Towards standardising output datasets using the numerical obstacle-resolving model MITRAS as an example

Abstract. The publication of well-described FAIR datasets is an important part of atmospheric modelling and research. Data standards ensure that datasets are delivered in a consistent way that is easy to understand for a data user. Standards define how the data is described, i.e. which variable names, descriptions and data formats are used. However, existing model data standards such as the CF conventions are mainly adapted for global or regional scale models. For atmospheric micro-scale obstacle-resolving (urban) models (ORMs), there is no discipline-specific model data standard and the existing ones are not fully suitable to adequately describe ORM datasets. To overcome the lack of standardisation processes, the ATMODAT STANDARD has been developed to promote the publication of FAIR datasets when no discipline-specific standard is available. This paper describes the process of producing standardised model results. The processing for ORM MITRAS serve as an example to show possible ways for the publication of FAIR datasets. The adaptation of the model's post-processing routine M2CDF and the development of a new post-processing routine called NC2ATMODAT are shown. The last may be applicable by other ORM modellers, its limitations, challenges and further use cases are discussed. Application of the two post-processors allows the preparation of datasets according to the requirements of the CF convention and the ATMODAT STANDARD. The first standardised MITRAS datasets are successfully processed and published.