• Aceto, L., T. Caloiero, A. A. Pasqua, and O. Petrucci, 2016: Analysis of damaging hydrogeological events in a Mediterranean region (Calabria). J. Hydrol., 541, 510522, https://doi.org/10.1016/j.jhydrol.2015.12.041.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Avolio, E., and S. Federico, 2018: WRF simulations for a heavy rainfall event in southern Italy: Verification and sensitivity tests. Atmos. Res., 209, 1435, https://doi.org/10.1016/j.atmosres.2018.03.009.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Avolio, E., O. Cavalcanti, L. Furnari, A. Senatore, and G. Mendicino, 2019: Brief communication: Preliminary hydro-meteorological analysis of the flash flood of 20 August 2018 in Raganello Gorge, southern Italy. Nat. Hazards Earth Syst. Sci., 19, 16191627, https://doi.org/10.5194/nhess-19-1619-2019.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bauer, H., T. Weusthoff, M. Dorninger, V. Wulfmeyer, T. Schwitalla, T. Gorgas, M. Arpagaus, and K. Warrach-Sagi, 2011: Predictive skill of a subset of models participating in D-PHASE in the COPS region. Quart. J. Roy. Meteor. Soc., 137, 287305, https://doi.org/10.1002/qj.715.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Buzzi, A., M. D’Isidoro, and S. Davolio, 2003: A case study of an orographic cyclone south of the Alps during the MAP SOP. Quart. J. Roy. Meteor. Soc., 129, 17951818, https://doi.org/10.1256/qj.02.112.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Buzzi, A., S. Davolio, P. Malguzzi, O. Drofa, and D. Mastrangelo, 2014: Heavy rainfall episodes over Liguria of autumn 2011: Numerical forecasting experiments. Nat. Hazards Earth Syst. Sci., 14, 13251340, https://doi.org/10.5194/nhess-14-1325-2014.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • CFM, 2015a: Rapporto speditivo di evento metopluviometrico del 12 agosto 2015 (in Italian). Centro Funzionale Multirischi della Calabria Tech. Rep., 17 pp., https://www.cfd.calabria.it//DatiVari/Pubblicazioni/rapporto%20di%20evento%2012%20agosto.pdf.

  • CFM, 2015b: Rapporto speditivo di evento metopluviometrico del 30 ottobre - 2 novembre 2015 (in Italian). Centro Funzionale Multirischi della Calabria Tech. Rep., 36 pp., https://www.cfd.calabria.it//DatiVari/Pubblicazioni/rapporto%20di%20evento%2030%20ottobre-2%20novembre2015.pdf.

  • CFM, 2016: Rapporto speditivo di evento metopluviometrico del 25-26 novembre 2016 (in Italian). Centro Funzionale Multirischi della Calabria Tech. Rep., 31 pp., https://www.cfd.calabria.it//DatiVari/Pubblicazioni/rapporto%20di%20evento%2025-26%20novembre2016.pdf.

  • Chen, S. H., and W.-Y. Sun, 2002: A one-dimensional time dependent cloud model. J. Meteor. Soc. Japan, 80, 99118, https://doi.org/10.2151/jmsj.80.99.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chiaravalloti, F., and S. Gabriele, 2009: Vibo Valentia flood and MSG rainfall evaluation. Atmos. Res., 93, 286294, https://doi.org/10.1016/j.atmosres.2008.10.027.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Clark, P., N. Roberts, H. Lean, S. P. Ballard, and C. Charlton-Perez, 2016: Convection-permitting models: A step-change in rainfall forecasting. Meteor. Appl., 23, 165181, https://doi.org/10.1002/met.1538.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Coppola, E., and et al. , 2018: A first-of-its-kind multi-model convection permitting ensemble for investigating convective phenomena over Europe and the Mediterranean. Climate Dyn., 55, 334, https://doi.org/10.1007/s00382-018-4521-8.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Davolio, S., F. Silvestro, and P. Malguzzi, 2015: Effects of increasing horizontal resolution in a convection-permitting model on flood forecasting: The 2011 dramatic events in Liguria, Italy. J. Hydrometeor., 16, 18431856, https://doi.org/10.1175/JHM-D-14-0094.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Davolio, S., R. Henin, P. Stocchi, and A. Buzzi, 2017: Bora wind and heavy persistent precipitation: Atmospheric water balance and role of air-sea fluxes over the Adriatic Sea. Quart. J. Roy. Meteor. Soc., 143, 11651177, https://doi.org/10.1002/qj.3002.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dee, D. P., and et al. , 2011: The ERA-Interim reanalysis: Configuration and performance of the data assimilation system. Quart. J. Roy. Meteor. Soc., 137, 553597, https://doi.org/10.1002/qj.828.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ducrocq, V., and et al. , 2014: HyMeX-SOP1: The field campaign dedicated to heavy precipitation and flash flooding in the northwestern Mediterranean. Bull. Amer. Meteor. Soc., 95, 10831100, https://doi.org/10.1175/BAMS-D-12-00244.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dudhia, J., 1989: Numerical study of convection observed during the winter monsoon experiment using a mesoscale two-dimensional model. J. Atmos. Sci., 46, 30773107, https://doi.org/10.1175/1520-0469(1989)046<3077:NSOCOD>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Federico, S., C. Bellecci, and M. Colacino, 2003: Quantitative precipitation of the Soverato flood: The role of orography and surface fluxes. Nuovo Cimento, 26, 722.

