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. The European Centre for Medium-Range Weather Forecasts' (ECMWF's)next-generation reanalysis ERA5 provides many improvements, but italso confronts the community with a “big data” challenge. Datastorage requirements for ERA5 increase by a factor of ∼80 compared with the ERA-Interim reanalysis, introduced a decade ago.Considering the significant increase in resources required forworking with the new ERA5 data set, it is important to assess itsimpact on Lagrangian transport simulations. To quantify thedifferences between transport simulations using ERA5 and ERA-Interimdata, we analyzed comprehensive global sets of 10-day forwardtrajectories for the free troposphere and the stratosphere for theyear 2017. The new ERA5 data have a considerable impact on thesimulations. Spatial transport deviations between ERA5 andERA-Interim trajectories are up to an order of magnitude larger thanthose caused by parameterized diffusion and subgrid-scale windfluctuations after 1 day and still up to a factor of 2–3 largerafter 10 days. Depending on the height range, the spatialdifferences between the trajectories map into deviations as large as3 K in temperature, 30 % in specific humidity, 1.8 % in potentialtemperature, and 50 % in potential vorticity after 1 day. Part ofthe differences between ERA5 and ERA-Interim is attributed to the betterspatial and temporal resolution of the ERA5 reanalysis, which allows fora better representation of convective updrafts, gravity waves,tropical cyclones, and other meso- to synoptic-scale features of theatmosphere. Another important finding is that ERA5 trajectoriesexhibit significantly improved conservation of potential temperaturein the stratosphere, pointing to an improved consistency of ECMWF'sforecast model and observations that leads to smaller dataassimilation increments. We conducted a number of downsamplingexperiments with the ERA5 data, in which we reduced the numbers ofmeteorological time steps, vertical levels, and horizontal gridpoints. Significant differences remain present in the transportsimulations, if we downsample the ERA5 data to a resolution similarto ERA-Interim. This points to substantial changes of the forecastmodel, observations, and assimilation system of ERA5 in addition toimproved resolution. A comparison of two Lagrangian trajectorymodels allowed us to assess the readiness of the codes and workflowsto handle the comprehensive ERA5 data and to demonstrate theconsistency of the simulation results. Our results will help toguide future Lagrangian transport studies attempting to navigate theincreased computational complexity and leverage the considerablebenefits and improvements of ECMWF's new ERA5 data set.

From ERA-Interim to ERA5: the considerable impact of ECMWF's next-generation reanalysis on Lagrangian transport simulations