Precipitation Nowcasting by a Spectral-Based Nonlinear Stochastic Model

Sabino Metta ISAC-CNR, Turin, Italy

Search for other papers by Sabino Metta in
Current site
Google Scholar
PubMed
Close
,
Jost von Hardenberg ISAC-CNR, Lecce, Italy

Search for other papers by Jost von Hardenberg in
Current site
Google Scholar
PubMed
Close
,
Luca Ferraris CIMA Research Foundation, Savona, Italy

Search for other papers by Luca Ferraris in
Current site
Google Scholar
PubMed
Close
,
Nicola Rebora CIMA Research Foundation, Savona, Italy

Search for other papers by Nicola Rebora in
Current site
Google Scholar
PubMed
Close
, and
Antonello Provenzale ISAC-CNR, Turin, Italy

Search for other papers by Antonello Provenzale in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

A novel rainfall nowcasting method based on the combination of an empirical nonlinear transformation of measured precipitation fields and the stochastic evolution in spectral space of the transformed fields is introduced. 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. The application of the method to a study case is illustrated, and it is shown that, with this procedure, a forecast skill can be obtained that is superior to those provided by Eulerian or Lagrangian persistence for a lead time of up to two hours.

* Current affiliation: ISAC-CNR, Turin, Italy.

Corresponding author address: Antonello Provenzale, Institute of Atmospheric Sciences and Climate (ISAC-CNR), Corso Fiume 4, I-10133 Turin, Italy. Email: a.provenzale@isac.cnr.it

Abstract

A novel rainfall nowcasting method based on the combination of an empirical nonlinear transformation of measured precipitation fields and the stochastic evolution in spectral space of the transformed fields is introduced. 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. The application of the method to a study case is illustrated, and it is shown that, with this procedure, a forecast skill can be obtained that is superior to those provided by Eulerian or Lagrangian persistence for a lead time of up to two hours.

* Current affiliation: ISAC-CNR, Turin, Italy.

Corresponding author address: Antonello Provenzale, Institute of Atmospheric Sciences and Climate (ISAC-CNR), Corso Fiume 4, I-10133 Turin, Italy. Email: a.provenzale@isac.cnr.it

Save
  • Andersson, T., and Ivarsson K-I. , 1991: A model for probability nowcasts of accumulated precipitation using radar. J. Appl. Meteor., 30 , 135141.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Balmforth, N., Provenzale A. , Spiegel E. , Martens M. , Tresser C. , and Wu C. W. , 1999: Red spectra from white and blue noise. Proc. Roy. Soc. London, B266 , 311314.

    • Search Google Scholar
    • Export Citation
  • Dixon, M., and Wiener G. , 1993: TITAN: Thunderstorm identification, tracking, analysis, and nowcasting—A radar-based methodology. J. Atmos. Oceanic Technol., 10 , 785797.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ferraris, L., Gabellani S. , Parodi U. , Rebora N. , von Hardenberg J. , and Provenzale A. , 2003a: Revisiting multifractality in rainfall fields. J. Hydrometeor., 4 , 544551.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ferraris, L., Gabellani S. , Rebora N. , and Provenzale A. , 2003b: A comparison of stochastic models for spatial rainfall downscaling. Water Resour. Res., 39 , 13681383. doi:10.1029/2003WR002504.

    • Search Google Scholar
    • Export Citation
  • Fox, N. I., and Wikle C. K. , 2005: A Bayesian quantitative precipitation nowcast scheme. Wea. Forecasting, 20 , 264275.

  • Fung, J. C. H., and Vassilicos J. C. , 1998: Two-particle dispersion in turbulentlike flows. Phys. Rev., 57 , 16771690. doi:10.1103/PhysRevE.57.1677.

