Towards UNified Error Reporting (TUNER) is an emerging SPARC activity and an ISSI International Team. This project aims to provide consistent and inter-comparable error estimates for atmospheric temperature and composition measurements from space. Along with this, a consistent and inter-comparable characterization of spatial resolution and content of a priori information of the remotely sensed data shall be provided. This is important, because quantitative work with remotely sensed data – data assimilation, data merging, time series analysis, testing of hypotheses, etc. – depends largely on the adequate characterization of the data. Currently, multiple retrieval methods are used by the different instrument groups, and along with this various approaches to error estimation are applied. Resulting errors are not always inter-comparable. Some kinds of uncertainties are sometimes not reported at all. The different altitude resolutions and the different content of prior information in the data products are a particular problem. Within TUNER, data characterization methods currently in use are identified, their completeness and inter-comparability are assessed, recommendations for how unified data characterization should be performed and how data uncertainties should be reported are developed, and unified error estimates for some selected data products are provided. Beyond this, data users are instructed how to best utilize these metadata. This special issue is meant to include papers covering one of the following topics:

• methodical work related to the uncertainty assessment of satellite data on atmospheric temperature and composition;
• the error budget of satellite-borne atmospheric sounders;
• the use of results of validation studies to judge the adequacy of uncertainty estimates;
• recommendations for unified error estimates;
• tutorial articles on the correct use of error estimates and other diagnostic data and related topics.
This special issue is open to contributions from outside the related SPARC and ISSI TUNER teams, provided that the content fits within the scope of TUNER. Further details are available at http://www.imk-asf.kit.edu/english/304_2689.php.