The paper introduces a stochastic technique for forecasting rainfall in space-time domain: the PRAISEST Model (Prediction of Rainfall Amount Inside Storm Events: Space and Time). The model is based on the assumption that the rainfall height H accumulated on an interval Δ between the instants iΔt and (i+1)Δt and on a spatial cell of size ΔxΔy is correlated either with a variable Z, representing antecedent precipitation at the same point, either with a variable W, representing simultaneous rainfall at neighbour cells. The mathematical background is given by a joined probability density fH,W,Z (h,w,z) in which the variables have a mixed nature, that is a finite probability for null value and infinitesimal probabilities for the positive values. As study area, the Calabria region, in Southern Italy, has been selected. The region has been discretised by 10 km10 km cell grid, according to the raingauge network density in this area. Storm events belonging to 1990-2004 period were analyzed to test performances of the PRAISEST model. © 2009 Author(s).

A space-time generator for rainfall nowcasting: The PRAISEST model / Versace, P.; Sirangelo, B.; De Luca, D. L.. - In: HYDROLOGY AND EARTH SYSTEM SCIENCES. - ISSN 1027-5606. - 13:4(2009), pp. 441-452. [10.5194/hess-13-441-2009]

A space-time generator for rainfall nowcasting: The PRAISEST model

De Luca D. L.
Ultimo
2009

Abstract

The paper introduces a stochastic technique for forecasting rainfall in space-time domain: the PRAISEST Model (Prediction of Rainfall Amount Inside Storm Events: Space and Time). The model is based on the assumption that the rainfall height H accumulated on an interval Δ between the instants iΔt and (i+1)Δt and on a spatial cell of size ΔxΔy is correlated either with a variable Z, representing antecedent precipitation at the same point, either with a variable W, representing simultaneous rainfall at neighbour cells. The mathematical background is given by a joined probability density fH,W,Z (h,w,z) in which the variables have a mixed nature, that is a finite probability for null value and infinitesimal probabilities for the positive values. As study area, the Calabria region, in Southern Italy, has been selected. The region has been discretised by 10 km10 km cell grid, according to the raingauge network density in this area. Storm events belonging to 1990-2004 period were analyzed to test performances of the PRAISEST model. © 2009 Author(s).
2009
rainfall nowcasting; stochastic models
01 Pubblicazione su rivista::01a Articolo in rivista
A space-time generator for rainfall nowcasting: The PRAISEST model / Versace, P.; Sirangelo, B.; De Luca, D. L.. - In: HYDROLOGY AND EARTH SYSTEM SCIENCES. - ISSN 1027-5606. - 13:4(2009), pp. 441-452. [10.5194/hess-13-441-2009]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1705652
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