Mitigating errors in surface temperature forecasts using approximate radiation updates

Due to computational expense, the radiation schemes in many weather and climate models are called infrequently in time and/or on a reduced spatial grid. The former can lead to a lag in the diurnal cycle of surface temperature, while the latter can lead to large surface temperature errors at coastal land points due to surface fluxes computed over the ocean being used where the skin temperature and surface albedo are very different. This paper describes a computationally efficient solution to these problems, in which the surface longwave and shortwave fluxes are updated every time step and grid point according to the local skin temperature and albedo. In order that energy is conserved, it is necessary to compute the change to the net flux profile consistent with the changed surface fluxes. The longwave radiation scheme has been modified to compute also the rate of change of the profile of upwelling longwave flux with respect to the value at the surface. Then at each grid point and time step, the upwelling flux and heatingrate profiles are updated using the new value of skin temperature. The computational cost of performing approximate radiation updates in the ECMWF model is only 2% of the cost of the full radiation scheme, so increases the overall cost of the model by only of order 0.2%. Testing the new scheme by running daily 5 day forecasts over an 8 month period reveals significant improvement in 2 m temperature forecasts at coastal stations compared to observations.