Preprints
https://doi.org/10.5194/egusphere-2026-4780
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/egusphere-2026-4780
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
19 Aug 2026
| 19 Aug 2026
Status: this preprint is open for discussion and under review for Natural Hazards and Earth System Sciences (NHESS).
Observed and projected changes in extreme precipitation intensity and temporal patterns: a case study of the Misa River Basin (Central Italy)
Abstract. Extreme hydrological events such as floods are intensifying under climate change, yet uncertainties in local-scale rainfall projections impede reliable adaptation strategies. This study examines future rainfall extremes and their daily timing in the Misa River basin (Central Italy) using the Weather Research and Forecasting (WRF) and Consortium for Small-scale Modeling in Climate Mode (COSMO-CLM) models, together with rain gauge observations, comparing historical periods (1979–2008 and 1981–2008, respectively) with a future period (2039–2068) under RCP8.5. Mean-state precipitation is projected to decrease annually and in summer, while November average daily precipitation increases. In contrast, extreme precipitation shows a different pattern: both models project more frequent extremes relative to their own historical baselines, with a historical 100-year event becoming 10–20 times more frequent by mid-century. However, the models diverge when evaluated against observed historical flood events: WRF shows a broadly uniform response, with return periods for past events reduced by nearly 50 % and annual exceedance probability doubling, while COSMO shows an event-dependent response, with events remaining within the 95 % confidence bound. Sub-daily event magnitudes, including average peak intensity and nine-hour maximum accumulation, decrease in both models. Overall, both models agree that extremes intensify in a model-relative sense, but this agreement breaks down against observed benchmarks and sub-daily magnitudes, reflecting model-chain spread rather than uniform intensification. These results suggest that historically based design standards may underestimate future rainfall hazards under some projections, underscoring the need to account for model-chain uncertainty in flood risk planning across the Misa River basin.
How to cite. Meskele, D. Y., Parodi, A., Napoli, A., Loffredo, G., and Brocchini, M.: Observed and projected changes in extreme precipitation intensity and temporal patterns: a case study of the Misa River Basin (Central Italy), EGUsphere [preprint], https://doi.org/10.5194/egusphere-2026-4780, 2026.
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.
Download & links
- Preprint
(3088 KB) - Metadata XML
-
Supplement
(1700 KB) - BibTeX
- EndNote
Status: open (until 14 Oct 2026)
Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor
| : Report abuse
-
RC1: 'Comment on egusphere-2026-4780', Anonymous Referee #1, 26 Aug 2026
reply
-
AC1: 'Reply on RC1', Dawit Meskele, 14 Sep 2026
reply
Reply to referee comments RC1.
Thank you for considering our study interesting and relevant to the regional and local context. We also thank the reviewer for highlighting the limitations of the study. Addressing these comments gave us the opportunity to strengthen our analysis, improve the robustness of the results, and ultimately provide a stronger manuscript. All comments have been addressed in the relevant sections point-by-point, and our responses are in "Bullet." The changes introduced in the revised manuscript are shown in "bullet italics."
1. Lines 190–240, 611–666: Historical events are reconstructed using 1.5-km ERA5-driven WRF, whereas future events come from 4-km WRF and ~2.2-km COSMO simulations. Please perform WRF-historical vs. WRF-future and COSMO-historical vs. COSMO-future comparisons using identical model configurations.- We accepted and acknowledged this comment. We clarify that our core extreme-value analysis already uses matched same-model configurations: Figure 8 compares COSMO-historical vs. COSMO-RCP8.5 (~2.2 km) and WRF-historical vs. WRF-RCP8.5 (4 km), each from continuous 30-year simulations within the same modeling chain, isolating the climate signal as recommended. The noted resolution mismatch applies specifically to the event-level structural comparison, where the eight historical benchmarks are event-scale hindcasts compared against future extremes drawn from the continuous WRF and COSMO climate runs. Restricting the historical benchmarks to only those falling within the model's 30-year historical period would exclude most of the catastrophic flood-causing events (6 of 8), while extending the continuous historical simulation to cover the full 82-year observational record at 1.5-km resolution would require a new multi-year, convection-permitting integration beyond this study's computational scope.
- We agree that this limits attribution of storm-structure differences exclusively to climate change for this comparison. Figure 8 and its matched-model GEV analysis were already part of the original manuscript; this matched-configuration comparison is distinct from the event-level structural comparison, which uses different-resolution modeling chains by design and is interpreted accordingly. Moreover, the 1.5-km hindcasts are devoted to reconstructing the observed meteorological evolution of specific events at high spatiotemporal resolution, whereas the future events emerge from independent, free-running climate trajectories; rerunning only the observed event dates at 4-km/2.2-km resolution would therefore test model sensitivity but would not constitute a paired historical–future climate experiment.
- Lines 311–331, 531–600: Please clarify how “basin-maximum precipitation” is defined.
