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Peer review report 1 On “Relative humidity effects on water vapour fluxes measured with closed-path eddy-covariance systems with short sampling lines”
Agricultural and Forest Meteorology 201S (2015) 502–503
Contents lists available at ScienceDirect
Agricultural and Forest Meteorology journal homepage: www.elsevier.com/locate/agrformet
Peer Review Report
Peer review report 1 On “Relative humidity effects on water vapour fluxes measured with closed-path eddy-covariance systems with short sampling lines”
Original Submission Recommendation Minor Revision Comments to Author This manuscript studies the high frequency underestimation of water vapor flux measured by closed- path eddy covariance (EC) system. In particular the authors proposed a new method to estimate the low pass filter effects of water vapour and to derive the related correction factors. Recently, it has been recognized by few experimental studies the importance to account for this effect, as the H2O time lag and low pass filter time constant strongly depend on relative humidity. There is some uncertainty about which are the key factors describing such mechanism, and for this reason more empirical evidences are welcome. The manuscript is well written and most of the chapters easy to follow. However some of the methodologies and results/figures are not fully explained and the manuscript need some improvements. The major referee’s concerns are:
found. What is the physical meaning of this behavior? If you would use in the Eq.3 the temperature power spectra instead of cospectra, probably you will not get values of Fl <1. Please comment on this. 4) Related to the previous comment, I disagree with the author’s statement at Lines 384- 390. In fact, let’s assume that the sensible heat flux is positive. Now, if there are negative components at certain frequency bins of the corresponding temperature cospectrum (and these are more likely the situations when the denominator in eq.3 is larger than the numerator), this does not mean that negative components of LE cospectrum are found at the same frequency bins. Please comment on this. 5) In Figure 5 latent heat flux from HS-7000 and HS-7500 are compared. Although the direct method gives a better regression slope, the offset value become worse, highlighting that the method does not work properly when the fluxes are small. Please comment on this. Moreover the LE values from the two setups do not match. Any possible explanation for this systematic error? How about the CO2 fluxes? 6) Related to the previous comment, it would be interesting to see similar scatter plots between the closed-path systems. 1.1. Minor comments
1) The main difference between IF07 and the approach proposed in this study is how you calculate Fl (Eq. 3), where single measured cospectra of temperature are used. On the other hand, the method used to estimate fc is the same as in IF07 (Appendix A). Since the estimation of fc and its dependence on RH (Eq.2) is a crucial aspect, did the authors try to cross-validate the fc values with estimations derived by using ensemble cospectra and not power spectra? 2) I am not sure if the method used for estimating HIIR (and then fc) is fully corrected. In fact, in each RH bin the ensemble power spectra are used, and when you are averaging on many runs, in order to get free of different wind speed (between different runs) and possible shift of the power spectral densities, I suggest to apply the Eq. 1A to different classes of wind speed (for example 1 m/s width). The different estimates of fc should be quite similar, and anyway you may take the average value of those for each RH bin. 3) On line 229 and later on, the authors correctly mentioned that, with the direct method, correction factor less than one can be
DOI of published article: http://dx.doi.org/10.1016/j.agrformet.2012.05.018. 0168-1923/$ – see front matter http://dx.doi.org/10.1016/j.agrformet.2015.07.077
L.65. I would simply say “very close to the inlet sampling line”. L.87. I would replace “..have shown that the dampening and lagging effects are potentially. . .” with “have shown that the dampening and RH effects are potentially. . .”. L.128. Add a comma after 2.5 m L.158 Add a comma after power spectra. L.161. This is not necessarily true, if only periods, when the estimated time lags do no depart much from the regression curve of time lag as a function of RH, are used for the calculation of fc. L.197. Replace ‘are to be’ with ‘have to be’. L.221. Add a comma after ‘estimation of Fl’ and after ‘From this’. L.222. Replace ‘minimising’ with ‘to minimise’. L.255. You should mention here if you performed the dilution correction in case of Licor 7000. L.339 Is this the updated model? L352. This is Figure 4 and not Figure 3. L 369. Add a comma after smooth surfaces L.375 From Figure 6 I cannot see values of correction factor larger than 8. L.394. Fig. 7 is not so clear. I would suggest to merge the information from Fig. 6 and 7 in a new figure where the correction factor
Peer Review Report / Agricultural and Forest Meteorology 201S (2015) 502–503
are plotted as a function of a dimensionless variable equal to cU/z (where U is mean wind speed, z measurement height and c the estimated time constant) for different classes of stability. L 402. “This is shown in Figure 8,. . ..” L. 415. “The study showed”. To which study are you referring here? Fig. 1 Are those power spectra normalized? And how? If yes change the figure caption accordingly. Moreover the
503
