Review of the article on  “Areal Reduction Factors from High-Resolution Rain Gauges in Austria” 

The paper presents an estimation of areal reduction factors using high-resolution rain gauges in Austria. The study utilizes a dense network of station data from which point extremes were estimated. A raster product was then employed for areal rainfall extremes prediction. Subsequently,  ARFs were estimated empirically from the estimated quantiles. The authors then explored the behavior of the ARFs as a function of duration, area, season, and topography. Overall, the paper is well-written, and I recommend publication, subject to some minor corrections.

Minor comments:

• While the literature review and state of the art on ARF have been extensively presented in the introduction, I think the novelty of the present study needs to be elaborated.
• What is the size of the study area?
• More information should be provided on the raster product. How long is the series in years? Is it a reanalysis or simply an interpolation of the station data?
• What is the role of the Data Product Generator?
• Is there any specific reason to relate the choice of the POT to the Euler number?
• What are the u and w parameters of the exponential distribution? I think the equation should be given, since the usual case is a one-parameter distribution.
• In the result section, the goodness-of-fit of the fitted models on the point and areal rainfall should be illustrated, at least for a few stations. Otherwise, it would be difficult to ascertain the quality of the model fits. Additionally, the claim of the agreement with the reference values from eHYD should be supported by a figure at least in the appendix.
• In line 211, the statement “The ARF increases with duration, and so does its range” does not seem to correspond to the figure.
• Figures 6 and 7 are interchanged both in the text and their labels.
• The ARF plots in Figure 6 should be elaborated. How were the values obtained? Are they for a given station? Which one? Or are they for the entire study area? How then were they obtained? Mean? Median?
• Could the deviation observed in Figures 6 and 7 regarding the 18 and 24 h be related to the estimation step? Probably the underlying EVT model didn’t correctly fit the data, thereby giving wrong quantiles?
• Additionally, the authors should highlight the key findings of their study that advance the state of the art. It seems most of the conclusions are already established by earlier studies. Or is the work meant to be a case study?

General comments

This manuscript presents an extensive empirical analysis of areal reduction factors (ARFs) based on a dense high-resolution rain gauge network in southeastern Austria. The dataset offers valuable opportunities to investigate sub-hourly spatial rainfall variability. The methodological framework is generally sound, and the paper is adequately  structured and well written.

However, several aspects related to data selection, climatological context, spatial representativeness, and interpretation require further clarification and, in some cases, additional analyses. In its current form, some conclusions appear too general given the limited spatial extent and specific climatic setting of the study area.

I therefore recommend major revision addressing the points below.

Major comments

Reference Data and use of design precipitation values

The manuscript uses official Austrian design precipitation values from eHYD for validation. However, eHYD provides different products (observational ÖKOSTRA values, hybrid design values ("Bemessungsniederschlag"), and model-based products).

Only the observational ÖKOSTRA values represent an independent reference suitable for validation in this context. The authors should clearly specify which eHYD products were used and justify their choice. Hybrid design values should not be used for validation, as they already incorporate modelling assumptions.

Climatological context and precipitation regimes

The interpretation of seasonal and return-period dependencies would benefit from a stronger climatological and synoptic context. The study area is located in a transition zone influenced by convective summer storms, frontal systems, and Mediterranean inflow.

A more explicit discussion of dominant precipitation regimes and seasonal weather types would help to interpret the observed ARF patterns and assess their broader relevance.

Spatial representativeness and generalizability

The study area covers only a few hundred square kilometres and exhibits relatively homogeneous climatic and orographic conditions. Nevertheless, several conclusions are formulated in a rather general manner, particularly regarding return-period effects at sub-hourly scales.

Given the limited spatial extent, it remains unclear whether these findings reflect general methodological effects or region-specific climatic characteristics. An extension to a larger surrounding region with lower station density, including additional available gauges from local meteorological and hydrological services, would help to disentangle these effects. 

Such an extended analysis would also strengthen the assessment of the scientific novelty of the study, as it would clarify whether the reported patterns represent transferable insights or primarily reflect local climatic peculiarities.

This issue is closely related to the interpretation of elevation effects (see below).

Elevation dependence

The elevation range within the study area is small (approximately 250–600 m), which strongly limits the interpretability of the reported weak ARF–elevation relationships. Additional analyses including higher-elevation stations from neighbouring regions would be required to draw more robust conclusions on topographic effects.

Regionalized precipitation product

The estimation of areal precipitation relies on a regionalized raster product derived from station data. Given its central role in ARF estimation, the derivation of this product should be described in more detail, including the interpolation method, smoothing effects, and associated uncertainties. Although limitations are briefly mentioned in the discussion, they should be addressed earlier and more explicitly in the methodology section.

Methodological framework and model performance

The study relies strongly on national guidelines (DWA, 2012) for extreme value analysis and IDF estimation. While this is appropriate in an applied context, the methodological implications and limitations should be more critically discussed and embedded in a broader international framework. In addition, the goodness-of-fit of the applied extreme value models should be illustrated and discussed more explicitly, both for point and areal precipitation.

Length of record and uncertainty

The analysed time series covers only 15 years. For POT-based extreme value analysis at sub-hourly scales and return periods up to 10 years, this is relatively short. A more explicit assessment of sampling uncertainty and parameter uncertainty would strengthen the robustness of the conclusions.

Interpretation and framing of results

Several interpretative aspects require further discussion and probably also analysis:

• Statements suggesting that the WegenerNet dataset is the first capable of revealing certain ARF behaviours should be moderated or more carefully justified, as comparable high-resolution datasets may exist internationally.
• The reported weak increase of ARF with return period at sub-hourly durations contradicts many previous studies. While this may be related to the exceptional data density, alternative explanations (e.g. local climatic effects, sampling variability, and interpolation effects) should be discussed more thoroughly. A complementary analysis on a larger regional scale within the same climatic setting would help to disentangle observational-scale effects from genuine regional climatic signals. If the observed behaviour persists beyond the dense core network, this would indicate a robust regional meteorological characteristic. If the effect weakens at larger scales, this would suggest that high station density is required to resolve sub-hourly spatial variability that remains obscured in conventional raingauge networks.

• The literature review is comprehensive but largely organized chronologically. A clearer thematic structure (e.g. by methodological approach, data source, climatic regime, and scale dependency) would improve readability and better position the present study within the existing literature.