Orographic Precipitation Extremes: An Application of LUME (Linear Upslope Model Extension) over the Alps and Apennines in Italy

Abstract

Critical hydrometeorological events are generally triggered by heavy precipitation. In complex terrain, precipitation may be perturbed by the upslope raising of the incoming humid airflow, causing in some cases extreme rainfall. In this work, the application of LUME—Linear Upslope Model Extension—to a group of extreme events that occurred across mountainous areas of the Central Alps and Apennines in Italy is presented. Based on the previous version, the model has been “extended” in some aspects, proposing a methodology for physically estimating the time-delay coefficients as a function of precipitation efficiency. The outcomes of LUME are encouraging for the cases studied, revealing the intensification of precipitation due to the orographic effect. A comparison between the reference rain gauge data and the results of the simulations showed good agreement. Since extreme precipitation is expected to increase due to climate change, especially across the Mediterranean region, LUME represents an effective tool to investigate more closely how these extreme phenomena originate and evolve in mountainous areas that are subject to potential hydrometeorological risks.

SLEM (Shallow Landslide Express Model): A Simplified Geo-Hydrological Model for Powerlines Geo-Hazard Assessment

“…In the recent past, this catchment was hit by severe geo-hydrological issues (i.e., flash floods, debris flows, and diffuse landslide failures) triggered by heavy rain events. In October 2015, the Trebbia River was affected by a flood caused by a convective storm that triggered over the basin several episodes of shallow landslides and debris flow that hit main roads and town buildings and interrupted local infrastructures [65,66,91]. Across the Trebbia basin, several electrical infrastructures are exposed to geo-hydrological hazards because they are located in the proximities of landslide polygons mapped by the IFFI (Inventario Fenomeni Franosi Italiano) census [16] (Figure 5).…”

Estimation of Real-Time Rainfall Fields Reflecting the Mountain Effect of Rainfall Explained by the WRF Rainfall Fields

“…Previous studies have highlighted the importance of orographic effects on the spatial distribution of rainfall in mountainous areas [1][2][3][4][5][6][7][8]. The mountain effect, also known as the orographic effect, may cause rainfall intensification, acting as a precursor of convective storm formation [9,10]. It is expected that climate change caused by global warming will intensify the spatio-temporal variability of rainfall and extreme phenomena [11], and this mountain effect can be strengthened.…”

“…Similarly, Patel et al [22] utilized WRF to predict extreme flooding in western coastal cities of India, and Caumont et al [23] simulated extreme storm events in France using a weather prediction numerical model. While numerical weather forecasting models excel in consistently simulating the dynamics of the atmosphere and addressing orographic precipitation generation mechanisms more accurately [9], their long computing time makes them unsuitable for forecasting and warning purposes.…”