Interactive 3-D visual analysis of ERA5 data: improving diagnostic indices for marine cold air outbreaks and polar lows

• Published in: Weather and Climate Dynamics
• Main Authors: M. Meyer, I. Polkova, K. R. Modali, L. Schaffer, J. Baehr, S. Olbrich, M. Rautenhaus
• Format: Article in Journal/Newspaper
• Language: English
• Published: Copernicus Publications 2021
• Subjects: Meteorology. Climatology; QC851-999; Nordic Seas
• Online Access: https://doi.org/10.5194/wcd-2-867-2021; https://doaj.org/article/0416b6a03d18409d83ad13082fd7c20c

Recent advances in visual data analysis are well suited to gain insights into dynamical processes in the atmosphere. We apply novel methods for three-dimensional (3-D) interactive visual data analysis to investigate marine cold air outbreaks (MCAOs) and polar lows (PLs) in the recently released ERA5 reanalysis data. Our study aims at revealing 3-D perspectives on MCAOs and PLs in ERA5 and at improving the diagnostic indices to capture these weather events in long-term assessments on seasonal and climatological timescales. Using an extended version of the open-source visualization framework Met.3D , we explore 3-D perspectives on the structure and dynamics of MCAOs and PLs and relate these to previously used diagnostic indices. Motivated by the 3-D visual analysis of selected MCAO and PL cases, we conceptualize alternative index variants that capture the vertical extent of MCAOs and their distance to the dynamical tropopause. The new index variants are evaluated, along with previously used indices, with a focus on their skill as a proxy for the occurrence of PLs. Testing the association of diagnostic indices with observed PLs in the Barents and the Nordic seas for the years 2002–2011 shows that the new index variants based on the vertical structure of cold air masses are more skilful in distinguishing the times and locations of PLs, compared with conventional indices based on sea–air temperature difference only. We thus propose using the new diagnostics for further analyses in climate predictions and climatological studies. The methods for visual data analysis applied here are available as an open-source tool and can be used generically for interactive 3-D visual analysis of atmospheric processes in ERA5 and other gridded meteorological data.