Accelerating research through community open source software for a standardized file format to improve process representation in numerical weather prediction models

Abstract. Improvements in process representation in numerical weather prediction (NWP) models requires informed collaboration between scientists making research-grade observations and scientist developing state-of-the-art NWP models. As a result, progress in model quality relies heavily on the ability to efficiently evaluate and reliably reconcile these two sources of information. To facilitate such progress, with focus on enhanced model skill in polar regions, the Year of Polar Prediction site Model Intercomparison Project (YOPPsiteMIP) community defined the Merged Data File (MDF) format. The file format is designed for high temporal and spatial resolution data for direct comparison between observations and model output to assess parameterized processes under various conditions. A broad overview of the MDF format is provided along with supporting use-cases defined by the research community, and present a set of free, open-source, computational tools for creating and utilizing this standardized format. Two free open source Python packages are discussed: 1) “The MDF toolkit", a data processing library for the creation of standardized datasets, and 2) "MDF visualization", a set of Python codes in notebook format that accelerate model evaluation and climate process research utilizing the MDF format. The benefits of such tools that may help unite diverse groups of researchers through a common data-format language are also discussed.