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We describe the change in operational instrument for the routine measurement of column-averaged dry-air mole fraction of several greenhouse gases (denoted Xgas) at the Lauder Total Carbon Column Observing Network (TCCON) site and the steps taken to demonstrate comparability between the two observation systems following a systematic methodology. Further, we intercompare retrieved Xgas values during an intensive intercomparison period during October and November 2018, when both instruments were performing optimally, and on subsequent, less frequent occasions. The average difference between the two observing systems was found to be well below the expected level of uncertainty for TCCON retrievals for all compared species. In the case of XCO2 the average difference was 0.0264±0.0465 % (0.11±0.19 µmol mol−1).

While the Montreal Protocol is reducing stratospheric ozone loss, recent increases in some ozone depleting substance (ODS) emissions have been identified that may impact southern hemisphere climate systems. In this study, we discuss characteristics of the 2018 and 2019 Antarctic ozone holes using surface in situ, satellite and reanalysis data to gain a better understanding of recent ozone variability. These ozone holes had strongly contrasting characteristics. In 2018, the Antarctic stratospheric vortex was relatively stable and cold in comparison to most years of the prior decade. This resulted in a large and persistent ozone hole that ranked in the upper-tercile of metrics quantifying Antarctic ozone depletion. In contrast, strong stratospheric warming in the spring of 2019 curtailed the development of the ozone hole, causing it to be anomalously small and of similar size to ozone holes in the 1980s. As known from previous studies, the ability of planetary waves to propagate into the stratosphere at high latitudes is an important factor that influences temperatures of the polar vortex and the overall amount of ozone loss in any particular year. Disturbance and warming of the vortex by strong planetary wave activity were the dominant factors in the small 2019 ozone hole. In contrast, planetary wave disturbances to the vortex in the winter–spring of 2018 were much weaker than in 2019. These results increase our understanding of the impact of Montreal Protocol controls on ODS and the effects of Antarctic ozone on the southern hemisphere climate system.

The historically large and severe wildfires in Australia from September 2019 to March 2020 are known to have injected a smoke plume into the stratosphere around New Year, due to pyro-cumulonimbus (pyro-Cb) activity, that was subsequently distributed throughout the Southern Hemisphere (SH). We show with satellite, ground based remote sensing, and in situ observations that the fires before New Year, had already a substantial impact on the SH atmosphere, starting as early as September 2019, with subsequent long-range transport of trace gas plumes in the upper-troposphere. Airborne in situ measurements above Southern Argentina in November 2019 show elevated CO mixing ratios at an altitude of 11 km and can be traced back using FLEXPART trajectories to the Australian fires in mid-November 2019. Ground based solar-FTS (Fourier Transform Spectroscopy) observations of biomass burning tracers CO, HCN and C2H6 at Lauder, South Island, New Zealand show enhanced tropospheric columns already starting in September 2019. In MLS observations averaged over 30°–60°S, enhanced CO mixing ratios compared to previous years become visible in late October 2019 only at and below the 147 hPa pressure level. Peak differences are found with satellite and ground-based observations for all altitude levels in the Southern Hemisphere in January. With still increased aerosol values following the Ulawun eruption in 2019, averaged satellite observations show no clear stratospheric and upper-tropospheric aerosol enhancements from the Australian fires, before the pyro-Cb events at the end of December 2019. However, with the clear enhancement of fire tracers, we suggest the period September to December 2019 (prior to the major pyro-Cb events) should be taken into account in terms of fire pollutant emissions when studying the impact of the Australian fires on the SH atmosphere.

