Abstract
Abstract. We present a comprehensive comparison of polar processing diagnostics derived from the National Aeronautics and Space Administration (NASA) Modern Era Retrospective-analysis for Research and Applications (MERRA) and the European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Reanalysis (ERA-Interim). We use diagnostics that focus on meteorological conditions related to stratospheric chemical ozone loss based on temperatures, polar vortex dynamics, and air parcel trajectories to evaluate the effects these reanalyses might have on polar processing studies. Our results show that the agreement between MERRA and ERA-Interim changes significantly over the 34 years from 1979 to 2013 in both hemispheres and in many cases improves. By comparing our diagnostics during five time periods when an increasing number of higher-quality observations were brought into these reanalyses, we show how changes in the data assimilation systems (DAS) of MERRA and ERA-Interim affected their meteorological data. Many of our stratospheric temperature diagnostics show a convergence toward significantly better agreement, in both hemispheres, after 2001 when Aqua and GOES (Geostationary Operational Environmental Satellite) radiances were introduced into the DAS. Other diagnostics, such as the winter mean volume of air with temperatures below polar stratospheric cloud formation thresholds (VPSC) and some diagnostics of polar vortex size and strength, do not show improved agreement between the two reanalyses in recent years when data inputs into the DAS were more comprehensive. The polar processing diagnostics calculated from MERRA and ERA-Interim agree much better than those calculated from earlier reanalysis data sets. We still, however, see fairly large differences in many of the diagnostics in years prior to 2002, raising the possibility that the choice of one reanalysis over another could significantly influence the results of polar processing studies. After 2002, we see overall good agreement among the diagnostics, which demonstrates that the ERA-Interim and MERRA reanalyses are equally appropriate choices for polar processing studies of recent Arctic and Antarctic winters.
Highlights
The depletion of stratospheric ozone in the polar regions is a consequence of chemical processing that is strongly dependent upon meteorological conditions (e.g., Solomon, 1999)
We present intercomparisons of polar processing diagnostics derived from the National Aeronautics and Space Administration (NASA) Modern Era Retrospective analysis for Research and Applications (MERRA) and the European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Reanalysis (ERA-Interim)
We have presented comparisons of stratospheric polar processing diagnostics derived from the Modern Era Retrospective-analysis for Research and Applications (MERRA) and ERAInterim reanalyses for Arctic and Antarctic winters from 1979 to 2013
Summary
The depletion of stratospheric ozone in the polar regions is a consequence of chemical processing that is strongly dependent upon meteorological conditions (e.g., Solomon, 1999). The global analyses of meteorological fields provided by data assimilation systems (DAS) that combine many of these measurements are invaluable for polar processing and ozone loss studies. Numerous such DAS analyses are available, facilitating both observational and modeling studies of polar processing (e.g., WMO, 2011, 2015, and references therein). Potential vorticity data from MERRA are available from GMAO only on a reduced 1 × 1.25◦ latitude/longitude grid (181 × 288 grid points) with 42 pressure levels up to 0.1 hPa; for the purposes of this study, MERRA PV is linearly interpolated to match the model levels and grid as was done in Manney et al (2011) These interpolations of the MERRA PV data cause some smoothing in the resulting PV fields, they preserve the strong PV gradients that define the polar vortex edge. All of the PV-based polar processing diagnostics we use depend strongly on the vortex edge and PV gradients (see Sect. 2.4.1), so these diagnostics are unlikely to be significantly affected by the errors introduced from interpolating MERRA PV to the model grid and levels
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