Preprints
https://doi.org/10.5194/acp-2020-254
https://doi.org/10.5194/acp-2020-254

  14 Apr 2020

14 Apr 2020

Review status: this preprint has been withdrawn by the authors.

Using a global network of temperature lidars to identify temperature biases in the upper stratosphere in ECMWF reanalyses

Graeme Marlton1, Andrew Charlton-Perez1, Giles Harrison1, Inna Polichtchouk2, Alain Hauchecorne3, Philippe Keckhut3, and Robin Wing3 Graeme Marlton et al.
  • 1Department of Meteorology, University of Reading, Reading, RG6 6LA
  • 2European Centre for Medium Range Weather Forecasts, Shinfield Road, Reading, UK
  • 3LATMOS/IPSL, UVSQ Université Paris-Saclay, Sorbonne Univerités, CNRS, Guyancourt, France

Abstract. To advance our understanding of the stratosphere, high quality observational datasets of the upper atmosphere are needed. It is commonplace that reanalysis is used to conduct stratospheric studies. However the accuracy of the standard reanalysis at these heights is hard to infer due to a lack of in-situ measurements. Satellite measurements provide one source of temperature information. As some satellite information is already assimilated into reanalyses, the direct comparison of satellite temperatures to the reanalysis is not truly independent. Stratospheric lidars use Rayleigh scattering to measure density in the upper atmosphere, allowing temperature profiles to be derived for altitudes from 30 km (where Mie scattering due to stratospheric aerosols becomes negligible) to 80–90 km (where the signal-to-noise begins to drop rapidly). The Network for the Detection of Atmospheric Composition Change (NDACC) contains several lidars at different latitudes that have measured atmospheric temperatures since the 1970s, resulting in a long running upper-stratospheric temperature dataset. These temperature datasets are useful for validating reanalysis datasets in the stratosphere, as they are not assimilated into reanalyses. Here we take stratospheric temperature data from lidars in the northern hemisphere for winter months between 1990–2017 and compare them with the European Centre for ECMWF's ERA-interim and ERA-5 reanalyses. To give confidence in any bias found, temperature data from NASA's EOS Microwave Limb Sounder is also compared to ERA-interim and ERA-5 at points over the lidar sites. In ERA-interim a cold bias of −3 to −4 K between 10 hPa and 1 hPa is found when compared to both measurement systems. Comparisons with ERA-5 found a small bias of magnitude 1 K which varies between cold and warm bias with height between 10 hPa and 3 hPa, indicating a good thermal representation of the upper atmosphere to 3 hPa. At heights above this, comparisons with EOS MLS yield a slight warm bias and the temperature lidar yield a cold bias. A further comparison is undertaken to see the effects of the assimilation of the Advanced Microwave Sounding Unit-A satellite data and the Constellation Observing System for Meteorology, Ionosphere, and Climate GPS Radio Occulation (COSMIC GPSRO) data on stratospheric temperatures. By comparing periods before and after the introduction of each data source it is clear that COSMIC GPSRO improves the cold bias in the 3 hPa to 0.5 hPa altitude range.

This preprint has been withdrawn.

Graeme Marlton et al.

Interactive discussion

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Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement

Graeme Marlton et al.

Graeme Marlton et al.

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This preprint has been withdrawn.

Short summary
A network of Rayleigh lidars have been used to infer the middle atmosphere temperature bias in ECMWF ERA-5 and ERA-interim reanalyses during 1990–2017. Results show that ERA-interim exhibits a cold bias of −3 to −4 K between 10 and 1 hPa. Comparisons with ERA-5 found a smaller bias of 1 K which varies between cold and warm between 10 and 3 hPa, indicating a good thermal representation of the atmosphere to 3 hPa. These biases must be accounted for in stratospheric studies using these reanalyses.
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