Traditional validation of atmospheric profiles is based on the intercomparison of two or more data sets in predefined ranges or classes of a given observational characteristic such as latitude or solar zenith angle. In this study we trained a self-organising map (SOM) with a full time series of relative difference profiles of SCIAMACHY limb v5.02 and lidar ozone profiles from seven observation sites. Each individual observation characteristic was then mapped to the obtained SOM to investigate to which degree variation in this characteristic is explanatory for the variation seen in the SOM map. For the studied data sets, altitude-dependent relations for the global data set were found between the difference profiles and studied variables. From the lowest altitude studied (18 km) ascending, the most influencing factors were found to be longitude, followed by solar zenith angle and latitude, sensor age and again solar zenith angle together with the day of the year at the highest altitudes studied here (up to 45 km). After accounting for both latitude and longitude, residual partial correlations with a reduced magnitude are seen for various factors. However, (partial) correlations cannot point out which (combination) of the factors drives the observed differences between the ground-based and satellite ozone profiles as most of the factors are inter-related. Clustering into three classes showed that there are also some local dependencies, with for instance one cluster having a much stronger correlation with the sensor age (days since launch) between 36 and 42 km. The proposed SOM-based approach provides a powerful tool for the exploration of differences between data sets without being limited to a priori defined data subsets.

The Jet Propulsion Laboratory (JPL) lidars, at the Mauna Loa Observatory, Hawaii (MLO, 19.5° N, 155.6° W) and the JPL Table Mountain Facility (TMF, California, 34.5° N, 117.7° W), have been measuring vertical profiles of stratospheric ozone routinely since the early 1990's and late-1980s respectively. Interannual variability of ozone above these two sites was investigated using a multi-linear regression analysis on the deseasonalised monthly mean lidar and satellite time-series at 1 km intervals between 20 and 45 km from January 1995 to April 2011, a period of low volcanic aerosol loading. Explanatory variables representing the 11 yr solar cycle, the El Niño Southern Oscillation, the Quasi-Biennial Oscillation, the Eliassen-Palm flux, and horizontal and vertical transport were used. A new proxy, the mid-latitude Ozone Depleting Gas Index, which shows a decrease with time as an outcome of the Montreal Protocol, was introduced and compared to the more commonly used linear trend method. The analysis also compares the lidar time-series and a merged time-series obtained from the space-borne Stratospheric Aerosol and Gas Experiment II, Halogen Occultation Experiment, and Aura-Microwave Limb Sounder instruments. The results from both lidar and satellite measurements are consistent with recent model simulations which propose changes in tropical upwelling. Additionally, at TMF the Ozone Depleting Gas Index explains as much variance as the Quasi-Biennial Oscillation in the upper stratosphere. Over the past 17 yr a diminishing downward trend in ozone was observed before 2000 and a net increase, and sign of ozone recovery, is observed after 2005. Our results which include dynamical proxies suggest possible coupling between horizontal transport and the 11 yr solar cycle response, although a dataset spanning a period longer than one solar cycle is needed to confirm this result.

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.

Recognizing the importance of water vapor in the upper troposphere and lower stratosphere (UTLS) and the scarcity of high-quality, long-term measurements, JPL began the development of a powerful Raman lidar in 2005 to try to meet these needs. This development was endorsed by the Network for the Detection of Atmospheric Composition Change (NDACC) and the validation program for the EOS-Aura satellite. In this paper we review the stages in the instrumental development, data acquisition and analysis, profile retrieval and calibration procedures of the lidar, as well as selected results from three validation campaigns: MOHAVE (Measurements of Humidity in the Atmosphere and Validation Experiments), MOHAVE-II, and MOHAVE 2009.In particular, one critical result from this latest campaign is the very good agreement (well below the reported uncertainties) observed between the lidar and the Cryogenic Frost-Point Hygrometer in the entire lidar range 3–20 km, with a mean bias not exceeding 2% (lidar dry) in the lower troposphere, and 3% (lidar moist) in the UTLS. Ultimately the lidar has demonstrated capability to measure water vapor profiles from ∼1 km above the ground to the lower stratosphere with a precision of 10% or better near 13 km and below, and an estimated accuracy of 5%. Since 2005, nearly 1000 profiles have been routinely measured, and since 2009, the profiles have typically reached 14 km for one-hour integration times and 1.5 km vertical resolution, and can reach 21 km for 6-h integration times using degraded vertical resolutions.These performance figures show that, with our present target of routinely running our lidar two hours per night, 4 nights per week, we can achieve measurements with a precision in the UTLS equivalent to that achieved if launching one CFH per month.

