Articles | Volume 28, issue 15
https://doi.org/10.5194/hess-28-3549-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-28-3549-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
06 Aug 2024
Research article |
| 06 Aug 2024
| 06 Aug 2024
Exploring patterns in precipitation intensity–duration–area–frequency relationships using weather radar data
Talia Rosin
CORRESPONDING AUTHOR
The Fredy and Nadine Herrmann Institute of Earth Sciences, the Hebrew University of Jerusalem, Jerusalem, 9190401, Israel
Francesco Marra
Department of Geosciences, University of Padua, Padua, Italy
The Fredy and Nadine Herrmann Institute of Earth Sciences, the Hebrew University of Jerusalem, Jerusalem, 9190401, Israel
Related authors
Talia Rosin, Francesco Marra, Marco Gabella, Urs Germann, Daniel Wolfensberger, and Efrat Morin
EGUsphere, https://doi.org/10.5194/egusphere-2026-1800, https://doi.org/10.5194/egusphere-2026-1800, 2026
This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
Short summary
Short summary
Extreme rainfall in mountainous regions is difficult to assess as it varies strongly across space and time, and rain gauges are often too sparse to capture it. Using 9 years of radar data, we analyse summer rainfall extremes across Switzerland for different durations and areas. We show that rainfall intensity depends strongly on scale and topography, and that radar better captures local extremes, improving flood hazard assessment, as demonstrated for three recent major flood-producing storms.
Talia Rosin, Francesco Marra, Marco Gabella, Urs Germann, Daniel Wolfensberger, and Efrat Morin
EGUsphere, https://doi.org/10.5194/egusphere-2026-1800, https://doi.org/10.5194/egusphere-2026-1800, 2026
This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
Short summary
Short summary
Extreme rainfall in mountainous regions is difficult to assess as it varies strongly across space and time, and rain gauges are often too sparse to capture it. Using 9 years of radar data, we analyse summer rainfall extremes across Switzerland for different durations and areas. We show that rainfall intensity depends strongly on scale and topography, and that radar better captures local extremes, improving flood hazard assessment, as demonstrated for three recent major flood-producing storms.
Rashid Akbary, Eleonora Dallan, Paul C. Astagneau, Raul R. Wood, Francesco Marra, Manuela I. Brunner, and Marco Borga
EGUsphere, https://doi.org/10.5194/egusphere-2026-1079, https://doi.org/10.5194/egusphere-2026-1079, 2026
Short summary
Short summary
Heavy short rain can trigger flash floods and debris flows. In this study we evaluated how well climate models reproduce these events in Switzerland. We compared finer and coarser resolution models with high-quality hourly precipitation observations across small to large areas. The finer models better captured where short, intense precipitation occurs, but their errors changed with area size. Flood risk studies should therefore account for these scale-related errors.
Yair Rinat, Moshe Armon, and Efrat Morin
EGUsphere, https://doi.org/10.5194/egusphere-2026-972, https://doi.org/10.5194/egusphere-2026-972, 2026
Short summary
Short summary
In the coming decades Mediterranean floods are expected to change due to increased urbanization and climate change. We simulate floods under different conditions and show that future rainfall will likely reduce flood magnitudes, but increased urbanization will make them higher. Flood intensification is more pronounced at upstream sections and when soil moisture is high. As future flood trends may change between different regions further research is needed to cope with upcoming challenges.
Saran Aadhar, Efrat Morin, and Utkarsh Gupta
EGUsphere, https://doi.org/10.5194/egusphere-2026-339, https://doi.org/10.5194/egusphere-2026-339, 2026
Short summary
Short summary
River basins in India are often affected by flooding during the summer monsoon, putting millions of people and livelihoods at risk. Understanding the processes that cause floods is critical to minimizing flood risk. Our investigations show how rainfall (short and long-duration), surface water flow, and the specific location of the drainage area contribute to flood events in the Godavari River basin using observations and hydrological model data.
Francesco Marra, Eleonora Dallan, Marco Borga, Roberto Greco, and Thom Bogaard
Nat. Hazards Earth Syst. Sci., 25, 5055–5061, https://doi.org/10.5194/nhess-25-5055-2025, https://doi.org/10.5194/nhess-25-5055-2025, 2025
Short summary
Short summary
We highlight an important conceptual difference between the duration used in intensity-duration thresholds and the duration used in the intensity-duration-frequency curves that has been overlooked by the landslide literature so far.
