigt line shapes continue to be expanded in the database. In this edition, important atmospheric absorbers that include CO₂, N₂O and CO, now have, not only Voigt, but also speed-dependent Voigt parameters (for both air- and self-broadening) for every transition of these molecules in the database. In addition, many molecules now have line-shape parameters due to ambient water-vapor pressure provided for all transitions. There are also substantially more molecules with parameters associated with the pressure of “planetary” gases: H₂, He and CO₂. Experimental cross-sections, aerosols, and collision induced absorption datasets have also been revised and extended. The new data were validated against laboratory and atmospheric spectra whenever possible.

Furthermore, HITRAN continues to evolve in terms of structure and scope. This evolution includes expanded capabilities and documentation for the online server and restructuring and optimization of HAPI, which now also has a GUI.

In summary, the capabilities of HITRAN have been significantly enhanced compared to previous editions, in terms of quality, extent and accessibility of the data.

The HITRAN compilation is free to use and can be accessed through www.hitran.org.

### 7.1. Future plans for expansion of HITRAN

#### 7.1.1. Double-power-law (DPL) representation of the temperature dependencies of the line-shape parameters

Recently, a new scheme of representing the temperature dependencies of the line-shape parameters was adopted in HITRAN [120]. The approach approximates the temperature dependencies with a double-power-law (DPL) function [119]. The scheme adopted in HITRAN [120] is very general and applicable also to beyond-Voigt cases. It should be noted, however, that for many molecular systems, not all the collisional effects are important at the considered accuracy level and, for a given experimental temperature range, a simple single-power law suffices. In such cases, either a single-power law and a smaller number of line-shape parameters will be stored in HITRAN, or the full DPL parametrization will be adopted but some of the coefficients will be set to zero.

In the most general case, the DPL parametrization involves 24 coefficients, i.e., four DPL coefficients per each of the six line-shape parameters, see Table 13. The explicit formulas for the DPL temperature dependencies are following [120]:

$$ \gamma_0(T) = g_0(T_{\text{ref}}/T)^n + g'_0(T_{\text{ref}}/T)^{n'} $$
<figure><img src="image_44.png" /></figure>

<figure><img src="image_45.png" /><figcaption>**Fig. 42.** Screenshots of the graphical user interface of HAPIEST. The upper window displays the tab where absorption cross-section spectra from HITRANonline can be queried and filtered, then downloaded using the "Fetch cross-section" button (circled orange). In this example, three absorption cross-sections of CFC-11 (CCl₃F) with different pressures have been selected by filtering the available CFC-11 absorption cross-sections between 800–900 cm⁻¹ and 200–300 K. Clicking the "Graphing" tab (circled green) allows users to create a plot of their chosen cross-section spectra. The same three CFC-11 cross-sections have been plotted in the lower window using the graphing functionality of HAPIEST. Here, users are able to adjust their plot using the tools on the lower left of the window (such as by zooming to compare spectral regions) and the results can be saved.</figcaption></figure>

tion cross-sections can be plotted on the same axes and compared, as shown in Fig. 42 for three different temperature-pressure sets of CFC-11.

## 6.4. Total internal partition sums (TIPS)

New total internal partition sums (TIPS) were calculated or recalculated for many HITRAN molecules and their isotopologues [417]. Naturally, TIPS were calculated for all new isotopologues (³³S¹⁶O₂, ¹⁶O³²S¹⁸O, ¹⁵N¹⁶O₂, ¹⁶O¹³C³⁴S, ¹²C₂H₅D) and molecules (SO, CH₃F, GeH₄, CS₂, CH₃I, NF₃) that have been introduced to the database for HITRAN2020 and were not included as part of TIPS2017 [178]. Also, partition sums were revised for a number of molecules and isotopologues. In particular, TIPS of ozone have been recalculated to eliminate discrepancies noted in Ref. [200]. The TIPS are calculated in one-degree intervals from 1 K until the convergence of each partition sum (which is different for each molecule) and will be provided as an update to TIPS2017, which was used for all isotopologues in the previous edition of HITRAN [16]. The full TIPS for each new isotopologue and molecule will be made available through the HITRANonline website (https://hitran.org/docs/iso-meta/) where the corresponding partition sum, Q(296 K), is provided at 296 K.

<caption>**Table 13**</caption>

A list of the 24 coefficients that define the DPL parametrization for all the six line-shape parameters: pressure broadening and shift (γ₀ and δ₀), speed dependence of pressure broadening and shift (γ₂ and δ₂), real and imaginary parts of the complex Dicke parameter (ṽopt and ṽopt).

<table><thead><tr><th></th><th>Coefficient 1</th><th>Coefficient 2</th><th>Exponent 1</th><th>Exponent 2</th></tr></thead><tbody><tr><td>γ₀(T)</td><td>g₀</td><td>g'<sub>0</sub></td><td>n</td><td>n'</td></tr><tr><td>δ₀(T)</td><td>d₀</td><td>d'<sub>0</sub></td><td>m</td><td>m'</td></tr><tr><td>γ₂(T)</td><td>g₂</td><td>g'<sub>2</sub></td><td>j</td><td>j'</td></tr><tr><td>δ₂(T)</td><td>d₂</td><td>d'<sub>2</sub></td><td>k</td><td>k'</td></tr><tr><td>ṽopt(T)</td><td>r</td><td>r'</td><td>p</td><td>p'</td></tr><tr><td>ṽopt(T)</td><td>i</td><td>i'</td><td>q</td><td>q'</td></tr></tbody></table>

## 7. Conclusions and future work

This article introduces and details the improvements and expansion of the new HITRAN2020 database release with respect to its predecessor, HITRAN2016 [16]. These improvements include the increased quality of reference spectral parameters, expansions of spectral and dynamic ranges, and new parametrizations and capabilities. The addition of new molecules and isotopologues or new collisional complexes is justified and explained. Non-Voigt line shapes continue to be expanded in the database. In this edition, important atmospheric absorbers that include CO₂, N₂O and CO, now have, not only Voigt, but also speed-dependent Voigt parameters (for both air- and self-broadening) for every transition of these molecules in the database. In addition, many molecules now have line-shape parameters due to ambient water-vapor pressure provided for all transitions. There are also substantially more molecules with parameters associated with the pressure of “planetary” gases: H₂, He and CO₂. Experimental cross-sections, aerosols, and collision induced absorption datasets have also been revised and extended. The new data were validated against laboratory and atmospheric spectra whenever possible.

Furthermore, HITRAN continues to evolve in terms of structure and scope. This evolution includes expanded capabilities and documentation for the online server and restructuring and optimization of HAPI, which now also has a GUI.

In summary, the capabilities of HITRAN have been significantly enhanced compared to previous editions, in terms of quality, extent and accessibility of the data.

The HITRAN compilation is free to use and can be accessed through www.hitran.org.

