Estimation of Urban Evapotranspiration at High Spatiotemporal Resolution and Considering Flux Footprints
Round 1
Reviewer 1 Report
Urban ET estimation remains a major challenge in current urban hydrology and regional climate research. This study proposed an urban ET model (PT-Urban) to estimate half-hourly ET at a 10-m resolution. The PT-Urban model was validated using observations from the Hotel Torni urban flux site during the 2018 growing season. Results show that PT-Urban performed well with an R2 and RMSE of 0.59 and 14.67 W m-2, respectively. Further analysis demonstrated that urban canopy heat storage and shading effects are essential for half-hourly urban energy balance, and ignoring shading effects led to a 38.7% overestimation of urban ET. In general, the manuscript is interesting to me, and the method is new and feasiable for urban ET estimation. In my opinion, the paper can be accepted for publication after minor revisions.
Minor comments:
1. What do you mean about the footprint of flux? it is not easy to understand. Please clarify the words (footprint) in the study.
2. Please add a time-series comparison of urban ET, since it is also important to show the temporal variation (e.g., diurnal change) in ET.
3. Figure 10 can be improved. It is not so clear.
Author Response
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Reviewer 2 Report
This work overall provides a limited analysis of the impacts of input flux footprint estimation, inclusion of shadowing in urban environments and to some extent the selection of NDVI/EVI on estimates of urban evapotransportation. The authors presentation of their findings is very reasonable way, with logical flow, and the introduction is very well though out and comprehensive. A modest of scrub of the English would be appropriate.
While this work does seem to demonstrate a modest improvement in ET for a single point over a very narrow period of time, its hard to tell if what if any these findings would have a similar impact at different sights, i.e. how generally applicable it is to modeling of urban ET or how transferable it is to different season or annual period. Can I used the 2018 data to enhance estimates of LE in 4/2018 or 9-10/2018 or 2017 or 2019 what about in Oslo. It seems like the majority of the data are used to develop the time varying footprints and only a small fraction intermixed with the training data are used to validate the model for the same point in time and space. Its not surprising that you get some benefit from using coincident truth data to inform ones estimates of any quantity. It's hard to say if it's the footprint or simply the fact that one used similar data to derive a weight that steers the answer in the correct direction. Unless one can use the model in an alternative time/space environment its hard to say if the model describes a general approach or just the conditions for a single location and time period. I don't think there is any question that there are a number of complex factors that drive, especially in urban environments, our understanding of the behavior of LE or other surface/atmospheric state parameters , but our understanding needs to be transferable to new locations and/or times to add value. While this work tries to indication that data is collected at multiple sites, the LE data used are only from a single location, and why the weather data were obtained from an alternative location is not well justified.
Overall I think this work does help illustrate that urban specific modeling approaches would most likely help in the estimation of urban LE, it lacks any strong quantitative evidence that the approach truly addresses a major contribution to errors in urban LE, and can be transferable to other locations or times. I have added some specific inline comments and possible alterations in the text
Comments for author File: 
Comments.pdf
Author Response
Thank you for your comments. The response to your comments has been uploaded in the attachment.
Author Response File: Author Response.docx
Round 2
Reviewer 2 Report
I think the author provided revisions have address the majority of the review comments, and I now think this work should be considered for publications with reservations. I still believe that the inherent correlation over the proposed very short time window may contribute significantly to the modeling efforts and not so much its representation of the underlaying general physical behavior.
I also think that the work by Lindburg et. al may have been for as the abstract suggests "The model is evaluated using 5 days of integral radiation measurements at two sites within a square surrounded by low-rise buildings and vegetation in Göteborg, Sweden (57°N)." not in Switzerland as stated by the authors. This should be addressed.
Author Response
Thank you for your comments. The response to your comments has been uploaded in the attachment.
Author Response File: Author Response.docx