The capability of the longest lidar data sets to monitor long-term temperature changes have been evaluated through comparisons with the successive Stratospheric Sounder Units (SSU) onboard NOAA satellites. Cross-consistency investigations between SSU and the lidar network can be considered as a first attempt to demonstrate how the synergistic use of space and ground-based instruments could provide reliable monitoring of the temperature of the middle atmosphere. The breakdown of the temperature cooling trend, and the following flattening observed in the satellite temperature series, is qualitatively confirmed by the lidars. However, there are still large differences that can either be due to SSU continuity (orbit drifts or weighting function modifications) or lidar operation changes (time of measurements, accuracy, sampling, etc.). SSU vertical weighting functions have been taken into account for comparisons. Some discontinuity events cannot be explained by the SSU weighting function drifts due to CO2. For the upper channels of SSU (peaking around 50km), the results are probably sensitive to the mesospheric part of the lidar profiles that can explain some discontinuities. Tropical lidar stations show clear inter-annual differences with the SSU channels covering the lowest altitude range that needs further investigations to understand if the origin is instrumental or geophysical. An attempt to derive non-linear trends with combinations of linear, hockey stick, and quadratic functions has been made. While the quadratic term is not highly significant, this approach allows the derivation of a better quantification of the linear trend terms.

The Measurements of Humidity in the Atmosphere and Validation Experiment (MOHAVE) 2009 campaign took place on 11-27 October 2009 at the JPL Table Mountain Facility in California (TMF). The main objectives of the campaign were to (1) validate the water vapor measurements of several instruments, including, three Raman lidars, two microwave radiometers, two Fourier-Transform spectrometers, and two GPS receivers (column water), (2) cover water vapor measurements from the ground to the mesopause without gaps, and (3) study upper tropospheric humidity variability at timescales varying from a few minutes to several days.A total of 58 radiosondes and 20 Frost-Point hygrometer sondes were launched. Two types of radiosondes were used during the campaign. Non negligible differences in the readings between the two radiosonde types used (Vaisala RS92 and InterMet iMet-1) made a small, but measurable impact on the derivation of water vapor mixing ratio by the Frost-Point hygrometers. As observed in previous campaigns, the RS92 humidity measurements remained within 5% of the Frost-point in the lower and mid-troposphere, but were too dry in the upper troposphere.Over 270 h of water vapor measurements from three Raman lidars (JPL and GSFC) were compared to RS92, CFH, and NOAA-FPH. The JPL lidar profiles reached 20 km when integrated all night, and 15 km when integrated for 1 h. Excellent agreement between this lidar and the frost-point hygrometers was found throughout the measurement range, with only a 3% (0.3 ppmv) mean wet bias for the lidar in the upper troposphere and lower stratosphere (UTLS). The other two lidars provided satisfactory results in the lower and mid-troposphere (2-5% wet bias over the range 3-10 km), but suffered from contamination by fluorescence (wet bias ranging from 5 to 50% between 10 km and 15 km), preventing their use as an independent measurement in the UTLS.The comparison between all available stratospheric sounders allowed to identify only the largest biases, in particular a 10% dry bias of the Water Vapor Millimeter-wave Spectrometer compared to the Aura-Microwave Limb Sounder. No other large, or at least statistically significant, biases could be observed.Total Precipitable Water (TPW) measurements from six different co-located instruments were available. Several retrieval groups provided their own TPW retrievals, resulting in the comparison of 10 different datasets. Agreement within 7% (0.7 mm) was found between all datasets. Such good agreement illustrates the maturity of these measurements and raises confidence levels for their use as an alternate or complementary source of calibration for the Raman lidars.Tropospheric and stratospheric ozone and temperature measurements were also available during the campaign. The water vapor and ozone lidar measurements, together with the advected potential vorticity results from the high-resolution transport model MIMOSA, allowed the identification and study of a deep stratospheric intrusion over TMF. These observations demonstrated the lidar strong potential for future long-term monitoring of water vapor in the UTLS.

