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First results of a model user survey on a micro-scale model data standard
  • +2
  • Vivien Voss,
  • K. Heinke Schlünzen,
  • David Grawe,
  • Daniel Heydebreck,
  • Anette Ganske
Vivien Voss
Universität Hamburg

Corresponding Author:[email protected]

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K. Heinke Schlünzen
Universität Hamburg
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David Grawe
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Daniel Heydebreck
Deutsches Klimarechenzentrum GmbH
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Anette Ganske
Technische Informationsbibliothek TIB
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Micro-scale models are important to assess processes in complex domains, for example cities. The most common data standard for atmospheric model output data are the CF-conventions, a data standard for netCDF files, but this standard is not adapted to the model output of micro-scale models. As a part of the project AtMoDat (Atmospheric Model Data) we want to develop a model data standard for obstacle resolving models (ORM), including the additional variables (i.e. building structures, wall temperatures) used by these models. In order to involve the micro-scale modeller community in this process, a web based survey was developed and distributed in the modeller community via conferences and email. With this survey we want to find out which micro-scale ORMs are currently in use, their model specifics (e.g. used grid, coordinate system), and the handling of the model result data. Furthermore, the survey provides the opportunity to include suggestions and ideas, what we should consider in the development of the standard. Between September 2019 and July 2020, the survey was accessed 29 times, but only 12 surveys were completed. The finished surveys refer to eight different models and their corresponding model information. Results show that these different models use different output formats and processing tools, which results in different model result handling routines. The participants suggested to use the netCDF data format and to provide information on model initialization, model settings and model input along with the model output data. This would enable an easier intercomparison between different models and repetition of model simulations. Standardized model output and variable names would also enhance the development of shared routines for the analysis of micro-scale model data and a better findability of the data with search engines. This survey will remain open with regular assessments of contents (i.e. November 2020, May 2021; https://uhh.de/orm-survey).