Dynamical Downscaling for Climate Model Projections

Question

Does anyone have experience with running high-resolution climate models on a regional sub-domain, i.e. dynamical downscaling for climate studies and climate projections?
Specifically, I am interested in the SRES A2 Scenario (Special Report on Emissions Scenario) in PRECIS Model.
Could you please give me some advice on how to use it and share some research papers on the subject?

Prem Baboo · Accepted Answer

Global climate models (GCMs) are our best tools for providing climate projections. A climate model is a mathematical representation of the climate system. Mathematical equations are solved on a super-computer at points on a 3-dimensional grid in the ocean and atmosphere, over a number of time-steps. Due to practical computing constraints, the spatial resolution (horizontal size of grid-cells) is about 200 km. the general name for a procedure to take information known at large scales to make predictions at local scales. The two main approaches to downscaling climate information are dynamical and statistical. Dynamical downscaling requires running high-resolution climate models on a regional sub-domain, using observational data or lower-resolution climate model output as a boundary condition.  These models use physical principles to reproduce local climates, but are computationally intensive.'s higher resolution atmosphere allows simulation of tropical cyclone activity.  CM2.5 has been applied to the problem of the future of global snow cover in a warming climate where its resolution allows improved simulation of changes in mountainous regions.A third stream of development attempted to improve CM2.1’s simulation by increasing the resolution of the atmospheric and oceanic components. This effort produced CM2.5 and its variants CM2.5FLOR and CM2.6. The resolution of the atmospheric and oceanic components of CM2.5 is increased by a factor of four compared to CM2.1, along with a 33% increase in the number of vertical levels in the atmosphere. A further refinement of the ocean component to 1/10o produced CM2.6 which can claim to resolve ocean eddies based on agreement with an observational estimate of the eddy kinetic energy. Statistical downscaling is a two-step process consisting of i) the development of statistical relationships between local climate variables (e.g., surface air temperature and precipitation) and large-scale predictors (e.g., pressure fields), and ii) the application of such relationships to the output of global climate model experiments to simulate local climate characteristics in the futureThe main tools used to project climate are General Circulation Model (GCMs), which are computer models that mathematically
represent various physical processes of the global climate system. These processes are generally well known but often cannot be fully represented in the models due to limitations on computing resources
and input data. Thus, GCM results should only be considered at global or continental scales for climatic conditions averaged at monthly, seasonal, annual, and longer time scales. 
https://www.climatechangeinaustralia.gov.au/
 
http://earthsystemcog.org/projects/ncpp /

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