dashed lines should be explained better. I guess they represent the normalized temperature power spectra multiplied by HIIR and Fn. Anonymous Available online 6 August 2015
Contents lists available at ScienceDirect
Agricultural and Forest Meteorology journal homepage: www.elsevier.com/locate/agrformet
Peer Review Report
Peer review report 1 On “Relative humidity effects on water vapour fluxes measured with closed-path eddy-covariance systems with short sampling lines”
Original Submission Recommendation Minor Revision Comments to Author This manuscript studies the high frequency underestimation of water vapor flux measured by closed- path eddy covariance (EC) system. In particular the authors proposed a new method to estimate the low pass filter effects of water vapour and to derive the related correction factors. Recently, it has been recognized by few experimental studies the importance to account for this effect, as the H2O time lag and low pass filter time constant strongly depend on relative humidity. There is some uncertainty about which are the key factors describing such mechanism, and for this reason more empirical evidences are welcome. The manuscript is well written and most of the chapters easy to follow. However some of the methodologies and results/figures are not fully explained and the manuscript need some improvements. The major referee’s concerns are:
found. What is the physical meaning of this behavior? If you would use in the Eq.3 the temperature power spectra instead of cospectra, probably you will not get values of Fl <1. Please comment on this. 4) Related to the previous comment, I disagree with the author’s statement at Lines 384- 390. In fact, let’s assume that the sensible heat flux is positive. Now, if there are negative components at certain frequency bins of the corresponding temperature cospectrum (and these are more likely the situations when the denominator in eq.3 is larger than the numerator), this does not mean that negative components of LE cospectrum are found at the same frequency bins. Please comment on this. 5) In Figure 5 latent heat flux from HS-7000 and HS-7500 are compared. Although the direct method gives a better regression slope, the offset value become worse, highlighting that the method does not work properly when the fluxes are small. Please comment on this. Moreover the LE values from the two setups do not match. Any possible explanation for this systematic error? How about the CO2 fluxes? 6) Related to the previous comment, it would be interesting to see similar scatter plots between the closed-path systems. 1.1. Minor comments
1) The main difference between IF07 and the approach proposed in this study is how you calculate Fl (Eq. 3), where single measured cospectra of temperature are used. On the other hand, the method used to estimate fc is the same as in IF07 (Appendix A). Since the estimation of fc and its dependence on RH (Eq.2) is a crucial aspect, did the authors try to cross-validate the fc values with estimations derived by using ensemble cospectra and not power spectra? 2) I am not sure if the method used for estimating HIIR (and then fc) is fully corrected. In fact, in each RH bin the ensemble power spectra are used, and when you are averaging on many runs, in order to get free of different wind speed (between different runs) and possible shift of the power spectral densities, I suggest to apply the Eq. 1A to different classes of wind speed (for example 1 m/s width). The different estimates of fc should be quite similar, and anyway you may take the average value of those for each RH bin. 3) On line 229 and later on, the authors correctly mentioned that, with the direct method, correction factor less than one can be
DOI of published article: http://dx.doi.org/10.1016/j.agrformet.2012.05.018. 0168-1923/$ – see front matter http://dx.doi.org/10.1016/j.agrformet.2015.07.077
L.65. I would simply say “very close to the inlet sampling line”. L.87. I would replace “..have shown that the dampening and lagging effects are potentially. . .” with “have shown that the dampening and RH effects are potentially. . .”. L.128. Add a comma after 2.5 m L.158 Add a comma after power spectra. L.161. This is not necessarily true, if only periods, when the estimated time lags do no depart much from the regression curve of time lag as a function of RH, are used for the calculation of fc. L.197. Replace ‘are to be’ with ‘have to be’. L.221. Add a comma after ‘estimation of Fl’ and after ‘From this’. L.222. Replace ‘minimising’ with ‘to minimise’. L.255. You should mention here if you performed the dilution correction in case of Licor 7000. L.339 Is this the updated model? L352. This is Figure 4 and not Figure 3. L 369. Add a comma after smooth surfaces L.375 From Figure 6 I cannot see values of correction factor larger than 8. L.394. Fig. 7 is not so clear. I would suggest to merge the information from Fig. 6 and 7 in a new figure where the correction factor
Peer Review Report / Agricultural and Forest Meteorology 201S (2015) 502–503
are plotted as a function of a dimensionless variable equal to cU/z (where U is mean wind speed, z measurement height and c the estimated time constant) for different classes of stability. L 402. “This is shown in Figure 8,. . ..” L. 415. “The study showed”. To which study are you referring here? Fig. 1 Are those power spectra normalized? And how? If yes change the figure caption accordingly. Moreover the
503
dashed lines should be explained better. I guess they represent the normalized temperature power spectra multiplied by HIIR and Fn. Anonymous Available online 6 August 2015