### 7.1. Future plans for expansion of HITRAN

#### 7.1.1. Double-power-law (DPL) representation of the temperature dependencies of the line-shape parameters

Recently, a new scheme of representing the temperature dependencies of the line-shape parameters was adopted in HITRAN [120]. The approach approximates the temperature dependencies with a double-power-law (DPL) function [119]. The scheme adopted in HITRAN [120] is very general and applicable also to beyond-Voigt cases. It should be noted, however, that for many molecular systems, not all the collisional effects are important at the considered accuracy level and, for a given experimental temperature range, a simple single-power law suffices. In such cases, either a single-power law and a smaller number of line-shape parameters will be stored in HITRAN, or the full DPL parametrization will be adopted but some of the coefficients will be set to zero.

In the most general case, the DPL parametrization involves 24 coefficients, i.e., four DPL coefficients per each of the six line-shape parameters, see Table 13. The explicit formulas for the DPL temperature dependencies are following [120]:

$$γ_0(T) = g_0(T_{\text{ref}}/T)^n + g'_0(T_{\text{ref}}/T)^{n'}$$
$$ 
\begin{aligned}
\delta_0(T) &= d_0(T_{\text{ref}}/T)^m + d'_0(T_{\text{ref}}/T)^{m'}, \\
\gamma_2(T) &= g_2(T_{\text{ref}}/T)^j + g'_2(T_{\text{ref}}/T)^{j'}, \\
\delta_2(T) &= d_2(T_{\text{ref}}/T)^k + d'_2(T_{\text{ref}}/T)^{k'}, \\
\bar{v}_{\text{opt}}^{r}(T) &= r(T_{\text{ref}}/T)^p + r'(T_{\text{ref}}/T)^{p'}, \\
\bar{v}_{\text{opt}}^{i}(T) &= i(T_{\text{ref}}/T)^q + i'(T_{\text{ref}}/T)^{q'},
\end{aligned}
\qquad (6) $$

where $T_{\text{ref}} = 296$ K.

The DPL parametrization replaces the four temperature ranges (4TR) representation introduced in 2016 [165]. It was shown in Ref. [120] that the DPL parametrization requires fewer parameters, gives better accuracy and is more self-consistent than 4TR. In the immediate update to HITRAN2020, the full structure of the DPL parametrization will be provided for the cases of self- and H perturbed H₂ lines.

### 7.1.2. Water-vapor continuum

In the last 50 years, HITRAN has made enormous progress toward being a complete source for all atmospheric absorption parameters. Nevertheless, it has not yet expanded to include continuum absorption by water vapor. This gap in the database will be filled in forthcoming updates to HITRAN2020.

Absorption and emission by the water-vapor continuum play an important role in radiative processes in the terrestrial atmosphere and have an appreciable impact on weather and the climate of the Earth [880–882]. There is still uncertainty with respect to the physical phenomena behind either the self (interactions of water vapor with other water vapor molecules) or the foreign (interaction of water vapor with dry air molecules) continuum, with bound dimers, quasi-stable dimers, and monomer far wings possibly contributing to the total absorption. Theoretical analysis has not yet been able to disentangle the relative contributions of these phenomena as a function of wavenumber and temperature. This is still the subject of an active debate (e.g., see reviews [883,884]).

The next version of HITRAN will include the updated and well-documented MT_CKD (Mlawer-Tobin_Clough-Kneizys-Davies) water-vapor continuum model [881], which is widely used in atmospheric radiative-transfer codes. The MT_CKD model is based on a combination of analyses of field measurements, laboratory measurements, and semi-empirical model calculations, and is a descendant of the CKD (Clough-Kneizys-Davies) continuum model [885] developed in the 1980s. The goal of these models is to provide a representation of smoothly varying water-vapor absorption that, once added to the absorption due to water vapor lines (cut-off at $25 \text{ cm}^{-1}$ from line center), best agrees with high-quality observations and theoretical calculations of the total water-vapor absorption. In many spectral regions, observations from different studies provide conflicting information on the strength of the water-vapor continuum, and a judgment must be made as to which source should provide the basis for the coefficients in MT_CKD. The overall perspective in developing the MT_CKD water-vapor continuum is consistent with that of HITRAN – regular updates to the spectroscopic parameters in order to agree with studies considered to be most accurate.

The importance of the water-vapor continuum and aforementioned discrepancies have sparked a number of new laboratory measurements in different spectral regions [883,886–900]. While many of these experiments show a decent level of consistency with MT_CKD (see discussion in Ref. [893], for instance) they nevertheless have warranted revisions to the model. For example, MT_CKD recently incorporated the results of numerous lab measurements in near-infrared windows by the group of Campargue at Grenoble, which provided water-vapor continuum absorption coefficients with stated uncertainties lower than had previously been reported in these regions. In some window regions, these

continuum values disagreed by more than an order of magnitude with previous measurements (see, for instance, the recent review [901]). These improvements to the MT_CKD self and foreign continuum due to the measurements in Grenoble [893–898,900] have made a noticeable positive impact on the retrievals of carbon dioxide with the OCO-2 mission [323]. Uncertainties still remain, however. The water-vapor continuum model from Paynter and Ramaswamy [902], named “BPS” due to the articles describing the input measurements [886,903–905], has different absorption coefficients than MT_CKD in certain near-infrared windows and other regions, leading to different results in the atmosphere.

Other recent updates to MT_CKD include the far-infrared foreign continuum, which was modified based on an analysis of field campaign observations [122]. Subsequent studies [906,907] have provided validation for these far-infrared absorption coefficients. The most recent revision was MT_CKD 3.5, which improved the continuum in the microwave (self and foreign) and far-infrared (self) based on analyses of field and lab experiments (see, e.g., Ref. [908]). Ongoing analyses are expected to lead to improvements in the MT_CKD model in the infrared window (self and possibly foreign) and water vapor $v_2$ band (foreign).

### 7.1.3. Pre-calculated absorption cross-sections

The complexity and the amount of the new parameters included in HITRAN is putting a lot of demand on the user community to know how to implement the new data in the radiative-transfer codes. While we provide tutorials and enable some of the tools through HAPI, it may still be challenging for some of the users. Therefore we plan to provide the pre-calculated sets of cross-sections to use for atmospheric research. There are some accepted format and parameter space used in many of the remote-sensing missions. For instance, OCO-2/3 [17,18] and TES [19] research teams employ the so-called ABSCO [323] format. We, therefore, plan to pre-calculate ABSCO-formatted cross-sections for selected molecules and spectral ranges, determined in consultation with the remote-sensing community. Other commonly used formats will also be explored.

## 8. Acknowledgements

The global COVID-19 pandemic has impacted the working conditions and lives of everyone involved in the production of HITRAN2020. In recognition of the difficult conditions of the previous year, we would like to extend our sincere gratitude to all researchers and collaborators who have been able to contribute to this edition. We also thank the anonymous reviewers for their very constructive criticism and suggestions.

Development of the HITRAN2020 database and associated tools was supported through the NASA grants NNX17AI78G, NNX16AG51G, 80NSSC20K0962, 80NSSC20K1059.

