From Deterministic to Probabilistic Forecasts: The ‘Shift-Target’ Approach in the Milan Urban Area (Northern Italy)

Abstract

The number of natural catastrophes that affect people worldwide is increasing; among these, the hydro-meteorological events represent the worst scenario due to the thousands of deaths and huge damages to private and state ownership they can cause. To prevent this, besides various structural measures, many non-structural solutions, such as the implementation of flood warning systems, have been proposed in recent years. In this study, we suggest a low computational cost method to produce a probabilistic flood prediction system using a single forecast precipitation scenario perturbed via a spatial shift. In fact, it is well-known that accurate forecasts of heavy precipitation, especially associated with deep moist convection, are challenging due to uncertainties arising from the numerical weather prediction (NWP), and high sensitivity to misrepresentation of the initial atmospheric state. Inaccuracies in precipitation forecasts are partially due to spatial misplacing. To produce hydro-meteorological simulations and forecasts, we use a flood forecasting system which comprises the physically-based rainfall-runoff hydrological model FEST-WB developed by the Politecnico di Milano, and the MOLOCH meteorological model provided by the Institute of Atmospheric Sciences and Climate (CNR-ISAC). The areas of study are the hydrological basins of the rivers Seveso, Olona, and Lambro located in the northern part of Milan city (northern Italy) where this system works every day in real-time. In this paper, we show the performance of reforecasts carried out between the years 2012 and 2015: in particular, we explore the 'Shift-Target' (ST) approach in order to obtain 40 ensemble members, which we assume equally likely, derived from the available deterministic precipitation forecast. Performances are shown through statistical indexes based on exceeding the threshold for different gauge stations over the three hydrological basins. Results highlight how the Shift-Target approach complements the deterministic MOLOCH-based flood forecast for warning purposes.

The Piedmont flood of November 1994: a testbed of forecasting capabilities of the CNR-ISAC meteorological model suite

“…They have been used for numerous scientific studies and applications, as for instance: sensitivity and impact studies, and diagnostics of meteorological phenomena including severe weather and storms (e.g. Malguzzi et al 2006 ; Cavaleri et al 2010 ; Fantini et al 2012 ; Cioni et al 2016 ; Davolio et al 2016 , 2017a ; Buzzi et al 2020 ); model coupling with hydrological and ocean models (Davolio et al 2015 ; Lombardi et al 2018 ; Ferrarin et al 2013 , 2019 ; Poletti et al 2019 ); theoretical and idealized studies of instability processes (Davolio et al 2009 ; Fantini and Malguzzi 2008 ); applications to probabilistic and ensemble forecasting, and atmospheric predictability studies (Uboldi and Trevisan 2015 ; Corazza et al 2018 ); data assimilation studies (Tiesi et al 2016 ; Davolio et al 2017b ); model validation and intercomparison projects (Nagata et al 2001 ; Casaioli et al 2013 ). The ISAC NWP models have also been employed as basic tools in many international field experiments such as the international forecasting demonstration project called MAP D-PHASE (Rotach et al 2009 ) and the HyMeX campaign SOP1 (Ducrocq et al 2014 ; Ferretti et al 2014 ), and in numerous European scientific projects.…”

Hydrological Hazard: Analysis and Prevention

“…Among the 13 articles published in the Special Issue, 1 is a Technical Note (Terranova et al [4]), 11 are Research Articles [5][6][7][8][9][10][11][12][13][14][15], and one is a Case Report (Schmid-Breton et al [16]). Figure 1 compares the geographic distribution of the authors and research teams publishing in the Special Issue (Figure 1a), as well as of the case studies and demonstration sites ( Figure 1b).…”

“…Lombardi et al [7] suggested a low computational cost method to produce a probabilistic flood prediction system using a single forecast precipitation scenario perturbed via a spatial shift. The method was applied to three basins located in the northern part of Milan city (northern Italy): Seveso, Olona, and Lambro.…”

“…Word cloud of the keywords published in the papers[4][5][6][7][8][9][10][11][12][13][14] of this Special Issue.…”

Hydrometeorological Ensemble Forecast of a Highly Localized Convective Event in the Mediterranean

“…On the other hand, complementary strategies for improving the forecast accuracy with a longer lead time can be based on both ensemble forecasts and data assimilation (e.g., [67,68]). Even the impact on the ground can be assessed through innovative approaches dealing with uncertainties, like [69], that is particularly useful for highly localized events.…”