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The North America-based Tropospheric Ozone Lidar Network (TOLNet) was recently established to provide high spatiotemporal vertical profiles of ozone, to better understand physical processes driving tropospheric ozone variability and to validate the tropospheric ozone measurements of upcoming spaceborne missions such as Tropospheric Emissions: Monitoring Pollution (TEMPO). The network currently comprises six tropospheric ozone lidars, four of which are mobile instruments deploying to the field a few times per year, based on campaign and science needs. In August 2016, all four mobile TOLNet lidars were brought to the fixed TOLNet site of JPL Table Mountain Facility for the 1-week-long Southern California Ozone Observation Project (SCOOP). This intercomparison campaign, which included 400 h of lidar measurements and 18 ozonesonde launches, allowed for the unprecedented simultaneous validation of five of the six TOLNet lidars. For measurements between 3 and 10 km a.s.l., a mean difference of 0.7 ppbv (1.7 %), with a root-mean-square deviation of 1.6 ppbv or 2.4 %, was found between the lidars and ozonesondes, which is well within the combined uncertainties of the two measurement techniques. The few minor differences identified were typically associated with the known limitations of the lidars at the profile altitude extremes (i.e., first 1 km above ground and at the instruments' highest retrievable altitude). As part of a large homogenization and quality control effort within the network, many aspects of the TOLNet in-house data processing algorithms were also standardized and validated. This thorough validation of both the measurements and retrievals builds confidence as to the high quality and reliability of the TOLNet ozone lidar profiles for many years to come, making TOLNet a valuable ground-based reference network for tropospheric ozone profiling.

The Tropospheric Ozone Lidar Network (TOLNet) is a unique network of lidar systems that measure high-resolution atmospheric profiles of ozone. The accurate characterization of these lidars is necessary to determine the uniformity of the network calibration. From July to August 2014, three lidars, the TROPospheric OZone (TROPOZ) lidar, the Tunable Optical Profiler for Aerosol and oZone (TOPAZ) lidar, and the Langley Mobile Ozone Lidar (LMOL), of TOLNet participated in the Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) mission and the Front Range Air Pollution and Photochemistry Éxperiment (FRAPPÉ) to measure ozone variations from the boundary layer to the top of the troposphere. This study presents the analysis of the intercomparison between the TROPOZ, TOPAZ, and LMOL lidars, along with comparisons between the lidars and other in situ ozone instruments including ozonesondes and a P-3B airborne chemiluminescence sensor. The TOLNet lidars measured vertical ozone structures with an accuracy generally better than ±15 % within the troposphere. Larger differences occur at some individual altitudes in both the near-field and far-field range of the lidar systems, largely as expected. In terms of column average, the TOLNet lidars measured ozone with an accuracy better than ±5 % for both the intercomparison between the lidars and between the lidars and other instruments. These results indicate that these three TOLNet lidars are suitable for use in air quality, satellite validation, and ozone modeling efforts.

The main purpose of the NASA Goddard Space Flight Center TROPospheric OZone DIfferential Absorption Lidar (GSFC TROPOZ DIAL) is to measure the vertical distribution of tropospheric ozone for science investigations. Because of the important health and climate impacts of tropospheric ozone, it is imperative to quantify background photochemical ozone concentrations and ozone layers aloft, especially during air quality episodes. For these reasons, this paper addresses the necessary procedures to validate the TROPOZ retrieval algorithm and confirm that it is properly representing ozone concentrations. This paper is focused on ensuring the TROPOZ algorithm is properly quantifying ozone concentrations, and a following paper will focus on a systematic uncertainty analysis. This methodology begins by simulating synthetic lidar returns from actual TROPOZ lidar return signals in combination with a known ozone profile. From these synthetic signals, it is possible to explicitly determine retrieval algorithm biases from the known profile. This was then systematically performed to identify any areas that need refinement for a new operational version of the TROPOZ retrieval algorithm. One immediate outcome of this exercise was that a bin registration error in the correction for detector saturation within the original retrieval was discovered and was subsequently corrected for. Another noticeable outcome was that the vertical smoothing in the retrieval algorithm was upgraded from a constant vertical resolution to a variable vertical resolution to yield a statistical uncertainty of opt) has been effective in retrieving nearly 200 m lower to the surface. Also, as compared to the previous version of the retrieval, the TROPOZopt had an overall mean improvement of 3.5 %, and large improvements (upwards of 10–15 % as compared to the previous algorithm) were apparent between 4.5 and 9 km. Finally, to ensure the TROPOZopt retrieval algorithm is robust enough to handle actual lidar return signals, a comparison is shown between four nearby ozonesonde measurements. The ozonesondes are mostly within the TROPOZopt retrieval uncertainty bars, which implies that this exercise was quite successful.

