World Library  

Add to Book Shelf
Flag as Inappropriate
Email this Book

Rainfall Nowcasting by at Site Stochastic Model P.R.A.I.S.E. : Volume 4, Issue 1 (29/01/2007)

By Sirangelo, B.

Click here to view

Book Id: WPLBN0003987821
Format Type: PDF Article :
File Size: Pages 27
Reproduction Date: 2015

Title: Rainfall Nowcasting by at Site Stochastic Model P.R.A.I.S.E. : Volume 4, Issue 1 (29/01/2007)  
Author: Sirangelo, B.
Volume: Vol. 4, Issue 1
Language: English
Subject: Science, Hydrology, Earth
Collections: Periodicals: Journal and Magazine Collection, Copernicus GmbH
Publication Date:
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications


APA MLA Chicago

De Luca, D. L., Versace, P., & Sirangelo, B. (2007). Rainfall Nowcasting by at Site Stochastic Model P.R.A.I.S.E. : Volume 4, Issue 1 (29/01/2007). Retrieved from

Description: Dipartimento di Difesa del Suolo, Università della Calabria – Rende (IT). The paper introduces a stochastic model to forecast rainfall heights at site: the P.R.A.I.S.E.~model (Prediction of Rainfall Amount Inside Storm Events). PRAISE is based on the assumption that the rainfall height Hi+1 accumulated on an interval Δt between the instants iΔt and (i+1)Δt is correlated with a variable Zi(Ν), representing antecedent precipitation. The mathematical background is given by a joined probability density fHi+1 Zi( Ν) (hi+1 ,zi(Ν)) in which the variables have a mixed nature, that is a finite probability in correspondence to the null value and infinitesimal probabilities in correspondence to the positive values. As study area, the Calabria region, in Southern Italy, was selected, to test performances of the PRAISE model.

Rainfall nowcasting by at site stochastic model P.R.A.I.S.E.

Abramowitz, M. and Stegun, I. A.: Handbook of mathematical functions, Dover, New York, 1970.; Bartlett, M. S.: The Spectral Analysis of Point Processes, J. R. Stat. Soc., B25, 264–296, 1963.; Box, G. E. P. and Jenkins, G. M.: Time series analysis: forecasting and control, Holden-Day. S.Francisco, 1976.; Bras, R. L. and Rodriguez-Iturbe, I.: Random functions and hydrology, Dover Publications, 1984.; Brockwell, P. J. and Davis, R. A .: Time Series. Theory and Methods, Springer Verlag, New York, NY, 1987.; Calenda, G. and Napolitano, F.: Parameter estimation of Neyman–Scott processes for temporal point rainfall simulation, J. Hydrol., 225, 45–66, 1999.; Chuang, Hui-Ya, and Sousounis, P. J.: A technique for generating idealized initial and boundary conditions for the PSU-NCAR Model MM5, Mon. Wea. Rev., 128, 2875–2882, 2000.; Cowpertwait, P. S. P.: Further developments of the Neyman-Scott clustered point process for modelling rainfall, Water Resour. Res., 27, 1431–1438, 1991.; Cowpertwait, P. S. P., O'Connell, P. E., Metcalfe, A. V., and Mawdsley, J. A.: Stochastic point process modelling of rainfall. I. Single site fitting and validation, J. Hydrol., 175, 17–46, 1996.; Cowpertwait, P. S. P.: Mixed rectangular pulses models of rainfall, Hydrol. Earth Syst. Sci., 8(5), 993–1000, 2004.; De Luca, D. L.: Metodi di previsione dei campi di pioggia. Tesi di Dottorato di Ricerca, Università della Calabria, Italy, 2005.; Hipel, K. W. and McLeod, A. I.: Time series Modeling of Water Resources and Environmental Systems, Elsevier Science, 1994.; Katz, R. W. and Parlange, M. B.: Generalizations of chain-dependent processes~: application to hourly precipitation, Water Resour. Res., 31(5), 1331–1341, 1995.; Kavvas, M. L. and Delleur, J. W.: A stochastic cluster model of daily rainfall sequences, Water Resour. Res., 17(4), 1151–1160, 1981.; Kotz, S., Balakrishanan, N., and Johnson N. L.: Continuous Multivariate Distributions – Models And Applications, Wiley, New York, NY, 2000.; Lewis, P. A. W.: Stochastic Point Processes, Wiley, New York, NY, 1964.; Montanari, A. and Brath, A.: Maximum likelihood estimation for the seasonal Neyman-Scott rectangular pulses model for rainfall, Proc. of the EGS Plinius Conference, 297–309, Maratea, Italy, 1999.; Onof, C. and Wheater, H. S.: Improved fitting of the Bartlett-Lewis Rectangular Pulse model for hourly rainfall, Hydrol. Sci. J., 39(6), 663–680, 1994.; Palmer, T. N., Brankovic, C., Buizza, R., Chessa, P., Ferranti, L., Hoskins, B. J., and Simmons, A. J.: A review of predictability and ECMWF forecast performance, with emphasis on Europe, ECMWF Research Department Technical Memorandum n. 326, ECMWF, Shinfield Park, Reading RG2-9AX, UK, 2000.; Press, W. H., Flannery, B. P., Teukolsky, S. A., and Vetterling, W. T.: Numerical Recipes in C. The art of scientific computing, Cambrige University Press, 1988.; Rodriguez-Iturbe, I., Gupta, V. K., and Waymire, E.: Scale consideration in modelling of temporal rainfall, Water Resour. Res., 20(11), 1611–1619, 1984.; Rodriguez-Iturbe, I.: Scale of fluctuation of rainfall models, Water Resour. Res., 22(9), 15S–37S, 1986.; Rodriguez-Iturbe, I., Cox, D. R., and Isham, V.: Some models for rainfall based on stochastic point processes, Proc. Royal Soc. London, A 410, 269–288, 1987.; Salas, J. D., Delleur, J. W., Yevjevich, V., and Lane, W. L.: Applied modelling of hydrologic time series, Water Resources Publications, Littleton, CO, 1980.; Sirangelo, B. and Iiritano, G.: Some aspects of the rainfall analysis through stochastic models, Excerpta, 11, 223–258, 1997.; Smith, J. A. and Karr, A. F.: A point process model of summer season rainfall occurrences, Water Resour. Res., 19(1), 95–103, 1983.; Toth, E., Brath, A., and Montanari, A.: Comparison of short-term rainfall prediction models for real-time flood foreca


Click To View

Additional Books

  • Do Effective Properties for Unsaturated ... (by )
  • An Overview of the Loess Plateau Mesa Re... (by )
  • Catchment Conceptualisation for Examinin... (by )
  • Dye Staining and Excavation of a Lateral... (by )
  • Comparison of Different Evaporation Esti... (by )
  • Confirmation of Acru Model Results for A... (by )
  • Urbanization Dramatically Altered the Wa... (by )
  • Book Review : Volume 8, Issue 6 (30/11/-... 
  • Laser Vision: Lidar as a Transformative ... (by )
  • Extreme Value Statistics of Scalable Dat... (by )
  • Combining Remotely Sensed Data Using Agg... (by )
  • Intensity-duration-frequency and Spatial... (by )
Scroll Left
Scroll Right


Copyright © World Library Foundation. All rights reserved. eBooks from Hawaii eBook Library are sponsored by the World Library Foundation,
a 501c(4) Member's Support Non-Profit Organization, and is NOT affiliated with any governmental agency or department.