Please refer to attached comments.

General comments

Accurate estimation and partitioning of evapotranspiration (ET) are critical for understanding land–atmosphere interactions, yet current land surface models (LSMs) still exhibit notable deficiencies in representing transpiration and evaporation, particularly soil evaporation. In this study, the authors introduce a dry surface layer (DSL) resistance parameterization into the ISBA model and conduct simulations and evaluations at two contrasting semi-arid sites, leveraging comprehensive observational data from the LIAISE campaign. Their results demonstrate that the new DSL parameterization effectively reduces bare soil evaporation and helps address existing shortcomings in ET modeling, offering valuable insights for improving LSM performance in estimating evapotranspiration.

The manuscript is well-organized, with a robust methodological approach and substantial supporting data. The logical structure and discussion are also appropriate. However, the text is somewhat lengthy, and there is room for improvement in both language clarity and figure presentation. Revisions are necessary before the manuscript can be considered for publication.

The estimation of soil evaporation and DSL resistance is influenced by soil state variables such as soil moisture and soil temperature. However, the simulation results of these variables presented in this study (Figures 10 and 11) appear to be unsatisfactory, which raises concerns about the reliability of subsequent model evaluation outcomes.

It is recommended to reorganize the introduction and Sect. 2.3.1 for improved clarity. Currently, the Introduction does not provide sufficient explanation of specialized terms such as soil resistance, particularly dry surface layer (DSL) resistance. As these concepts may not be familiar to the broader readership of GMD, it would be beneficial to consider moving part of the description of soil resistance from Sect. 2.3.1 into the Introduction.

Sect. 5.4 presents the results of the sensitivity analysis. However, it would be helpful to briefly introduce the concept of sensitivity analysis and the specific method adopted in this study in the earlier methodological sections. This would provide clearer context and improve the continuity of the manuscript.

Specific comments

Line 1: Latent heat flux (LE) and evapotranspiration are closely related but conceptually distinct terms, with different physical meanings and units. The manuscript should carefully review its use of both terms to avoid confusion. In particular, Figure 8 incorrectly labels the unit of LE as “mm,” which is not appropriate.

Line 61-64: It is recommended to number the four drying stages to make it easier for the reader to understand.

Line 83: The term “surface energy budget (SEB)” appears for the first time here, rather than at line 257.

Line 131: I don’t quite understand what N and X represent in this context.

Line 216: Please revise the citation “(Iden et al. 2021)” to “Iden et al., (2021)” to match the correct citation style. Similar formatting inconsistencies may exist elsewhere and should be reviewed.

Line 308: For La Cendrosa, irrigation was treated as rainfall by adding 30 mm of water between 00:00 and 02:00 UTC.

Line 323-324: While the alfalfa field is clearly identified as a C3 crop, the grass type used for Els Plans is not specified as either C3 or C4. Given that this distinction may affect model performance, the authors should clarify which type was used. Additionally, in Table 1, the crop is classified under the “C4 crop” category. Please check if this classification is correct.

Line 330-331: It would be helpful if the manuscript could briefly clarify what the “AST option” within SURFEX refers to.

Line 347: “is” to “in”.

Line 353: “one” to “1”.

Table 1: It is recommended to unify the formatting of the table and add border lines to both the top and bottom.

Figure 9: It is necessary to provide a clear explanation of the meaning of the error bars and the orange horizontal lines shown in the figure.