Tropospheric ozone profiles have been retrieved from the new ground-based National Aeronautics and Space Administration (NASA) Goddard Space Flight Center TROPospheric OZone DIfferential Absorption Lidar (GSFC TROPOZ DIAL) in Greenbelt, MD (38.99° N, 76.84° W, 57 m a.s.l.), from 400 m to 12 km a.g.l. Current atmospheric satellite instruments cannot peer through the optically thick stratospheric ozone layer to remotely sense boundary layer tropospheric ozone. In order to monitor this lower ozone more effectively, the Tropospheric Ozone Lidar Network (TOLNet) has been developed, which currently consists of five stations across the US. The GSFC TROPOZ DIAL is based on the DIAL technique, which currently detects two wavelengths, 289 and 299 nm, with multiple receivers. The transmitted wavelengths are generated by focusing the output of a quadrupled Nd:YAG laser beam (266 nm) into a pair of Raman cells, filled with high-pressure hydrogen and deuterium, using helium as buffer gas. With the knowledge of the ozone absorption coefficient at these two wavelengths, the range-resolved number density can be derived. An interesting atmospheric case study involving the stratospheric–tropospheric exchange (STE) of ozone is shown, to emphasize the regional importance of this instrument as well as to assess the validation and calibration of data. There was a low amount of aerosol aloft, and an iterative aerosol correction has been performed on the retrieved data, which resulted in less than a 3 ppb correction to the final ozone concentration. The retrieval yields an uncertainty of 16–19% from 0 to 1.5 km, 10–18% from 1.5 to 3 km, and 11–25% from 3 to 12 km according to the relevant aerosol concentration aloft. There are currently surface ozone measurements hourly and ozonesonde launches occasionally, but this system will be the first to make routine tropospheric ozone profile measurements in the Baltimore–Washington, D.C. area.

MIPAS observations of temperature, water vapor, and ozone in October 2009 as derived with the scientific level-2 processor run by Karlsruhe Institute of Technology (KIT), Institute for Meteorology and Climate Research (IMK) and CSIC, Instituto de Astrofísica de Andalucía (IAA) and retrieved from version 4.67 level-1b data have been compared to co-located field campaign observations obtained during the MOHAVE-2009 campaign at the Table Mountain Facility near Pasadena, California in October 2009. The MIPAS measurements were validated regarding any potential biases of the profiles, and with respect to their precision estimates. The MOHAVE-2009 measurement campaign provided measurements of atmospheric profiles of temperature, water vapor/relative humidity, and ozone from the ground to the mesosphere by a suite of instruments including radiosondes, ozonesondes, frost point hygrometers, lidars, microwave radiometers and Fourier transform infra-red (FTIR) spectrometers. For MIPAS temperatures (version V4O_T_204), no significant bias was detected in the middle stratosphere; between 22 km and the tropopause MIPAS temperatures were found to be biased low by up to 2 K, while below the tropopause, they were found to be too high by the same amount. These findings confirm earlier comparisons of MIPAS temperatures to ECMWF data which revealed similar differences. Above 12 km up to 45 km, MIPAS water vapor (version V4O_H2O_203) is well within 10% of the data of all correlative instruments. The well-known dry bias of MIPAS water vapor above 50 km due to neglect of non-LTE effects in the current retrievals has been confirmed. Some instruments indicate that MIPAS water vapor might be biased high by 20 to 40% around 10 km (or 5 km below the tropopause), but a consistent picture from all comparisons could not be derived. MIPAS ozone (version V4O_O3_202) has a high bias of up to +0.9 ppmv around 37 km which is due to a non-identified continuum like radiance contribution. No further significant biases have been detected. Cross-comparison to co-located observations of other satellite instruments (Aura/MLS, ACE-FTS, AIRS) is provided as well.