Ella Thomas, Petr Vohnicky, Marco Borga, Nadav Peleg, and Francesco Marra
EGUsphere, https://doi.org/10.5194/egusphere-2025-4741, https://doi.org/10.5194/egusphere-2025-4741, 2025
Short summary
Short summary
Extreme rainfall is expected to grow in magnitude with increasing temperature. We assess whether very rare extremes increase with temperature faster than moderate extremes, and we test methods to include this effect into a model to predict future extremes called TENAX. We find that this dependence on temperature is typically observed but including it in the model without prior information on its magnitude may lead to disproportionately large uncertainty.
Nathalia Correa-Sánchez, Xiaoli Guo Larsén, Giorgia Fosser, Eleonora Dallan, Marco Borga, and Francesco Marra
Wind Energ. Sci., 10, 2551–2561, https://doi.org/10.5194/wes-10-2551-2025, https://doi.org/10.5194/wes-10-2551-2025, 2025
Short summary
Short summary
We examined the power spectra of wind speed in three convection-permitting models in central Europe and found that these models have a better representation of wind variability characteristics than standard wind datasets like the New European Wind Atlas, due to different simulation approaches, providing more reliable extreme wind predictions.
Nathalia Correa-Sánchez, Xiaoli Guo Larsén, Eleonora Dallan, Marco Borga, and Fracesco Marra
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2025-172, https://doi.org/10.5194/wes-2025-172, 2025
Revised manuscript under review for WES
Short summary
Short summary
This research presents the first use of SMEV for wind extremes, extending it to wind energy applications. We use a categories framework combining climate, roughness, and topography for CPM evaluation. We find that model formulation drives inter-model uncertainties, rather than surface conditions. Also, there is a higher model agreement in winter (synoptic) and lower in summer (convective). CPM uncertainty analysis improves the reliability of extreme winds for design parameters.
Rajani Kumar Pradhan, Yannis Markonis, Francesco Marra, Efthymios I. Nikolopoulos, Simon Michael Papalexiou, and Vincenzo Levizzani
Hydrol. Earth Syst. Sci., 29, 4929–4949, https://doi.org/10.5194/hess-29-4929-2025, https://doi.org/10.5194/hess-29-4929-2025, 2025
Short summary
Short summary
This study compared global satellite and reanalysis precipitation datasets to assess diurnal variability. We found that all datasets capture key diurnal precipitation patterns, with maximum precipitation in the afternoon over land and early morning over the ocean. However, there are differences in the exact timing and amount of precipitation. This suggests that it is better to use a combination of datasets for potential applications rather than relying on a single dataset.
Francesco Marra, Nadav Peleg, Elena Cristiano, Efthymios I. Nikolopoulos, Federica Remondi, and Paolo Tarolli
Nat. Hazards Earth Syst. Sci., 25, 2565–2570, https://doi.org/10.5194/nhess-25-2565-2025, https://doi.org/10.5194/nhess-25-2565-2025, 2025
Short summary
Short summary
Climate change is escalating the risks related to hydro-meteorological extremes. This preface introduces a special issue originating from a European Geosciences Union (EGU) session. It highlights the challenges posed by these extremes, ranging from hazard assessment to mitigation strategies, and covers both water excess events like floods, landslides, and coastal hazards and water deficit events such as droughts and fire weather. The collection aims to advance understanding, improve resilience, and inform policy-making.
Kevin Kenfack, Francesco Marra, Zéphirin Yepdo Djomou, Lucie Angennes Djiotang Tchotchou, Alain Tchio Tamoffo, and Derbetini Appolinaire Vondou
Weather Clim. Dynam., 5, 1457–1472, https://doi.org/10.5194/wcd-5-1457-2024, https://doi.org/10.5194/wcd-5-1457-2024, 2024
Short summary
Short summary
The results of this study show that moisture advection induced by horizontal wind anomalies and vertical moisture advection induced by vertical velocity anomalies were crucial mechanisms behind the anomalous October 2019 exceptional rainfall increase over western central Africa. The information we derive can be used to support risk assessment and management in the region and to improve our resilience to ongoing climate change.
Shai Abir, Hamish A. McGowan, Yonatan Shaked, Hezi Gildor, Efrat Morin, and Nadav G. Lensky
Atmos. Chem. Phys., 24, 6177–6195, https://doi.org/10.5194/acp-24-6177-2024, https://doi.org/10.5194/acp-24-6177-2024, 2024
Short summary
Short summary
Understanding air–sea heat exchange is vital for studying ocean dynamics. Eddy covariance measurements over the Gulf of Eilat revealed a 3.22 m yr-1 evaporation rate, which is inconsistent with bulk formulae estimations in stable atmospheric conditions, requiring bulk formulae to be revisited in these environments. The surface fluxes have a net cooling effect on the gulf water on an annual mean (-79 W m-2), balanced by a strong exchange flux between the Red Sea and the Gulf of Eilat.
