A New Method to Estimate Reference Crop Evapotranspiration from Geostationary Satellite Imagery: Practical Considerations
Round 1
Reviewer 1 Report
The manuscript entitled “A new approach to estimate reference crop evapotranspiration from geostationary satellite imagery: practical considerations” provides an interesting study about a new approach for assessing reference evapotranspiration combining remote sensing data and weather forecasts. In the revision process some concerns and comments have been identified:
Lines 13-14. Following the information indicated in Line 49, also weather forecast is required in the proposed approach. This must be indicated in the Abstract
Lines 109, 111, 218 and 253. Some mistakes are done in “Anadalucia”, “Cordoa”, “lysimter”, “equation”, respectively. Please correct.
Line 137. The equation is not clear. Please revise.
Line 166. Please, define bias here (the first time that this term appears in the manuscript)
Figure 1. This Figure must be replaced by a graph comparing ETo measurements in situ (in one axis) and ETo provided by LSA-SAF (in the other axis). It is required to explain if these measurements in situ are from lysimeter or by the weather station using PM. In addition, the ground conditions for this weather station is required.
Figure 2. The same comments than for Figure 1.
Lines 196-199. The equation (Ta-15) was found for Cordoba and it is described in the reference [3]. A discussion about the use of this equation in other locations is required.
Lines 220-222. Could you provide additional information of the origin of the term 0.8Q*? Which values could be considered outside of the April-September period (to be considered for example, for natural vegetation)?
Lines 271-274. Authors indicated that “ETo estimates using FAO PM methodology are very close to observations for both Cabauw (LAE-free) and Cordoba. The FAO PM methodology requires input data collected over a reference-like surface, otherwise…”. Where was located the weather station in Cordoba? Because analyzing the previous sentences the weather station in Cordoba must be on well-watered field conditions. However, the RIA station considering the text in Figure 5 was located over non-irrigated surface, and then this cannot be considered a reference conditions under the weather conditions of Cordoba. Were considered data from two weather stations in the same site, one under irrigated conditions and the other one on non-watered conditions? Could you describe the ground conditions and location of both weather stations?
Author Response
The authors would like to thank reviewer 1 for the careful report that was provided.
A point by point reply is provided in a separate document, where we have also indicated how the manuscript was revised to address the reviewer's remarks and requests for clarifications.
Author Response File: 
Author Response.docx
Reviewer 2 Report
======= MAIN Issues ============
== Is it new ? ==
I guess my biggest complaint is that pages 1-6 are basically the same as ref [3], and the discussion, which starts to talk about operational considerations, almost immediately [~line 200] requires the user to go back to that source for complete information , why not show PM-ETo on figures 1 & 2, and describe the bias and std dev. for PM-ETo as well.
== does it help operationally ? ==
Plus, I don't think the role of LAE in PM-ETo is really ambiguous, as you've said it's not a thermodynic model, and those transport mechanisms are accounted for in e_a and u2. And since you show PM-ETo is good, then it IS included in PM-ETo based advisories. So, that must mean is SHOULD be included in LSA-SAF advisories.
Also, from a operational standpoint, I don't think you given good advice on when to include Q_adv and when not to. Without this, everyone would add it, and then you are not helping reduce overwatering which is supposedly one main goal.
Finally from a practical standpoint, you used constants B=20 and Cs=110 in your note without ant discussion about if these are really constant everywhere?
===== Questions about the Figures, Implications =======
Figure 3. I don't really understand Figure 3 for Cordoba. You are saying that there is an additional Q_adv in Cordoba, say after 12. But that doesn't explain to me why H would be going negative at that time. Is that what the T-ABL model predicts? H=(1-EF)*(Q_* + Q_adv) (EF=evap fraction). If this added B term in ET (for non-saturated values) also affects H, then how? is H'=H-B? That sort of makes sense as a higher evaporated cooling, but then you should describe that explicitly.
• Figure 4, I_a, is this a maximum instantaneous or a daily measure?
• Figures 4,5, you say advection Index in text (sometimes Aridity too), and Aridity index in figures.
Figure 4,5 = I really don't know what you are trying to say with figures 4, and 5. You are comparing apples and oranges, or you are showing how good the PM-ETo is. I don't think you are showing the affect you are trying to show.
In figure 4, you show lysimeter ET vs Q*, fine. it's shows LAE. Then you show PM-ETo vs Q* and it looks similar, like it's effectively capturing LAE. So if the correlation of Lysimeter ET to PM-ETo is good, then those other weather parameters are just great. If they are off, but maybe you only needed to adjust T_a, then that supports your claim about measurements not over grass fields, but says nothing about PM-ETo and LAE.
And of course your LSA-SAF is most certainly affected by this index, you have to somehow decide if you need to include your LAE correction or not operationally beforehand, something you don't have to do with PM-ETo
====== SYNTAX ISSUES ================
You need to be very careful on defining which ETo you are is discussing.
Even after reading this, I don't know the difference between T-ABL vs LSA-SAF vs METRef of ETo. It seems to me T-ABL and LSA SAF are the same just where you specify the data source? We don't say PM-ETo and (Weather Station X) ETo
84, 120,137, etc. Ta= Mean Air Temp, but in FAO, Ta=(Tn+Tx)/2 not mean over day, if they are all the same, please Identify that Ta=(Tn+Tx)/2 for daily
[119.,235 etc] for latent heat of vaporization, I would prefer \lamba or \Delta H_vap over L.
==== Line by Line Issues ======
[1] 59-60 = This recent analysis should say T-ABL or LSA-SAF ETo not (ETo). It's a particular model that shows this, not eg. PM-ETo, although you could certainly make some estimate on an LAE contribution from there.
96. LSA SAF ETo
73 - reference [3] should be [2] or [2,3].
73-77 - Sentence is confusing, and missing info. "Provided well calibrated ????"
121. Under what conditions is constant B=20 valid?
122. Under what conditions is Cs=110 valid?
Maybe call these B_cob Cs_cob and then give numbers?
234-241 = Not sure what this paragraph is for? So, don't use this model? IF you want to show this, you can draw LINE graphs that compare T-ABL to HS and Makkink for various Q* and T with and without LAE right? Then do that.
248 = You didn't analyze ETo data you analyzed the weather parameters need to compute PM-ETo.
269:271 - PM-ETo absolutely assumes that Rs is the main driver of ET over it's reference surface. This is crazy talk.
272 - I believe your contention, but your Figure 5 doesn't validate that.
Author Response
The authors would like to thank reviewer 2 for the careful report that was provided.
A point by point reply is provided in a separate document, where we have also indicated how the manuscript was revised to address the reviewer's remarks and requests for clarifications.
Author Response File: Author Response.docx
Round 2
Reviewer 1 Report
The new version of the manuscript entitled “A new method to estimate reference crop evapotranspiration from geostationary satellite imagery: practical considerations” by de Bruin and Trigo has been significantly improved. All the comments and suggestions provided by this reviewer has been correctly done.
Reviewer 2 Report
Thank you to the authors. All of my concerns were addressed adequately
