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© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  25 May 2020

25 May 2020

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A revised version of this preprint is currently under review for the journal ACP.

Technical note: Lowermost-stratospheric moist bias in ECMWF IFS model diagnosed from airborne GLORIA observations during winter/spring 2016

Wolfgang Woiwode1, Andreas Dörnbrack2, Inna Polichtchouk3, Sören Johansson1, Ben Harvey4, Michael Höpfner1, Jörn Ungermann5, and Felix Friedl-Vallon1 Wolfgang Woiwode et al.
  • 1Institute of Meteorology and Climate Research – Atmospheric Trace Gases and Remote Sensing (IMK-ASF), Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
  • 2Deutsches Zentrum für Luft- und Raumfahrt, Institut für Physik der Atmosphäre, Oberpfaffenhofen, Germany
  • 3European Centre for Medium‐Range Weather Forecasts, Reading, UK
  • 4National Centre for Atmospheric Science, University of Reading, Reading, UK
  • 5Institute of Energy and Climate Research – Stratosphere (IEK-7), Forschungszentrum Jülich, Jülich, Germany

Abstract. Numerical weather forecast systems like the ECMWF IFS (European Centre for Medium-Range Weather Forecasts – Integrated Forecasting System) are known to be affected by a moist bias in the extratropical lowermost stratosphere (LMS) which results in a systematic cold bias there. We use high spatial resolution water vapour measurements by the airborne 15 infrared limb-imager GLORIA (Gimballed Limb Observer for Radiance Imaging of the Atmosphere) during the PGS (POLSTRACC/GW-LCYLCE-II/SALSA) campaign to study the LMS moist bias in ECMWF analyses and 12 h forecasts in the season from January to March 2016. Thereby, we exploit the 2-dimensional observational capabilities of GLORIA, when compared to in situ observations, and the higher vertical and horizontal resolution, when compared to satellite observations. Using GLORIA observations taken during five flights in the polar sub-vortex region around Scandinavia and Greenland, we 20 diagnose a systematic moist bias in the LMS peaking at +50 % at potential vorticity levels of 6 to 10 PVU. In the diagnosed time period, the moist bias reduces at the highest and driest air masses observed, but clearly persists at lower levels until mid-March. Sensitivity experiments with more frequent temporal output, lower horizontal resolution, and higher/lower vertical resolution, show the short-term forecasts to be practically insensitive to these parameters on time scales of < 12 hours. Our results confirm that the diagnosed moist bias is present already in the initial conditions (i.e., the analysis) and thus supports 25 the hypothesis that the cold bias develops as a result of forecast initialisation. The moist bias in the analysis might be explained by a model bias and/or the lack of water vapour observations suitable for assimilation by the model above the tropopause.

Wolfgang Woiwode et al.

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Wolfgang Woiwode et al.

Data sets

GLORIA Chemistry Mode temperature and trace gas retrievals from the POLSTRACC/GW-LCYCLEII/GWEX/SALSA campaigns 2015/2016 S. Johansson, W. Woiwode, and M. Höpfner

HALO database HALO consortium

Wolfgang Woiwode et al.


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Latest update: 29 Sep 2020
Publications Copernicus
Short summary
The Arctic winter/spring lowermost stratospheric moist bias in ECMWF analyses and 12 h forecasts and its seasonal cycle are diagnosed by using 2-dimensional GLORIA water vapour observations. The bias is found to be present already in the forecast initialisation, and sensitivity forecasts show hardly any sensitivity to modified spatial resolution and output frequency. Possible sources are a model bias and/or lacking water vapour observations for data assimilation above the tropopause.
The Arctic winter/spring lowermost stratospheric moist bias in ECMWF analyses and 12 h forecasts...