COST 732

Quality Assurance and Improvement of Micro-Scale Meteorological Models

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The emergence of increasingly powerful computers enabled the development of tools that have the potential to predict flow and transport processes within the urban canopy layer. These new tools are micro-scale meteorological models of prognostic or diagnostic type. Prognostic models are based on the Reynolds-averaged Navier-Stokes (RANS) equations, whereas diagnostic models are less sophisticated and ensure only the conservation of mass. These two model types are presently supplemented by even simpler engineering tools. It is to be expected, however, that the latter will sooner or later be replaced by RANS codes or the even more complex Large Eddy Simulation (LES) models.

 

Models have begun to play an important and often dominant role in environmental assessment and urban climate studies that are undertaken to investigate and to quantify the effects of human activity on air quality and the local climate. Their increasing use, however, is paralleled by a growing awareness that the majority of these models have never been the subject of rigorous evaluation. Consequently there is a lack of confidence in the modelled results.

 

The main objective of the COST action is to improve and assure the quality of micro-scale meteorological models that are applied for predicting flow and transport processes in urban or industrial environments.


Material available for download


Official documents

COST 732 has produced several official documents which are available from the Official documents web page.

Excel tools

As part of the COST 732 action more than a dozen different research groups have modelled the MUST experiment, as simulated in a wind tunnel. Tools in the form of Excel workbooks have been developed to allow exploratory analyses of model performance. These tools are available from the web site http://envs.au.dk/en/knowledge/air/models/background/exceltools/

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Test data

Within the scope of the Action, two reference data sets were compiled. Following the general data concept developed by the Action, the test data were assembled from from test campaigns for which field data as well as corresponding laboratory results are available. Regarding data quality, data density and documentation of the results, the MUST field experiment and the Joint Urban 2003 Oklahoma City Atmospheric Dispersion Study were found to be most suitable to be used as exemplary complex test cases. A link to the data compiled and used by COST 732 can be found on the Official Documents web page.