Francesco Marra, Marika Koukoula, Antonio Canale, and Nadav Peleg
Hydrol. Earth Syst. Sci., 28, 375–389, https://doi.org/10.5194/hess-28-375-2024, https://doi.org/10.5194/hess-28-375-2024, 2024
Short summary
Short summary
We present a new physical-based method for estimating extreme sub-hourly precipitation return levels (i.e., intensity–duration–frequency, IDF, curves), which are critical for the estimation of future floods. The proposed model, named TENAX, incorporates temperature as a covariate in a physically consistent manner. It has only a few parameters and can be easily set for any climate station given sub-hourly precipitation and temperature data are available.
Stefan Steger, Mateo Moreno, Alice Crespi, Peter James Zellner, Stefano Luigi Gariano, Maria Teresa Brunetti, Massimo Melillo, Silvia Peruccacci, Francesco Marra, Robin Kohrs, Jason Goetz, Volkmar Mair, and Massimiliano Pittore
Nat. Hazards Earth Syst. Sci., 23, 1483–1506, https://doi.org/10.5194/nhess-23-1483-2023, https://doi.org/10.5194/nhess-23-1483-2023, 2023
Short summary
Short summary
We present a novel data-driven modelling approach to determine season-specific critical precipitation conditions for landslide occurrence. It is shown that the amount of precipitation required to trigger a landslide in South Tyrol varies from season to season. In summer, a higher amount of preparatory precipitation is required to trigger a landslide, probably due to denser vegetation and higher temperatures. We derive dynamic thresholds that directly relate to hit rates and false-alarm rates.
Nadav Peleg, Herminia Torelló-Sentelles, Grégoire Mariéthoz, Lionel Benoit, João P. Leitão, and Francesco Marra
Nat. Hazards Earth Syst. Sci., 23, 1233–1240, https://doi.org/10.5194/nhess-23-1233-2023, https://doi.org/10.5194/nhess-23-1233-2023, 2023
Short summary
Short summary
Floods in urban areas are one of the most common natural hazards. Due to climate change enhancing extreme rainfall and cities becoming larger and denser, the impacts of these events are expected to increase. A fast and reliable flood warning system should thus be implemented in flood-prone cities to warn the public of upcoming floods. The purpose of this brief communication is to discuss the potential implementation of low-cost acoustic rainfall sensors in short-term flood warning systems.
Eleonora Dallan, Francesco Marra, Giorgia Fosser, Marco Marani, Giuseppe Formetta, Christoph Schär, and Marco Borga
Hydrol. Earth Syst. Sci., 27, 1133–1149, https://doi.org/10.5194/hess-27-1133-2023, https://doi.org/10.5194/hess-27-1133-2023, 2023
Short summary
Short summary
Convection-permitting climate models could represent future changes in extreme short-duration precipitation, which is critical for risk management. We use a non-asymptotic statistical method to estimate extremes from 10 years of simulations in an orographically complex area. Despite overall good agreement with rain gauges, the observed decrease of hourly extremes with elevation is not fully represented by the model. Climate model adjustment methods should consider the role of orography.
Shalev Siman-Tov and Francesco Marra
Nat. Hazards Earth Syst. Sci., 23, 1079–1093, https://doi.org/10.5194/nhess-23-1079-2023, https://doi.org/10.5194/nhess-23-1079-2023, 2023
Short summary
Short summary
Debris flows represent a threat to infrastructure and the population. In arid areas, they are observed when heavy rainfall hits steep slopes with sediments. Here, we use digital surface models and radar rainfall data to detect and characterize the triggering and non-triggering rainfall conditions. We find that rainfall intensity alone is insufficient to explain the triggering. We suggest that antecedent rainfall could represent a critical factor for debris flow triggering in arid regions.
Sella Nevo, Efrat Morin, Adi Gerzi Rosenthal, Asher Metzger, Chen Barshai, Dana Weitzner, Dafi Voloshin, Frederik Kratzert, Gal Elidan, Gideon Dror, Gregory Begelman, Grey Nearing, Guy Shalev, Hila Noga, Ira Shavitt, Liora Yuklea, Moriah Royz, Niv Giladi, Nofar Peled Levi, Ofir Reich, Oren Gilon, Ronnie Maor, Shahar Timnat, Tal Shechter, Vladimir Anisimov, Yotam Gigi, Yuval Levin, Zach Moshe, Zvika Ben-Haim, Avinatan Hassidim, and Yossi Matias
Hydrol. Earth Syst. Sci., 26, 4013–4032, https://doi.org/10.5194/hess-26-4013-2022, https://doi.org/10.5194/hess-26-4013-2022, 2022
Short summary
Short summary
Early flood warnings are one of the most effective tools to save lives and goods. Machine learning (ML) models can improve flood prediction accuracy but their use in operational frameworks is limited. The paper presents a flood warning system, operational in India and Bangladesh, that uses ML models for forecasting river stage and flood inundation maps and discusses the models' performances. In 2021, more than 100 million flood alerts were sent to people near rivers over an area of 470 000 km2.
