Atmospheric Regional Reanalysis simulations, based on RAMS model, as input for crop modeling

A meteorological data production system, as input for crop modelling in several agricultural areas in Italy, has been developed based on the Regional Atmospheric Modelling System (RAMS) at the Institute of Biometeorology – CNR. The adopted strategy is to provide a “Regional Reanalysis” (RR) in a quasi realtime framework to provide high quality atmospheric datasets at high spatial resolution as input to crop models. In order to increase reliabilty of the surface information used, a strategy has been set by initialising the RAMS only with observed first – guess fields. In particular we use analysed fields form GFS model for atmosphere and sea surface temperature fields, at 4 km of horizontal resolution over the Mediterranean sea, from NOAA. Simulated output weather data are then used to run the DELPHI wheat growth simulation model and obtain spatial yield and quality prediction. In this study, a whole season has been simulated and results are analysed. Advantages and disadvantages of this approach compared to more conventional solutions used by the crop modellers are considered and evaluated in different ways. An objective evaluation of RAMS RR atmospheric datasets intrinsic reliability against observed data at surface stations is proposed.