We gratefully acknowledge the many researchers who provided data, experimental and/or theoretical: Ad van der Avoird, Yury Baranov, Chris Benner, Yury Borkov, Christian Boulet, Daniil Chistikov, Malathy Devi, Randika Dodangodage, Samuel Gordon, Gerrit Groenenboom, Magnus Gustafsson, Adrian Hjältén, Shuiming Hu, Christof Janssen, Aleksandra Kyuberis, Julien Lamouroux, Daniel Lisak, Anwen Liu, Sergei Lokshtanov, Marie Aline Martin-Drumel, Andrey Muraviev, Harrald Mutschke, Laurence Régalia, Shanelle Samuels, Mary-Ann Smith, Alexander M. Solodov, Alexander A. Solodov, Ryan Thalman, Mikhail Tretyakov, Yixin Wang, Edward Wishnow, Wim van der Zande, Konstantin Vodopyanov, Rainer Volkamer, Shanshan Yu, Nikolai Zobov.

Those who provided independent validations are also acknowledged: Matthew Alvarado, Juyeson Bak, Natasha Batalha, Chris Boone, Ryan Cole, Sergio DeSouza-Machado, Richard Larsson, Xiong Liu, Emile Medvedev, Clayton Mulvihill, Fabiano Oyafuso, Erwan
$$
\begin{align}
\delta_0(T) &= d_0(T_{\text{ref}}/T)^m + d'_0(T_{\text{ref}}/T)^{m'}, \nonumber \\
\gamma_2(T) &= g_2(T_{\text{ref}}/T)^j + g'_2(T_{\text{ref}}/T)^{j'}, \nonumber \\
\delta_2(T) &= d_2(T_{\text{ref}}/T)^k + d'_2(T_{\text{ref}}/T)^{k'}, \nonumber \\
\bar{v}_{\text{opt}}^r(T) &= r(T_{\text{ref}}/T)^p + r'(T_{\text{ref}}/T)^{p'}, \nonumber \\
\bar{v}_{\text{opt}}^i(T) &= i(T_{\text{ref}}/T)^q + i'(T_{\text{ref}}/T)^{q'}, \tag{6}
\end{align}
$$

where $T_{\text{ref}} = 296$ K.

The DPL parametrization replaces the four temperature ranges (4TR) representation introduced in 2016 [165]. It was shown in Ref. [120] that the DPL parametrization requires fewer parameters, gives better accuracy and is more self-consistent than 4TR. In the immediate update to HITRAN2020, the full structure of the DPL parametrization will be provided for the cases of self- and H perturbed H₂ lines.

### 7.1.2. Water-vapor continuum

In the last 50 years, HITRAN has made enormous progress toward being a complete source for all atmospheric absorption parameters. Nevertheless, it has not yet expanded to include continuum absorption by water vapor. This gap in the database will be filled in forthcoming updates to HITRAN2020.

Absorption and emission by the water-vapor continuum play an important role in radiative processes in the terrestrial atmosphere and have an appreciable impact on weather and the climate of the Earth [880–882]. There is still uncertainty with respect to the physical phenomena behind either the self (interactions of water vapor with other water vapor molecules) or the foreign (interaction of water vapor with dry air molecules) continuum, with bound dimers, quasi-stable dimers, and monomer far wings possibly contributing to the total absorption. Theoretical analysis has not yet been able to disentangle the relative contributions of these phenomena as a function of wavenumber and temperature. This is still the subject of an active debate (e.g., see reviews [883,884]).

The next version of HITRAN will include the updated and well-documented MT_CKD (Mlawer-Tobin_Clough-Kneizys-Davies) water-vapor continuum model [881], which is widely used in atmospheric radiative-transfer codes. The MT_CKD model is based on a combination of analyses of field measurements, laboratory measurements, and semi-empirical model calculations, and is a descendant of the CKD (Clough-Kneizys-Davies) continuum model [885] developed in the 1980s. The goal of these models is to provide a representation of smoothly varying water-vapor absorption that, once added to the absorption due to water vapor lines (cut-off at $25 \text{ cm}^{-1}$ from line center), best agrees with high-quality observations and theoretical calculations of the total water-vapor absorption. In many spectral regions, observations from different studies provide conflicting information on the strength of the water-vapor continuum, and a judgment must be made as to which source should provide the basis for the coefficients in MT_CKD. The overall perspective in developing the MT_CKD water-vapor continuum is consistent with that of HITRAN – regular updates to the spectroscopic parameters in order to agree with studies considered to be most accurate.

The importance of the water-vapor continuum and aforementioned discrepancies have sparked a number of new laboratory measurements in different spectral regions [883,886–900]. While many of these experiments show a decent level of consistency with MT_CKD (see discussion in Ref. [893], for instance) they nevertheless have warranted revisions to the model. For example, MT_CKD recently incorporated the results of numerous lab measurements in near-infrared windows by the group of Campargue at Grenoble, which provided water-vapor continuum absorption coefficients with stated uncertainties lower than had previously been reported in these regions. In some window regions, these

continuum values disagreed by more than an order of magnitude with previous measurements (see, for instance, the recent review [901]). These improvements to the MT_CKD self and foreign continuum due to the measurements in Grenoble [893–898,900] have made a noticeable positive impact on the retrievals of carbon dioxide with the OCO-2 mission [323]. Uncertainties still remain, however. The water-vapor continuum model from Paynter and Ramaswamy [902], named “BPS” due to the articles describing the input measurements [886,903–905], has different absorption coefficients than MT_CKD in certain near-infrared windows and other regions, leading to different results in the atmosphere.

Other recent updates to MT_CKD include the far-infrared foreign continuum, which was modified based on an analysis of field campaign observations [122]. Subsequent studies [906,907] have provided validation for these far-infrared absorption coefficients. The most recent revision was MT_CKD 3.5, which improved the continuum in the microwave (self and foreign) and far-infrared (self) based on analyses of field and lab experiments (see, e.g., Ref. [908]). Ongoing analyses are expected to lead to improvements in the MT_CKD model in the infrared window (self and possibly foreign) and water vapor $\nu_2$ band (foreign).

### 7.1.3. Pre-calculated absorption cross-sections

The complexity and the amount of the new parameters included in HITRAN is putting a lot of demand on the user community to know how to implement the new data in the radiative-transfer codes. While we provide tutorials and enable some of the tools through HAPI, it may still be challenging for some of the users. Therefore we plan to provide the pre-calculated sets of cross-sections to use for atmospheric research. There are some accepted format and parameter space used in many of the remote-sensing missions. For instance, OCO-2/3 [17,18] and TES [19] research teams employ the so-called ABSCO [323] format. We, therefore, plan to pre-calculate ABSCO-formatted cross-sections for selected molecules and spectral ranges, determined in consultation with the remote-sensing community. Other commonly used formats will also be explored.

## 8. Acknowledgements

The global COVID-19 pandemic has impacted the working conditions and lives of everyone involved in the production of HITRAN2020. In recognition of the difficult conditions of the previous year, we would like to extend our sincere gratitude to all researchers and collaborators who have been able to contribute to this edition. We also thank the anonymous reviewers for their very constructive criticism and suggestions.

Development of the HITRAN2020 database and associated tools was supported through the NASA grants NNX17AI78G, NNX16AG51G, 80NSSC20K0962, 80NSSC20K1059.

