全球智库信息集成服务系统

This work presents the conditioned upscaling procedure applied in the Po-FEWS system by Hydrology area of ARPA SIMC Emilia Romagna to select the rainfall daily scenarios which better fit seasonal meteorological forecasts. Seasonal meteorological forecast provides qualitatively useful information for management activities over a short-medium term horizon, but their temporal aggregation time is too coarse to be allow quantitatively considerations. For this reason, Hydrology area of ARPA SIMC Emilia Romagna developed a conditioned upscaling procedure to obtain daily scenarios coherent with the seasonal forecasts. The daily scenarios are the inputs to the hydrological/hydraulics chains available in the Po-FEWS system for short-medium term forecasts. The daily rainfall scenarios are generated through a Spatio-Temporal Neymann Scott Rectangular Pulse model calibrated using daily observations over the period 1987-2008. Seasonal forecasts provide also the expected anomalies of minimum and maximum temperatures. Minimum and maximum temperatures are simulated at daily scale using a multilinear regression model conditioned on rainfall scenarios.