Articles | Volume 21, issue 8 
            
                
                    
                    
            
            
            https://doi.org/10.5194/acp-21-6079-2021
                    © Author(s) 2021. This work is distributed under 
the Creative Commons Attribution 4.0 License.
                the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-21-6079-2021
                    © Author(s) 2021. This work is distributed under 
the Creative Commons Attribution 4.0 License.
                the Creative Commons Attribution 4.0 License.
Using a network of temperature lidars to identify temperature biases in the upper stratosphere in ECMWF reanalyses
Graeme Marlton
CORRESPONDING AUTHOR
                                            
                                    
                                            Department of Meteorology, University of Reading, Reading, RG6 6LA, United Kingdom
                                        
                                    Andrew Charlton-Perez
                                            Department of Meteorology, University of Reading, Reading, RG6 6LA, United Kingdom
                                        
                                    Giles Harrison
                                            Department of Meteorology, University of Reading, Reading, RG6 6LA, United Kingdom
                                        
                                    Inna Polichtchouk
                                            European Centre for Medium-Range Weather Forecasts, Shinfield Road, Reading, United Kingdom
                                        
                                    Alain Hauchecorne
                                            LATMOS/IPSL, UVSQ Université Paris-Saclay, Sorbonne Univerité, CNRS, Guyancourt, France
                                        
                                    Philippe Keckhut
                                            LATMOS/IPSL, UVSQ Université Paris-Saclay, Sorbonne Univerité, CNRS, Guyancourt, France
                                        
                                    Robin Wing
                                            LATMOS/IPSL, UVSQ Université Paris-Saclay, Sorbonne Univerité, CNRS, Guyancourt, France
                                        
                                    Thierry Leblanc
                                            JPL Table Mountain Facility, 24490 Table Mountain Road, Wrightwood, CA, USA
                                        
                                    Wolfgang Steinbrecht
                                            Deutscher Wetterdienst, Albin-Schwaiger-Weg 10, 82383 Hohenpeissenberg, Germany
                                        
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                            Cited
18 citations as recorded by crossref.
- Evidence for Large Increases in Clear‐Air Turbulence Over the Past Four Decades M. Prosser et al. 10.1029/2023GL103814
- Air Temperature Intermittency and Photofragment Excitation A. Tuck 10.3390/meteorology2040026
- Impact of Polar Vortex Modes on Winter Weather Patterns in the Northern Hemisphere A. Mariaccia et al. 10.3390/atmos15091062
- Stratospheric Polar Vortex Revisited: New Diagnostic for the Vortex Breakup J. SEO & W. CHOI 10.2151/jmsj.2022-036
- Classification of Stratosphere Winter Evolutions Into Four Different Scenarios in the Northern Hemisphere A. Mariaccia et al. 10.1029/2022JD036662
- Assessment of ERA-5 Temperature Variability in the Middle Atmosphere Using Rayleigh LiDAR Measurements between 2005 and 2020 A. Mariaccia et al. 10.3390/atmos13020242
- Effects of reanalysis forcing fields on ozone trends and age of air from a chemical transport model Y. Li et al. 10.5194/acp-22-10635-2022
- How well do the reanalysis datasets capture hot and cold extremes and their trends in India? S. Bhattacharyya et al. 10.1016/j.atmosres.2025.108073
- Scaling Up: Molecular to Meteorological via Symmetry Breaking and Statistical Multifractality A. Tuck 10.3390/meteorology1010003
- Gravity Wave Breaking Associated with Mesospheric Inversion Layers as Measured by the Ship-Borne BEM Monge Lidar and ICON-MIGHTI R. Wing et al. 10.3390/atmos12111386
- The Doppler wind, temperature, and aerosol RMR lidar system at Kühlungsborn, Germany – Part 1: Technical specifications and capabilities M. Gerding et al. 10.5194/amt-17-2789-2024
- Limb Temperature Observations in the Stratosphere and Mesosphere Derived from the OMPS Sensor P. Da Costa Louro et al. 10.3390/rs16203878
- Mesospheric and Upper Stratospheric Temperatures From OMPS‐LP Z. Chen et al. 10.1029/2022EA002763
- Why the Real Atmosphere Has More Energy than Climate Models: Implications for Ground-Based Telescopes A. Tuck 10.3390/atmos16010056
- The Generation of Wind Velocity via Scale Invariant Gibbs Free Energy: Turbulence Drives the General Circulation A. Tuck 10.3390/e27070740
- Analysis of the Correctness of Retrieving the Vertical Atmospheric Temperature Distribution from Lidar Signals of Molecular Scattering at the Main Lidar of the Siberian Lidar Station S. Bobrovnikov et al. 10.1134/S1024856022060057
- Intercomparison of middle atmospheric meteorological analyses for the Northern Hemisphere winter 2009–2010 J. McCormack et al. 10.5194/acp-21-17577-2021
- Gravity‐Wave‐Driven Seasonal Variability of Temperature Differences Between ECMWF IFS and Rayleigh Lidar Measurements in the Lee of the Southern Andes S. Gisinger et al. 10.1029/2021JD036270
18 citations as recorded by crossref.
- Evidence for Large Increases in Clear‐Air Turbulence Over the Past Four Decades M. Prosser et al. 10.1029/2023GL103814
- Air Temperature Intermittency and Photofragment Excitation A. Tuck 10.3390/meteorology2040026
- Impact of Polar Vortex Modes on Winter Weather Patterns in the Northern Hemisphere A. Mariaccia et al. 10.3390/atmos15091062
- Stratospheric Polar Vortex Revisited: New Diagnostic for the Vortex Breakup J. SEO & W. CHOI 10.2151/jmsj.2022-036
- Classification of Stratosphere Winter Evolutions Into Four Different Scenarios in the Northern Hemisphere A. Mariaccia et al. 10.1029/2022JD036662
- Assessment of ERA-5 Temperature Variability in the Middle Atmosphere Using Rayleigh LiDAR Measurements between 2005 and 2020 A. Mariaccia et al. 10.3390/atmos13020242
- Effects of reanalysis forcing fields on ozone trends and age of air from a chemical transport model Y. Li et al. 10.5194/acp-22-10635-2022
- How well do the reanalysis datasets capture hot and cold extremes and their trends in India? S. Bhattacharyya et al. 10.1016/j.atmosres.2025.108073
- Scaling Up: Molecular to Meteorological via Symmetry Breaking and Statistical Multifractality A. Tuck 10.3390/meteorology1010003
- Gravity Wave Breaking Associated with Mesospheric Inversion Layers as Measured by the Ship-Borne BEM Monge Lidar and ICON-MIGHTI R. Wing et al. 10.3390/atmos12111386
- The Doppler wind, temperature, and aerosol RMR lidar system at Kühlungsborn, Germany – Part 1: Technical specifications and capabilities M. Gerding et al. 10.5194/amt-17-2789-2024
- Limb Temperature Observations in the Stratosphere and Mesosphere Derived from the OMPS Sensor P. Da Costa Louro et al. 10.3390/rs16203878
- Mesospheric and Upper Stratospheric Temperatures From OMPS‐LP Z. Chen et al. 10.1029/2022EA002763
- Why the Real Atmosphere Has More Energy than Climate Models: Implications for Ground-Based Telescopes A. Tuck 10.3390/atmos16010056
- The Generation of Wind Velocity via Scale Invariant Gibbs Free Energy: Turbulence Drives the General Circulation A. Tuck 10.3390/e27070740
- Analysis of the Correctness of Retrieving the Vertical Atmospheric Temperature Distribution from Lidar Signals of Molecular Scattering at the Main Lidar of the Siberian Lidar Station S. Bobrovnikov et al. 10.1134/S1024856022060057
- Intercomparison of middle atmospheric meteorological analyses for the Northern Hemisphere winter 2009–2010 J. McCormack et al. 10.5194/acp-21-17577-2021
- Gravity‐Wave‐Driven Seasonal Variability of Temperature Differences Between ECMWF IFS and Rayleigh Lidar Measurements in the Lee of the Southern Andes S. Gisinger et al. 10.1029/2021JD036270
Latest update: 30 Oct 2025
Short summary
                    A network of Rayleigh lidars have been used to infer the upper-stratosphere 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.
                    A network of Rayleigh lidars have been used to infer the upper-stratosphere temperature bias in...
                    
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