Abstract
The disastrous flood that occurred in the southern area of Piedmont (north‐western Italy) at the beginning of November 1994 was associated with heavy rainfall episodes over a relatively small area in a course of events spanning the period 3–6 November 1994. The most intense rainfall (for which values over 200 mm were reported) occurred in two regions located in the upper reach of the Tanaro and Bormida river basins (Maritime Alps) and over the north‐west sector of the Alps. The distribution of rainfall intensities was different in the two areas where the precipitation peaks were observed. In the former, almost all rainfall was concentrated between the 4 and 5 November; in the second, rainfall was intense but spread over the entire period. The intense rainfall over these two mountain areas was enhanced by the confluence of the surface south‐easterly flow and of the upper‐level southerly current. This confluence was strongest over the two zones in which the maxima of rainfall and vertical wind velocity were observed. The cyclonic area was stationary over Western Europe for three consecutive days (4–6 November), due to the blocking situation over Eastern Europe. The mesoscale Regional Atmospheric Modelling System (RAMS), driven by the European Centre for Medium‐Range Weather Forecasts analyses, was used to simulate this event. We focused our attention on the target area (Tanaro and Bormida valleys). As we were interested in the hydrologic budget during the flood, we replaced the original soil scheme of RAMS (a version of Biosphere Atmosphere Transfer Scheme (BATS), too simplified to allow very detailed pattern resolution) with the Land Surface Process Model (LSPM). This method allowed all components of the hydrologic budget to be inferred during the flood episode, particularly the runoff and soil moisture content. The results of the simulation demonstrated that the coupled model RAMS–LSPM was able to give a quite realistic representation of a mesoscale event such as the flood event in this study. The coupling with LSPM improved RAMS not only because the coupled model can represent the upper‐ and surface‐level fields (geopotential, potential temperature and specific humidity), but also because it provides quantitative estimates of the hydrologic budget and other surface parameters. Copyright © 2002 John Wiley & Sons, Ltd.