We gratefully acknowledge the many researchers who provided data, experimental and/or theoretical: Ad van der Avoird, Yury Baranov, Chris Benner, Yury Borkov, Christian Boulet, Daniil Chistikov, Malathy Devi, Randika Dodangodage, Samuel Gordon, Gerrit Groenenboom, Magnus Gustafsson, Adrian Hjältén, Shuiming Hu, Christof Janssen, Aleksandra Kyuberis, Julien Lamouroux, Daniel Lisak, Anwen Liu, Sergei Lokshtanov, Marie Aline Martin-Drumel, Andrey Muraviev, Harrald Mutschke, Laurence Régalia, Shanelle Samuels, Mary-Ann Smith, Alexander M. Solodov, Alexander A. Solodov, Ryan Thalman, Mikhail Tretyakov, Yixin Wang, Edward Wishnow, Wim van der Zande, Konstantin Vodopyanov, Rainer Volkamer, Shanshan Yu, Nikolai Zobov.

Those who provided independent validations are also acknowledged: Matthew Alvarado, Juyeson Bak, Natasha Batalha, Chris Boone, Ryan Cole, Sergio DeSouza-Machado, Richard Larsson, Xiong Liu, Emile Medvedev, Clayton Mulvihill, Fabiano Oyafuso, Erwan
Pannier, Vivienne Payne, Olivier Pirali, Greg Rieker, Keith Shine, Clara Sousa-Silva, Kang Sun, Boris Voronin.

Portions of the research described in this paper were performed at the Jet Propulsion Laboratory, California Institute of Technology, under contract with NASA. The research from the V.E. Zuev Institute of Atmospheric Optics of Siberian Branch of Russian Academy of Sciences were supported by the Ministry of Science and Higher Education of the Russian Federation. The work of the Tomsk group on ozone spectroscopy was supported by the Russian Science Foundation RNF grant no. 19-12-00171. GSMA Reims and LiPhy Grenoble acknowledge support from the French-Russian collaboration program LIA CNRS "SAMIA". AGC, TF, and RT received support from the ELTE Institutional Excellence Program (TKP2020-IKA-05) and from NKFIH (K119658). OLP and JT received support from the UK Natural Environment Research Council under grants NE/N001508/1 and the European Research Council under ERC Advanced Investigator grant 8838302

## Declaration of Competing Interest

The 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.

## Appendix A. Abbreviations

When describing the inclusion of data into HITRAN, the following abbreviations, acronyms, and initialisms have been used at various points throughout the article:

* 4TR – Four-temperature range

* ABSCO – Absorption coefficient [323]

* ACE – Atmospheric Chemistry Experiment [21]

* API – Application programming interface

* ARIEL – Atmospheric Remote-sensing Infrared Exoplanet Large-survey [47]

* ARTS – Atmospheric Radiative Transfer Simulator [31]

* ASCII – American standard code for information interchange

* CCSD(T) – Coupled-cluster singles, doubles, and perturbative triples

* CDMS – Cologne Database for Molecular Spectroscopy [344]

* CDSD – Carbon Dioxide Spectroscopic Database [135]

* CFC – Chlorofluorocarbon

* CIA – Collision-induced absorption

* CLS – Canadian Light Source

* CRDS – Cavity ring-down spectroscopy

* DLR – Deutsches Zentrum für Luft und Raumfahrt (German Aerospace Center)

* DMS – Dipole moment surface

* DOI – Digital object identifier

* DPL – Double-power law

* DU – Dobson unit

* EDTM – Effective dipole transition moment

* EH – Effective Hamiltonian

* EPG – Exponential power gap

* ESA – European Space Agency

* FIR – Far-infrared

* FORUM – Far-infrared Outgoing Radiation Understanding and Monitoring [24]

* FT – Fourier transform

* FTIR – Fourier transform infrared

* FTS – Fourier transform spectrometer

* GARLIC – Generic Atmospheric Radiation Line-by-line Infrared Code [32]

* GeCaSDa – Germane Calculated Spectroscopic Database [594]

* GEISA – Gestion et Etude des Informations Spectroscopiques Atmosphériques (Management and Study of Atmospheric Spectroscopic Information) [418]

* GEMS – Geostationary Environment Monitoring Spectrometer [23]

* GENLN – General Line-by-line Atmospheric Transmittance and Radiance Model [29]

* GOSAT – Greenhouse Gases Observing Satellite [20]

* HAPI – HITRAN Application Programming Interface [52]

* HAPIEST – HITRAN Application Programming Interface and Efficient Spectroscopic Tools

* HCFC – Hydrochlorofluorocarbon

* HDF-5 – Hierarchical Data Format version 5

* HITRAN – High-resolution transmission molecular absorption database [16]

* HITEMP – High-temperature molecular spectroscopic database [53]

* HR – High-resolution

* HT – Hartmann–Tran

* HTTPS – Hypertext transfer protocol secure

* IAO – Institute of Atmospheric Optics

* IASI – Infrared Atmospheric Sounding Interferometer [186]

* ICB – Laboratoire Interdisciplinaire Carnot de Bourgogne

* IDL – Interactive Design Language

* IR – Infrared

* JIRAM – Jovian Infrared Auroral Mapper [652]

* JPL – Jet Propulsion Laboratory

* JSON – JavaScript Object Notation

* JWST – James Webb Space Telescope [46]

* LBL – Line-by-line

* LBLRTM – Line-by-line Radiative Transfer Model [27]

* LERMA – Laboratoire d'étude du rayonnement et de la matière en astrophysique

* LIDAR – Light detection and ranging

* LISA – Laboratoire Interuniversitaire des Systèmes Atmosphériques

* MARVEL – Measured Active Rotational-Vibrational Energy Levels [58,59]

* MATS – Multi-spectrum analysis tool for spectroscopy [238]

* MCRB – Modified complex Robert-Bonamy

* MIR – Mid-infrared

* MODTRAN – Moderate resolution atmospheric transmission code [28]

* MT_CKD – Mlawer-Tobin Clough-Kneizys-Davies [881]

* MW – Microwave

* NASA – National Aeronautics and Space Administration

* NDSD-1000 – Nitrogen Dioxide Spectroscopic Data Bank at 1000 K [398,399]

* NEMESIS – Non-linear optimal estimator for multivariate spectral analysis [35]

* netCDF – Network common data form

* NIR – Near-infrared

* NIST – National Institute of Standards and Technology

* NMHC – Non-methane hydrocarbon

* NOSD-1000 – Nitrous Oxide Spectroscopic Data Bank at 1000 K [243]

* NSO – National Solar Observatory

* OCO – Orbiting Carbon Observatory [17,18]

* ODU – Old Dominion University

* ORM – Object-relational mapping

* PES – Potential energy surface

* PNNL – Pacific Northwest National Laboratory

* PSC – Polar stratospheric cloud

* PSG – Planetary Spectrum Generator [37]

* rCMDS – Requantized Classical Molecular Dynamics Simulation
Pannier, Vivienne Payne, Olivier Pirali, Greg Rieker, Keith Shine, Clara Sousa-Silva, Kang Sun, Boris Voronin.

