|I would like to thank the authors for clarifying the concerns I had in the previous version of the manuscript and for having taken the time to detail the limitations of their study in the manuscript.|
I am however sorry to say that I have a major concern regarding the use of only one LST image for model evaluation. Former model evaluations that used LST tried to acquire as many images as possible for one period. The argument that Landsat 8 images is more representative of the heterogeneity of the surface urban climate is receivable but not sufficient. These heterogeneities are also captured by MODIS data for instance, although smoothed by the lower resolution. Bechtel et al. 2019 who did a somparative study of LST in different cities using LCZ, MODIS and Landsat data found out that there was a great spatial correlation between the two. I believe they should be used jointly. Hu et al. (2014), Wouters et al. (2016) and Brousse et al. (2020) also used MODIS LST for evaluation of their model simulations. I would therefore like the authors to include such additional evaluation before acceptance of the manuscript.
Finally, I still have some questions which I would like to see answered before accepting the manuscript for publication:
1. I still did not understand the rationale with having air temperature measured at the Pinggu station and upwind from the airport. The reasoning with the wind measurements being WMO standard makes sense. But then why not simply use the air temperature from the airport itself as it can be considered as rural too?
2. The implications on the results from adapting the surface resistance to evaporation for LCZ 4 6 and 9 need to be discussed.
Hu, L., Brunsell, N. A., Monaghan, A. J., Barlage, M., & Wilhelmi, O. V. (2014). How can we use MODIS land surface temperature to validate long‐term urban model simulations?. Journal of Geophysical Research: Atmospheres, 119(6), 3185-3201.
Wouters, H., Demuzere, M., Blahak, U., Fortuniak, K., Maiheu, B., Camps, J., ... & van Lipzig, N. P. (2016). The efficient urban canopy dependency parametrization (SURY) v1. 0 for atmospheric modelling: description and application with the COSMO-CLM model for a Belgian summer. Geoscientific Model Development, 9(9), 3027-3054.
Bechtel, B., Demuzere, M., Mills, G., Zhan, W., Sismanidis, P., Small, C., & Voogt, J. (2019). SUHI analysis using Local Climate Zones—A comparison of 50 cities. Urban Climate, 28, 100451.
Brousse, O., Wouters, H., Demuzere, M., Thiery, W., Van de Walle, J., & Van Lipzig, N. P. (2020). The local climate impact of an African city during clear‐sky conditions—Implications of the recent urbanization in Kampala (Uganda). International Journal of Climatology, 40(10), 4586-4608.