Column-averaged dry-air mole fraction of CO (XCO) measurements are obtained from two ground-based Fourier transform infrared (FTIR) spectrometer networks: the Total Carbon Column Observing Network (TCCON) and the Network for the Detection of Atmospheric Composition Change (NDACC). In this study, the differences between the TCCON and NDACC XCO measurements are investigated and discussed based on six NDACC–TCCON sites using data over the period 2007–2017. A direct comparison shows that the NDACC XCO measurements are about 5.5 % larger than the TCCON data at Ny-Ålesund, Bremen, and Izaña (Northern Hemisphere), and the absolute bias between the NDACC and TCCON data is within 2 % at Saint-Denis, Wollongong and Lauder (Southern Hemisphere). The hemispheric dependence of the bias is mainly attributed to their smoothing errors. The systematic smoothing error of the TCCON XCO data varies in the range between 0.2 % (Bremen) and 7.9 % (Lauder), and the random smoothing error varies in the range between 2.0 % and 3.6 %. The systematic smoothing error of NDACC data is between 0.1 % and 0.8 %, and the random smoothing error of NDACC data is about 0.3 %. For TCCON data, the smoothing error is significant because it is higher than the reported uncertainty, particularly at Southern Hemisphere sites. To reduce the influence from the a priori profiles and different vertical sensitivities, the scaled NDACC a priori profiles are used as the common a priori profiles for comparing TCCON and NDACC retrievals. As a result, the biases between TCCON and NDACC XCO measurements become more consistent (5.6 %–8.5 %) with a mean value of 6.8 % at these sites. To determine the sources of the remaining bias, regular AirCore measurements at Orléans and Sodankylä are compared to co-located TCCON measurements. It is found that TCCON XCO measurements are 6.1 ± 1.6 % and 8.0 ± 3.2 % smaller than the AirCore measurements at Orléans and Sodankylä, respectively, indicating that the scaling factor of TCCON XCO data should be around 1.0000 instead of 1.0672. Further investigations should be carried out in the TCCON community to determine the correct scaling factor to be applied to the TCCON XCO data. This paper also demonstrates that the smoothing error must be taken into account when comparing FTIR XCO data, and especially TCCON XCO data, with model or satellite data.

The Sentinel-5 Precursor (S5P) mission with the TROPOspheric Monitoring Instrument (TROPOMI) onboard has been measuring solar radiation backscattered by the Earth's atmosphere and its surface since its launch on 13 October 2017. Methane (CH4) and carbon monoxide (CO) data with a spatial resolution (initially 7 x 7 km2, upgraded to 5.5 x 7 km2 on 6th of August 2019) have been retrieved from shortwave infrared (SWIR) and near-infrared (NIR) measurements since the end of November 2017 and made available to the experts for early validation and quality checks before the official product release. In this paper, we present for the first time the S5P CH4 and CO validation results (covering a period from November 2017 to September 2020) using global Total Carbon Column Observing Network (TCCON) and Infrared Working Group of the Network for the Detection of Atmospheric Composition Change (NDACC-IRWG) network data, accounting for a priori alignment and smoothing uncertainties in the validation, and testing the sensitivity of validation results towards the application of advanced co-location criteria.We found that the required bias (systematic error) of 1.5 % and random error of 1 % for the S5P standard and bias-corrected methane data are met for measurements over land surfaces with pixels having quality assurance (QA) value > 0.5. The systematic difference between the S5P standard XCH4 and TCCON data is on average −0.69 ± 0.73 %. The systematic difference changes to a value of −0.25 ± 0.57 % for the S5P bias-corrected XCH4 data. We found a correlation of above 0.6 for most stations, which is mostly dominated by the seasonal cycle. The contributions of smoothing uncertainty at the individual stations are estimated and found to be dependent on the location. The highest contribution of the smoothing uncertainty is observed for mid-latitude TCCON stations and high latitude stations for NDACC. A seasonal dependency of the relative bias is seen. We observe a high bias during the springtime measurements at high SZA and a decreasing bias with increasing SZA for the rest of the year.We found that the required bias (systematic error) of 15 % and random error of < 10 % for the S5P carbon monoxide data are met in general for measurements over all surfaces with pixels having quality assurance value of > 0.5. There are a few stations where this is not the case, mostly due to co-location mismatches and the limited availability of co-located data. We compared the S5P XCO data with respect to standard TCCON XCO and unscaled TCCON XCO (without application of the empirical scaling factor) data sets. The systematic difference between the S5P XCO and the TCCON data is on average 9.14 ± 3.33 % (standard TCCON XCO data) and 2.36 ± 3.22 % (unscaled TCCON XCO data). We found that the systematic difference between the S5P CO column and NDACC CO column data (excluding two stations that were obvious outliers) is on average 6.44 ± 3.79 %. We found a correlation of above 0.9 for most TCCON and NDACC stations indicating that the temporal variations in CO column captured by the ground-based instruments are reproduced very similarly by the S5P CO column. The contribution of smoothing uncertainty at the individual stations is estimated and found to be significant. They are found to be dependent on the location with large changes seen for stations located in the Southern Hemisphere as compared to the Northern Hemisphere and at highly polluted stations. A cone co-location criterion, which gives a better match between the ground-based instrument's line-of-sight and satellite pixels, seems to give better results for high latitude stations and stations located close to emission sources. The validation results for the clear-sky and cloud cases of S5P pixels are comparable to the validation results including all pixels with quality assurance value of > 0.5. We observe that the relative bias increases with increasing SZA. We estimated this increase is about 10 % over the complete range of measurement SZAs.The study shows the high quality of S5P CH4 and CO data by validating the products against reference global TCCON and NDACC stations covering a wide range of latitudinal bands, atmospheric conditions, and surface conditions.

