STEPS: A probabilistic precipitation forecasting scheme which merges an extrapolation nowcast with downscaled NWP

Abstract

SUMMARYAn ensemble-based probabilistic precipitation forecasting scheme has been developed that blends an extrapolation nowcast with a downscaled NWP forecast, known as STEPS: Short-Term Ensemble Prediction System. The uncertainties in the motion and evolution of radar-inferred precipitation fields are quantified, and the uncertainty in the evolution of the precipitation pattern is shown to be the more important. The use of ensembles allows the scheme to be used for applications that require forecasts of the probability density function of areal and temporal averages of precipitation, such as fluvial flood forecasting-a capability that has not been provided by previous probabilistic precipitation nowcast schemes. The output from a NWP forecast model is downscaled so that the small scales not represented accurately by the model are injected into the forecast using stochastic noise. This allows the scheme to better represent the distribution of precipitation rate at spatial scales finer than those adequately resolved by operational NWP. The performance of the scheme has been assessed over the month of March 2003. Performance evaluation statistics show that the scheme possesses predictive skill at lead times in excess of six hours.

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“…Golding, 1998;Pierce et al, 2000;Bowler et al, 2006;Atencia et al, 2010). Recently Wilson et al (2010) showed that these techniques did not perform better than nowcasting systems during the Beijing 2008 Forecast Demonstration Project; they state that the blending approach will be successful as long as numerical models continue to improve on the nowcasting spatio-temporal scale.…”

A radar-based regional extreme rainfall analysis to derive the thresholds for a novel automatic alert system in Switzerland

“…On the other hand, nowcasting by radar-based heuristic systems, such as Lagrangian extrapolation or analogues, quickly provides forecasts of rainfall and outperforms numerical model forecasts for the first hours, even though it strongly suffers from the lack of growth and decay mechanisms able to predict the evolution of the storms for lead times longer than a few hours (e.g., Panziera et al, 2011;Mandapaka et al, 2012). Finally, some studies propose a merging of the forecasts obtained with numerical weather prediction models and heuristic systems (e.g., Golding, 1998;Bowler et al, 2006;Atencia et al, 2010;Haiden et al, 2011), but this approach will be successful as long as numerical models could provide good forecasts at the nowcasting spatiotemporal scales (Wilson et al, 2010).…”

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