The validation of ozone profiles retrieved by satellite instruments through comparison with data from ground-based instruments is important to monitor the evolution of the satellite instrument, to assist algorithm development and to allow multi-mission trend analyses.In this study we compare ozone profiles derived from GOMOS night-time observations with measurements from lidar, microwave radiometer and balloon sonde. Collocated pairs are analysed for dependence on several geophysical and instrument observational parameters. Validation results are presented for the operational ESA level 2 data (GOMOS version 5.00) obtained during nearly seven years of observations and a comparison using a smaller dataset from the previous processor (version 4.02) is also included.The profiles obtained from dark limb measurements (solar zenith angle >107°) when the provided processing flag is properly considered match the ground-based measurements within ±2 percent over the altitude range 20 to 40 km. Outside this range, the pairs start to deviate more and there is a latitudinal dependence: in the polar region where there is a higher amount of straylight contamination, differences start to occur lower in the mesosphere than in the tropics, whereas for the lower part of the stratosphere the opposite happens: the profiles in the tropics reach less far down as the signal reduces faster because of the higher altitude at which the maximum ozone concentration is found compared to the mid and polar latitudes. Also the bias is shifting from mostly negative in the polar region to more positive in the tropicsProfiles measured under "twilight" conditions are often matching the ground-based measurements very well, but care has to be taken in all cases when dealing with "straylight" contaminated profiles.For the selection criteria applied here (data within 800 km, 3 degrees in equivalent latitude, 20 h (5 h above 50 km) and a relative ozone error in the GOMOS data of 20% or less), no dependence was found on stellar magnitude, star temperature, nor the azimuth angle of the line of sight. No evidence of a temporal trend was seen either in the bias or frequency of outliers, but a comparison applying less strict data selection criteria might show differently.

In the lowermost layer of the atmosphere-the troposphere-ozone is an important source of the hydroxyl radical, an oxidant that breaks down most pollutants and some greenhouse gases. High concentrations of tropospheric ozone are toxic, however, and have a detrimental effect on human health and ecosystem productivity. Moreover, tropospheric ozone itself acts as an effective greenhouse gas. Much of the present tropospheric ozone burden is a consequence of anthropogenic emissions of ozone precursors resulting in widespread increases in ozone concentrations since the late 1800s. At present, east Asia has the fastest-growing ozone precursor emissions. Much of the springtime east Asian pollution is exported eastwards towards western North America. Despite evidence that the exported Asian pollution produces ozone, no previous study has found a significant increase in free tropospheric ozone concentrations above the western USA since measurements began in the late 1970s. Here we compile springtime ozone measurements from many different platforms across western North America. We show a strong increase in springtime ozone mixing ratios during 1995-2008 and we have some additional evidence that a similar rate of increase in ozone mixing ratio has occurred since 1984. We find that the rate of increase in ozone mixing ratio is greatest when measurements are more heavily influenced by direct transport from Asia. Our result agrees with previous modelling studies, which indicate that global ozone concentrations should be increasing during the early part of the twenty-first century as a result of increasing precursor emissions, especially at northern mid-latitudes, with western North America being particularly sensitive to rising Asian emissions. We suggest that the observed increase in springtime background ozone mixing ratio may hinder the USA's compliance with its ozone air quality standard.

