Thank you for the perceptive comments! Responses to them are as follows:

1. While LBLRTM also computes the gas absorption cross-sections from the HITRAN spectral line data, HAPI2LIBIS has several strengths and differences compared to it. HAPI2LIBIS is simpler and easier to use, with only two Python code files (one of which is the HITRAN API) and a configuration file, to create customized absorption molecular absorption file for libRadtran. In addition, HAPI2LIBIS automatically downloads the latest available molecular line data from the HITRAN database, so manual absorption line updating and configuration is unnecessary. In HAPI2LIBIS, it is possible to select which line broadening functions are utilized, and the computed absorption cross-sections are stored in a dynamic interpolation tables for reuse.
2. Almost always retrieval algorithms are based on pre-computed tables of spectral radiances or gas absorption cross-sections, so very rarely are line broadening calculations done on-the-fly, so to say. However, the interpolation from the HAPI2LIBIS tables is rapid, as long as sufficient amount of parameter points are added, so in principle it could be used to replace spectral absorption tables, such as ABSCO [1], within a retrieval algorithm. On the other hand, in some retrievals, such as CH4 profile retrieval algorithm SWIRLAB [2], the gas absorption cross-sections are computed as a part of the retrieval algorithm, because high spectral and temperature-pressure dependency accuracies are needed. In such retrieval algorithms, HAPI2LIBIS could prove to be practical.

We will revise the manuscript by adding a brief introduction to LBLRTM along with a discussion about the differences between it and HAPI2LIBIS. We will also add a paragraph with the focus on discussion about the computational efficiency aspect as per the suggestions.

References:

[1]: https://www.sciencedirect.com/science/article/pii/S0022407320302016

[2]: https://agupubs.onlinelibrary.wiley.com/doi/full/10.1002/2015JD024657

Thank you for the comments. Since the open discussion has closed, we will provide a brief initial response without going into detail here and address the concrete changes to improve the manuscript at a later time. Our responses are as follows.

1. We initially wrote the abstract to be concise and include only the main purpose/functionality of HAPI2LIBIS. However, we now see that the abstract is lacking necessary information about the techniques presented in the manuscript. We will extend the abstract to include these techniques and contributions and rephrase the abstract accordingly.
2. Thank you for the paper suggestions. While these models could be of use for libRadtran, it is up to the libRadtran authors to include them there. Some spectral RT speedup methods are already included in libRadtran, such as correlated-k and pseudo-spectral calculation. It must be noted that HAPI2LIBIS only creates the line-by-line input for libRadtran, whereas these methods are distinct approaches for handling spectral RT. Including fast, efficient, and accurate models for gas absorption in HAPI2LIBIS is something that could be added in the future. We will add a mention of fast models and their potential in the manuscript.
3. The difference plot between HAPI2LIBIS and REPTRAN will be added to the manuscript.
4. Fair comparison is presented in Figure 3. The purpose of Figure 4 is to demonstrate the effect of O3 in the wavelength range 630--635 nm and highlight the capability of HAPI2LIBIS to include new gas information, as in this particular case where the O3 absorption data is missing in HITRAN for this wavelength range. We will rephrase and expand the section where Figure 4 is shown to improve clarity and motivation for this figure.
5. Figure 5 will be clarified to make the altitude-dependence of the absorption lines more visible.
6. Despite the water vapour continuum absorption being available on HITRAN, we have decided to focus here on the distinct gas absorption lines. Continuum absorption could be included later on as part of HAPI2LIBIS, but for example, the MT_CKD_H2O continuum absorption model is released under a non-free license and would thus not be straightforward to include in HAPI2LIBIS.
7. Example image of the optical thickness of different gases in thermal infrared wavelength band will be included along with the appropriate discussion of the results.