This is the resource link to the larger data set stored at the EODC. Please download the data as follows by selecting: https://data.eodc.eu/collections/LARA/[ PERIOD ]/ [ YEAR ]/[ MONTH ]/[ VARIABLE ] PERIODs: 1. 1940-1947 2. 1947-1954 3. 1954-1961 4. 1961-1968 5. 1968-1975 6. 1975-1982 7. 1982-1989 8. 1989-1996 9. 1996-2003 10. 2003-2010 11. 2010-2017 12. 2017-2024 VARIABLEs: - lon: Longitude of Particle - lat: Latitude of Particle - z: Height of Particle - pv: Potential Vorticity at Particle location - sh: Specific Humidity at Particle location - rho: Density at Particle location - T: Temperature a Particle location - prs: Pressure at Particle location Averaged VARIABLEs: - lon_av: Longitude - lat_av: Latitude - z_av: Height - pv_av: Potential Vorticity at Particle location - sh_av: Specific Humidity at Particle location - rho_av: Density at Particle location - T_av: Temperature a Particle location - prs_av: Pressure at Particle location gridded VARIABLEs: - hmix: Atmospheric boundary layer height - tro: Tropopause height - to: Topography (fixed in time)

Meteorological reanalyses are crucial datasets in atmospheric research, providing the foundation for many scientific applications. However, most reanalyses follow a Eulerian framework, providing data at specific, fixed points in space and time. This fixed-location approach is suitable for many scientific analyses, but studies focused on transport in the atmosphere would benefit from a Lagrangian framework, which provides data along dynamic, continuous trajectories following the movement of air. To achieve this, the Lagrangian particle dispersion model FLEXPART was driven off-line with data from ECMWF’s (European Centre for Medium-Range Weather Forecasts) latest reanalysis, ERA5, to convert the Eulerian ERA5 data into a Lagrangian format. FLEXPART utilises the grid-scale winds from ERA5 and stochastic parameterisations of turbulence and convection to advect particles in a domain-filling mode, where the global atmosphere is represented by 6 million particles that move freely in the atmosphere, with their number density following closely the density of air. The resulting new Lagrangian Reanalysis (LARA) dataset has been stored in an easily searchable database and made accessible to researchers all over the world. It will enable a wide range of studies, including global and regional analyses of extreme events, water and energy transport in the atmosphere, and atmospheric energy budgets. Here, we describe the data format, and how the data can be accessed and analysed. Using four examples, we give a non-exhaustive list of possible applications for which LARA could be used for. We show methods for how the evolution of air masses and their properties can be studied, and how climatologies can be established. Our examples include a study of the evolution of the Hadley cell circulation, a climatology of warm conveyor belt events, a measure of continentality by time it takes air to reach land from the ocean, and an evaluation of the dynamical consistency between subsequent ERA5 meteorological fields.