    • Search Google Scholar
    • Export Citation
  • Federico, S., E. Avolio, C. Bellecci, A. Lavagnini, M. Colacino, and R. L. Walko, 2008: Numerical analysis of an intense rainstorm occurred in southern Italy. Nat. Hazards Earth Syst. Sci., 8, 1935, https://doi.org/10.5194/nhess-8-19-2008.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Fiori, E., A. Comellasa, D. Molini, N. Rebora, F. Siccardi, D. Gochis, S. Tanelli, and A. Parodi, 2014: Analysis and hindcast simulations of an extreme rainfall event in the Mediterranean area: The Genoa 2011 case. Atmos. Res., 138, 1329, https://doi.org/10.1016/j.atmosres.2013.10.007.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Flaounas, S., L. Fita, K. Lagouvardos, and V. Kotroni, 2019: Heavy rainfall in Mediterranean cyclones, Part II: Water budget, precipitation efficiency and remote water sources. Climate Dyn., 53, 25392555, https://doi.org/10.1007/s00382-019-04639-x.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gascòn, E., S. Laviola, A. Merino, and M. M. Miglietta, 2016: Analysis of a localized flash-flood event over the central Mediterranean. Atmos. Res., 182, 256268, https://doi.org/10.1016/j.atmosres.2016.08.007.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gochis, D. J., W. Yu, and D. N. Yates, 2015: The WRF-Hydro model technical description and user’s guide, version 3.0. NCAR Tech. Doc., 123 pp., https://ral.ucar.edu/sites/default/files/public/WRF_Hydro_User_Guide_v3.0_CLEAN.pdf.

  • Grell, G. A., L. Schade, R. Knoche, A. Pfeiffer, and J. Egger, 2000: Nonhydrostatic climate simulations of precipitation over complex terrain. J. Geophys. Res., 105, 29 59529 608, https://doi.org/10.1029/2000JD900445.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hennermann, K., and P. Berrisford, 2018: What are the changes from ERA-Interim to ERA5? ECMWF, https://confluence.ecmwf.int/pages/viewpage.action?pageId=74764925.

  • Hersbach, H., and D. Dee, 2016: ERA5 reanalysis is in production. ECMWF Newsletter, No. 147, ECMWF, Reading, United Kingdom, 7, https://www.ecmwf.int/en/newsletter/147/news/era5-reanalysis-production.

