The formulation of physical processes

The effect of sub-scale physical processes on weather systems is expressed in terms of resolved model variables in a technique called parametrization. It involves both statistical methods and simplified mathematical-physical models, such as adjustment proc­esses. So, for example, the air closest to the earth’s surface exchanges heat with the surface through turbulent diffusion or convection, which adjusts unstable air towards neutral stability (Jung et al, 2010).

The convection scheme does not predict individual convective clouds, only their physical effect on the surrounding atmosphere, in terms of latent heat release, precipitation and the associated transport of moisture and momentum. The scheme differentiates between deep, shallow and mid-level convection. Only one type of convection can occur at any given grid point at one time (see Figure 1).

Figure 1: The ECMWF total convective rainfall forecast from 28 November 2010 12 UTC + 30h. The convection scheme has difficulty in advecting wintery showers inland over Scotland and northern England from the relatively warm North Sea. The convection scheme is diagnostic and works on a model column, so cannot produce large amounts of precipitation over the relatively dry and cold (stable) wintery land areas.In nature these showers succeed in penetrating inland through a convectively induced upper-level warm anomaly leading to large-scale lifting and saturation.

Clouds, both convective and non-convective, are handled by explicit equations for cloud water, ice and cloud cover. Liquid and frozen precipitation are strongly coupled to other parametrized processes, in particular the convective scheme and the radiation. The scheme also takes into account important cloud processes, such as cloud-top entrainment and the evaporation of water. Fog is represented in the scheme as clouds that form in the lowest model level.

The radiation spectrum is divided into a long-wave part (thermal) and a short-wave part (solar radiation). Since it has to take the cloud-radiation interaction into account in considerable detail, it makes use of a cloud-overlap algorithm, which calculates the relative placement of clouds across levels. For the sake of computational efficiency, the radiation scheme is called less frequently than the model time step on a reduced grid. Nevertheless, it accounts for a considerable fraction of the total computational time.

For the precipitation and hydrological cycles both convective and stratiform precipitation are included in the ECMWF model. Evaporation of the precipitation, before it reaches the ground, is assumed not to take place within the cloud, only in the cloud-free, non-saturated air beside or below the model clouds. The melting of falling snow occurs in a thin layer of a few hundred metres below the freezing level. It is assumed that snow can melt in each layer, whenever the temperature exceeds 0°C. The cloud-overlap algorithm is also impor­tant for the “life history” of falling precipitation: from level-with-cloud to level-with-clear-sky and vice versa.

The near-surface wind forecast displays severe weaknesses in some mountain areas, due to the difficulty in parametrizing the interaction between the air flow and the highly varying sub-grid orography (see Figure 2). As with many other sub-grid-scale physical processes that need to be treated in simplified ways, this problem will ultimately be reduced when the air-surface interaction can be described explicitly, thanks to a higher and appropriate resolution. The system also produces wind-gust forecasts as part of post-processing (Balsamo et al, 2011).

Figure 2: MSLP and 10 m wind forecast from 2 March 2011 12 UTC + 12 h. The 10 m winds are unrealistically weak over the rugged Norwegian mountains. Values of 10 m/s might be realistic in sheltered valleys, but not on exposed mountain ranges.