Portions of the research described in this paper were performed at the Jet Propulsion Laboratory, California Institute of Technology, under contract with NASA. The research from the V.E. Zuev Institute of Atmospheric Optics of Siberian Branch of Russian Academy of Sciences were supported by the Ministry of Science and Higher Education of the Russian Federation. The work of the Tomsk group on ozone spectroscopy was supported by the Russian Science Foundation RNF grant no. 19-12-00171. GSMA Reims and LiPhy Grenoble acknowledge support from the French-Russian collaboration program LIA CNRS "SAMIA". AGC, TF, and RT received support from the ELTE Institutional Excellence Program (TKP2020-IKA-05) and from NKFIH (K119658). OLP and JT received support from the UK Natural Environment Research Council under grants NE/N001508/1 and the European Research Council under ERC Advanced Investigator grant 8838302

## Declaration of Competing Interest

The 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.

## Appendix A. Abbreviations

When describing the inclusion of data into HITRAN, the following abbreviations, acronyms, and initialisms have been used at various points throughout the article:

* 4TR – Four-temperature range

* ABSCO – Absorption coefficient [323]

* ACE – Atmospheric Chemistry Experiment [21]

* API – Application programming interface

* ARIEL – Atmospheric Remote-sensing Infrared Exoplanet Large-survey [47]

* ARTS – Atmospheric Radiative Transfer Simulator [31]

* ASCII – American standard code for information interchange

* CCSD(T) – Coupled-cluster singles, doubles, and perturbative triples

* CDMS – Cologne Database for Molecular Spectroscopy [344]

* CDSD – Carbon Dioxide Spectroscopic Database [135]

* CFC – Chlorofluorocarbon

* CIA – Collision-induced absorption

* CLS – Canadian Light Source

* CRDS – Cavity ring-down spectroscopy

* DLR – Deutsches Zentrum für Luft und Raumfahrt (German Aerospace Center)

* DMS – Dipole moment surface

* DOI – Digital object identifier

* DPL – Double-power law

* DU – Dobson unit

* EDTM – Effective dipole transition moment

* EH – Effective Hamiltonian

* EPG – Exponential power gap

* ESA – European Space Agency

* FIR – Far-infrared

* FORUM – Far-infrared Outgoing Radiation Understanding and Monitoring [24]

* FT – Fourier transform

* FTIR – Fourier transform infrared

* FTS – Fourier transform spectrometer

* GARLIC – Generic Atmospheric Radiation Line-by-line Infrared Code [32]

* GeCaSDa – Germane Calculated Spectroscopic Database [594]

* GEISA – Gestion et Etude des Informations Spectroscopiques Atmosphériques (Management and Study of Atmospheric Spectroscopic Information) [418]

* GEMS – Geostationary Environment Monitoring Spectrometer [23]

* GENLN – General Line-by-line Atmospheric Transmittance and Radiance Model [29]

* GOSAT – Greenhouse Gases Observing Satellite [20]

* HAPI – HITRAN Application Programming Interface [52]

* HAPIEST – HITRAN Application Programming Interface and Efficient Spectroscopic Tools

* HCFC – Hydrochlorofluorocarbon

* HDF-5 – Hierarchical Data Format version 5

* HITRAN – High-resolution transmission molecular absorption database [16]

* HITEMP – High-temperature molecular spectroscopic database [53]

* HR – High-resolution

* HT – Hartmann–Tran

* HTTPS – Hypertext transfer protocol secure

* IAO – Institute of Atmospheric Optics

* IASI – Infrared Atmospheric Sounding Interferometer [186]

* ICB – Laboratoire Interdisciplinaire Carnot de Bourgogne

* IDL – Interactive Design Language

* IR – Infrared

* JIRAM – Jovian Infrared Auroral Mapper [652]

* JPL – Jet Propulsion Laboratory

* JSON – JavaScript Object Notation

* JWST – James Webb Space Telescope [46]

* LBL – Line-by-line

* LBLRTM – Line-by-line Radiative Transfer Model [27]

* LERMA – Laboratoire d'étude du rayonnement et de la matière en astrophysique

* LIDAR – Light detection and ranging

* LISA – Laboratoire Interuniversitaire des Systèmes Atmosphériques

* MARVEL – Measured Active Rotational-Vibrational Energy Levels [58,59]

* MATS – Multi-spectrum analysis tool for spectroscopy [238]

* MCRB – Modified complex Robert-Bonamy

* MIR – Mid-infrared

* MODTRAN – Moderate resolution atmospheric transmission code [28]

* MT_CKD – Mlawer-Tobin Clough-Kneizys-Davies [881]

* MW – Microwave

* NASA – National Aeronautics and Space Administration

* NDSD-1000 – Nitrogen Dioxide Spectroscopic Data Bank at 1000 K [398,399]

* NEMESIS – Non-linear optimal estimator for multivariate spectral analysis [35]

* netCDF – Network common data form

* NIR – Near-infrared

* NIST – National Institute of Standards and Technology

* NMHC – Non-methane hydrocarbon

* NOSD-1000 – Nitrous Oxide Spectroscopic Data Bank at 1000 K [243]

* NSO – National Solar Observatory

* OCO – Orbiting Carbon Observatory [17,18]

* ODU – Old Dominion University

* ORM – Object-relational mapping

* PES – Potential energy surface

* PNNL – Pacific Northwest National Laboratory

* PSC – Polar stratospheric cloud

* PSG – Planetary Spectrum Generator [37]

* rCMDS – Requantized Classical Molecular Dynamics Simulation
* REST API – Representational state transfer application programming interface

* RFM – Reference Forward Model [30]

* RI – Refractive indices

* RKR – Rydberg-Klein-Rees

* RMS – Root mean square

* RT – Rototranslational

* S&MPO – Spectroscopy and Molecular Properties of Ozone [194]

* SB RAS – Siberian Branch, Russian Academy of Sciences

* SDV – Speed-dependent Voigt

* SEOM-IAS – Scientific Exploitation of Operational Missions - Improved Atmospheric Spectroscopy Databases

* SHeCaSDa – Sulfur Hexafluoride Calculated Spectroscopic Database [594]

* SI – Système International

* SISAM – Spectromètre Interférentiel à Sélection par l'Amplitude de la Modulation (Interferential Spectrometer by Selection of Amplitude Modulation)

* SNR – Signal to noise ratio

* SOA – Secondary organic aerosol

* SRP – Standard reference photometer

* TCCON – Total Carbon Column Observing Network [145,146]

* TEMPO – Tropospheric Emissions: Monitoring of Pollution [25]

* TES – Tropospheric Emission Spectrometer [19]

* TFMeCaSDa – TetraFluoro-Methane Calculated Spectroscopic Database [594]

* TheoReTS – Theoretical Reims-Tomsk Spectral data [310]

* TIPS – Total Internal Partition Sums

* TROPOMI – Tropospheric Monitoring Instrument [22]

* UCL – University College London

* ULB – Université Libre de Bruxelles

* UV – Ultraviolet

* UVES – Ultraviolet-Visual Echelle Spectrograph [909]

* VAMDC – Virtual Atomic and Molecular Data Centre [656]

* VLIDORT – Vector Linearized Discrete Ordinate Radiative Transfer [34]

* VP – Voigt profile

## Supplementary material

Supplementary material associated with this article can be found, in the online version, at 10.1016/j.jqsrt.2021.107949

## References

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[2] McClatchey R, Benedict W, Clough S, Burch D, Calfee R, Fox K, et al. AFRL atmospheric absorption line parameters compilation. Environ Res Pap 1973;434:1–86. https://lweb.cfa.harvard.edu/HITRAN/Download/AFCRL73.pdf

[3] Rothman LS, McClatchey RA. Updating of the AFRL atmospheric absorption line parameters compilation. Appl Opt 1976;15(11):2616–17. doi:10.1364/AO.15.2616_1.

