Interactive 3-D visual analysis of ERA 5 data: improving diagnostic indices for marine cold air outbreaks

Abstract. We inspect the 3-D structure of Marine Cold Air Outbreaks (MCAOs) and Polar Lows (PLs) in ERA5 data with the aim of improving diagnostic indices to capture these weather events in long-term assessments on seasonal and climatological time-scales. For this study, we designed a workflow that starts with the interactive 3-D visual exploration of single MCAO and PL events, using an extended version of the open-source visualization framework Met.3D, followed by the design and statistical testing of new diagnostic indices in long-term assessments. Results from the interactive visual data exploration provide insights into the complex 3-D shape and dynamics of MCAOs and PLs in ERA5 data. Motivated by the visual analysis of single cases, we extend widely-used diagnostics by conceptualizing a simple index to capture the vertical extent of the lower-level instability induced by MCAOs. Testing the association of diagnostic indices with observed PLs in the Barents and the Nordic Seas (STARS data) shows that, the new MCAO index introduced here has an important advantage: it is a more skillful indicator for distinguishing the times and locations of PLs, compared with previously-used indices. We thus propose the new index for further analyses in seasonal climate predictions and climatological studies. The methods for interactive 3-D visual data analysis presented here are available as a generic open-source tool for investigating atmospheric processes in ERA5 and other gridded meteorological data.