Adaptive Mesh Modelling of the Global Atmosphere

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Current weather and climate forecasting models use fixed, uniform resolution, so that all regions are represented using the same grid spacing. This has enabled efficient, valuable forecasts, but it may be possible to improve the representation of the atmosphere by varying the grid spacing depending on the local weather conditions, that is, adaptive mesh modelling. This could improve the representation of, for example, heavy precipitation or mountain ranges. The overarching themes of this research are to try to make adaptive mesh modelling sufficiently accurate and efficient for operational use and give a realistic assessment of whether this is possible. It is first proposed to study vertical discretisation; the splitting of the atmosphere vertical layers around mountains. Climate models currently use terrain following layers which are draped over mountains like blankets, becoming squashed at summits and spaced out in valleys. This is accurate for the coarse resolution used in climate models since the layers are never very steep. Once resolution increases, steeper slopes are simulated and accuracy can be compromised. Therefore cut cells have been used in some small scale models, whereby the mountains break through flat layers. Cut cells have different accuracy compromises. Novel hybrids between terrain following layers and cut cells will be created in order to minimise both sources of error and compared with discretisations which do not use layers. If the computational mesh can be aligned with the flow, with wide mesh spacing in directions in which conditions change little and fine spacing in directions in which conditions change rapidly, then accuracy can be maximised for the cost. The creation of these anisotropic meshes first requires anisotropic refinement criteria and then an algorithm to generate a mesh with the desired properties. Both of these will be addressed. There has been little work done on where to increase resolution in order to improve atmospheric simulation using the minimum extra computing resources, ie mesh refinement criteria. This is a challenging topic due to the complex inter-dependencies between the weather in different regions and the impossibility of resolving everything in a single global model, even with adaptive meshing. A new anticipative mesh refinement technique will be developed, involving a coarse resolution prediction of where resolution will be needed followed by the adapted mesh simulation. The refined mesh will therefore be in place before small scale features appear, improving accuracy. Cost will be reduced since the expensive mesh adaptation needs only to be done infrequently. Clouds and precipitation are crucial aspects of atmospheric circulation and can be influential on the weather thousands of kilometres away. However they are usually predicted poorly in climate models, with some improvement in higher resolution weather forecasting models. If adaptive meshes can be used to resolve the deepest clouds associated with deep convection, then atmospheric simulation may be improved. However criteria to identify in advance where convection will need high resolution have not before been created. In climate models, deep convection cannot be resolved so schemes have been developed which estimate in which grid boxes sub-grid scale convection may occur. In this project it is planned to use criteria from existing convection schemes in order to enable refinement of deep convection before it breaks out. The work on vertical discretisation is necessary for higher horizontal resolution around mountains with either adaptive meshes or static grids. The other work involves creating optimal meshes for adaptive modelling, with optimal cell shapes and orientations, mesh refinement frequency and criteria and novel strategies for resolving deep convection before it breaks out. These achievements could greatly improve the fidelity and competitiveness of adaptive mesh modelling of the global atmosphere.