| description abstract | A new radiation package, ?McRad,? has become operational with cycle 32R2 of the Integrated Forecasting System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF). McRad includes an improved description of the land surface albedo from Moderate Resolution Imaging Spectroradiometer (MODIS) observations, the Monte Carlo independent column approximation treatment of the radiative transfer in clouds, and the Rapid Radiative Transfer Model shortwave scheme. The impact of McRad on year-long simulations at TL159L91 and higher-resolution 10-day forecasts is then documented. McRad is shown to benefit the representation of most parameters over both shorter and longer time scales, relative to the previous operational version of the radiative transfer schemes. At all resolutions, McRad improves the representation of the cloud?radiation interactions, particularly in the tropical regions, with improved temperature and wind objective scores through a reduction of some systematic errors in the position of tropical convection as a result of a change in the overall distribution of diabatic heating over the vertical plane, inducing a geographical redistribution of the centers of convection. Although smaller, the improvement is also seen in the rmse of geopotential in the Northern and Southern Hemispheres and over Europe. Given the importance of cloudiness in modulating the radiative fluxes, the sensitivity of the model to cloud overlap assumption (COA) is also addressed, with emphasis on the flexibility that is inherent to this new RT approach when dealing with COA. The sensitivity of the forecasts to the space interpolation that is required to efficiently address the high computational cost of the RT parameterization is also revisited. A reduction of the radiation grid for the Ensemble Prediction System is shown to be of little impact on the scores while reducing the computational cost of the radiation computations. McRad is also shown to decrease the cold bias in ocean surface temperature in climate integrations with a coupled ocean system. | |
