the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 26 Feb 2025
Rockfall triggering and meteorological variables in the Dolomites (Italian Eastern Alps)
Abstract. Alpine areas are undergoing the highest change in temperature and rainfall intensity that represent main rockfall triggering factors. Since few approaches were proposed to analyse it, a new approach using meteorological variable frequencies was developed to comprehend climatic scenarios from 1970 to 2019 with implication on triggering historical rockfall events in the Dolomites.
The analysis considered key climate variables: mean air temperature, precipitation, thermal amplitude, freeze/thaw cycles and icing, under different aggregation scales. Results reveal that highest warming rates were observed during spring, while a notable reduction in icing and freeze-thaw cycles frequency was obtained during spring and autumn. An anticipation of both starting of summer and ending of winter was detected. Analyses with Rescaled Adjustment Partial Sums method provided valuable insights into precipitation long-term trends and fluctuations.
The analysis showed an increasing trend over last decade (2000–2019) suggesting variation in precipitation frequencies over years. The Bayesian method was employed to study conditional probability of meteorological variables on rockfall events. Rockfalls and high intensity rainfall are correlated in autumn, while with mean temperature at different altitudes in summer and autumn. Higher values probability of temperature amplitude characterises spring, while autumn seasons are interested to high temperature variation values. Finally, it was observed strong dependency of the freeze-thaw cycles and icing periods by regional timeseries.
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Status: open (until 08 May 2025)
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RC1: 'Comment on egusphere-2024-4122', Anonymous Referee #1, 02 Apr 2025
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General comments
"Rockfall triggering and meteorological variables in the Dolomites (Italian Eastern Alps)" by Bonometti et al. aims to investigate the relationship between meteorological variables and rockfall occurrence in the Italian Eastern Alps. Specifically, a statistical modelling approach based on previous studies and on the Bayesian method has been exploited to assess the frequency of meteorological variables in the ongoing context of climate change and as potential triggers of rockfall events in the studied area in the period 1970-2019. Alongside, an in-depth analysis of the impact of long-term meteorological trends of air temperature, precipitation, temperature variations and freeze-thaw cycles at different aggregation scales on rockfall occurrence has been provided.
The manuscript represents a valuable and innovative contribution to the understanding of meteorological variables-related impact on the rockfall risk. Results of this study are very interesting and properly compared to previous works on the same topic. Despite not being a mother-tongue, I think that the paper is in general well-written.
However, I believe that some major revisions are needed to enhance the overall quality and clarity of the paper before acceptance for publication.
While the methodology is generally well-explained from a technical point of view, there are some assumptions and flows that need clarification. Further, the paper would benefit from a more logical structure, particularly in the Results and Discussion sections. Some parts of the methodology are discussed in the Results, which is not consistent with the purpose of the section. Similarly, some results are overlooked in the Results section and rather included in the Discussion. The Introduction needs some refinements, to better highlight the aim of the work and its novelty with respect to previous mentioned works.
Further details are given below.
Specific comments
Abstract
L 18: This sentence is not clear, please rephrase.
Introduction
Rather than focusing on limitations of the previous method, it seems that this is addressing a different aim. The mentioned works concentrate on the probability occurrence of extremes in the meteorological variables leading to slope failures, using a non-parametric approach to link meteorological anomalies to landslides occurrence. In contrast, this work shifts the focus to long-term trends and frequency over time, specifically investigating how these trends influence rockfall occurrences, especially considering the impacts of warming and changing weather patterns. I think that the primary aim is to assess how the variation in climate variables over time and space affect changes in rockfall frequency, rather than identifying the role of specific climate extremes as triggering events. I invite the authors to refine this part to better highlight the purpose and novelty of the work.
L62-65 This part is more suited in the methodology section.
Case study
A concise overview of the climate of the study area is suggested. Some text from the discussion should be moved here to better contextualize the study area from a climatological point of view.
L 111 Please provide references for these datasets if available.
L115 Are you thus considering all landslide events in the region regardless of the elevation? Please clarify.
Method
As far as I understand, the method focuses on the frequency of meteorological values within their characteristics value ranges in the period preceding slope failure occurrence. A more detailed explanation of these “characteristics value ranges” and how they are defined should be provided.