This paper presents extensive {bias determination} analyses of ozone observations from the Atmospheric Chemistry Experiment (ACE) satellite instruments: the ACE Fourier Transform Spectrometer (ACE-FTS) and the Measurement of Aerosol Extinction in the Stratosphere and Troposphere Retrieved by Occultation (ACE-MAESTRO) instrument. Here we compare the latest ozone data products from ACE-FTS and ACE-MAESTRO with coincident observations from nearly 20 satellite-borne, airborne, balloon-borne and ground-based instruments, by analysing volume mixing ratio profiles and partial column densities. The ACE-FTS version 2.2 Ozone Update product reports more ozone than most correlative measurements from the upper troposphere to the lower mesosphere. At altitude levels from 16 to 44 km, the average values of the mean relative differences are nearly all within +1 to +8%. At higher altitudes (45–60 km), the ACE-FTS ozone amounts are significantly larger than those of the comparison instruments, with mean relative differences of up to +40% (about +20% on average). For the ACE-MAESTRO version 1.2 ozone data product, mean relative differences are within ±10% (average values within ±6%) between 18 and 40 km for both the sunrise and sunset measurements. At higher altitudes (~35–55 km), systematic biases of opposite sign are found between the ACE-MAESTRO sunrise and sunset observations. While ozone amounts derived from the ACE-MAESTRO sunrise occultation data are often smaller than the coincident observations (with mean relative differences down to −10%), the sunset occultation profiles for ACE-MAESTRO show results that are qualitatively similar to ACE-FTS, indicating a large positive bias (mean relative differences within +10 to +30%) in the 45–55 km altitude range. In contrast, there is no significant systematic difference in bias found for the ACE-FTS sunrise and sunset measurements.

The evolution of the aerosols in the tropical stratosphere since the beginning of the Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) mission in June 2006 is investigated using Cloud‐Aerosol Lidar with Orthogonal Polarization (CALIOP) lidar data. It is shown that the current operational calibration requires adjustment in the tropics. Indeed, on the basis of the assumption of pure Rayleigh scattering between 30 and 34 km the current calibration leads to an average underestimation of the scattering ratio by 6% because of the significant amount of aerosols up to 35 km altitude in the tropics, in contrast to midlatitudes. A better result is obtained by adjusting the calibration to higher altitudes, 36–39 km, where past Stratospheric Aerosol and Gas Experiment (SAGE) II extinction measurements showed an almost complete absence of aerosols. After recalibration the tropical stratospheric aerosol picture provided by CALIOP during the first 2 years of the mission reveals significant changes in the aerosol concentration associated with different transport processes. In the stratosphere the slow ascent of several volcanic layers and their meridional transport toward the subtropics are very consistent with the Brewer‐Dobson circulation. The near‐zero vertical velocity observed around 20 km during the Northern Hemisphere (NH) summer is in good agreement with radiative heating calculation. In the Tropical Tropopause Layer (TTL), weak depolarizing particles are observed during land convective periods, particularly intense over South Asia during the monsoon season. Finally, seasonal fast occurrence of apparent clean air in the TTL during the NH winter requires more investigations to understand its origin.

Satellite sensors provide global measurements of ozone concentration that can be used to study the effects of the implementation of the Montreal Protocol. However, a key issue in deriving long-term ozone trends from successive satellite instruments is inter-comparability. Ground-based measurements offer continuous time series, but only at a few locations. The combination of ground-based measurements with satellite data is therefore an effective means to evaluate satellite instrument inter-comparability. In this study, we present validation results of ozone profiles from three atmospheric sensors onboard ENVISAT by comparison with lidar measurements. Results for the SCIAMACHY ozone profiles (version 3.01) show reasonable agreement with ground-based measurements (0 to −20%). The MIPAS full-resolution (version 4.61) dataset has good agreement with lidar (0 to 10%), whereas a small positive bias (up to 20%) was found for the MIPAS reduced-resolution prototype data. GOMOS dark-limb data (version 5.00) agree very well (0 ± 5%) with the correlative data, but underestimate ozone concentration at the polar regions.