Assaf Hochman, Francesco Marra, Gabriele Messori, Joaquim G. Pinto, Shira Raveh-Rubin, Yizhak Yosef, and Georgios Zittis
Earth Syst. Dynam., 13, 749–777, https://doi.org/10.5194/esd-13-749-2022, https://doi.org/10.5194/esd-13-749-2022, 2022
Short summary
Short summary
Gaining a complete understanding of extreme weather, from its physical drivers to its impacts on society, is important in supporting future risk reduction and adaptation measures. Here, we provide a review of the available scientific literature, knowledge gaps and key open questions in the study of extreme weather events over the vulnerable eastern Mediterranean region.
Francesco Marra, Moshe Armon, and Efrat Morin
Hydrol. Earth Syst. Sci., 26, 1439–1458, https://doi.org/10.5194/hess-26-1439-2022, https://doi.org/10.5194/hess-26-1439-2022, 2022
Short summary
Short summary
We present a new method for quantifying the probability of occurrence of extreme rainfall using radar data, and we use it to examine coastal and orographic effects on extremes. We identify three regimes, directly related to precipitation physical processes, which respond differently to these forcings. The methods and results are of interest for researchers and practitioners using radar for the analysis of extremes, risk managers, water resources managers, and climate change impact studies.
Yoav Ben Dor, Francesco Marra, Moshe Armon, Yehouda Enzel, Achim Brauer, Markus Julius Schwab, and Efrat Morin
Clim. Past, 17, 2653–2677, https://doi.org/10.5194/cp-17-2653-2021, https://doi.org/10.5194/cp-17-2653-2021, 2021
Short summary
Short summary
Laminated sediments from the deepest part of the Dead Sea unravel the hydrological response of the eastern Mediterranean to past climate changes. This study demonstrates the importance of geological archives in complementing modern hydrological measurements that do not fully capture natural hydroclimatic variability, which is crucial to configure for understanding the impact of climate change on the hydrological cycle in subtropical regions.
Cited articles
Allamano, P., Claps, P., Laio, F., and Thea, C.: A data-based assessment of the dependence of short-duration precipitation on elevation, Phys. Chem. Earth, 34, 635–641, https://doi.org/10.1016/J.PCE.2009.01.001, 2009.
Araujo, D., Marra, F., Ali, H., Fowler, H. J., and Nikolopoulos, E. I.: Relation Between Storm Characteristics and Extreme Precipitation Statistics Over CONUS, Adv. Water Resour., 178, 104497, https://doi.org/10.1016/j.advwatres.2023.104497, 2023.
Armon, M., Morin, E., and Enzel, Y.: Overview of modern atmospheric patterns controlling rainfall and floods into the Dead Sea: Implications for the lake's sedimentology and paleohydrology, Quaternary Sci. Rev., 216, 58–73, https://doi.org/10.1016/J.QUASCIREV.2019.06.005, 2019.
Armon, M., Marra, F., Enzel, Y., Rostkier-Edelstein, D., and Morin, E.: Radar-based characterisation of heavy precipitation in the eastern Mediterranean and its representation in a convection-permitting model, Hydrol. Earth Syst. Sci., 24, 1227–1249, https://doi.org/10.5194/hess-24-1227-2020, 2020.
Avanzi, F., De Michele, C., Gabriele, S., Ghezzi, A., and Rosso, R.: Orographic Signature on Extreme Precipitation of Short Durations, J. Hydrometeorol., 16, 278–294, https://doi.org/10.1175/JHM-D-14-0063.1, 2015.
Barredo, J. I.: Normalised flood losses in Europe: 1970–2006, Nat. Hazards Earth Syst. Sci., 9, 97–104, https://doi.org/10.5194/nhess-9-97-2009, 2009.
Barros, A. P. and Kuligowski, R. J.: Orographic Effects during a Severe Wintertime Rainstorm in the Appalachian Mountains, Mon. Weather Rev., 126, 2648–2672, https://doi.org/10.1175/1520-0493(1998)126<2648:OEDASW>2.0.CO;2, 1998.
