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

Abstract : To advance our understanding of the stratosphere, high-quality observational datasets of the stratosphere are needed. It is commonplace that reanalysis datasets are used to conduct stratospheric studies. However, the accuracy of these reanalyses 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 in- formation is already assimilated into reanalyses, the direct comparison of satellite temperatures to the reanalysis is not truly independent. Stratospheric lidars use Rayleigh scatter- ing to measure density in the middle and upper atmosphere, allowing temperature profiles to be derived for altitudes from 30 km (where Mie scattering due to stratospheric aerosols be- comes negligible) to 80–90 km (where the signal-to-noise ra- tio begins to drop rapidly). The Network for the Detection of Atmospheric Composition Change (NDACC) contains sev- eral lidars at different latitudes that have measured atmo- spheric temperatures since the 1970s, resulting in a long- running upper-stratospheric temperature dataset. These tem- perature datasets are useful for validating reanalysis datasets in the stratosphere, as they are not assimilated into reanaly- ses. Here, stratospheric temperature data from lidars in the Northern Hemisphere between 1990–2017 were compared with the European Centre for Medium-Range Weather Fore- casts ERA-Interim and ERA5 reanalyses. To give confidence to any bias found, temperature data from NASA’s EOS Mi- crowave Limb Sounder were also compared to ERA-Interim and ERA5 at points over the lidar sites. In ERA-Interim a cold bias of −3 to −4 K between 10 and 1 hPa was found when compared to both measurement systems. Comparisons with ERA5 found a small bias of magnitude 1 K which varies between cold and warm bias with height between 10 and 1 hPa, indicating a good thermal representation of the middle atmosphere up to 1 hPa. A further comparison was under- taken looking at the temperature bias by year to see the ef- fects of the assimilation of the Advanced Microwave Sound- ing Unit-A (AMSU-A) satellite data and the Constellation Observing System for Meteorology, Ionosphere, and Climate GPS Radio Occultation (COSMIC GPSRO) data on strato- spheric temperatures within the aforementioned ERA anal- yses. It was found that ERA5 was sensitive to the introduc- tion of COSMIC GPSRO in 2007 with the reduction of the cold bias above 1 hPa. In addition to this, the introduction of AMSU-A data caused variations in the temperature bias between 1–10 hPa between 1997–2008.
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Graeme Marlton, Andrew Charlton-Perez, Giles Harrison, Inna Polichtchouk, Alain Hauchecorne, et al.. Using a network of temperature lidars to identify temperature biases in the upper stratosphere in ECMWF reanalyses. Atmospheric Chemistry and Physics, European Geosciences Union, 2021, 21 (8), pp.6079-6092. ⟨10.5194/acp-21-6079-2021⟩. ⟨insu-02961869v2⟩

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