  • Hong, S.-Y., and M. Kanamitsu, 2014: Dynamical downscaling: Fundamental issues from an NWP point of view and recommendations. Asia-Pac. J. Atmos. Sci., 50, 83104, https://doi.org/10.1007/s13143-014-0029-2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Janjić, Z. I., 1994: The step-mountain Eta coordinate model: Further developments of the convection, viscous sublayer, and turbulence closure schemes. Mon. Wea. Rev., 122, 927945, https://doi.org/10.1175/1520-0493(1994)122<0927:TSMECM>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kain, J. S., 2004: The Kain–Fritsch convective parameterization: An update. J. Appl. Meteor., 43, 170181, https://doi.org/10.1175/1520-0450(2004)043<0170:TKCPAU>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Khodayar, S., and et al. , 2016: A seamless weather-climate multi-model intercomparison on the representation of a high impact weather event in the western Mediterranean: HyMeX IOP12. Quart. J. Roy. Meteor. Soc., 142, 433452, https://doi.org/10.1002/qj.2700.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Li, L., M. Pontoppidan, S. Sobolowski, and A. Senatore, 2020: The impact of initial conditions on convection-permitting simulations of a flood event over complex mountainous terrain. Hydrol. Earth Syst. Sci., 24, 771791, https://doi.org/10.5194/hess-24-771-2020.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Llasat, M. C., M. Llasat-Botija, O. Petrucci, A. A. Pasqua, J. Rosselló, F. Vinet, and L. Boissier, 2013: Towards a database on societal impact of Mediterranean floods within the framework of the HYMEX project. Nat. Hazards Earth Syst. Sci., 13, 13371350, https://doi.org/10.5194/nhess-13-1337-2013.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Malguzzi, P., G. Grossi, A. Buzzi, R. Ranzi, and R. Buizza, 2006: The 1966 ‘century’ flood in Italy: A meteorological and hydrological revisitation. J. Geophys. Res., 111, D24106, https://doi.org/10.1029/2006JD007111.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mass, C. F., D. Ovens, K. Westrick, and B. A. Colle, 2002: Does increasing horizontal resolution produce more skillful forecasts? Bull. Amer. Meteor. Soc., 83, 407430, https://doi.org/10.1175/1520-0477(2002)083<0407:DIHRPM>2.3.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mellor, G. L., and T. Yamada, 1982: Development of a turbulence closure model for geophysical fluid problems. Rev. Geophys., 20, 851875, https://doi.org/10.1029/RG020i004p00851.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Merchant, C. J., M. J. Filipiak, P. Le Borgne, H. Roquet, E. Autret, J. F. Piolle, and S. Lavender, 2008: Diurnal warm-layer events in the western Mediterranean and European shelf seas. Geophys. Res. Lett., 35, L04601, https://doi.org/10.1029/2007GL033071.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mlawer, E. J., S. J. Taubman, P. D. Brown, M. J. Iacono, and S. A. Clough, 1997: Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave. J. Geophys. Res., 102, 16 66316 682, https://doi.org/10.1029/97JD00237.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Morcrette, J. J., H. W. Barker, J. N. S. Cole, M. J. Iacono, and R. Pincus, 2008: Impact of a new radiation package, McRad, in the ECMWF integrated forecasting system. Mon. Wea. Rev., 136, 47734798, https://doi.org/10.1175/2008MWR2363.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pappenberger, F., K. J. Beven, N. M. Hunter, P. D. Bates, B. T. Gouweleeuw, J. Thielen, and A. P. J. de Roo, 2005: Cascading model uncertainty from medium range weather forecasts (10 days) through a rainfall-runoff model to flood inundation predictions within the European Flood Forecasting System (EFFS). Hydrol. Earth Syst. Sci., 9, 381393, https://doi.org/10.5194/hess-9-381-2005.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Polemio, M., and O. Petrucci, 2012: The occurrence of floods and the role of climate variations from 1880 in Calabria (southern Italy). Nat. Hazards Earth Syst. Sci., 12, 129142, https://doi.org/10.5194/nhess-12-129-2012.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pontoppidan, M., J. Reuder, S. Mayer, and E. W. Kolstad, 2017: Downscaling an intense precipitation event in complex terrain: The importance of high grid resolution. Tellus, 69A, 1271561, https://doi.org/10.1080/16000870.2016.1271561.

    • Search Google Scholar
    • Export Citation
  • Prein, A. F., and et al. , 2015: A review on regional convection-permitting climate modeling: Demonstrations, prospects, and challenges. Rev. Geophys., 53, 323361, https://doi.org/10.1002/2014RG000475.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Richard, E. A., A. Buzzi, and G. Zängl, 2007: Quantitative precipitation forecasting in the Alps: The advances achieved by the Mesoscale Alpine Programme. Quart. J. Roy. Meteor. Soc., 133, 831846, https://doi.org/10.1002/qj.65.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ritter, B., and J. F. Geleyn, 1992: A comprehensive radiation scheme for numerical weather prediction models with potential applications in climate simulations. Mon. Wea. Rev., 120, 303325, https://doi.org/10.1175/1520-0493(1992)120<0303:ACRSFN>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Roberts, N. M., 2008: Assessing the spatial and temporal variation in the skill of precipitation forecasts from an NWP model. Meteor. Appl., 15, 163169, https://doi.org/10.1002/met.57.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Roberts, N. M., and H. W. Lean, 2008: Scale-selective verification of rainfall accumulations from high-resolution forecasts of convective events. Mon. Wea. Rev., 136, 7897, https://doi.org/10.1175/2007MWR2123.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Robinson, I., J. F. Piolle, P. Leborgne, D. Poulter, C. Donlon, and O. Arino, 2012: Widening the application of AATSR SST data to operational tasks through the Medspiration Service. Remote Sens. Environ., 116, 126139, https://doi.org/10.1016/j.rse.2010.12.019.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rossa, A., P. Nurmi, and E. Ebert, 2008: Overview of methods for the verification of quantitative precipitation forecasts. Precipitation: Advances in Measurement, Estimation and Prediction, S. Michaelides, Ed., Springer, 419452, https://doi.org/10.1007/978-3-540-77655-0_16.

