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Being able to predict meteorological droughts several weeks ahead would add value to many sectors including agriculture, river shipping as well as water and energy management. A commonly used meteorological drought index is the standardized precipitation index SPI-N, which puts precipitation anomalies of the past N months into a climatological perspective. The SPI correlates with anomalies of soil-moisture, streamflow or groundwater storage, and thus serves as an inexpensive and attractive hydrological proxy. In this study we quantify how well the SPI-N can be skillfully forecasted in Switzerland. Using ECMWF IFS extended-range forecasts quantile mapped from its native 36 km to a 2 km grid, we produce ensembles of SPI-N forecasts for the Swiss drought warning regions. While previous research has underlined the challenges faced by ensemble forecasting systems in accurately predicting daily precipitation in Europe beyond lead week 1, our analysis reveals that the skill of SPI-1, SPI-3, and SPI-6 forecasts extends into weeks 3 and 4. It generally holds that skill SPI-6 > skill SPI-3 > skill SPI-1. For example, we find that the skill of an SPI-3 forecast for week 4 is comparable to the skill of an SPI-1 forecast for week 2. Overall, the results indicate the potential for skillful prediction of meteorological drought on sub-seasonal timescales. We link the extended predictability horizon to the inherent characteristics of the SPI being a temporal aggregate: the SPI is less sensitive to the exact timing of precipitation events, while also retaining memory of past precipitation. The latter manifests in larger skill for longer accumulation time N, in which more observation are weighted into the forecasted SPI. Finally, we show how SPI forecasts and hydrological forecasts are devised as factors for the combined drought indicator, which forms the numerical basis of the new Swiss drought early warning system.
Imamovic et al. (Fri,) studied this question.