Modeling Solar Radiation Data for Reference Evapotranspiration Estimation at a Daily Time Step for Poland
Round 1
Reviewer 1 Report
Comments and Suggestions for AuthorsIn my opinion this article is a good approach to the study of solar energy and evapotranspiration, focused on local geographical and climate characteristics. It provides a clever indirect computation of solar energy concluding to the computation of ET. The study is clearly analyzed, and the reader could realize what and why is happening, especially when the difference between coastal and inland stations are studied. Of course the study can be characterized as average for me, but clear and helpful. I would like to see somewhere (for example tables) the real solar energy values and only the related statistics. Also, I would like to see a clearer Figure 2. Finally, “then” should be replaced by “than” (line 378).
Thank you
Author Response
Please refer to the attachment.
Author Response File: 
Author Response.pdf
Reviewer 2 Report
Comments and Suggestions for AuthorsPeer review report
Review Paper
Manuscript ID: water – 3859378
Title: Modelling solar radiation data for reference evapotranspiration estimation at a daily time step for Poland
Overview and general recommendation
The reviewed article addresses the issue of improving modelling of solar radiation (H) based on its relationship with sunshine duration and daily temperature variability. The modeling methods applied originate from the first half of the 20th century and have been the subject of numerous publications. This raises the question of whether another publication on this topic is necessary. The answer is yes. Increasingly long meteorological measurement series allow for improved modeling of meteorological processes. The manuscript submitted for review fits well within this trend.
The main objective of the reviewed article is the calibration and accuracy assessment of solar radiation (H) models: the Angström–Prescott model, which is based on sunshine duration measurements, and the Hargreaves and Samani model, which utilizes daily air temperature variability. The study was conducted using data from 10 meteorological stations located in various parts of Poland, covering the period from 2000 to 2015.
The research results are presented in two main areas. First, the authors present findings related to the regression coefficients used in the Angström–Prescott and Hargreaves and Samani models. The validation of the proposed coefficients is carried out by comparing the obtained values of global solar radiation with measurement data.
The second stage of the study involves comparing reference evapotranspiration (ETâ‚€) values (during the growing season) calculated using the FAO-56 Penman–Monteith method, based on measured solar radiation, with those obtained using the modified Angström–Prescott and Hargreaves and Samani models. The validation is essentially limited to discussing the Root Mean Square Error (RMSE) and Mean Bias Error (MBE) values, identifying spatial trends, and highlighting which regression coefficients result in ETâ‚€ values most closely matching those derived from direct solar radiation measurements.
In general, the paper has a methodological character and fits within the scope of improving reference evapotranspiration measurements. Since direct measurements of evapotranspiration are quite challenging and the measurement network for this parameter is relatively sparse, in practice, the assessment of evapotranspiration relies on estimating theoretical reference evapotranspiration values based on selected meteorological parameters. Unfortunately, some of these meteorological parameters are also not commonly measured at meteorological stations. Therefore, methods have been developed to estimate specific parameters based on selected weather conditions. One such parameter is solar radiation, which forms the basis for determining the radiation balance—a value that defines the energy resources available for evapotranspiration.
The use of the Angström–Prescott and Hargreaves and Samani models, along with the modification of regression coefficients used in these formulas, aligns with the long-standing standard for calculating ETâ‚€ recommended by the FAO.
As previously mentioned, the literature in this field is quite extensive. Moreover, numerous similar studies have been conducted over the past two decades due to the growing importance of solar energy. In addition to the formulas used by the authors to calculate H, this issue has also been addressed using other approaches. I suggest expanding the literature review in section “1 Introduction” to include more studies in this area, and additionally mention research involving satellite remote sensing or reanalysis data (e.g., ERA5 or NCEP/NCAR).
The study covers the years 2000–2015, but the validation of the proposed modifications to the Angström–Prescott and Hargreaves and Samani models was conducted for the years 2002, 2010, 2011, 2013, and 2015. This part of the article should be expanded to include a brief characterization of these years—for example, whether they were marked by high or low precipitation compared to climatic norms. Such a characterization would enrich the discussion of the obtained results, both in terms of solar radiation values and reference evapotranspiration.
In summary, the submitted article requires revision before publication.
Specific comments:
L 112 - total extraterrestrial solar radiation; I suggest adding (H0),
L113 - daily maximum sunshine duration; I suggest adding (S0),
L 122 - I suggest adding information on how the growing season was defined,
L 310 - Annual mean… - the paper presents results for the growing season. I suggest changing it. The term "Annual mean" in this case is somewhat misleading,
L 323 - similar to the comment above.
Author Response
Please refer to the attachment.
Author Response File: Author Response.pdf
Reviewer 3 Report
Comments and Suggestions for AuthorsAuthors determined the coefficients of A-P and H-S equations for Poland as well as global using the measured sunshine duration and air temperature, and made calculations of evapotranspiration. The results show that better predictive power of the solar radiation model usually resulted in better accuracy of evapotranspiration estimation. But, there were some exceptions. The comments are as follows.
L107, please change “Daily solar radiation values (H) were” to “Daily sums of solar radiation (H) were”.
In Equation 1, the parameters are daily sum or daily average? Also, please explain all other related parameters for sum or average in the following part.
Table 2, please show and add MBE and RMSE values in MJm-2 and in percent unit (%). What’s the unit of RMSE, MJm-2? Please introduce how to get the coefficients of the model for Poland and global.
L233-234, please explain the reason for the great variation of a than b.
Table 3, please add MBE and RMSE values in MJm-2 and in percent unit (%), and in the following related Tables. Please also introduce how to get the coefficients of the model for Poland and global.
For the results showed in Tables 2 and 3, why there are large differences for a and b at same sites between Tables 2 and 3?
Table 5, please add the bottom line, introduce MBE in the text, and add MBE and RMSE in percent units. Most similar comments are to Table 6.
L378, “worse then with local but”, worse than?
It is suggested to evaluate all model performances, and make more comparisons with other models.
Author Response
Please refer to the attachment.
Author Response File: Author Response.pdf
Round 2
Reviewer 2 Report
Comments and Suggestions for AuthorsI have no comments on the revised version of the article. The revised version of the article is acceptable as it stands.
