Short description of the GLOBO model (CNR-ISAC)
1. Model characteristics
The GLOBO model is a grid-point based Atmospheric General Circulation Model (AGCM), developed at CNR-ISAC (Bologna) in recent years. GLOBO integrates the atmospheric equations on a regular latitude/longitude grid.
The GLOBO model shares with the BOLAM model most of dynamical and physical aspects, although the grid geometry differs considerably near the Poles, where special filtering techniques (digital and Fourier) are applied to cope with the singularity in regular latitude-longitude coordinates. The sea surface temperature (SST) evolution is modelled with a mixed layer ocean.
A full description of the dynamics and physical parameterizations of the model is given in Malguzzi et al (2011).
The GLOBO model has been revised and updated in several physical and numerical aspects. In particular, upgrades mainly concerning the radiation (Morcrette et al, 2008), cloud and stratiform precipitation schemes have been introduced recently in a similarly to what has been done for the BOLAM model.
2. Model applications
GLOBO is currently used at ISAC-CNR to produce 6-day global forecasts, at the resolution of 0.29 x .40 degrees and 60 levels, using NOAA-GFS analysis fields as initial conditions.
The monthly forecasting activity, based on GLOBO (Mastrangelo et al, 2012), makes use of recalibrated ensemble forecasts, with initial conditions derived from unperturbed and perturbed analyses of NOAA-NCEP, with prescribed SST anomaly superimposed on the seasonal SST cycle. The SST is relaxed to a prescribed field, computed as a sum of the climatological temperature and of the initial observed anomaly, the latter is assumed to decay slowly in time. The sea ice fraction is computed starting from the observed initial state and applying an observed climatological tendency.
The GLOBO model is presently employed in this ensemble mode with a resolution of 1.0 x 0.75 degrees, and with 50 vertical levels.
A joint project with ECMWF and ARPA-ER is presently under way, aimed at assessing the benefits of using the multimodel approach for the monthly forecast. In collaboration with INFN-CNAF, a grid-computing technique is currently experimented in order to re-evaluate the GLOBO model systematic error for the monthly forecast.
Malguzzi, P., A. Buzzi and O. Drofa, 2011: The meteorological global model GLOBO at the ISAC-CNR of Italy: assessment of 1.5 years of experimental use for medium range weather forecast. Wea. Forecasting, 26, 1045-1055.
Mastrangelo, D., P. Malguzzi, C. Rendina, O. Drofa, and A. Buzzi, 2012: First outcomes from the CNR-ISAC monthly forecasting system. Adv. Sci. Res., 8, 77-82.
Morcrette, J.-J., H.W. Barker, J.N.S. Cole, M.J. Iacono, and R. Pincus, 2008: Impact of a new radiation package, McRad, in the ECMWF Integrated Forecasting System. Mon. Wea. Rev., 136, 4773-4798.