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@ARTICLE{Hoffmann:861315,
      author       = {Hoffmann, Lars and Günther, Gebhard and Li, Dan and Stein,
                      Olaf and Wu, Xue and Griessbach, Sabine and Heng, Yi and
                      Konopka, Paul and Müller, Rolf and Vogel, Bärbel and
                      Wright, Jonathon S.},
      title        = {{F}rom {ERA}-{I}nterim to {ERA}5: the considerable impact
                      of {ECMWF}'s next-generation reanalysis on {L}agrangian
                      transport simulations},
      journal      = {Atmospheric chemistry and physics},
      volume       = {19},
      number       = {5},
      issn         = {1680-7324},
      address      = {Katlenburg-Lindau},
      publisher    = {EGU},
      reportid     = {FZJ-2019-01807},
      pages        = {3097 - 3124},
      year         = {2019},
      abstract     = {The European Centre for Medium-Range Weather Forecasts'
                      (ECMWF's) next-generation reanalysis ERA5 provides many
                      improvements, but it also confronts the community with a
                      “big data” challenge. Data storage 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 for working with
                      the new ERA5 data set, it is important to assess its impact
                      on Lagrangian transport simulations. To quantify the
                      differences between transport simulations using ERA5 and
                      ERA-Interim data, we analyzed comprehensive global sets of
                      10-day forward trajectories for the free troposphere and the
                      stratosphere for the year 2017. The new ERA5 data have a
                      considerable impact on the simulations. Spatial transport
                      deviations between ERA5 and ERA-Interim trajectories are up
                      to an order of magnitude larger than those caused by
                      parameterized diffusion and subgrid-scale wind fluctuations
                      after 1 day and still up to a factor of 2–3 larger after
                      10 days. Depending on the height range, the spatial
                      differences between the trajectories map into deviations as
                      large as 3 K in temperature, $30 \%$ in specific
                      humidity, $1.8 \%$ in potential temperature, and $50 \%$
                      in potential vorticity after 1 day. Part of the differences
                      between ERA5 and ERA-Interim is attributed to the better
                      spatial and temporal resolution of the ERA5 reanalysis,
                      which allows for a better representation of convective
                      updrafts, gravity waves, tropical cyclones, and other meso-
                      to synoptic-scale features of the atmosphere. Another
                      important finding is that ERA5 trajectories exhibit
                      significantly improved conservation of potential temperature
                      in the stratosphere, pointing to an improved consistency of
                      ECMWF's forecast model and observations that leads to
                      smaller data assimilation increments. We conducted a number
                      of downsampling experiments with the ERA5 data, in which we
                      reduced the numbers of meteorological time steps, vertical
                      levels, and horizontal grid points. Significant differences
                      remain present in the transport simulations, if we
                      downsample the ERA5 data to a resolution similar to
                      ERA-Interim. This points to substantial changes of the
                      forecast model, observations, and assimilation system of
                      ERA5 in addition to improved resolution. A comparison of two
                      Lagrangian trajectory models allowed us to assess the
                      readiness of the codes and workflows to handle the
                      comprehensive ERA5 data and to demonstrate the consistency
                      of the simulation results. Our results will help to guide
                      future Lagrangian transport studies attempting to navigate
                      the increased computational complexity and leverage the
                      considerable benefits and improvements of ECMWF's new ERA5
                      data set.},
      cin          = {JSC / IEK-7 / JARA-HPC},
      ddc          = {550},
      cid          = {I:(DE-Juel1)JSC-20090406 / I:(DE-Juel1)IEK-7-20101013 /
                      $I:(DE-82)080012_20140620$},
      pnm          = {511 - Computational Science and Mathematical Methods
                      (POF3-511) / 244 - Composition and dynamics of the upper
                      troposphere and middle atmosphere (POF3-244) / Chemisches
                      Lagrangesches Modell der Stratosphäre (CLaMS)
                      $(jicg11_20090701)$},
      pid          = {G:(DE-HGF)POF3-511 / G:(DE-HGF)POF3-244 /
                      $G:(DE-Juel1)jicg11_20090701$},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000460839900003},
      doi          = {10.5194/acp-19-3097-2019},
      url          = {https://juser.fz-juelich.de/record/861315},
}