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Castel Guelfo di Bologna, Italy

Spisni A.,Servizio IdroMeteoClima | Tomei F.,Servizio IdroMeteoClima | Pignone S.,Agenzia Regionale di Protezione Civile dellEmilia Romagna | Muzzi E.,University of Bologna | And 7 more authors.
Italian Journal of Remote Sensing / Rivista Italiana di Telerilevamento | Year: 2011

In this paper we present an operational chain developed in the Emilia-Romagna region (Italy) to monitor snow cover and snow water equivalent (SWE) over the area managed by the Regional Catchment Technical Service. Remote sensing data from medium resolution sensors (MODIS and AVHRR/3) are used as input for snow cover detection algorithms. Hourly weather station measurements are used as input for a snow melt and accumulation model in order to estimate the snow water equivalent. The model reliability is mainly related to the network density of heated rain gauges detecting snow precipitation. The products are disseminated as web bulletins and they are used in monitoring chain and alert for the Civil Protection Agency. Source

di Giuseppe F.,Servizio IdroMeteoClima | Cesari D.,Servizio IdroMeteoClima | Bonafe G.,Servizio IdroMeteoClima
Monthly Weather Review | Year: 2011

Three diverse methods of initializing soil moisture and temperature in limited-area numerical weather prediction models are compared and assessed through the use of nonstandard surface observations to identify the approach that best combines ease of implementation, improvement in forecast skill, and realistic estimations of soil parameters. The first method initializes the limited-area model soil prognostic variables by a simple interpolation from a parent global model that is used to provide the lateral boundary conditions for the forecasts, thus ensuring that the limited-area model's soil field cannot evolve far from the host model. The second method uses the soil properties generated by a previous limited-area model forecast, allowing the soil moisture to evolve over time to a new equilibrium consistent with the regional model's hydrological cycle. The third method implements a new local soil moisture variational analysis system that uses screen-level temperature to adjust the soil water content, allowing the use of high-resolution station data that may be available to a regional meteorological service. The methods are tested in a suite of short-term weather forecasts performed with the Consortium for Small Scale Modeling (COSMO) model over the period September-November 2008, using the ECMWF Integrated Forecast System (IFS) model to provide the lateral boundary conditions. Extensive comparisons to observations show that substantial improvements in forecast skills are achievable with improved soil temperature initialization while a smaller additional benefit in the prediction of surface fluxes is possible with the soil moisture analysis. The analysis suggests that keeping the model prognostic variables close to equilibrium with the soil state, especially for temperature, is more relevant than correcting the soil moisture initial values. In particular, if a local soil analysis system is not available, it seems preferable to adopt an "open loop" strategy rather than the interpolation from the host global model analysis. This appears to be especially true for the COSMO model in its current operational configuration since the soil-vegetation-atmosphere transfer (SVAT) scheme of the ECMWF global host model and that of COSMO are radically diverse. © 2011 American Meteorological Society. Source

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