Belachsen, I., Marra, F., Peleg, N., and Morin, E.: Convective rainfall in a dry climate: relations with synoptic systems and flash-flood generation in the Dead Sea region, Hydrol. Earth Syst. Sci., 21, 5165–5180, https://doi.org/10.5194/hess-21-5165-2017, 2017.
Biondi, D., Greco, A., and De Luca, D. L.: Fixed-area vs storm-centered areal reduction factors: a Mediterranean case study, J. Hydrol., 595, 125654, https://doi.org/10.1016/J.JHYDROL.2020.125654, 2021.
Borga, M. and Morin, E.: Characteristics of Flash Flood Regimes in the Mediterranean Region, in: Advances in Natural and Technological Hazards Research, Vol. 39, Springer, Dordrecht, 65–76, https://doi.org/10.1007/978-94-007-7948-8_5, 2014.
Dallan, E., Marra, F., Fosser, G., Marani, M., Formetta, G., Schär, C., and Borga, M.: How well does a convection-permitting regional climate model represent the reverse orographic effect of extreme hourly precipitation?, Hydrol. Earth Syst. Sci., 27, 1133–1149, https://doi.org/10.5194/hess-27-1133-2023, 2023.
Daniels, E. E., Lenderink, G., Hutjes, R. W. A., and Holtslag, A. A. M.: Spatial precipitation patterns and trends in The Netherlands during 1951–2009, Int. J. Climatol., 34, 1773–1784, https://doi.org/10.1002/JOC.3800, 2014.
De Michele, C., Kottegoda, N. T., and Rosso, R.: IDAF (intensity-duration-area frequency) curves of extreme storm rainfall: a scaling approach, Water Sci. Technol., 45, 83–90, https://doi.org/10.2166/WST.2002.0031, 2002.
Formetta, G., Marra, F., Dallan, E., Zaramella, M., and Borga, M.: Differential orographic impact on sub-hourly, hourly, and daily extreme precipitation, Adv. Water Resour., 159, 104085, https://doi.org/10.1016/j.advwatres.2021.104085, 2022.
Goldreich, Y.: The climate of Israel: observation, research and application, Springer, 298 pp., ISBN 978-0306474453, 2003.
Guan, H., Wilson, J. L., and Makhnin, O.: Geostatistical Mapping of Mountain Precipitation Incorporating Autosearched Effects of Terrain and Climatic Characteristics, J. Hydrometeorol., 6, 1018–1031, https://doi.org/10.1175/JHM448.1, 2005.
Gupta, V. K. and Waymire, E.: Multiscaling properties of spatial rainfall and river flow distributions, J. Geophys. Res., 95, 1999–2009, https://doi.org/10.1029/JD095ID03P01999, 1990.
Haiden, T., Kerschbaum, M., Kahlig, P., and Nobilis, F.: A refined model of the influence of orography on the mesoscale distribution of extreme precipitation, Hydrolog. Sci. J., 37, 417–427, https://doi.org/10.1080/02626669209492609, 1992.
Houze Jr., R., James, C. N., and Medina, S.: Radar observations of precipitation and airflow on the Mediterranean side of the Alps: Autumn 1998 and 1999, Q. J. Roy. Meteor. Soc., 127, 2537–2558, https://doi.org/10.1002/QJ.49712757804, 2001.
Hu, L., Nikolopoulos, E. I., Marra, F., Morin, E., Marani, M., and Anagnostou, E. N.: Evaluation of MEVD-based precipitation frequency analyses from quasi-global precipitation datasets against dense rain gauge networks, J. Hydrol., 590, 125564, https://doi.org/10.1016/J.JHYDROL.2020.125564, 2020.
Innocenti, S., Mailhot, A., and Frigon, A.: Simple scaling of extreme precipitation in North America, Hydrol. Earth Syst. Sci., 21, 5823–5846, https://doi.org/10.5194/hess-21-5823-2017, 2017.
Israel Meteorological Service: Meteorological Database, https://ims.gov.il/en/data_gov, last access: 10 April 2024a.
Israel Meteorological Service: Radar raw data, https://ims.gov.il/en/node/179, last access: 10 April 2024b.
Johnson, G. L. and Hanson, C. L.: Topographic and Atmospheric Influences on Precipitation Variability over a Mountainous Watershed, J. Appl. Meteorol. Clim., 34, 68–87, https://doi.org/10.1175/1520-0450-34.1.68, 1995.
Kao, S. C., DeNeale, S. T., Yegorova, E., Kanney, J., and Carr, M. L.: Variability of precipitation areal reduction factors in the conterminous United States, J. Hydrol. X, 9, 100064, https://doi.org/10.1016/j.hydroa.2020.100064, 2020.
