Using a global network of temperature lidars to identify temperature biases in the upper stratosphere in ECMWF reanalysesMarlton, G. ORCID: https://orcid.org/0000-0002-8466-6779, Charlton-Perez, A. ORCID: https://orcid.org/0000-0001-8179-6220, Harrison, G. ORCID: https://orcid.org/0000-0003-0693-347X, Polichtchouk, I., Hauchecorne, A. ORCID: https://orcid.org/0000-0001-9888-6994, Keckhut, P., Wing, R. ORCID: https://orcid.org/0000-0002-2895-4012, Leblanc, T. and Steinbrecht, W. ORCID: https://orcid.org/0000-0003-0680-6729 (2021) Using a global network of temperature lidars to identify temperature biases in the upper stratosphere in ECMWF reanalyses. Atmospheric Chemistry and Physics Discussions, 21. pp. 6079-6092. ISSN 1680-7375
It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing. To link to this item DOI: 10.5194/acp-21-6079-2021 Abstract/SummaryTo 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 temper1ature 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 15 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.
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