This manuscript presents a rigorous, multi-season evaluation of the NOAA HRRR model v4 in the U.S. Northeast coastal marine boundary layer using unique, high-quality remote sensing observations from WFIP3. The work addresses a critical knowledge gap and delivers clear, physically consistent results relevant to offshore wind energy, aviation, and marine forecasting. The paper is well-structured, technically sound, and I have only four major comments:

Major Comments:

1. The manuscript suggests that overestimated SST contributes to warm biases near the bottom of the stability layer and therefore to underestimated static stability. This is plausible and supported by the weak negative correlation between SST error and stability error at NANT and BLOC. However, the correlations are modest, and the relationship is not evident at RHOD. Therefore, the causal wording should be softened in places. For example, instead of implying that SST errors are the primary cause of stability errors, the authors could state that SST errors are “a likely contributing factor,” particularly for island sites and southwesterly flow regimes. Other possible contributors, such as boundary-layer mixing, surface-layer parameterization, vertical resolution, land–sea mask representation, and horizontal advection errors, should also be acknowledged. This would make the interpretation more balanced and avoid over-attribution.2. Site Representation Uncertainty
2. The authors use a modified Bonner-type LLJ criterion with a wind speed threshold of 8 m s⁻¹, which is lower than in some previous studies. The justification is that many profiles with clear LLJ structure would otherwise be missed. This is reasonable, but the choice of threshold can strongly influence LLJ frequency, CSI, frequency bias, and the classification of weak LLJs. Since about 35–40% of observed LLJs are classified as the weakest class 0, the results may be sensitive to this threshold. I suggest adding a short sensitivity test, perhaps in the supplement, showing how LLJ frequency and model skill change if a 10 m s⁻¹ threshold is used. Even a brief comparison would help readers assess whether the main conclusions are robust to the LLJ definition.
3. The analysis of bulk Richardson number is a strong part of the manuscript. The finding that HRRR underrepresents low-Ri regimes during LLJ hits is important because it links wind and thermodynamic errors to the dynamic stability of the marine boundary layer. However, the physical implications could be explained more clearly. For instance, if the model overestimates Ri because it underestimates shear more strongly than it underestimates static stability, this could imply that the model boundary layer is dynamically too stable, potentially affecting turbulent mixing, rotor-layer structure, wind-energy-relevant shear, and LLJ maintenance. The authors should briefly discuss how this error might influence forecast applications and model physics development.
4. The discussion of HRRR errors in low-level temperature, static stability, and wind shear could be strengthened by briefly considering uncertainties in surface energy budget representation. The manuscript mainly attributes some near-surface errors to SST and land-sea thermal contrast, which is reasonable. However, other surface energy exchange processes may also influence boundary-layer structure, especially under precipitation conditions. Studies (Gillett & Cullen. 2011; Zhou et al. 2024a,b) have shown that precipitation-induced surface sensible heat flux, a process often neglected in weather and climate models, can modify surface energy partitioning and affect regional simulations. I suggest that the authors briefly discussing broader uncertainties in surface energy budget processes and model physics.

Gillett, S., & Cullen, N. J. (2011). Atmospheric controls on summer ablation over Brewster Glacier, New Zealand. International Journal of Climatology, 31(13), 2033–2048.

Zhou, X., Ray, P., Tan, H., Dudhia, J., Ajayamohan, R. S., Gomes, H., & Pan, Y. (2024). Rain‐induced surface sensible heat flux reduces monsoonal rainfall over India. Geophysical Research Letters, 51(14), e2023GL107796

Zhou, X., Ray, P., Dudhia, J., Tewari, M., Nikolopoulos, E., Johnson, N. C., & Hagos, S. (2024). On the importance of precipitation‐induced surface sensible heat flux for diurnal cycle of precipitation in the maritime continent. Geophysical Research Letters, 51, e2024GL111940.

Minor comments:

1. The abstract is clear and informative, but the statement that SST errors partly explain the weakened stability should be phrased cautiously because the evidence is site-dependent and correlations are weak to moderate.
2. In Sect. 3.2, the authors show that wind speed standard deviation increases with forecast hour, while mean biases remain relatively stable. This is an interesting result and could be highlighted more clearly as evidence that forecast variability errors grow faster than systematic mean errors.
3. The conclusion should more clearly separate robust findings from site-specific findings. For example, the underestimation of static stability appears robust across sites, while the source of shear error differs by site.

Please see attached.