Abstract

Abstract. A standardized approach for the definition, propagation, and reporting of uncertainty in the ozone differential absorption lidar data products contributing to the Network for the Detection for Atmospheric Composition Change (NDACC) database is proposed. One essential aspect of the proposed approach is the propagation in parallel of all independent uncertainty components through the data processing chain before they are combined together to form the ozone combined standard uncertainty. The independent uncertainty components contributing to the overall budget include random noise associated with signal detection, uncertainty due to saturation correction, background noise extraction, the absorption cross sections of O3, NO2, SO2, and O2, the molecular extinction cross sections, and the number densities of the air, NO2, and SO2. The expression of the individual uncertainty components and their step-by-step propagation through the ozone differential absorption lidar (DIAL) processing chain are thoroughly estimated. All sources of uncertainty except detection noise imply correlated terms in the vertical dimension, which requires knowledge of the covariance matrix when the lidar signal is vertically filtered. In addition, the covariance terms must be taken into account if the same detection hardware is shared by the lidar receiver channels at the absorbed and non-absorbed wavelengths. The ozone uncertainty budget is presented as much as possible in a generic form (i.e., as a function of instrument performance and wavelength) so that all NDACC ozone DIAL investigators across the network can estimate, for their own instrument and in a straightforward manner, the expected impact of each reviewed uncertainty component. In addition, two actual examples of full uncertainty budget are provided, using nighttime measurements from the tropospheric ozone DIAL located at the Jet Propulsion Laboratory (JPL) Table Mountain Facility, California, and nighttime measurements from the JPL stratospheric ozone DIAL located at Mauna Loa Observatory, Hawai'i.

Highlights

  • The present article is the second of three companion papers that provide a comprehensive description of recent recommendations made to the Network for Detection of Strato-Published by Copernicus Publications on behalf of the European Geosciences Union.T

  • The present article is the second of three companion papers on the recommendations made to the NDACC lidar community for the standardization of vertical resolution and uncertainty in their lidar data processing algorithms

  • The focus was on the ozone differential absorption lidar (DIAL) uncertainty budget

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Summary

Introduction

The present article (Part 2) provides a detailed description of the approach proposed by the ISSI team for a standardized treatment of uncertainty in the ozone differential absorption lidar (DIAL) retrievals. Another companion paper (Part 3) (Leblanc et al, 2016c) presents a similar approach for the standardized treatment of uncertainty in the temperature lidar retrievals. In the framework of the NDACC, various groups have set up lidar instruments for the measurement of ozone in the troposphere and stratosphere They have generally described their lidar systems with a detailed assessment of the measurement errors (e.g., Godin, 1987; Uchino and Tabata, 1991; McDermid et al, 1990; Papayannis et al, 1990; McGee et al, 1991; Godin-Beekmann et al, 2003).

Proposed reference definition: combined standard uncertainty
Standard uncertainty
Combined standard uncertainty
Minimizing correlation between input quantities for actual measurements
Lidar equation
The DIAL equation
Uncertainty owing to detection noise
Uncertainty owing to background noise extraction
Uncertainty owing to the ozone absorption cross section differential
Random component
Systematic component
Uncertainty owing to the Rayleigh extinction cross section differential
Uncertainty owing to the interfering gases’ cross section differential
Uncertainty owing to O2 absorption cross section differential
Uncertainty owing to interfering gases’ atmospheric profiles
Estimation from air number density profile
Estimation from air temperature and pressure profile
4.10 Propagation of uncertainty when combining two intensity ranges
4.11 Ozone combined standard uncertainty
Two examples of actual ozone DIAL uncertainty budget
Ozone uncertainty budget for the tropospheric O3 DIAL at Table Mountain
Conclusion
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