Karklinsky, M. and Morin, E.: Spatial characteristics of radar-derived convective rain cells over southern Israel, Meteorol. Z., 15, 513–520, https://doi.org/10.1127/0941-2948/2006/0153, 2006.
Kidd, C., Becker, A., Huffman, G. J., Muller, C. L., Joe, P., Skofronick-Jackson, G., and Kirschbaum, D. B.: So, How Much of the Earth's Surface Is Covered by Rain Gauges?, B. Am. Meteorol. Soc., 98, 69–78, https://doi.org/10.1175/BAMS-D-14-00283.1, 2017.
Kim, J., Lee, J., Kim, D., and Kang, B.: The role of rainfall spatial variability in estimating areal reduction factors, J. Hydrol., 568, 416–426, https://doi.org/10.1016/j.jhydrol.2018.11.014, 2019.
Lassegues, P.: Daily and climatological fields of precipitation over the western Alps with a high density network for the period of 1990–2012, Theor. Appl. Climatol., 131, 1–17, https://doi.org/10.1007/s00704-016-1954-z, 2018.
Lee, T., Jo, J., and Singh, V. P.: Temporal downscaling of daily precipitation to 10 min data for assessment of climate change impact on floods in small-size watersheds applied to Jinju, South Korea, Clim. Dynam., 59, 2381–2407, https://doi.org/10.1007/s00382-022-06216-1, 2022.
Lengfeld, K., Kirstetter, P. E., Fowler, H. J., Yu, J., Becker, A., Flamig, Z., and Gourley, J.: Use of radar data for characterizing extreme precipitation at fine scales and short durations, Environ. Res. Lett., 15, 085003, https://doi.org/10.1088/1748-9326/AB98B4, 2020.
Marani, M. and Ignaccolo, M.: A metastatistical approach to rainfall extremes, Adv. Water. Resour., 79, 121–126, https://doi.org/10.1016/j.advwatres.2015.03.001, 2015.
Marra, F.: A Unified Framework for Extreme Sub-daily Precipitation Frequency Analyses based on Ordinary Events – data & codes, Zenodo [code], https://doi.org/10.5281/zenodo.3971558, 2020.
Marra, F. and Morin, E.: Use of radar QPE for the derivation of Intensity–Duration–Frequency curves in a range of climatic regimes, J. Hydrol., 531, 427–440, https://doi.org/10.1016/J.JHYDROL.2015.08.064, 2015.
Marra, F. and Morin, E.: Autocorrelation structure of convective rainfall in semiarid-arid climate derived from high-resolution X-Band radar estimates, Atmos. Res., 200, 126–138, https://doi.org/10.1016/j.atmosres.2017.09.020, 2018.
Marra, F., Morin, E., Peleg, N., Mei, Y., and Anagnostou, E. N.: Intensity–duration–frequency curves from remote sensing rainfall estimates: comparing satellite and weather radar over the eastern Mediterranean, Hydrol. Earth Syst. Sci., 21, 2389–2404, https://doi.org/10.5194/hess-21-2389-2017, 2017.
Marra, F., Nikolopoulos, E. I., Creutin, J. D., and Borga, M.: Radar rainfall estimation for the identification of debris-flow occurrence thresholds, J. Hydrol., 519, 1607–1619, https://doi.org/10.1016/J.JHYDROL.2014.09.039, 2014.
Marra, F., Nikolopoulos, E. I., Anagnostou, E. N., and Morin, E.: Metastatistical Extreme Value analysis of hourly rainfall from short records: Estimation of high quantiles and impact of measurement errors, Adv. Water. Resour., 117, 27–39, https://doi.org/10.1016/J.ADVWATRES.2018.05.001, 2018.
Marra, F., Zoccatelli, D., Armon, M., and Morin, E.: A simplified MEV formulation to model extremes emerging from multiple nonstationary underlying processes, Adv. Water. Resour., 127, 280–290, https://doi.org/10.1016/j.advwatres.2019.04.002, 2019a.
Marra, F., Nikolopoulos, E. I., Anagnostou, E. N., Bárdossy, A., and Morin, E.: Precipitation frequency analysis from remotely sensed datasets: A focused review, J. Hydrol., 574, 699–705, https://doi.org/10.1016/J.JHYDROL.2019.04.081, 2019b.
Marra, F., Borga, M., and Morin, E.: A Unified Framework for Extreme Subdaily Precipitation Frequency Analyses Based on Ordinary Events, Geophys. Res. Lett., 47, e2020GL090209, https://doi.org/10.1029/2020GL090209, 2020.
