Diagnosing lateral boundary spin‐up in regional models using an age‐of‐air diagnostic

Abstract Despite the rapid development of global‐storm‐resolving models, computational expense hampers widespread deployment of these for operational forecasting. Thus, regional models at convection‐permitting resolutions still need to be deployed to take advantage of explicitly representing smaller‐scale processes that improve the forecast. Often, the choice of domain size is made subjectively, despite both domain size and location with respect to prevailing meteorology significantly impacting how constrained the regional model is to its driving model. This has implications on error growth, upscale impacts of mesoscale variability, along with ensemble spread. Here, we introduce a novel diagnostic designed to characterise lateral boundary spin‐up by quantifying the age of air, or the time since the air entered the model through the lateral boundaries. We apply this diagnostic to a variety of case studies over regional domains in Australia, and contrast this to a larger pan‐Australia domain, demonstrating that larger‐domain models exhibit more realistic atmospheric structures and reduced spin‐up at the boundaries, directly correlated with the age‐of‐air metric. Additionally, we show that large‐domain models demonstrate quicker spin‐up of mesoscale kinetic energy and subsequent upscale energy growth, evidenced by power spectral analysis. We further generalise the age‐of‐air diagnostic by applying it to reanalysis, providing climatological perspectives of the age of air which aid future applications such as characterising error growth in regional versus driving models in different weather regimes, and determining optimal time scales to blend regional and global model fields in data assimilation.