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Reforecasting the Flooding of Florence of 4 November 1966 With Global and Regional Ensembles
Author(s) -
Capecchi Valerio,
Buizza Roberto
Publication year - 2019
Publication title -
journal of geophysical research: atmospheres
Language(s) - English
Resource type - Journals
eISSN - 2169-8996
pISSN - 2169-897X
DOI - 10.1029/2018jd030231
Subject(s) - predictability , precipitation , meteorology , climatology , environmental science , range (aeronautics) , numerical weather prediction , event (particle physics) , ensemble forecasting , quantitative precipitation forecast , global forecast system , computer science , flooding (psychology) , hydrometeorology , geography , statistics , mathematics , geology , psychology , materials science , physics , quantum mechanics , composite material , psychotherapist
Providing skilful predictions of high‐impact weather up to 2 weeks ahead is on the agenda of international weather centers. Evaluating the capabilities of current numerical systems in predicting past events can bring extremely valuable contributions to the assessment of the information content available today with operational models. In the framework of the activities for the fiftieth anniversary of the extreme precipitation event that occurred in Italy in November 1966, this paper investigates its predictability using state‐of‐the‐art global and regional ensemble simulations. The first goal is to assess if and how many days in advance, this event can be predicted by current European Centre for Medium‐Range Weather Forecasts (ECMWF) global ensembles. A second goal is to evaluate the potential added value of running nested higher‐resolution and convection‐permitting ensembles. It is shown that ECMWF ensembles are able to provide valuable information up to 3 days before the event. Within this forecast range, convection‐permitting simulations can provide more accurate estimations of precipitation maxima. However, the results indicate also a strong underestimation of rainfall amounts with both global and regional models even at short forecast range. To partially explain this shortcoming, we discuss how the scarcity of observations available in 1966 for the analysis process limits the quality of the ensemble initial conditions and we adopt a method to obtain more reliable ensemble forecasts. The paper concludes with a comparison with previous similar works; results indicate a gain in predictability of up to 12 hr with respect to numerical revisitations performed to mark the fortieth anniversary of the event.