Upper stratospheric ozone anomalies from the satellite-borne Solar Backscatter Ultra-Violet (SBUV), Stratospheric Aerosol and Gas Experiment II (SAGE II), Halogen Occultation Experiment (HALOE), Global Ozone Monitoring by Occultation of Stars (GOMOS), and Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) instruments agree within 5% or better with ground-based data from lidars and microwave radiometers at five stations of the Network for the Detection of Atmospheric Composition Change (NDACC), from 45 degrees S to 48 degrees N. From 1979 until the late 1990s, all available data show a clear decline of ozone near 40 km, by 10%-15%. This decline has not continued in the last 10 years. At some sites, ozone at 40 km appears to have increased since 2000, consistent with the beginning decline of stratospheric chlorine. The phaseout of chlorofluorocarbons after the International Montreal Protocol in 1987 has been successful, and is now showing positive effects on ozone in the upper stratosphere. Temperature anomalies near 40 km altitude from European Centre for Medium Range Weather Forecast reanalyses (ERA-40), from National Centers for Environmental Prediction (NCEP) operational analyses, and from HALOE and lidar measurements show good consistency at the five stations, within about 3 K. Since about 1985, upper stratospheric temperatures have been fluctuating around a constant level at all five NDACC stations. This non-decline of upper stratospheric temperatures is a significant change from the more or less linear cooling of the upper stratosphere up until the mid-1990s, reported in previous trend assessments. It is also at odds with the almost linear 1 K per decade cooling simulated over the entire 1979-2010 period by chemistry-climate models (CCMs). The same CCM simulations, however, track the historical ozone anomalies quite well, including the change of ozone tendency in the late 1990s.

The Jet Propulsion Laboratory operates lidar systems at Table Mountain Facility (TMF), California (34.4°N, 117.7°W) and Mauna Loa Observatory, Hawaii (19.5°N, 155.6°W) under the framework of the Network for the Detection of Atmospheric Composition Change. To complement these systems a new Raman lidar has been developed at TMF with particular attention given to optimizing water vapor profile measurements up to the tropopause and lower stratosphere. The lidar has been designed for accuracies of 5% up to 12 km in the free troposphere and a detection capability of <5 ppmv. One important feature of the lidar is a precision alignment system using range resolved data from eight Licel transient recorders, allowing fully configurable alignment via a LABVIEW/C++ graphical user interface (GUI). This allows the lidar to be aligned on any channel while simultaneously displaying signals from other channels at configurable altitude/bin combinations. The general lidar instrumental setup and the details of the alignment control system, data acquisition, and GUI alignment software are described. Preliminary validation results using radiosonde and lidar intercomparisons are briefly presented.

The Measurements of Humidity in the Atmosphere and Validation Experiments (MOHAVE, MOHAVE-II) inter-comparison campaigns took place at the Jet Propulsion Laboratory (JPL) Table Mountain Facility (TMF, 34.5ºN) in October 2006 and 2007 respectively. Both campaigns aimed at evaluating the capability of three Raman lidars for the measurement of water vapor in the upper troposphere and lower stratosphere (UT/LS). During each campaign, more than 200 hours of lidar measurements were compared to balloon borne measurements obtained from 10 Cryogenic Frost-point Hygrometer (CFH) flights and over 50 Vaisala RS92 radiosonde flights. During MOHAVE, fluorescence in all three lidar receivers was identified, causing a significant wet bias above 10-12 km in the lidar profiles as compared to the CFH. All three lidars were reconfigured after MOHAVE, and no such bias was observed during the MOHAVE-II campaign. The lidar profiles agreed very well with the CFH up to 13-17 km altitude, where the lidar measurements become noise limited. The results from MOHAVE-II have shown that the water vapor Raman lidar will be an appropriate technique for the long-term monitoring of water vapor in the UT/LS given a slight increase in its power- aperture, as well as careful calibration.

An ensemble of space-borne and ground-based instruments has been used to evaluate the quality of the version 2.2 temperature retrievals from the Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS). The agreement of ACE-FTS temperatures with other sensors is typically better than 2 K in the stratosphere and upper troposphere and 5 K in the lower mesosphere. There is evidence of a systematic high bias (roughly 3–6 K) in the ACE-FTS temperatures in the mesosphere, and a possible systematic low bias (roughly 2 K) in ACE-FTS temperatures near 23 km. Some ACE-FTS temperature profiles exhibit unphysical oscillations, a problem fixed in preliminary comparisons with temperatures derived using the next version of the ACE-FTS retrieval software. Though these relatively large oscillations in temperature can be on the order of 10 K in the mesosphere, retrieved volume mixing ratio profiles typically vary by less than a percent or so. Statistical comparisons suggest these oscillations occur in about 10% of the retrieved profiles. Analysis from a set of coincident lidar measurements suggests that the random error in ACE-FTS version 2.2 temperatures has a lower limit of about ±2 K.