[4] Rothman LS. Update of the AFGL atmospheric absorption line parameters compilation. Appl Opt 1978;17(22):3517–18. doi:10.1364/AO.17.003517.

[5] Rothman LS, Clough SA, McClatchey RA, Young LG, Snider DE, Goldman A. AFGL trace gas compilation. Appl Opt 1978;17(4):507. doi:10.1364/AO.17.000507.

[6] Rothman LS, Goldman A, Gillis JR, Tipping RH, Brown LR, Margolis JS, et al. AFGL trace gas compilation: 1980 version. Appl Opt 1981;20(8):1323–8. doi:10.1364/AO.20.0001323.

[7] Rothman LS, Gamache RR, Barbe A, Goldman A, Gillis JR, Brown LR, et al. AFGL atmospheric absorption line parameters compilation: 1982 edition. Appl Opt 1983;22(15):2247–56. doi:10.1364/AO.22.0002247.

[8] Rothman LS, Goldman A, Gillis JR, Gamache RR, Pickett HM, Poynter RL, et al. AFGL trace gas compilation: 1982 version. Appl Opt 1983;22(11):1616–27. doi:10.1364/AO.22.0001616.

[9] Rothman LS, Gamache RR, Goldman A, Brown LR, Toth RA, Pickett HM, et al. The HITRAN database: 1986 edition. Appl Opt 1987;26:4058–97. doi:10.1364/AO.26.004058.

[10] Rothman L, Gamache R, Tipping R, Rinsland C, Smith M, Benner D, et al. The HITRAN molecular database: editions of 1991 and 1992. J Quant Spectrosc Radiat Transf 1992;48(5-6):469–507. doi:10.1016/0022-4073(92)90115-K.

[11] Rothman LS, Rinsland CP, Goldman A, Massie ST, Edwards DP, Flaud J-M, et al. The HITRAN molecular spectroscopic database and HAWKS (HITRAN atmospheric workstation): 1996 edition. J Quant Spectrosc Radiat Transf 1998;60:665–710. doi:10.1016/S0022-4073(98)00078-8.

[12] Rothman LS, Barbe A, Benner DC, Brown LR, Camy-Peyret C, Carleer MR, et al. The HITRAN molecular spectroscopic database: edition of 2000 including updates through 2001. J Quant Spectrosc Radiat Transf 2003;82:5–44. doi:10.1016/S0022-4073(03)00146-8.

[13] Rothman LS, Jacquemart D, Barbe A, Chris Benner D, Birk M, Brown LR, et al. The HITRAN 2004 molecular spectroscopic database. J Quant Spectrosc Radiat Transf 2005;96:139–204. doi:10.1016/j.jqsrt.2004.10.008.

[14] Rothman LS, Gordon IE, Barbe A, Benner DC, Bernath PF, Birk M, et al. The HITRAN 2008 molecular spectroscopic database. J Quant Spectrosc Radiat Transf 2009;110:533–72. doi:10.1016/j.jqsrt.2009.02.013.

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[33] Desouza-Machado S, Larrabee Strow L, Motteler H, Hannon S. kCARTA: a fast pseudo line-by-line radiative transfer algorithm with analytic Jacobians, fluxes, nonlocal thermodynamic equilibrium, and scattering for the infrared. Atmos Meas Tech 2020;13:323–39. doi:10.5194/amt-13-323-2020.

[34] Spurr RJ. VLIDORT: a linearized pseudo-spherical vector discrete ordinate radiative transfer code for forward model and retrieval studies in multilayer multiple scattering media. J Quant Spectrosc Radiat Transf 2006;102(2):316–42. doi:10.1016/j.jqsrt.2006.05.005.

[35] Irwin PGJ, Teanby NA, de Kok R, Fletcher LN, Howett CJA, Tsang CCC, et al. The
* REST API – Representational state transfer application programming interface

* RFM – Reference Forward Model [30]

* RI – Refractive indices

* RKR – Rydberg-Klein-Rees

* RMS – Root mean square

* RT – Rototranslational

* S&MPO – Spectroscopy and Molecular Properties of Ozone [194]

* SB RAS – Siberian Branch, Russian Academy of Sciences

* SDV – Speed-dependent Voigt

* SEOM-IAS – Scientific Exploitation of Operational Missions - Improved Atmospheric Spectroscopy Databases

* SHeCaSDa – Sulfur Hexafluoride Calculated Spectroscopic Database [594]

* SI – Système International

* SISAM – Spectromètre Interférentiel à Sélection par l'Amplitude de la Modulation (Interferential Spectrometer by Selection of Amplitude Modulation)

* SNR – Signal to noise ratio

* SOA – Secondary organic aerosol

* SRP – Standard reference photometer

* TCCON – Total Carbon Column Observing Network [145,146]

* TEMPO – Tropospheric Emissions: Monitoring of Pollution [25]

* TES – Tropospheric Emission Spectrometer [19]

* TFMeCaSDa – TetraFluoro-Methane Calculated Spectroscopic Database [594]

* TheoReTS – Theoretical Reims-Tomsk Spectral data [310]

* TIPS – Total Internal Partition Sums

* TROPOMI – Tropospheric Monitoring Instrument [22]

* UCL – University College London

* ULB – Université Libre de Bruxelles

* UV – Ultraviolet

* UVES – Ultraviolet-Visual Echelle Spectrograph [909]

* VAMDC – Virtual Atomic and Molecular Data Centre [656]

* VLIDORT – Vector Linearized Discrete Ordinate Radiative Transfer [34]

* VP – Voigt profile

## Supplementary material

Supplementary material associated with this article can be found, in the online version, at 10.1016/j.jqsrt.2021.107949

## References

[1] Rothman LS. History of the HITRAN database. Nat Rev Phys 2021;0123456789. doi:10.1038/s42254-021-00309-2. http://www.nature.com/articles/s42254-021-00309-2

[2] McClatchey R, Benedict W, Clough S, Burch D, Calfee R, Fox K, et al. AFRL atmospheric absorption line parameters compilation. Environ Res Pap 1973;434:1–86. https://lweb.cfa.harvard.edu/HITRAN/Download/AFCRL73.pdf

[3] Rothman LS, McClatchey RA. Updating of the AFRL atmospheric absorption line parameters compilation. Appl Opt 1976;15(11):2616–17. doi:10.1364/AO.15.2616_1.

[4] Rothman LS. Update of the AFGL atmospheric absorption line parameters compilation. Appl Opt 1978;17(22):3517–18. doi:10.1364/AO.17.003517.

[5] Rothman LS, Clough SA, McClatchey RA, Young LG, Snider DE, Goldman A. AFGL trace gas compilation. Appl Opt 1978;17(4):507. doi:10.1364/AO.17.000507.

