Daily quantitative precipitation forecasts based on the analogue method: Improvements and application to a French large river basin

• A precipitation forecast method based on analogues is adapted to a large river basin.
• Temperature is introduced to take into account seasonal effects on precipitation.
• Vertical velocity is introduced to better characterise large-scale vertical motion.
• The upgraded analogue method is then applied in operational forecasting context.
• A substantial increase in skill is obtained until the lead-time of three days.

This paper presents some improvements of a probabilistic quantitative precipitation forecasting method based on analogues, formerly developed on small basins located in South-Eastern France. The scope is extended to large scale basins mainly influenced by frontal systems, considering a case study area related to the Saône river, a large basin in eastern France. For a given target situation, this method consists in searching for the most similar situations observed in a historical meteorological archive. Precipitation amounts observed during analogous situations are then collected to derive an empirical predictive distribution function, i.e. the probabilistic estimation of the precipitation amount expected for the target day. The former version of this forecasting method (Bontron, 2004) has been improved by introducing two innovative variables: temperature, that allows taking seasonal effects into account and vertical velocity, which enables a better characterization of the vertical atmospheric motion. The new algorithm is first applied in a perfect prognosis context (target situations come from a meteorological reanalysis) and then in an operational forecasting context (target situations come from weather forecasts) for a three years period. Results show that this approach yields useful forecasts, with a lower false alarm rate and improved performances from the present day D to day D + 2.