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The mitigation of debris flow (DF) risk can be achieved by the means of reliable warning systems. At present time, operational warning systems are mostly based on critical rainfall thresholds (CRT) derived through the elaboration of past event records. The prediction ability of these systems strictly depends on the quality and availability of historical data. In order to overcome these limitations, in this work the CRT curves are derived from mathematical and numerical simulations carried out using a coupled hydrological-stability model. The CRT curves thus obtained are combined with rainfall nowcasts based on the observations of meteorological radar network. A case study in central Switzerland is presented. The performances of the proposed system are tested through a playback analysis of a past event. It results that the use of nowcasting allows for a crucial increment of the advance time interval.

Quantitative Precipitation Nowcasting (QPN) is one of the main applications of radar observations. On one hand, one of the most used nowcasting algorithms is Lagrangian extrapolation. It shows skill in specifying the timing and location of precipitation over short time periods, but shows low skill when using past precipitation trends to predict changes in precipitation intensity. On the other hand, Numerical Weather Prediction (NWP) models have roof skill at predicting the precise timing and location of precipitation, although they provide useful information about the intensity trends. It is therefore to investigate whether this additional information provided by NWP could be used to improve QPN. SBMcast (Berenguer et al., 2011) is an ensemble nowcasting algorithm based on Lagrangian extrapolation of recent radar observations. It generates a set of future rainfall scenarios (ensemble members) compatible with observations and preserving the spatial and temporal structure of the rainfall field according to the String of Beads model (Pegram and Clothier, 2001). This study shows the first results obtained with a methodology to constrain the spread of SBMcast ensembles with the additional information provided by NWP.

Tactical Environmental Processor (TEP) is a through-the-sensor technique that converts radar returns from the AN/SPY-1 into environmental information known as spectral moments. TEP was installed aboard the USS Normandy (CG 60) in May 2000 to support a Limited Objective Experiment during Joint Task Force Exercise (JTFEX) 00-2. On 15 May, TEP observed severe weather associated with a line of passing thunderstorms. These weather events proved serious enough to suspend mid-cycle flight operations for the USS George Washington (CVN 73) during its simulated wartime scenario. TEP is a significant benefit to nowcast weather forecasting and supports at-sea METOC and warfighters in two primary areas: improved situational awareness and optimization of sensors, weapons and tactics. Results from this case study demonstrate the importance of TEP as a Doppler at-sea weather radar in support of naval operations. http://archive.org/details/utilityoftactica109455850 Lieutenant, United States Navy Approved for public release; distribution is unlimited.

The objective of this study is to assess the skill of a precipitation nowcasting (very short range forecasting) system, with particular emphasis on hig-impact Heavy Precipitation Events (HPE). A threshold amount of 20 mm in 30 minutes is adopted, according to the first warning level issued for high rainfall rates by the Meteorological Service of Catalonia (NE Spain). These type of events are relatively frequent during autumn in the Mediterranean area and may produce flash-floods and substantial socio-economic losses when affecting densely populated areas in small catchments near the coast. Moreover, they can also produce local damage due to severe weather induced by winds of convective origin such as tornadoes or microbursts. Therefore, under these circumstances nowcasting systems producing very-short range (