[6] Rothman LS, Goldman A, Gillis JR, Tipping RH, Brown LR, Margolis JS, et al. AFGL trace gas compilation: 1980 version. Appl Opt 1981;20(8):1323–8. doi:10.1364/AO.20.0001323.

[7] Rothman LS, Gamache RR, Barbe A, Goldman A, Gillis JR, Brown LR, et al. AFGL atmospheric absorption line parameters compilation: 1982 edition. Appl Opt 1983;22(15):2247–56. doi:10.1364/AO.22.0002247.

[8] Rothman LS, Goldman A, Gillis JR, Gamache RR, Pickett HM, Poynter RL, et al. AFGL trace gas compilation: 1982 version. Appl Opt 1983;22(11):1616–27. doi:10.1364/AO.22.0001616.

[9] Rothman LS, Gamache RR, Goldman A, Brown LR, Toth RA, Pickett HM, et al. The HITRAN database: 1986 edition. Appl Opt 1987;26:4058–97. doi:10.1364/AO.26.004058.

[10] Rothman L, Gamache R, Tipping R, Rinsland C, Smith M, Benner D, et al. The HITRAN molecular database: editions of 1991 and 1992. J Quant Spectrosc Radiat Transf 1992;48(5-6):469–507. doi:10.1016/0022-4073(92)90115-1.

[11] Rothman LS, Rinsland CP, Goldman A, Massie ST, Edwards DP, Flaud J-M, et al. The HITRAN molecular spectroscopic database and HAWKS (HITRAN atmospheric workstation): 1996 edition. J Quant Spectrosc Radiat Transf 1998;60:665–710. doi:10.1016/S0022-4073(98)00078-8.

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[13] Rothman LS, Jacquemart D, Barbe A, Chris Benner D, Birk M, Brown LR, et al. The HITRAN 2004 molecular spectroscopic database. J Quant Spectrosc Radiat Transf 2005;96:139–204. doi:10.1016/j.jqsrt.2004.10.008.

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[37] Villanueva GL, Smith MD, Protopapa S, Faggi S, Mandell AM. Planetary spectrum generator: an accurate online radiative transfer suite for atmospheres, comets, small bodies and exoplanets. J Quant Spectrosc Radiat Transf 2018;217:86-104. doi:10.1016/j.jqsrt.2018.05.023.

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[40] Titov DV, Svedhem H, McCoy D, Lebreton JP, Barabash S, Bertaux JL, et al. Venus express: scientific goals, instrumentation, and scenario of the mission. Cosm Res 2006;44(4):334-48. doi:10.1134/S0010952506040071.

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[42] Korablev O, Montmessin F, Trokhimovskiy A, Fedorova AA, Shakun AV, Grigoriev AV, et al. The Atmospheric Chemistry Suite (ACS) of three spectrometers for the ExoMars 2016 trace gas orbiter. Space Sci Rev 2018;214(1):29. doi:10.1007/s11214-017-0437-6.

[43] Vandaele AC, Lopez-Moreno J-J, Patel MR, Bellucci G, Daerden F, Ristic B, et al. NOMAD, an integrated suite of three spectrometers for the ExoMars trace gas mission: technical description, science objectives and expected performance. Space Sci Rev 2018;214(5):80. doi:10.1007/s11214-018-0517-2.

[44] Jaffe LD, Herrell LM. Cassini/Huygens science instruments, spacecraft, and mission. J Space Rocket 1997;34(4):509-21. doi:10.2541/2.3241.

[45] Tsiaras A, Waldmann IP, Rocchetto M, Varley P, Morello G, Damiano M, et al. A new approach to analyzing HST spatial scans: the transmission spectrum of HD 209458 b. Astrophys J 2016;832(2). doi:10.3847/0004-637X/832/2/202.

[46] Baudino J-L, Mollière P, Venot O, Tremblin P, Bézard B, Lagage P-O. Toward the analysis of JWST exoplanet spectra: identifying troublesome model parameters. Astrophys J 2017;850(2). doi:10.3847/1538-4357/aa95be.

[47] Tinetti G, Drossart P, Eccleston P, Hartogh P, Heske A, Leconte J, et al. A chemical survey of exoplanets with ARIEL. Exp Astron 2018;46(1):135-209. doi:10.1007/s10686-018-9598-x.

[48] Bertaux JL, Lallemand R, Ferron S, Boonje C, Bodichon R. TAPAS, a web-based service of atmospheric transmission computation for astronomy. Astron Astrophys 2014;564:46. doi:10.1051/0004-6361/201322383.

[49] Tan Y, Kochanov RV, Rothman LS, Gordon IE. Introduction of water-vapor broadening parameters and their temperature-dependent exponents into the HITRAN database: Part I—CO₂, N₂O, CO, CH₄, O₂, NH₃, and H₃S. J Geophys Res (Atmos) 2019;124(21) 580-11. doi:10.1029/2019JD030929.

[50] Hill C, Gordon IE, Rothman LS, Tennyson J. A new relational database structure and online interface for the HITRAN database. J Quant Spectrosc Radiat Transf 2013;130:51-61. doi:10.1016/j.jqsrt.2013.04.027.

[51] Hill C, Gordon IE, Kochanov RV, Barrett L, Wilzewski JS, Rothman LS. HITRAN-Online: an online interface and the flexible representation of spectroscopic data in the HITRAN database. J Quant Spectrosc Radiat Transf 2016;177:4-14. doi:10.1016/j.jqsrt.2015.12.012.

[52] Kochanov RV, Gordon IE, Rothman LS, Wcisło P, Hill C, Wilzewski JS. HITRAN Application Programming Interface (HAPI): a comprehensive approach to working with spectroscopic data. J Quant Spectrosc Radiat Transf 2016;177:15-30. doi:10.1016/j.jqsrt.2016.03.005.

[53] Rothman LS, Gordon IE, Barber RJ, Dothe H, Gamache RR, Goldman A, et al. HITEMP, the high-temperature molecular spectroscopic database. J Quant Spectrosc Radiat Transf 2010;111:2139-50. doi:10.1016/j.jqsrt.2010.05.001.

[54] Rothman LS, Wattson RB, Gamache R, Schroeder JW, McCann A. HITRAN HAWKS and HITEMP: high-temperature molecular database. In: Dainty JC, editor. Atmospheric propagation and remote sensing IV. Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, 2471; 1995. p. 105-11. doi:10.1117/12.211919.

[55] Hargreaves RJ, Gordon IE, Rothman LS, Tashkun SA, Perevalov VI, Lukashevskaya AA, et al. Spectroscopic line parameters of NO, NO₂, and N₂O for the HITEMP database. J Quant Spectrosc Radiat Transf 2019;232:35-53. doi:10.1016/j.jqsrt.2019.04.040.

[56] Hargreaves RJ, Gordon IE, Rey M, Nikitin AV, Tyuterek VG, Kochanov RV, et al. An accurate, extensive, and practical line list of methane for the HITEMP database. Astrophys J Suppl Ser 2020;247(2). doi:10.3847/1538-4365/ab7a1a.