Extreme pyrocumulonimbus (pyroCb) blowups that pollute the stratosphere have been documented on at least five occasions. However, the frequency of these events is still uncertain. One published pyroCb case study, the Chisholm Fire in May 2001, was restricted to the convective phase and its immediate aftermath. Here and in a companion paper we describe the stratospheric impact of the Chisholm pyroCb. The companion paper focuses on nadir satellite views of the plume. This paper synthesizes a broad array of space‐, balloon‐, and ground‐based profile measurements. The Chisholm pyroCb, which we identify as the singular cause of stratospheric aerosol increase in northern spring/summer of 2001, created a doubling of the zonal average aerosol optical depth in the lowermost stratosphere. The meridional spread of the plume was from the tropics (20°N) to the high Arctic (79°N) within the first month. The stratospheric Chisholm smoke became a hemispheric phenomenon in midlatitudes and northern tropics and persisted for at least 3 months. A size‐resolved particle concentration profile over Laramie, Wyoming, indicated a lower stratospheric aerosol with a twofold to threefold increase in volume of particles with radii between 0.3 and 0.6 μm. We also find evidence of localized warming in the air masses of four of the lidar‐measured smoke layers. This work contains the first reported stratospheric smoke layers measured by lidar at Ny Ålesund, Esrange, Kühlungsborn, Garmisch‐Partenkirchen, Boulder, and Mauna Loa. In addition, the first detection of smoke‐enhanced aerosol extinction at near IR wavelengths by the Halogen Occultation Experiment (HALOE) is introduced.

