From Past to Present: Decoding Precipitation Patterns in a Complex Mediterranean River Basin

Round 1

Reviewer 1 Report

The paper focuses on reconstructing homogeneous areal precipitation data in the complex terrain of the Calore River Basin (CRB) in Southern Italy from 1869 to 2020. However, the validation procedure was performed into a short length data time series that seem to be particularly chose between 1978 and 1993.

A profuse procedure of validation deserves to be carried out to stress out the study in that basin.

Some typical techniques must be mentioned and motivated (and why was those discharged) such like dynamic modeling including Arima, Arma from time series discipline (https://otexts.com/fpp3/). The benchmark method Naive is mandatory in this kind of studies, so its discard deserve to be well motivated.

Check the typos, e.g., second sentence at the introduction.

Author Response

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Reviewer 2 Report

I only found some minor errors, which shouldbe corrected before publication:

 Line 41: such as the relocation of  observing stations over extended time periods (e.g. 50–100 years), leading to changes in local features (e.g. increased vegetation, slight elevation differences). 
à I don’t understand the sentence: do you mean that a station is at the same place for several decades and that within this period the surrounding may change, e.g. because small trees grow? Or do you want to say, that the relocation of stations is a problem, because then the surrounding of the station is often different, e.g. the elevation? 

 Line 92: Recognising the spatial heterogeneity inherent in the precipitation data, Benevento (BNOBS) and Montevergine (MVOBS) à this sentence is not complete. I would also mention Figure 1c, where the location of the two stations can be seen.

 Line 115: Sorry, but I can’t see the pluviometric network in figure 1b. Perhaps it’s a question of contrast?

 Line 165: Since then, the updated and data from the observatory à the updated data?

 Line 167: The variables used for model development…. à I would start a new paragraph

Line 169: The years selected for model calibration (Fig. 2, grey bands) were 1935-1942 and 1951-1977 à the grey bands in Fig. 2 shows a longer period with no gap.

Line 171: (mean: 37±6 mm à I assume the parts of the text were lost. Mean of what? Which period?

 Figure 3 a + b: Why does the amount of precipitation reaches less than 800 mm/year in the black box in Figure 3 a and up to 1900 mm/year in Figure 3b. I doubt that the mean of the numbers in Figure 3b are equal to the numbers in Fig. 3b.

Formula 2: Is there a “=” missing? Explain A.

 Line 304: Montevergine represents meteorological conditions at higher altitudes, while Benevento represents conditions at ground level.
 à Benevento represents conditions at lower altitudes – I assume that both measurements are made at ground level.

 Line 312: Additionally, the Nash-Sutcliffe (NSI) efficiency index (Nash and Sutcliffe, 1970), which also has an optimum value of 1, was maximised.
 à Please explain in a short sentence why you additionally use NSI and what is measured with NSI .

References:  Please add DOIs where applicable.

 

 

Author Response

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Reviewer 3 Report

Dear Author,

Thank you for your submission. The methodology developed and described in your paper could be of wider interest.

The paper is well structured and easy to read. All the figures are relevant, quality is fine.  

I have a couple of questions for you.

Have you checked that the instrument used for measuring precipitation is of the same type over the whole period? Have you tested each station data for homogeneity (maybe there were changes in instruments, microlocation)? Even at the same location different types of rain gauges can give slightly different precipitation amounts. The same applied when classic rain gauges are substituted by an automatic weather station. Even among classic rain gauges there are differences because some of them are designed to compensate for the impact of wind. Have you checked for the potential impact of changes near the measuring sites (changing land use, like growing forests, buildings, …)? Have you noticed any impact of presence of volcano ash in the air on precipitation in the CRB?

If your aim is to use data for water balance computation it is advisable to correct measured amounts for the impact of wind, especially for the measuring sites in the mountains.

I am also wondering if you have tested your data for a potential impact of NAO and AO? It might also be that the variations in SST in the Mediterranean could have an impact on variability of precipitation in the selected area. This could be relevant in future and could have a significant impact on water balance in the CRB.

Best wishes. 

Author Response

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Reviewer 4 Report

1. The paper presents a method for the analysis of the Mean Areal Precipitation (MAP) in the Calore River Basin (CRB), Italy, in the period 1860-2022. The methodology relies on techniques such as Thiessen polygonal estimation and regression analysis. The paper's contents are of interests to those interested in regional precipitation shifts. 

2. Please specify the area in km² of the Calore River basin. 

 

3. One of the main paper's findings is that the average MAP declined from 1157 mm yr^-1 (1869-1951) to 998 mm yr^-1 (1952-2022). But, did the MAP truly change? Because the authors state in the paper that the rain gauge network has evolved in density, in the quality of measurement technology, in the personnel in charge of processing and archiving data. Could it be that the change is not truly a statistical feature of the MAP, but, rather, that it can be explained by the lack of consistency over time in data collection and processing. 

4. In this respect, were the precipitation data subjected to consistency analysis by methods such as the mass analysis to test temporal consistency of rain gauge measurement?

5. Figure 3: difficult to read the latitude / longitude coordinates in 3 (a) and 3 (b).

6.  Figure 3(b) use "... related downscaling within the Calore River Basin (enclosed within black perimeter). " Please increase the thickness of the CRB black perimeter. 

7. Figure 4: why do you show the 0.5 reference ET? Is it not sufficient to show the reference ET?

8. Section 2.3: the paper use the Thiessen polygons method to calculate the MAP; however, there are significant orographic effects that influence precipitation in the CRB; the Thiessen method assumes spatial stationary of the precipitation field, which is not compatible with the topography of the central and southern Apennines. 

9. What is the meaning of the parameter C in equation (3)? 

10. I recommend major revision.

minor editing needed.

Author Response

Thank you for your review report. Please see the file attached below:

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Round 2

Reviewer 1 Report

The author answered the enquiries.

Author Response

Thank you for the favorable advice.

Reviewer 4 Report

The revised paper correct previous errors and deficiencies. 

I recommend accepting the revised paper. 

Minor editing needed.

Author Response

Thank you for the favorable advice. Please specify the minor edits required.