    • Crossref
    • Export Citation
  • Schwartz, C. S., and et al. , 2009: Next-day convection-allowing WRF model guidance: A second look at 2-km versus 4-km grid spacing. Mon. Wea. Rev., 137, 33513372, https://doi.org/10.1175/2009MWR2924.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Senatore, A., G. Mendicino, H. R. Knoche, and H. Kunstmann, 2014: Sensitivity of modeled precipitation to sea surface temperature in region with complex topography and coastlines: A case study for the Mediterranean. J. Hydrometeor., 15, 23702396, https://doi.org/10.1175/JHM-D-13-089.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Senatore, A., G. Mendicino, D. J. Gochis, W. Yu, D. N. Yates, and H. Kunstmann, 2015: Fully coupled atmosphere-hydrology simulations for the central Mediterranean: Impact of enhanced hydrological parameterization for short and long time scales. J. Adv. Model. Earth Syst., 7, 16931715, https://doi.org/10.1002/2015MS000510.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Senatore, A., L. Furnari, and G. Mendicino, 2020: Impact of high-resolution sea surface temperature representation on the forecast of small Mediterranean catchments’ hydrological response to heavy precipitation. Hydrol. Earth Syst. Sci., 24, 269291, https://doi.org/10.5194/hess-24-269-2020.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sinclair, S., and G. Pegram, 2005: Combining radar and rain gauge rainfall estimates using conditional merging. Atmos. Sci. Lett., 6, 1922, https://doi.org/10.1002/asl.85.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Skamarock, W. C., and et al. , 2008: A description of the advanced research WRF version 3. NCAR Tech. Note NCAR/TN-475+STR, 113 pp., https://doi.org/10.5065/D68S4MVH.

    • Crossref
    • Export Citation
  • Skok, G., and N. Roberts, 2016: Analysis of fractions skill score properties for random precipitation fields and ECMWF forecasts. Quart. J. Roy. Meteor. Soc., 142, 25992610, https://doi.org/10.1002/qj.2849.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Stark, J. D., C. J. Donlon, M. J. Martin, and M. E. McCulloch, 2007: OSTIA: An operational, high resolution, real time, global sea surface temperature analysis system. Oceans 2007–Europe, Aberdeen, Scotland, IEEE, 1–4, https://doi.org/10.1109/OCEANSE.2007.4302251.

    • Crossref
    • Export Citation
  • Stocchi, P., and S. Davolio, 2017: Intense air-sea exchanges and heavy orographic precipitation over Italy: The role of Adriatic Sea surface temperature uncertainty. Atmos. Res., 196, 6282, https://doi.org/10.1016/j.atmosres.2017.06.004.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tewari, M., and et al. , 2004: Implementation and verification of the unified NOAH land surface model in the WRF model. 20th Conf. on Weather Analysis and Forecasting/16th Conf. on Numerical Weather Prediction, Silver Spring, MD, Amer. Meteor. Soc., 14.2a, https://ams.confex.com/ams/84Annual/techprogram/paper_69061.htm.

  • Verri, G., N. Pinardi, D. Gochis, J. Tribbia, A. Navarra, G. Coppini, and T. Vukicevic, 2017: A meteo-hydrological modelling system for the reconstruction of river runoff: The case of the Ofanto River catchment. Nat. Hazards Earth Syst. Sci., 17, 17411761, https://doi.org/10.5194/nhess-17-1741-2017.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Weusthoff, T., F. Ament, M. Arpagaus, and M. W. Rotach, 2010: Assessing the benefits of convection permitting models by neighborhood verification: Examples from MAP D-PHASE. Mon. Wea. Rev., 138, 34183433, https://doi.org/10.1175/2010MWR3380.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wilks, S. D., 2006: Statistical Methods in the Atmospheric Sciences. 2nd ed. International Geophysics Series, Vol. 100, Academic Press, 648 pp.

