PhaSt: a phase-diffusion model for stochastic nowcasting

PHAST is an ensemble rainfall nowcasting technique based on the extrapolation of radar observations by a diffusive process in Fourier space, where power spectral amplitudes are kept constant and Fourier phases evolve by a Ornstein-Uhlenbeck stochastic process (Metta et al. 2009; Rebora and Silvestro, 2012);

Description & Technical Information


Phast nowcasting method is based on the combination of an empirical nonlinear transformation of measured precipitation fields and the stochastic evolution in spectral space of the transformed fields. The power spectrum and the amplitude distribution of precipitation are kept constant during the forecast, and a Langevin-type model is used to evolve the Fourier phases (Metta et al. 2009).

The Phast algorithm should work both on deterministic and probabilistic version. The latter is the operational mode for Liguria and Italian domain and should be capable to generate reliable stochastic forecasts ensemble of precipitation intensities on scales of the order of kilometres, up to a few hours in advance (Rebora and Silvestro, 2012). Ensemble rainfall nowcasting allows to characterize the uncertainty associated with nowcasting procedures by providing a probabilistic forecast of the evolution of an event.

Phast is simply based on the last couple of observations (can be single radar or mosaic of radars data) and gives as output:

  • Radar based rainfall accumulation forecast (Nowcasting rainfall field)
  • Radar based rainfall accumulation probability (Probabilistic map)
  • Radar based centroid path forecast (Nowcasting centroid paths)

Technical information

Hazard ,
References (2) Rebora, N. and Silvestro, F. (2012). PhaSt: stochastic phase-diffusion model for ensemble rainfall nowcasting. IAHS-AISH publication, 305-310.
References (3) Silvestro, F., Rebora, N., Cummings, G., & Ferraris, L. (2015). Experiences of dealing with flash floods using an ensemble hydrological nowcasting chain: implications of communication, accessibility and distribution of the results. Journal of Flood Risk Management.
Developer CIMA
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