Marra, F., Armon, M., Borga, M., and Morin, E.: Orographic Effect on Extreme Precipitation Statistics Peaks at Hourly Time Scales, Geophys. Res. Lett., 48, e2020GL091498, https://doi.org/10.1029/2020GL091498, 2021.
Marra, F., Armon, M., and Morin, E.: Coastal and orographic effects on extreme precipitation revealed by weather radar observations, Hydrol. Earth Syst. Sci., 26, 1439–1458, https://doi.org/10.5194/hess-26-1439-2022, 2022.
Marra, F., Amponsah, W., and Papalexiou, S. M.: Non-asymptotic Weibull tails explain the statistics of extreme daily precipitation, Adv. Water. Resour., 173, 104388, https://doi.org/10.1016/J.ADVWATRES.2023.104388, 2023.
Mascaro, G., Papalexiou, S. M., and Wright, D. B.: Advancing Characterization and Modeling of Space-Time Correlation Structure and Marginal Distribution of Short-Duration Precipitation, Adv. Water. Resour., 177, 104451, https://doi.org/10.1016/J.ADVWATRES.2023.104451, 2023.
Mazzoglio, P., Butera, I., Alvioli, M., and Claps, P.: The role of morphology in the spatial distribution of short-duration rainfall extremes in Italy, Hydrol. Earth Syst. Sci., 26, 1659–1672, https://doi.org/10.5194/hess-26-1659-2022, 2022.
Mélèse, V., Blanchet, J., and Creutin, J. D.: A Regional Scale-Invariant Extreme Value Model of Rainfall Intensity-Duration-Area-Frequency Relationships, Water. Resour. Res., 55, 5539–5558, https://doi.org/10.1029/2018WR024368, 2019.
Miniussi, A. and Marra, F.: Estimation of extreme daily precipitation return levels at-site and in ungauged locations using the simplified MEV approach, J. Hydrol., 603, 126946, https://doi.org/10.1016/j.jhydrol.2021.126946, 2021.
Morin, E. and Gabella, M.: Radar-based quantitative precipitation estimation over Mediterranean and dry climate regimes, J. Geophys. Res.-Atmos., 112, 20108, https://doi.org/10.1029/2006JD008206, 2007.
Napoli, A., Crespi, A., Ragone, F., Maugeri, M., and Pasquero, C.: Variability of orographic enhancement of precipitation in the Alpine region, Sci. Rep., 9, 1–8, https://doi.org/10.1038/s41598-019-49974-5, 2019.
Nguyen, V. T. V., Nguyen, T. D., and Ashkar, F.: Regional frequency analysis of extreme rainfalls, Water Sci. Technol., 45, 75–81, https://doi.org/10.2166/WST.2002.0030, 2002.
Northrop, P.: A clustered spatial-temporal model of rainfall, P. Roy. Soc. A-Math. Phy., 454, 1875–1888, https://doi.org/10.1098/RSPA.1998.0238, 1998.
Olivera, F., Choi, J., Kim, D., and Li, M.-H.: Estimation of Average Rainfall Areal Reduction Factors in Texas Using NEXRAD Data, J. Hydrol. Eng., 13, 438–448, https://doi.org/10.1061/(asce)1084-0699(2008)13:6(438), 2008.
Overeem, A., Buishand, A., and Holleman, I.: Rainfall depth-duration-frequency curves and their uncertainties, J. Hydrol., 348, 124–134, https://doi.org/10.1016/J.JHYDROL.2007.09.044, 2008.
Overeem, A., Buishand, A., Holleman, I., and Uijlenhoet, R.: Extreme value modeling of areal rainfall from weather radar, Water Resour. Res., 46, W09514, https://doi.org/10.1029/2009WR008517, 2010.
Panthou, G., Vischel, T., Lebel, T., Quantin, G., and Molinié, G.: Characterising the space–time structure of rainfall in the Sahel with a view to estimating IDAF curves, Hydrol. Earth Syst. Sci., 18, 5093–5107, https://doi.org/10.5194/hess-18-5093-2014, 2014.
Pavlovic, S., Perica, S., St Laurent, M., and Mejía, A.: Intercomparison of selected fixed-area areal reduction factor methods, J. Hydrol., 537, 419–430, https://doi.org/10.1016/J.JHYDROL.2016.03.027, 2016.
Peleg, N. and Morin, E.: Convective rain cells: Radar-derived spatiotemporal characteristics and synoptic patterns over the eastern Mediterranean, J. Geophys. Res.-Atmos., 117, 15116, https://doi.org/10.1029/2011JD017353, 2012.
