An extensive evaluation of system analysis techniques for obtaining short-term quantitative precipitation nowcasting based on radar maps is presented. The analysis considers four rainfall events monitored through radar scans collected at San Pietro Capofiume (northern Italy). These maps have temporal and spatial resolutions equal to 15 minutes and 1 x 1 km2, respectively. The nowcasting is performed by considering four different approaches, ranging from purely heuristic techniques to system analysis methods for modelling storm advection and dynamic storm evolution in a Lagrangian reference frame, travelling along with the storm. Stochastic models of the autoregressive type, as well as neural networks, are applied for modelling the Lagrangian storm dynamic. The dependence of the forecasting skills on prediction lead time and spatial size of the radar map pixels is investigated.
Titolo: | A comparison of systems analysis methods for quantitative precipitation nowcasting based on radar observations |
Autore/i: | Montanari L.; TOTH, ELENA; MONTANARI, ALBERTO; Amorati R. |
Autore/i Unibo: | |
Anno: | 2004 |
Titolo del libro: | Combination of data from remote sensing technologies for flood forecasting, 1st ACTIF Workshop |
Pagina iniziale: | - |
Pagina finale: | - |
Abstract: | An extensive evaluation of system analysis techniques for obtaining short-term quantitative precipitation nowcasting based on radar maps is presented. The analysis considers four rainfall events monitored through radar scans collected at San Pietro Capofiume (northern Italy). These maps have temporal and spatial resolutions equal to 15 minutes and 1 x 1 km2, respectively. The nowcasting is performed by considering four different approaches, ranging from purely heuristic techniques to system analysis methods for modelling storm advection and dynamic storm evolution in a Lagrangian reference frame, travelling along with the storm. Stochastic models of the autoregressive type, as well as neural networks, are applied for modelling the Lagrangian storm dynamic. The dependence of the forecasting skills on prediction lead time and spatial size of the radar map pixels is investigated. |
Data prodotto definitivo in UGOV: | 28-set-2005 |
Appare nelle tipologie: | 4.01 Contributo in Atti di convegno |