    • Search Google Scholar
    • Export Citation
  • Germann, U., and Zawadzki I. , 2002: Scale-dependence of the predictability of precipitation from continental radar images. Part I: Description of the methodology. Mon. Wea. Rev., 130 , 28592873.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Germann, U., and Zawadzki I. , 2004: Scale dependence of the predictability of precipitation from continental radar images. Part II: Probability forecasts. J. Appl. Meteor., 43 , 7489.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Grecu, M., and Krajewski W. , 2000: A large-sample investigation of statistical procedures for radar-based short-term quantitative precipitation forecasting. J. Hydrol., 239 , 6984.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gupta, V., and Waymire E. , 1993: A statistical analysis of mesoscale rainfall as a random cascade. J. Appl. Meteor., 32 , 251267.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Herring, J. R., and Kraichnan R. H. , 1972: Comparison of some approximations for isotropic turbulence. Statistical Models and Turbulence, M. Rosenblatt and C. M. Van Atta, Eds., Lecture Notes in Physics, Vol. 12, Springer, 148–194.

    • Search Google Scholar
    • Export Citation
  • Kraichnan, R. H., 1970: Diffusion by a random velocity field. Phys. Fluids, 13 , 2231.

  • Krzysztofowicz, R., 2001: The case for probabilistic forecasting in hydrology. J. Hydrol., 249 , 29.

  • Kumar, P., and Foufoula-Georgiou E. , 1993: A multicomponent decomposition of spatial rainfall fields. 2. Self-similarity in fluctuations. Water Resour. Res., 29 , 25332544.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lovejoy, S., and Mandelbrot B. , 1985: Fractal properties of rain and a fractal model. Tellus, 37A , 209232.

  • Mellor, D., Sheffield J. , O’Connell P. E. , and Metcalfe A. V. , 2000: A stochastic space-time rainfall forecasting system for real time flow forecasting I: Development of MTB conditional rainfall scenario generator. Hydrol. Earth Syst. Sci., 4 , 603615.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rebora, N., Ferraris L. , von Hardenberg J. , and Provenzale A. , 2006: RainFARM: Rainfall downscaling by a filtered autoregressive model. J. Hydrometeor., 7 , 724738.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schertzer, D., and Lovejoy S. , 1987: Physical analysis and modeling of rain and clouds by anisotropic scaling multiplicative processes. J. Geophys. Res., 92 , 96939714.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schreiber, T., and Schmitz A. , 1996: Improved surrogate data for nonlinearity tests. Phys. Rev. Lett., 77 , 635638.

  • Seed, A. W., 2003: A dynamical and spatial scaling approach to advection forecasting. J. Appl. Meteor., 42 , 381388.

  • van Dop, H., Nieuwstadt F. T. M. , and Hunt J. C. R. , 1985: Random walk models for particle displacements in inhomogeneous unsteady turbulent flows. Phys. Fluids, 28 , 16391653.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wilks, D. S., 1995: Statistical Methods in the Atmospheric Sciences: An Introduction. International Geophysics Series, Vol. 59, Academic Press, 467 pp.

    • Search Google Scholar
    • Export Citation
  • Wilson, J. W., Crook N. A. , Mueller C. K. , Sun J. , and Dixon M. , 1998: Nowcasting thunderstorms: A status report. Bull. Amer. Meteor. Soc., 79 , 20792099.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wilson, J. W., Ebert E. E. , Saxen T. R. , Roberts R. D. , Mueller C. K. , Sleigh M. , Pierce C. E. , and Seed A. , 2004: Sydney 2000 forecast demonstration project: Convective storm nowcasting. Wea. Forecasting, 19 , 131150.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Xu, G., and Chandrasekar V. , 2005: Operational feasibility of neural-network-based radar rainfall estimation. IEEE Geosci. Remote Sens. Lett., 2 , 1317.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zawadzki, I. I., 1973: Statistical properties of precipitation patterns. J. Appl. Meteor., 12 , 459472.

  • Zawadzki, I. I., Morneau J. , and Laprise R. , 1994: Predictability of precipitation patterns: An operational approach. J. Appl. Meteor., 33 , 15621571.

    • Crossref
    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 398 45 3
PDF Downloads 198 25 2