Clouds and radiation
Clouds and their interaction with the earth and solar radiation are one of the major weaknesses in climate models and numeric weather forecast models. SMHI works actively with the development of parameterisations which describe the complex interaction between humidity and radiation in the atmosphere. The work concentrates on a resolution of 10-50 km. In particular the following are studied:
- New methods to parameterise radiation
- Humidity-preserving turbulence scheme and statistic cloud scheme
- Parameterisation of precipitation
- The development of Kain-Fitsch’s convection scheme
- Assumptions regarding overlapping clouds
Land and vegetation
A land surface scheme linked to the climate model must be able to describe processes on a timescale of 1-24 hours. The land surface scheme in RCA is developed in order to describe processes in all types of climates, but with a particular focus on physical processes of intermediate and high latitudes where there is snow and frozen ground. The land surface scheme has three main aims:
- To act as a lower boundary condition to the atmosphere. Which means to supply the atmosphere with realistic radiation, heat and momentum flows
- To supply the seas with realistic discharge
- To stimulate important variables on ground level, such as temperature and humidity at a height of 2 m, wind speed and a height of 10 m and snow cover
From an atmospheric point of view, the land surface scheme has three characteristics taking into consideration temperature: forest, open land and snow. The open land is divided up into a vegetation covered area and an area that lacks vegetation with regard to the latent heat flow (ground resistance). The specific latent flows of heat and momentum are weighted together based on the tile’s relative sizes. The ground surface is assumed to be in equilibrium locally across each tile, which means that each tile has its own aerodynamic resistance.
The forest tile is internally divided up into three subtiles: foliage, the ground surface and snow on the ground surface. These are tightly interconnected through temperature and humidity conditions in the air around the foliage.
All in all, there are 3-5 different energy balances at ground level dependent on whether or not there is snow. The ground in the land surface scheme is three metres deep and divided up into five layers with regard to temperature.
In total, water is stored prognostically in eight different ways in the land surface scheme. Interception of water on the vegetation of open land and forest foliage, the snow’s water equivalent on open land and forest, water content in both types of snow and two ground humidity levels.
Sea ice
Rossby Centre is developing a three-dimensional coupled sea ice model for climate studies of the sea. The sea model is based on primitive equations. The sea ice model is a two-level model of the Hibler type with elastic-viscous-plastic reology. In particular the following are studied:
- Parameterisation of mixing
- Formulations of open boundary conditions
- Modelling of boundary layers on the sea bottom
- Parameterisation of heat flows and freshwater flows on the surface of the sea
- Ice models with several ice categories
- Techniques to improve the parallelisation in the model
Model evaluation
Model development and model evaluation are closely related. Even if models are based on physics, they incorporate empirical limitations due to insufficient observations of a process and/or limitations due to the availability of computer resources.
The purpose of model development and model evaluation is of course that it will provide a model system which is better than previous model systems. ”Better” in this respect has more than one meaning. To improve and identify the weakness in the description of a process is a way of improving the model.
A broader objective of model development is however to be able to improve the description of the actual physical system. And improved physical description does not necessarily immediately provide a better concordance between model results and available observations. This is nevertheless an improvement of the basis for further development of both models and theory. That is why you can accept that a new model version performs somewhat worse than the old version, at least as an intermediate stage in the development process, if the changes in the model are justified by a physical reasoning.