The Michelson Interferometer for Passive Atmospheric Sounding (MIPAS), on-board the European ENVIronmental SATellite (ENVISAT) launched on 1 March 2002, is a middle infrared Fourier Transform spectrometer measuring the atmospheric emission spectrum in limb sounding geometry. The instrument is capable to retrieve the vertical distribution of temperature and trace gases, aiming at the study of climate and atmospheric chemistry and dynamics, and at applications to data assimilation and weather forecasting. MIPAS operated in its standard observation mode for approximately two years, from July 2002 to March 2004, with scans performed at nominal spectral resolution of 0.025 cm−1 and covering the altitude range from the mesosphere to the upper troposphere with relatively high vertical resolution (about 3 km in the stratosphere). Only reduced spectral resolution measurements have been performed subsequently. MIPAS data were re-processed by ESA using updated versions of the Instrument Processing Facility (IPF v4.61 and v4.62) and provided a complete set of level-2 operational products (geo-located vertical profiles of temperature and volume mixing ratio of H2O, O3, HNO3, CH4, N2O and NO2) with quasi continuous and global coverage in the period of MIPAS full spectral resolution mission. In this paper, we report a detailed description of the validation of MIPAS-ENVISAT operational ozone data, that was based on the comparison between MIPAS v4.61 (and, to a lesser extent, v4.62) O3 VMR profiles and a comprehensive set of correlative data, including observations from ozone sondes, ground-based lidar, FTIR and microwave radiometers, remote-sensing and in situ instruments on-board stratospheric aircraft and balloons, concurrent satellite sensors and ozone fields assimilated by the European Center for Medium-range Weather Forecasting.A coordinated effort was carried out, using common criteria for the selection of individual validation data sets, and similar methods for the comparisons. This enabled merging the individual results from a variety of independent reference measurements of proven quality (i.e. well characterized error budget) into an overall evaluation of MIPAS O3 data quality, having both statistical strength and the widest spatial and temporal coverage. Collocated measurements from ozone sondes and ground-based lidar and microwave radiometers of the Network for the Detection Atmospheric Composition Change (NDACC) were selected to carry out comparisons with time series of MIPAS O3 partial columns and to identify groups of stations and time periods with a uniform pattern of ozone differences, that were subsequently used for a vertically resolved statistical analysis. The results of the comparison are classified according to synoptic and regional systems and to altitude intervals, showing a generally good agreement within the comparison error bars in the upper and middle stratosphere. Significant differences emerge in the lower stratosphere and are only partly explained by the larger contributions of horizontal and vertical smoothing differences and of collocation errors to the total uncertainty. Further results obtained from a purely statistical analysis of the same data set from NDACC ground-based lidar stations, as well as from additional ozone soundings at middle latitudes and from NDACC ground-based FTIR measurements, confirm the validity of MIPAS O3 profiles down to the lower stratosphere, with evidence of larger discrepancies at the lowest altitudes. The validation against O3 VMR profiles using collocated observations performed by other satellite sensors (SAGE II, POAM III, ODIN-SMR, ACE-FTS, HALOE, GOME) and ECMWF assimilated ozone fields leads to consistent results, that are to a great extent compatible with those obtained from the comparison with ground-based measurements. Excellent agreement in the full vertical range of the comparison is shown with respect to collocated ozone data from stratospheric aircraft and balloon instruments, that was mostly obtained in very good spatial and temporal coincidence with MIPAS scans. This might suggest that the larger differences observed in the upper troposphere and lowermost stratosphere with respect to collocated ground-based and satellite O3 data are only partly due to a degradation of MIPAS data quality. They should be rather largely ascribed to the natural variability of these altitude regions and to other components of the comparison errors. By combining the results of this large number of validation data sets we derived a general assessment of MIPAS v4.61 and v4.62 ozone data quality.A clear indication of the validity of MIPAS O3 vertical profiles is obtained for most of the stratosphere, where the mean relative difference with the individual correlative data sets is always lower than ±10%. Furthermore, these differences always fall within the combined systematic error (from 1 hPa to 50 hPa) and the standard deviation is fully consistent with the random error of the comparison (from 1 hPa to ~30–40 hPa). A degradation in the quality of the agreement is generally observed in the lower stratosphere and upper troposphere, with biases up to 25% at 100 hPa and standard deviation of the global mean differences up to three times larger than the combined random error in the range 50–100 hPa. The larger differences observed at the bottom end of MIPAS retrieved profiles can be associated, as already noticed, to the effects of stronger atmospheric gradients in the UTLS that are perceived differently by the various measurement techniques. However, further components that may degrade the results of the comparison at lower altitudes can be identified as potentially including cloud contamination, which is likely not to have been fully filtered using the current settings of the MIPAS cloud detection algorithm, and in the linear approximation of the forward model that was used for the a priori estimate of systematic error components. The latter, when affecting systematic contributions with a random variability over the spatial and temporal scales of global averages, might result in an underestimation of the random error of the comparison and add up to other error sources, such as the possible underestimates of the p and T error propagation based on the assumption of a 1 K and 2% uncertainties, respectively, on MIPAS temperature and pressure retrievals.At pressure lower than 1 hPa, only a small fraction of the selected validation data set provides correlative ozone data of adequate quality and it is difficult to derive quantitative conclusions about the performance of MIPAS O3 retrieval for the topmost layers.

We present validation studies of MLS version 2.2 upper tropospheric and stratospheric ozone profiles using ozonesonde and lidar data as well as climatological data. Ozone measurements from over 60 ozonesonde stations worldwide and three lidar stations are compared with coincident MLS data. The MLS ozone stratospheric data between 150 and 3 hPa agree well with ozonesonde measurements, within 8% for the global average. MLS values at 215 hPa are biased high compared to ozonesondes by ∼20% at middle to high latitude, although there is a lot of variability in this altitude region. Comparisons between MLS and ground‐based lidar measurements from Mauna Loa, Hawaii, from the Table Mountain Facility, California, and from the Observatoire de Haute‐Provence, France, give very good agreement, within ∼5%, for the stratospheric values. The comparisons between MLS and the Table Mountain Facility tropospheric ozone lidar show that MLS data are biased high by ∼30% at 215 hPa, consistent with that indicated by the ozonesonde data. We obtain better global average agreement between MLS and ozonesonde partial column values down to 215 hPa, although the average MLS values at low to middle latitudes are higher than the ozonesonde values by up to a few percent. MLS v2.2 ozone data agree better than the MLS v1.5 data with ozonesonde and lidar measurements. MLS tropical data show the wave one longitudinal pattern in the upper troposphere, with similarities to the average distribution from ozonesondes. High upper tropospheric ozone values are also observed by MLS in the tropical Pacific from June to November.