- We thank the reviewer for this comment. Basin-maximum precipitation on a given day is taken as the highest daily precipitation value recorded among all grid (modeled) or gauge stations (observed) within the basin boundary. This approach is more appropriate for extreme hazard analysis because it captures the wettest location within the basin and avoids diluting local precipitation extremes through spatial averaging.
- We added these updates to the revised manuscript in section 2.3.2. “...Basin-maximum precipitation on a given day is taken as the highest daily precipitation value recorded among all modeled grid or gauge stations within the basin boundary. The annual maximum series used for GEV fitting was then obtained by taking the annual maximum of this daily basin-maximum time series...”
- Lines 255–295: With only five long-term gauges, IDW may strongly influence spatial patterns. Please provide the full workflow and a sensitivity analysis of interpolation assumptions.
- We acknowledged this comment. As this sensitivity analysis is the robustness of the study, we have summarized the workflow and rationale in the Methods (Section 2.3.1) of the revised manuscript, with full leave-one-out cross-validation results and the comparison of IDW against nearest-neighbor, elevation-regression, and unweighted-average interpolation provided in the Supplementary Material (Table S2, Fig. S2):
- “...Given the limited number of gauges (five stations) in the basin, the sensitivity of the IDW-based interpolation (p = 2) to interpolation assumptions was assessed through leave-one-out cross-validation and by comparison against nearest-neighbor/Thiessen assignment, unweighted spatial averaging, and elevation-regression interpolation, and their results are provided in the Supplementary Material (Table S2, Fig. S2). This sensitivity analysis indicated that basin-representative return levels varied by no more than ~6% across the IDW power parameter and by ~4% when compared against nearest-neighbor and elevation-regression interpolation, supporting IDW as appropriate for this gauge network...”
- Lines 286–299: Daily bias correction followed by redistribution using raw-model hourly fractions doesn’t independently correct hourly precipitation structure. Validate sub-daily characteristics against hourly observations where possible or clearly state this limitation when interpreting future hourly extremes.
- We thank the reviewer for this comment. We agree and have added the following clarification in Section 4.
- We have added an explicit statement of this limitation in Section 4, in the revised manuscript: “... The method of fragments preserves the raw model's hourly timing but does not independently correct sub-daily structure; in the absence of hourly gauge observations for validation, sub-daily statistics should be interpreted as inherited from the raw model rather than independently bias-corrected. More broadly, robust validation of sub-daily precipitation structure in CPMs requires high-resolution hourly observations from both rain gauge networks and gridded observational products; such data remain notably limited across much of Italy, and their expansion represents an important direction for future model evaluation in basins....”
- Lines 355–361: The choice of a 70-mm threshold and exactly eight future events need stronger justification.
- We thank the reviewer for this valuable suggestion; providing a more detailed explanation of our methodological choices strengthens the manuscript by making the rationale clearer. We have clarified the rationale for both the 70-mm threshold and the selection of eight future events in Section 2.3.2 of the revised manuscript:
- "...A minimum daily precipitation threshold of 70 mm for the basin peak was adopted, corresponding to the lowest daily peak recorded among the eight historical flood-causing events (71.4 mm, which has a return period of 1.8 years), rounded down to a conservative value. The threshold was applied independently to each future model output over the projection period, identifying 19 exceedance events in COSMO and 24 in WRF. The eight future events with the highest basin-peak precipitation from each model were selected for comparison with the eight benchmark events, thereby providing equal-sized samples for a consistent comparison of their rainfall characteristics. This fixed-rank selection was performed independently for each model and was intended solely to identify comparable upper-tail events for event-based analysis, rather than to characterize projected exceedance frequency, which is assessed separately using the complete exceedance populations and the GEV-based analysis..."
- Lines 778–799: The sensitivity analysis shows that some 9-h windows capture only 40–60% of daily precipitation. Please complement the 9-h analysis with full-event or 24-h rainfall characteristics, especially when discussing flood impacts.
- We thank the reviewer for this comment. In Section 3.2.3, we have added concrete hourly intensity evidence for events of 40–60% of daily, which has lower 9-hour core capture (e.g., Historical E06, COSMO E04, WRF E01, etc.), showing their secondary peaks and full-day structure (Fig. S8), which complements the 9-hour analysis with full-event, 24-hour characteristics. We have also added pointers to this 24-hour characterization at the two points in the mass-curve discussion (Sect. 3.2.2). These updates appear in Sections 3.2.2 and 3.2.3.
- Lines 531–600: Table 3 contains extremely wide confidence intervals. Therefore, precise values such as 182→97 or 182→860 years should not be overemphasized.
- We thank the reviewer for this comment. We agree that the wide confidence intervals warrant caution in interpreting the point estimates. We have revised the text so that every return period value is explicitly framed as a "central estimate" rather than a precise value, and we direct the reader to the full 95% confidence intervals in Table 3 at each relevant point in the discussion.
- These updates are made in Section 3.1.2 (ii) in the revised manuscript.
- Lines 819–859 and Abstract: The models strongly disagree for observed benchmark events, sub-daily comparisons contain model-chain uncertainty, and no hydrological model is used. Please distinguish clearly between projected precipitation hazard and actual flood risk.