Peleg, N., Marra, F., Fatichi, S., Paschalis, A., Molnar, P., and Burlando, P.: Spatial variability of extreme rainfall at radar subpixel scale, J. Hydrol., 556, 922–933, https://doi.org/10.1016/J.JHYDROL.2016.05.033, 2018.
Pöschmann, J. M., Kim, D., Kronenberg, R., and Bernhofer, C.: An analysis of temporal scaling behaviour of extreme rainfall in Germany based on radar precipitation QPE data, Nat. Hazards Earth Syst. Sci., 21, 1195–1207, https://doi.org/10.5194/nhess-21-1195-2021, 2021.
Roe, G. H.: Orographic Precipitation, Annu. Rev. Earth Pl. Sc., 33, 645–671, https://doi.org/10.1146/ANNUREV.EARTH.33.092203.122541, 2005.
Schellander, H., Lieb, A., and Hell, T.: Error Structure of Metastatistical and Generalized Extreme Value Distributions for Modeling Extreme Rainfall in Austria, Earth and Space Science, 6, 1616–1632, https://doi.org/10.1029/2019EA000557, 2019.
Sherman, C. W.: Maximum Rates of Rainfall at Boston, T. Am. Soc. Civ. Eng., 54, 173–180, https://doi.org/10.1061/TACEAT.0001686, 1905.
Sivapalan, M. and Blöschl, G.: Transformation of point rainfall to areal rainfall: Intensity-duration-frequency curves, J. Hydrol., 204, 150–167, https://doi.org/10.1016/S0022-1694(97)00117-0, 1998.
Svensson, C. and Jones, D. A.: Review of methods for deriving areal reduction factors, J. Flood Risk Manag., 3, 232–245, https://doi.org/10.1111/j.1753-318X.2010.01075.x, 2010.
Tang, G., Long, D., Hong, Y., Gao, J., and Wan, W.: Documentation of multifactorial relationships between precipitation and topography of the Tibetan Plateau using spaceborne precipitation radars, Remote Sens. Environ., 208, 82–96, https://doi.org/10.1016/J.RSE.2018.02.007, 2018.
Thorndahl, S., Nielsen, J. E., and Rasmussen, M. R.: Estimation of storm-centred areal reduction factors from radar rainfall for design in urban hydrology, Water, 11, 1120, https://doi.org/10.3390/w11061120, 2019.
Vidrio-Sahagún, C. T. and He, J.: Hydrological frequency analysis under nonstationarity using the Metastatistical approach and its simplified version, Adv. Water Resour., 166, 104244, https://doi.org/10.1016/j.advwatres.2022.104244, 2022.
Wang, L.-P., Marra, F., and Onof, C.: Modelling sub-hourly rainfall extremes with short records – a comparison of MEV, Simplified MEV and point process methods, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6061, https://doi.org/10.5194/egusphere-egu2020-6061, 2020.
Wilson, P. S. and Toumi, R.: A fundamental probability distribution for heavy rainfall, Geophys. Res. Lett., 32, 8076–8082, https://doi.org/10.1029/2005GL022465, 2005.
Wright, D. B., Mantilla, R., and Peters-Lidard, C. D.: A remote sensing-based tool for assessing rainfall-driven hazards, Environ. Modell. Softw., 90, 34–54, https://doi.org/10.1016/J.ENVSOFT.2016.12.006, 2017.
Yamoat, N., Hanchoowong, R., Yamoad, O., Chaimoon, N., and Kangrang, A.: Estimation of regional intensity–duration–frequency relationships of extreme rainfall by simple scaling in Thailand, J. Water Clim. Change, 14, 796–810, https://doi.org/10.2166/WCC.2023.430, 2023.
Zoccatelli, D., Marra, F., Armon, M., Rinat, Y., Smith, J. A., and Morin, E.: Contrasting rainfall-runoff characteristics of floods in desert and Mediterranean basins, Hydrol. Earth Syst. Sci., 23, 2665–2678, https://doi.org/10.5194/hess-23-2665-2019, 2019.
Zorzetto, E., Botter, G., and Marani, M.: On the emergence of rainfall extremes from ordinary events, Geophys. Res. Lett., 43, 8076–8082, https://doi.org/10.1002/2016GL069445, 2016.
Short summary
Knowledge of extreme precipitation probability at various spatial–temporal scales is crucial. We estimate extreme precipitation return levels at multiple scales (10 min–24 h, 0.25–500 km2) in the eastern Mediterranean using radar data. We show our estimates are comparable to those derived from averaged daily rain gauges. We then explore multi-scale extreme precipitation across coastal, mountainous, and desert regions.
Knowledge of extreme precipitation probability at various spatial–temporal scales is crucial. We...
