Preprints
https://doi.org/10.5194/acp-2022-505
https://doi.org/10.5194/acp-2022-505
 
22 Jul 2022
22 Jul 2022
Status: a revised version of this preprint was accepted for the journal ACP and is expected to appear here in due course.

Vertical structure of the lower-stratospheric moist bias in the ERA5 reanalysis and its connection to mixing processes

Konstantin Krüger1, Andreas Schäfler1, Martin Wirth1, Martin Weissmann3, and George Craig2 Konstantin Krüger et al.
  • 1Deutsches Zentrum für Luft- und Raumfahrt (DLR), Institut für Physik der Atmosphäre, Oberpfaffenhofen, Germany
  • 2Meteorologisches Institut München, Ludwig-Maximilians-Universität, Munich, Germany
  • 3Institut für Meteorologie und Geophysik, Universität Wien, Vienna, Austria

Abstract. Numerical weather prediction models (NWP) are known to possess a distinct moist bias in the mid-latitude lower stratosphere which is expected to affect the ability to accurately predict weather and climate. This paper investigates the vertical structure of this bias in the European Centre for Medium-Range Weather Forecast’s (ECMWF) latest global reanalysis ERA5 using a unique multi-campaign data set of highly-resolved water vapor profiles observed with a differential absorption lidar (DIAL) onboard the High Altitude and LOng Range Research Aircraft (HALO). In total, 41 flights in the midlatitudes provide more than 31000 humidity profiles varying by four orders of magnitude. The data set covers different synoptic situations and seasons and thus is suitable to characterize the strong vertical gradients in the upper troposphere and lower stratosphere (UTLS). The comparison to ERA5 indicates high positive and negative deviations in the UT which on average lead to a slightly positive bias (+20 %). In the LS, the bias rapidly increases up to a maximum of +55 % at 1.3 km altitude above the thermal tropopause (tTP), and decreases again to 15–20 % at 4 km altitude. This vertical structure is reproduced in all flights. The depth of the layer of increased bias is smaller at high tropopause altitudes and larger when the tropopause is located low. Our results also suggest a seasonality of the bias, with the maximum in summer exceeding fall by up to a factor of 3. During one field campaign, co-located ozone and water vapor profile observations enable a classification of the observations into tropospheric, stratospheric and mixed air using H2O-O3 correlations. It is shown that the bias is higher in the mixed air while being small in tropospheric and stratospheric air which highlights that excessive transport of moisture into the LS plays a decisive role for the formation of the bias. Future climatological studies should consider the analysed lower-stratospheric moist bias in ERA5. Our results show that a better representation of mixing processes in NWP models could lead to a reduced LS moist bias that, in turn, may have a positive impact on weather and climate forecasts. The moist bias should be borne in mind for climatological studies using reanalysis data.

Konstantin Krüger et al.

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on acp-2022-505', Anonymous Referee #1, 14 Aug 2022
  • RC2: 'Comment on acp-2022-505', Anonymous Referee #2, 07 Oct 2022
  • EC1: 'Comment on acp-2022-505', Farahnaz Khosrawi, 10 Oct 2022

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on acp-2022-505', Anonymous Referee #1, 14 Aug 2022
  • RC2: 'Comment on acp-2022-505', Anonymous Referee #2, 07 Oct 2022
  • EC1: 'Comment on acp-2022-505', Farahnaz Khosrawi, 10 Oct 2022

Konstantin Krüger et al.

Konstantin Krüger et al.

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Short summary
A comprehensive data set of airborne lidar water vapor profiles is compared with ERA5 reanalyses for a robust characterization of the vertical structure of the mid-latitude lower-stratospheric moist bias. We confirm a moist bias of up to 55 % at 1.3 km altitude above the tropopause and uncover a decreasing bias beyond. Co-located O3 and H2O observations reveal a particularly strong bias in the mixing layer providing indication for insufficiently modelled transport processes fostering the bias.
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