Within the Operational Project "PROTERINA-C" (a forecast and prevention system for climate change impacts on risk variability for wildlands and urban areas), co-funded by the European Regional Development Fund (ERDF) under the Italy-France Maritime Program, methods and strategies, already in use in the regions of Sardinia, Liguria and Corsica, for the predictions of wildlands fires have been developed and adapted; RISICO System, by CIMA Foundation which plays the role of technical and scientific support for the region of Liguria, used by the Italian National Civil Protection Department, is one of them. In such a prediction model of risk of wildlands fires, it was arranged the integration, on a regional scale, of products related to the main meteorological, diagnostics and prognostics forcing, measured by ground stations, weather radar and advanced limited area weather prediction models. ARPAS and his partners, in the -Phase 5? of the project, have designed and developed an operational chain to insert data from ground meteorological monitoring network operating in Sardinia, in RISICO model to improve prediction of fire. In fact, the forecast errors can be reduced by conditioning the initial state of dynamic models of fuel moisture on the information obtained from sensors on land, at each time interval at which the fields of meteorological variables of interest are available, these fields can be obtained by a process of interpolation of the measures to the ground possibly complemented by large-scale measures obtained from remote sensors. In the present work are argued the characteristics of the system, in particular the configuration of the network of meteorological stations and the operational diagnostic chain to include the weather measures in the model of wildfire risk, and some preliminary results are discussed

An operational diagnostic chain, implemented within the Proterina-C project, to include weather measures in RISICO model

Casula M;
2012

Abstract

Within the Operational Project "PROTERINA-C" (a forecast and prevention system for climate change impacts on risk variability for wildlands and urban areas), co-funded by the European Regional Development Fund (ERDF) under the Italy-France Maritime Program, methods and strategies, already in use in the regions of Sardinia, Liguria and Corsica, for the predictions of wildlands fires have been developed and adapted; RISICO System, by CIMA Foundation which plays the role of technical and scientific support for the region of Liguria, used by the Italian National Civil Protection Department, is one of them. In such a prediction model of risk of wildlands fires, it was arranged the integration, on a regional scale, of products related to the main meteorological, diagnostics and prognostics forcing, measured by ground stations, weather radar and advanced limited area weather prediction models. ARPAS and his partners, in the -Phase 5? of the project, have designed and developed an operational chain to insert data from ground meteorological monitoring network operating in Sardinia, in RISICO model to improve prediction of fire. In fact, the forecast errors can be reduced by conditioning the initial state of dynamic models of fuel moisture on the information obtained from sensors on land, at each time interval at which the fields of meteorological variables of interest are available, these fields can be obtained by a process of interpolation of the measures to the ground possibly complemented by large-scale measures obtained from remote sensors. In the present work are argued the characteristics of the system, in particular the configuration of the network of meteorological stations and the operational diagnostic chain to include the weather measures in the model of wildfire risk, and some preliminary results are discussed
2012
fire
risk
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/395073
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