  • Yucel, I., A. Onen, K. Yilmaz, and D. J. Gochis, 2015: Calibration and evaluation of a flood forecasting system: Utility of numerical weather prediction model, data assimilation and satellite-based rainfall. J. Hydrol., 523, 4966, https://doi.org/10.1016/j.jhydrol.2015.01.042.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zampieri, M., P. Malguzzi, and A. Buzzi, 2005: Sensitivity of quantitative precipitation forecasts to boundary layer parameterization: A flash flood case study in the western Mediterranean. Nat. Hazards Earth Syst. Sci., 5, 603612, https://doi.org/10.5194/nhess-5-603-2005.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zappa, M., and et al. , 2010: Propagation of uncertainty from observing systems and NWP into hydrological models: COST731 working group 2. Atmos. Sci. Lett., 11, 8391, https://doi.org/10.1002/asl.248.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zeng, X., and A. Beljaars, 2005: A prognostic scheme of sea surface skin temperature for modeling and data assimilation. Geophys. Res. Lett., 32, L14605, https://doi.org/10.1029/2005GL023030.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zsoter, E., H. Cloke, E. Stephens, P. de Rosnay, J. Muñoz-Sabater, C. Prudhomme, and F. Pappenberger, 2019: How well do operational numerical weather prediction setups represent hydrology? J. Hydrometeor., 20, 15331552, https://doi.org/10.1175/JHM-D-18-0086.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
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Reconstructing Flood Events in Mediterranean Coastal Areas Using Different Reanalyses and High-Resolution Meteorological Models

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  • 1 Department of Environmental Engineering, University of Calabria, Rende, Italy
  • | 2 Institute of Atmospheric Sciences and Climate, CNR-ISAC, Bologna, Italy
  • | 3 Department of Environmental Engineering, University of Calabria, Rende, Italy
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Abstract

Reliable reanalysis products can be exploited to drive mesoscale numerical models and generate high-resolution reconstructions of high-impact weather events. Within this framework, regional weather and climate models may greatly benefit from the recent release of the ERA5 product, an improvement to the ERA-Interim dataset. In this study, two different convection-permitting models driven by these two reanalysis datasets are used to reproduce three heavy precipitation events affecting a Mediterranean region. Moreover, different sea surface temperature (SST) initializations are tested to assess how higher-resolution SST fields improve the simulation of high-impact events characterized by strong air–sea interactions. Finally, the coupling with a distributed hydrological model allows evaluating the impact at the ground, specifically assessing the possible added value of the ERA5 dataset for the high-resolution simulation of extreme hydrometeorological events over the Calabria region (southern Italy). Results, based on the comparison against multiple-source precipitation observations, show no clear systematic benefit to using the ERA5 dataset; moreover, intense convective activity can introduce uncertainties masking the signal provided by the boundary conditions of the different reanalyses. The effect of the high-resolution SST fields is even more difficult to detect. The uncertainties propagate and amplify along the modeling chain, where the spatial resolution increases up to the hydrological model. Nevertheless, even in very small catchments, some of the experiments provide reasonably accurate results, suggesting that an ensemble approach could be suitable to cope with uncertainties affecting the overall meteo-hydrological chain, especially for small catchments.

Corresponding author: Alfonso Senatore, alfonso.senatore@unical.it

Abstract

Reliable reanalysis products can be exploited to drive mesoscale numerical models and generate high-resolution reconstructions of high-impact weather events. Within this framework, regional weather and climate models may greatly benefit from the recent release of the ERA5 product, an improvement to the ERA-Interim dataset. In this study, two different convection-permitting models driven by these two reanalysis datasets are used to reproduce three heavy precipitation events affecting a Mediterranean region. Moreover, different sea surface temperature (SST) initializations are tested to assess how higher-resolution SST fields improve the simulation of high-impact events characterized by strong air–sea interactions. Finally, the coupling with a distributed hydrological model allows evaluating the impact at the ground, specifically assessing the possible added value of the ERA5 dataset for the high-resolution simulation of extreme hydrometeorological events over the Calabria region (southern Italy). Results, based on the comparison against multiple-source precipitation observations, show no clear systematic benefit to using the ERA5 dataset; moreover, intense convective activity can introduce uncertainties masking the signal provided by the boundary conditions of the different reanalyses. The effect of the high-resolution SST fields is even more difficult to detect. The uncertainties propagate and amplify along the modeling chain, where the spatial resolution increases up to the hydrological model. Nevertheless, even in very small catchments, some of the experiments provide reasonably accurate results, suggesting that an ensemble approach could be suitable to cope with uncertainties affecting the overall meteo-hydrological chain, especially for small catchments.

Corresponding author: Alfonso Senatore, alfonso.senatore@unical.it
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