Action 3: Modelling and Simulation
Present activities & status
As already mentioned INRaSTES carries significant experience in area of atmospheric modelling and simulation, developing and applying a series of tools for diverse scales from global down to urban. The main categories of modelling tools include:
- Prognostic - diagnostic meteorology and data assimilation. At present multi domain operational forecast produce daily data on different spatial scales from the European down to Attica, publicly available on the web (http://www2.ipta.demokritos.gr/forecast).
- Environmental Computational Fluid Dynamics. Atmospheric turbulent flows in complex terrains (local-to meso-scale) – Atmospheric turbulence modelling – Large Eddy Simulation
- Global Circulation Models (GCM). The NASA Global Modeling Initiative (GMI; http://gmi.gsfc.nasa.gov) has been installed and tested. GMI is a global 3D chemical-transport model specifically developed for impact assessment studies that allows easy interchange of different model components while maintaining all others identical. The common modeling framework allows a direct intercomparison of results obtained between alternate representations of aerosol, chemistry and transport processes, without the uncertainties typically associated with comparison of output from different GCMs.
- Chemistry models with photochemistry and aerosol parameterizations. The community model for air quality, CMAQ a state of the science Eulerian model, has been installed and tested for diverse applications.
A collaborative effort is the on-going research that attempts to downscale the output of GCM into a high resolution domain for Greece providing valuable insights about future evolution of air pollution from gaseous compounds and aerosols.
Research Vision and Associated Actions in EnTeC
An important task is the installation and use of the 9-layer NASA Goddard Institute for Space Studies (GISS) general circulation model (GCM) Model II’. It is a state of the art three-dimensional global climate model that numerically solves the physical conservation equations for energy, mass, momentum and moisture as well as the equation of state. The standard version of this model has a 4 × 5 horizontal resolution, nine vertical layers (from surface to 10 mbar) in the atmosphere and two ground hydrology layers. The model accounts for both the seasonal and diurnal solar cycles in its temperature calculations.
Additionally, the Community Climate System Model (CCSM), a coupled climate model for simulating the earth's climate system will be installed and validated. Composed of four separate models simultaneously simulating the earth's atmosphere, ocean, land surface and sea-ice, and one central coupler component, the CCSM allows researchers to conduct fundamental research into the earth's past, present and future climate states.
Complimentary to the GISS-Model II, a regional circulation model (RCM) is foreseen to be installed and validated in INRaSTES. The RCM will cover the entire Western Mediterranean Region, accepting boundary and initial conditions from the GCM simulations. Also, a regional increase in resolution can be attained through the specific use of nested RCMs to account for sub-GCM grid-scale forcings. The expected impact in nested regional climate modeling activities will be the production of continuous RCM multi-year climate simulations.
An additional task that is foreseen by the members of INRaSTES will be the compilation of high resolution, detailed emission inventories of greenhouse gases, aerosols and priority pollutants on a regional level and future horizons – adapting IPCC scenarios. This would significantly improve the performance and modelling capability of the applied chemical models. During this process, data collected from field campaigns and laboratory analysis will be used to fine tune the inventories and further reduce related uncertainties.
The high quality data that will be derived from the field stations and laboratory analysis, both for aerosols and gaseous compounds, will be used into state of the art source apportionment models that will be used to identify the number, characteristics and contribution of major polluting sources. The scientific personnel of INRaSTES has extensive knowledge and experience from the application of source apportionment models (e.g. Positive Matrix Factorization, Chemical Mass Balance) and the development of models based on factor analysis and clustering algorithms.
A series of statistical tools will be developed that will be readily available by INRaSTES researchers and collaborators to examine, process and treat data collected from the field campaigns, laboratory analysis and continuous monitoring systems. The proposed tools include linear and non-linear (e.g. artificial intelligence) techniques, extreme value modelling, Granger causality to identify bidirectional cause between examined parameters.