Thirteen clear nights in October 2005 allowed successful intercomparison of the lidar operated since 1987 by the German Weather Service (DWD) at Hohenpeißenberg (47.8° N, 11.0° E) with the Network for the Detection of Atmospheric Composition Change (NDACC) travelling standard lidar operated by NASA's Goddard Space Flight Center. Both lidars provide ozone profiles in the stratosphere, and temperature profiles in the strato- and mesosphere. Additional ozone profiles came from on-site Brewer/Mast ozonesondes, additional temperature profiles from Vaisala RS92 radiosondes launched at Munich (65 km north-east), and from operational analyses by the US National Centers for Environmental Prediction (NCEP). The intercomparison confirmed a low bias for ozone from the DWD lidar in the 33 to 43 km region, by up to 10%. This bias is caused by the DWD ozone algorithm, and is consistent with previous comparisons of the DWD lidar with SAGE, GOMOS and other instruments. During HOPE, precision (repeatability) for ozone data from both lidars was better than 5% between 20 and 40 km altitude, dropping to 10% near 45 km, and to 50% near 50 km. These results are consistent with previous NDACC intercomparisons, and confirm the reliability of the NASA NDACC travelling standard lidar. Temperature from the DWD lidar showed a 1 to 2 K cold bias from 30 to 65 km against the NASA lidar, and a 2 to 4 K cold bias against radiosondes and NCEP. This is also consistent with previous intercomparisons. Temperature precision (repeatability) for the DWD lidar was better than 2 K from 30 to 50 km, decreasing to 10 K near 70 km. For the NASA lidar, precision is expected to be better than 1 K over the 30 to 70 km range. However, due to the much lower temperature precision of the DWD lidar, this could not be checked during HOPE. It was noted that the current DWD algorithm over-estimates temperature uncertainty, which should be reduced by a factor of 2.2 (e.g. from 22 K to 10 K near 70 km). The HOPE intercomparison did uncover a 290 m range error (upward shift) of the DWD lidar data. When this shift is removed, the bias of the ozone algorithm is corrected, and a better background estimation is used, ozone profiles from the DWD lidar agree very well with both the NASA lidar and SAGE. Systematic differences are then smaller than 3% between 20 and 44 km, and smaller than 5% between 17 and 47 km. These differences are close to zero, and are not (statistically) significant. The cold temperature bias against the NASA lidar also disappears when the DWD temperature processing is corrected for the 290 m range error, and more appropriate values for the Earth's gravity acceleration are used. Compared to the radiosondes or NCEP analyses, however, both lidars show 1 to 2 K lower temperatures over the entire 15 to 35 km range. Temperature and ozone variations are tracked well by both lidars, by ozone- and radiosondes, and by NCEP analyses. Correlations exceed 0.8 to 0.9 at most stratospheric levels. They decrease at levels above 40 km, especially for ozone or NCEP temperature. The ozone and temperature bias of the DWD lidar does not appear to have changed over time. Records of ozone and temperature from the DWD lidar should be consistent over the years. Nevertheless, the HOPE intercomparison was instrumental in uncovering and repairing several long-standing errors. HOPE also confirmed the reliability of the NASA lidar as a travelling standard. Now the entire DWD lidar data record needs to be reprocessed with the improved and revised algorithms.