the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 22 Jan 2026
Areal Reduction Factors from High-Resolution Rain Gauges in Austria
Abstract. Areal Reduction Factors (ARFs) are widely used to convert point design precipitation derived from intensity–duration–frequency (IDF) curves into areal precipitation values for hydrological design. Despite their importance, ARFs remain highly uncertain, particularly for short durations and small areas, due to insufficient representation of precipitation spatial variability. In this study, ARFs are empirically derived using a fixed-area approach for the Feldbach region in southeastern Austria using the WegenerNet, a dense rain gauge network with high temporal resolution (5 minutes) for the period 2007–2022. The results confirm that ARFs generally increase with duration and decrease with area, while pronounced dependencies on season and return period are observed, particularly for sub-hourly durations. Contrary to common assumptions, an application of ARF is required even for areas as small as 1 km2, indicating that point measurements and pixel-based precipitation estimates cannot be considered equivalent. For sub-hourly durations, ARFs increase partially with the return period. Seasonal analysis reveals smaller ARFs during spring and summer, associated with convective precipitation, and higher values during winter. The relationship between ARFs and topography is found to be weak, with only negligible correlations between ARFs and station elevation.
Competing interests: At least one of the (co-)authors is a member of the editorial board of Natural Hazards and Earth System Sciences.
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.-
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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Preprint
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
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- Final revised paper
Journal article(s) based on this preprint
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2026-186', Anonymous Referee #1, 17 Feb 2026
- AC1: 'Reply on RC1', Hannes Müller-Thomy, 30 Apr 2026
-
RC2: 'Comment on egusphere-2026-186', Anonymous Referee #2, 21 Feb 2026
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.
Citation: https://doi.org/10.5194/egusphere-2026-186-RC2 - AC1: 'Reply on RC1', Hannes Müller-Thomy, 30 Apr 2026
Peer review completion
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2026-186', Anonymous Referee #1, 17 Feb 2026
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?
Citation: https://doi.org/10.5194/egusphere-2026-186-RC1 - AC1: 'Reply on RC1', Hannes Müller-Thomy, 30 Apr 2026
-
RC2: 'Comment on egusphere-2026-186', Anonymous Referee #2, 21 Feb 2026
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.
Citation: https://doi.org/10.5194/egusphere-2026-186-RC2 - AC1: 'Reply on RC1', Hannes Müller-Thomy, 30 Apr 2026
Peer review completion
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Golbarg Goshtasbpour
Jannick Alpers
Kai Schröter
Hannes Müller-Thomy
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(1497 KB) - Metadata XML
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: