Abstract

Abstract. A two-part intercomparison campaign was conducted at Observatoire de Haute-Provence (OHP) for the validation of lidar ozone and temperature profiles using the mobile NASA Stratospheric Ozone Lidar (NASA STROZ), satellite overpasses from the Microwave Limb Sounder (MLS), the Sounding of the Atmosphere using Broadband Emission Radiometry (SABER), meteorological radiosondes launched from Nîmes, and locally launched ozonesondes. All the data were submitted and compared “blind”, before the group could see results from the other instruments. There was good agreement between all ozone measurements between 20 and 40 km, with differences of generally less than 5 % throughout this region. Below 20 km, SABER and MLS measured significantly more ozone than the lidars or ozonesondes. Temperatures for all lidars were in good agreement between 30 and 60 km, with differences on the order of ±1 to 3 K. Below 30 km, the OHP lidar operating at 532 nm has a significant cool bias due to contamination by aerosols. Systematic, altitude-varying bias up to ±5 K compared to the lidars was found for MLS at many altitudes. SABER temperature profiles are generally closer to the lidar profiles, with up 3 K negative bias near 50 km. Total uncertainty estimates for ozone and temperature appear to be realistic for nearly all systems. However, it does seem that the very low estimated uncertainties of lidars between 30 and 50 km, between 0.1 and 1 K, are not achieved during Lidar Validation Network for the Detection of Atmospheric Composition Change (NDACC) Experiment (LAVANDE). These estimates might have to be increased to 1 to 2 K.

Highlights

  • The international Network for the Detection of Atmospheric Composition Change (NDACC; http://www.ndacc.org, last access: 17 June 2018), formerly the Network for the Detection of Stratospheric Change (NDSC), is composed of more than 70 research stations worldwide (Kurylo et al, 2016; De Mazière et al, 2018)

  • The purpose of the present paper is to report on the Lidar Validation NDACC Experiment (LAVANDE), which took place in July 2017 and March 2018 at Observatoire de HauteProvence (OHP) in southern France

  • 1 ftp://ftp.cpc.ncep.noaa.gov/ndacc/station/ohp/, 2 http://weather.uwyo.edu/upperair/sounding.html, 3 ftp://ftp.cpc.ncep.noaa.gov/ndacc/ncep/temp/, 4 https://disc.gsfc.nasa.gov/datasets?keywords=Microwave Limb Sounder (MLS), and 5 SABER temperature and ozone profiles are available at http://saber.gats-inc.com/

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Summary

Introduction

The international Network for the Detection of Atmospheric Composition Change (NDACC; http://www.ndacc.org, last access: 17 June 2018), formerly the Network for the Detection of Stratospheric Change (NDSC), is composed of more than 70 research stations worldwide (Kurylo et al, 2016; De Mazière et al, 2018). NDACC lidars, for example, have been intercompared in the 1989 Stratospheric Ozone Intercomparison Campaign in Table Mountain, California (STOIC; Margitan et al, 1995); the 1995 Ozone Profiler Assessment in Lauder, New Zealand (OPAL; McDermid et al, 1998); the 1997 OTOIC intercomparison in Haute-Provence (Braathen et al, 2004); the 1998 Ny-Ålesund Ozone Measurements Intercomparison in Spitsbergen, Norway (NAOMI; Steinbrecht et al, 1999); the 1999 DIfferential Absorption Lidar (DIAL) algorithm intercomparison campaign (Godin et al, 1999); the 2005 Hohenpeissenberg Ozone Profiling Experiment in Germany (HOPE; Steinbrecht et al, 2009b); and the 2009 Measurements of Humidity in the Atmosphere and Validation Experiments in Table Mountain, California (MOHAVE; Leblanc et al, 2011) Many of these campaigns have resulted in corrections and improvements for the involved lidar systems and their analysis software. The referee carried out all the comparison data analysis

Instruments used for LAVANDE
Lidars
NASA STROZ
Co-located satellite overpasses
Co-locating satellite profiles and ground-based profiles
Campaign overview
Example comparisons
Comparisons with satellites
Intercomparison results for ozone
Intercomparison results for temperature
Lidar temperature uncertainty analysis
Satellite temperature uncertainty analysis
Findings
Conclusions

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