The methodology is partially based on Paranunzio et al., particularly the time series sampling approach at different time aggregation scales. Then it differs by applying a Bayesian method to assess the relative influence of a variable to act as a trigger of a rockfall in terms of conditional probability. Thus, it seems that the computation of the non-exceedance probability, using a defined alpha level (as stated in the Introduction in reference to previous works) for the detection of potential anomalous values (in statistical sense) is not fully addressed in this paper. However, the outcomes of this approach are then presented in the discussion (L 553 on, Fig. 21.). This creates some confusion, as the linkage between the methodology and the results is not clearly explained. The paper should provide a clearer explanation of how this method connects to the presented results.
L 127 The concept is not clear to me: meteorological variables like e.g. temperature are continuous variables, thus what does the premise” this method focuses on the frequency of meteorological values” mean exactly?
Eq (4) Define j
L 208 In my opinion, this statement is based on a flawed assumption. The method illustrated in Paranunzio et al. is a statistical approach based on the detection of meteorological anomalies (percentiles). As such, this allows to remove possible bias in the absolute rainfall estimates. Paranunzio et al. compute the probability distribution using the climate data recorded at the reference stations as they are and did not transpose the temperature or precipitation measurements from the meteorological stations to the geographical location and elevation of the rockfall detachment zone. This is because the application of a constant lapse rate (as in the case of temperature) would only shift the values, without influencing the probability estimate associated with V. Therefore, I think that it is not accurate to claim that the method presented in this work addresses an issue overlooked in previous methods. Rather, they provide an alternative approach to handling spatial variability in absolute values instead of percentiles. This point needs to be clarified.
L 221 Generally, an environmental lapse rate which considers air temperature decreasing with height at a rate of approx. 0.6 °C/100 m is used, but this does not take into account that the warming rate increases with elevation (see some suggested references below). It is worth to briefly discuss it in this section.
Pepin N, Bradley RS, Diaz HF et al (2015) Elevation-dependent warming in mountain regions of the world. Nat Clim Chang 5:424–430. doi:10.1038/nclimate2563
Nigrelli, G., Fratianni, S., Zampollo, A., Turconi, L., & Chiarle, M. (2018). The altitudinal temperature lapse rates applied to high elevation rockfalls studies in the Western European Alps. Theoretical and Applied Climatology, 131, 1479-1491.
L 212 The Delaunay method assumes a smooth transition among points, but temperature gradients can be non-linear, especially in regions characterized by microclimates or highly varying topography (as raised in the previous point). The authors should be cautious of how elevation is included in the model, especially in mountain regions with high complex topography and when weather stations with high elevation difference are used. Moreover, this triangulation assumes uniformity in space, this means that stations should be distributed in a reasonably uniform manner. In the case of sparse station networks or if the stations are unevenly spaced, as often occur in complex terrain like mountain regions, the method could not accurately represent the spatial variation of the variables, leading to skewed results. Also, the sensitivity to outliers should be considered (that is, the fact that interpolation process could amplify these errors).
Figure 2 Define A and B
Results
L 239 Did the authors set a minimum record length in the period 1970-2019?
Figure 4-5 It is not clear to what trend the arrows refer to, please clarify.
L 315-316 “which delay summer and advances winter” sounds misleading, please rephrase.
L 356 Not sure the aim here is to assess a correlation in statistical sense.
L 364 Not clear if the authors are referring to total precipitation or precipitation intensity (also in Figure 11).
Discussion
Some key findings are presented in the Discussion rather than the Results section, which diminishes the clarity of both parts. The Results section should be dedicated solely to presenting the outcomes of the analysis. Outputs should be moved in the dedicated section, leaving comments and comparison to other works here. As an example, Section 5.1 Climate which addresses changing climate patterns and long-term trends over the last decades in the area is not suited to the Discussion section in its current form (additionally, a climatological introduction of the study area should be included in the Study area section). Similarly, some parts of the methodology are presented for the first time within this section, which contradicts its intended purpose.
L 506-519 The RAPS method is mentioned in the discussion for the first time, but it should be included in the methodology, since it supports results and conclusions of the work.
L 537 How did the authors measure the correlation?
Figure 17-20: these and related description are more suited for the results section (e.g., L 452-457, L 485-489).
Figure 21 As in the previous comment, results of this analysis (L 560 on) this should be anticipated in the Results section and briefly contextualized in the Discussion.
Technical corrections
L 1 Alpine areas are undergoing “a high change” in…
L 12 An anticipation of “both the onset of summer and the end of winter”…
L 15 over “the” last…
Figure 11a) Correct “conditional”
Figure 10 Please indicate the elevation ranges in d)
Citation: https://doi.org/10.5194/egusphere-2024-4122-RC1
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