- To clearly state model-chain uncertainty and distinguish projected precipitation hazard from flood risk, we replace "flood risk" terminology with "precipitation/rainfall hazard" throughout, since no hydrological and/or hydraulic simulation was done in this manuscript, but it’s suggested for future/other works.
- We clearly made these changes in the revised abstract and relevant body sections.
- Please check consistency in terminology, including “CPM,” “RCM,” “extreme event,” “benchmark event,” and “historical event,” as these terms are sometimes used interchangeably.
- We acknowledge highlighting this terminology issue. We have clarified and standardized the terminology throughout the manuscript. “RCM” refers broadly to regional climate models, while “CPM” is used for the convection-permitting simulations (finer resolutions). “Benchmark events” refers specifically to the eight documented flood events, whereas “extreme events” refers to precipitation values that are extremely relative to a defined statistical distribution or threshold. The term “historical event” has been avoided where it does not denote a distinct methodological category.
Citation: https://doi.org/10.5194/egusphere-2026-4780-AC1
-
AC1: 'Reply on RC1', Dawit Meskele, 14 Sep 2026
reply
Viewed
Total article views: 232 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 19 Aug 2026)
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 114 | 57 | 61 | 232 | 37 | 58 | 54 |
- HTML: 114
- PDF: 57
- XML: 61
- Total: 232
- Supplement: 37
- BibTeX: 58
- EndNote: 54
Viewed (geographical distribution)
Total article views: 224 (including HTML, PDF, and XML)
Thereof 224 with geography defined
and 0 with unknown origin.
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
Latest update: 29 Sep 2026
Dawit Y. Meskele
CORRESPONDING AUTHOR
University of Polytechnic Marche, Department of Construction, Civil Engineering, and Architecture (DICEA), Via Brecce Bianche 12, 60131 Ancona, Italy
Antonio Parodi
CIMA Research Foundation, Via Armando Magliotto 17100, Savona, Italy
Anna Napoli
C3A - Center Agriculture Food Environment, Via Mach 1, San Michele all'Adige, Italy
DICAM - Department of Civil, Environmental and Mechanical Engineering, University of Trento, Via Mesiano 77, Trento, Italy
Gianluca Loffredo
Presidency of the Council of Ministers, Extraordinary Deputy Commissioner of the Government for the Emilia-Romagna, Marche, and Tuscany 2023 floods, Italy
Maurizio Brocchini
University of Polytechnic Marche, Department of Construction, Civil Engineering, and Architecture (DICEA), Via Brecce Bianche 12, 60131 Ancona, Italy
Short summary
The Misa River basin in Italy, hit by a devastating flood in 2022, faces growing rainfall risks. Two climate models were used to project rainfall changes there by mid-century under a high-emissions scenario. Results show less rainfall overall but more intense single-day downpours. Both models project extremes 10 to 20 times more frequent relative to their own historical baselines but diverge when compared against past observed flood events, leaving flood risk uncertain.
The Misa River basin in Italy, hit by a devastating flood in 2022, faces growing rainfall risks....
The manuscript investigates historical and projected changes in extreme precipitation in the Misa River Basin. The topic has regional relevance and may provide useful information for local flood-risk assessment and climate adaptation. However, several methodological and statistical issues limit the robustness of the results. Therefore, substantial revisions are required before the manuscript can be considered for publication.
1. Lines 190–240, 611–666: Historical events are reconstructed using 1.5-km ERA5-driven WRF, whereas future events come from 4-km WRF and ~2.2-km COSMO simulations. Please perform WRF-historical vs. WRF-future and COSMO-historical vs. COSMO-future comparisons using identical model configurations.
2. Lines 311–331, 531–600: Please clarify how “basin-maximum precipitation” is defined.
3. Lines 255–295: With only five long-term gauges, IDW may strongly influence spatial patterns. Please provide the full workflow and a sensitivity analysis to interpolation assumptions.
4. Lines 286–299: Daily bias correction followed by redistribution using raw-model hourly fractions does not independently correct hourly precipitation structure. Validate sub-daily characteristics against hourly observations where possible or clearly state this limitation when interpreting future hourly extremes.
5. Lines 355–361: The choice of a 70-mm threshold and exactly eight future events needs stronger justification.
6. Lines 778–799: The sensitivity analysis shows that some 9-h windows capture only 40–60% of daily precipitation. Please complement the 9-h analysis with full-event or 24-h rainfall characteristics, especially when discussing flood impacts.
7. Lines 531–600: Table 3 contains extremely wide confidence intervals. Therefore, precise values such as 182→97 or 182→860 years should not be overemphasized.
8. Lines 819–859 and Abstract: The models strongly disagree for observed benchmark events, sub-daily comparisons contain model-chain uncertainty, and no hydrological model is used. Please distinguish clearly between projected precipitation hazard and actual flood risk.
9. Please check consistency in terminology, including “CPM,” “RCM,” “extreme event,” “benchmark event,” and “historical event,” as these terms are sometimes used interchangeably.