Review of the manuscript titled “Evaluation of hydroclimatic variables over Nordic Fennoscandia using WRF-CTSM”.

This paper integrates ELM v2.1 with the Weather Research and Forecasting (WRF) Model through a modified Lightweight Infrastructure for Land Atmosphere Coupling (LILAC) framework, enabling affordable high-resolution regional modeling by leveraging ELM’s innovative features alongside WRF’s diverse atmospheric parameterization options. High-resolution (4 km) WRF-ELM ensemble simulations over the Great Lakes Region (GLR) in the summer of 2018 are evaluated with observations, reanalysis data, and the WRF-CTSM. The manuscript is very well-written and has a very nice flow to it. I have some minor comments and suggestions to strengthen the manuscript:

1. Figure 6: The numbers on the top right of (c)-(f) indicate the spatial correlation coefficient between each reanalysis product and the two simulation results. However, the numbers and figure 6f are missing.
2. The partitioning of surface energy between latent and sensible heat fluxes plays an important role in regulating heat and water exchange between the land surface and the atmosphere. The spatial distributions of latent and sensible heat fluxes should be evaluated in the manuscript.

This study introduces the development of the U.S. Department of Energy’s Energy Exascale Earth System Model (E3SM) Land Model (ELM) with Weather Research and Forecasting (WRF) Model coupled by a modified Lightweight Infrastructure for Land-Atmosphere Coupling (LILAC) framework (WRF-ELM v1.0). It is well-written and easy to understand. The method is publishable to improve the performance of land-atmosphere interaction in the land surface model regarding land heterogeneity. However, it will need major and minor revisions before it is considered for publication. This is because the authors made ESMF coupler (LILAC) but did not provide any improved performance of the model. Please see the following comments:

General/ Major Comments:

1) Land-atmosphere interactions (Atmosphere-land interaction in the title):

How much does WRF-ELM improve to represent land-atmosphere interaction? Figures and tables in the paper show that WRF-ELM and WRF-CTSM have similar performances (surface sensible heat flux looks improved). The authors show figures of energy fluxes/temperature (land) and precipitation (atmosphere) but do not include information about land-atmosphere interaction.

2)  Heterogeneous Land Use:

Table 3 and figure 11 are made by forest regions from AmeriFlux. It is hard to generalize that the improvement in the model within only forest regions and the time series and biases of AmeriFlux are not matched with both models.

3) Urban heat island (UHI):

It is suspicious that figure 9 is related to UHI, urban physics. It looks like more depending on the location by lake physics. Urban locations are closer than crop ones from the lake. For the maximum temperature from the diurnal cycle, urban regions are cooler than crop regions . It would not be the proper representation of UHI. It would be better to write the representation of lake breezes on urbanization in models, as mentioned in Wang et al. (2023), authors’ reference. FYI, ASOS sites also show that urbans are cooler than crops.

Minor Comments:

1) Figure1: There are lots of abbreviations. It would be needed to make a supplementary table to explain them.

2) Figure 4 and MPI: If geographic domain is 7 x 4 gird cells, does MPI not work due to P0 is not equal to P1?

3) Table 2: NCEP Stabe IV dataset missed.

4) I may think that figure 7 and L346 – 347 are not necessary. I am not sure about the relationship between spatial smoothing and land heterogeneity.

5)  Are soil properties updated in WRF-ELM?

Other comments:

1) Title: “Atmosphere-land” but “Land-atmosphere” in the context.

2) Figure 2 and L262: Plant functional type (PFT)