[57] De Biévre P, Gallet M, Holden NE, Barnes IL. Isotopic abundances and atomic weights of the elements. J Phys Chem Ref Data 1984;13(3):809-91. doi:10.1063/1.555720.

[58] Furtenbacher T, Császár AG, Tennyson J. MARVEL: measured active rotational-vibrational energy levels. J Mol Spectrosc 2007;245:115-25. doi:10.1016/j.jms.2007.07.005.

[59] Furtenbacher T, Császár AG. MARVEL: measured active rotational-vibrational energy levels. II. Algorithmic improvements. J Quant Spectrosc Radiat Transf 2012;113:929-35. doi:10.1016/j.jqsrt.2012.01.005.

[60] Tennyson J, Bernath PF, Brown LR, Campargue A, Császár AG, Daumont L, et al. A database of water transitions from experiment and theory (IUPAC technical report). Pure Appl Chem 2014;86:71-83. doi:10.1515/pac-2014-5012.

[61] Toth RA. Linelist of water vapor parameters from 500 to 8000 cm⁻¹; 2009. https://mark4sun.jpl.nasa.gov/h2o.html.

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[88] Wilson EM, Wenger JC, Venables DS. Upper limits for absorption by water vapor in the near-UV. J Quant Spectrosc Radiat Transf 2016;170:194-9. doi:10.1016/j.jqsrt.2015.11.015.

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[91] Mikhailenko S, Kassi S, Mondelain D, Campargue A. Water vapor absorption between 5690 and 8340 cm⁻¹: accurate empirical line centers and validation tests of calculated line intensities. J Quant Spectrosc Radiat Transf 2020;245:106840. doi:10.1016/j.jqsrt.2020.106840.

[92] Bubukina II, Polyansky OL, Zobov NF, Yurchenko SN. Optimized semiempirical potential energy surface for H₂¹⁶O up to 26 000 cm⁻¹. Opt Spectrosc 2011;110:160-6. doi:10.1134/S0030400X11020032.

[93] Mizus II, Kyuberis AA, Zobov NF, Makhnev VY, Polyansky OL, Tennyson J. High accuracy water potential energy surface for the calculation of infrared spectra. Philos Trans R Soc Lond A 2018;376:20170149. doi:10.1098/rsta.2017.0149.

[94] Császár AG, Furtenbacher T. Spectroscopic networks. J Mol Spectrosc 2011;266:99-103. doi:10.1016/j.jms.2011.03.031.

[95] Tóbiás R, Furtenbacher T, Simkö I, Császár AG, Diouf ML, Cozijn FMJ, et al. Spectroscopic-network-assisted precision spectroscopy and its application to water. Nat Commun 2020;11(1):1708. doi:10.1038/s41467-020-15430-6.

[96] Furtenbacher T, Tóbiás R, Tennyson J, Polyansky OL, Császár AG. W2020: a database of validated rovibrational experimental transitions and empirical energy levels of H₂¹⁶O. J Phys Chem Ref Data 2020;49(3):033101. doi:10.1063/5.0008253.

[97] Furtenbacher T, Tóbiás R, Tennyson J, Polyansky OL, Kyuberis AA, Ovsyannikov RI, et al. The W2020 database of validated rovibrational experimental transitions and empirical energy levels of water isotopologues. II. H₂¹⁷O and H₂¹⁸O with an update to H₂¹⁶O. J Phys Chem Ref Data 2020;49(4):043103. doi:10.1063/5.00030680.

[98] Conway EK, Gordon IE, Polyansky OL, Tennyson J. Determination of quantum labels based on projections of the total angular momentum on the molecule-fixed axis. J Quant Spectrosc Radiat Transf 2021;270:107716. doi:10.1016/j.jqsrt.2021.107716.

[99] Hose G, Taylor HS. Quantum Kolmogorov-arnol'd-moser-like theorem: fundamentals of localization in quantum theory. Phys Rev Lett 1983;51:947-50. doi:10.1103/PhysRevLett.51.947.

[100] Tennyson J, Kostin MA, Barletta P, Harris GJ, Polyansky OL, Ramanlal J, et al. DVR3D: a program suite for the calculation of rotation-vibration spectra of triatomic molecules. Comput Phys Commun 2004;163:85-116. doi:10.1016/j.cpc.2003.10.003.

[101] Harder JW, Brault JW. Atmospheric measurements of water vapor in the 442-nm region. J Geophys Res Atmos 1997;102(D5):6245-52. doi:10.1029/96JD01730.

[102] Loos J, Birk M, Wagner G. Measurement of air-broadening line shape parameters and temperature dependence parameters of H₂O lines in the spectral ranges 1850-2280 cm⁻¹ and 239-4000 cm⁻¹. J Quant Spectrosc Radiat Transf 2017;203:103-18. doi:10.1016/j.jqsrt.2017.03.033. HITRAN2016 Special Issue

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[104] Birk M, Wagner G, Loos J, Lodi L, Polyansky OL, Kyuberis AA, et al. Accurate line intensities for water transitions in the infrared: comparison of theory and experiment. J Quant Spectrosc Radiat Transf 2017;203:88-102. doi:10.1016/j.jqsrt.2017.03.040. HITRAN2016 Special Issue

[105] Conway EK, Gordon IE, Polyansky OL, Tennyson J. Use of the complete basis set limit for computing highly accurate ab initio dipole moments. J Chem Phys 2020;152(2):024105. doi:10.1063/1.5135931.

[106] Toth RA, Sung K, Brown LR. H₂¹⁶O line strengths revisited: v₂ and 2v₂- v₂ at 6 µm. J Mol Spectrosc 2011;265(2):59-68. doi:10.1016/j.jms.2010.10.009.

[107] Campargue A, Kassi S, Yachmenev A, Kyuberis AA, Küpper J, Yurchenko SN. Observation of electric-quadrupole infrared transitions in water vapor. Phys Rev Res 2020;2:023091. doi:10.1103/PhysRevResearch.2.023091.

[108] Campargue A, Solodov AM, Solodov AA, Yachmenev A, Yurchenko SN. Detection of electric-quadrupole transitions in water vapour near 5.4 and 2.5 µm. Phys Chem Phys Chem 2020;22(22):12476-81. doi:10.1039/d0cp01667e.

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[110] Owens A, Yachmenev A. Richmol: a general variational approach for rovibrational molecular dynamics in external electric fields. J Chem Phys 2018;148(12):124102. doi:10.1063/1.5023874.

[111] Borger C, Beirle S, Dörner S, Sihler H, Wagner T. Total column water vapour

retrieval from S-5P/TROPOMI in the visible blue spectral range. Atmos Meas Tech 2020;13(5):2751-83. doi:10.5194/amt-13-2751-2020.

[112] Wallace L, Livingston W. An atlas of the solar spectrum in the infrared from 1850 to 9000 cm⁻¹ (1.1 to 5.4 micrometer); 2003.

[113] Tanaka M, Naumenko O, Brault JW, Tennyson J. Fourier transform absorption spectra of H₂¹⁸O and H₂¹⁷O in the 3v+δ and 4v polyad region. J Mol Spectrosc 2005;234(1):1-9. doi:10.1016/j.jms.2005.07.007.

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