Toward Real-Time Daily PQPF by an Analog Sorting Approach: Application to Flash-Flood Catchments

International audienceHeavy rainfall events are rather common in Southern France and result frequently in devastating flash floods. Thus, an appropriate anticipation of future rainfall is required for early flood warning, at least 12 to 24 hours in advance, as well as for alerting operational services, at least 2 or 3 days ahead. Precipitation forecasts are generally provided by numerical weather prediction models (NWP) and their associated uncertainty is generally estimated through an ensemble approach. Precipitation forecasts have also to be adapted to hydrological scales. This study describes an alternative approach to commonly used Limited Area Models. Probabilistic Quantitative Precipitation Forecasts (PQPFs) are provided through an analog sorting technique, which directly links synoptic scale NWP output to catchment scale rainfall probability distributions. A first issue concerns our latest developments to implement a daily version of this technique into operational conditions. It is shown that the obtained PQPFs depend on the meteorological forecasts used for selecting analogous days and that the methodology has to be re-optimized when changing the source of synoptic forecasts, because of the NWP output uncertainties. Secondly, an evaluation of the PQPFs demonstrates that the analog technique performs well for early warning of heavy rainfall events and provides useful information as potential input of a hydrological ensemble prediction system. However, it is shown that the obtained daily rainfall distributions can be unreliable. A statistical correction of the observed bias is proposed as a function of the no rain frequency values, leading to a significant improvement in PQPF's sharpness