Solar trackers are often used by spectrometers to measure atmospheric trace gas concentrations using direct sun spectroscopy. The ideal solar tracker should be sufficiently accurate, highly reliable, and with a longevity that exceeds the lifetime of the spectrometer that it serves. It should also be affordable, easy to use, and not too complex should maintenance be required. In this paper we present a design that fulfils these requirements using some simple innovations. Our altitude–azimuth design features a custom coaxial power transformer, enabling continuous 360∘ azimuth rotation. This increases reliability and avoids the need to reverse the tracker each day. In polar regions, measurements can continue uninterrupted through the summer polar day. Tracking accuracy is enhanced using a simple optical feedback technique that adjusts error offset variables while monitoring the edges of a focused solar image with four photodiodes. Control electronics are modular, and our software is written in Python, running as a web server on a recycled laptop with a Linux operating system. Over a period of 11 years we have assembled four such trackers. These are in use at Lauder (45∘ S), New Zealand, and Arrival Heights (78∘ S), Antarctica, achieving a history of good reliability even in polar conditions. Tracker accuracy is analysed regularly and can routinely produce a pointing accuracy of 0.02∘.

We describe the change of operational instrument for the routine measurement of column-averaged dry-air mole fraction of several greenhouse gases (denoted Xgas) at the Lauder Total Carbon Column Observing Network (TCCON) site and the steps taken to demonstrate comparability between the two observation systems following a systematic methodology. Further, we intercompare retrieved Xgas values during an intensive intercomparison period during October and November 2018, when both instruments were performing optimally, and on subsequent, less frequent occasions. The average difference between the two observing systems was found to be well below the expected level of uncertainty for TCCON retrievals for all compared species. In the case of XCO2 the average difference was 0.0264 ± 0.0465 % (0.11 ± 0.19 μmol mol−1).

TROPOMI (the TROPOspheric Monitoring Instrument), on board the Sentinel-5 Precursor (S5P) satellite, has been monitoring the Earth's atmosphere since October 2017 with an unprecedented horizontal resolution (initially 7 km2×3.5 km2, upgraded to 5.5 km2×3.5 km2 in August 2019). Monitoring air quality is one of the main objectives of TROPOMI; it obtains measurements of important pollutants such as nitrogen dioxide, carbon monoxide, and formaldehyde (HCHO). In this paper we assess the quality of the latest HCHO TROPOMI products versions 1.1.(5-7), using ground-based solar-absorption FTIR (Fourier-transform infrared) measurements of HCHO from 25 stations around the world, including high-, mid-, and low-latitude sites. Most of these stations are part of the Network for the Detection of Atmospheric Composition Change (NDACC), and they provide a wide range of observation conditions, from very clean remote sites to those with high HCHO levels from anthropogenic or biogenic emissions. The ground-based HCHO retrieval settings have been optimized and harmonized at all the stations, ensuring a consistent validation among the sites. In this validation work, we first assess the accuracy of TROPOMI HCHO tropospheric columns using the median of the relative differences between TROPOMI and FTIR ground-based data (BIAS). The pre-launch accuracy requirements of TROPOMI HCHO are 40 %–80 %. We observe that these requirements are well reached, with the BIAS found below 80 % at all the sites and below 40 % at 20 of the 25 sites. The provided TROPOMI systematic uncertainties are well in agreement with the observed biases at most of the stations except for the highest-HCHO-level site, where it is found to be underestimated. We find that while the BIAS has no latitudinal dependence, it is dependent on the HCHO concentration levels: an overestimation (+26±5 %) of TROPOMI is observed for very low HCHO levels (<2.5×1015 molec. cm−2), while an underestimation (-30.8%±1.4 %) is found for high HCHO levels (>8.0×1015 molec. cm−2). This demonstrates the great value of such a harmonized network covering a wide range of concentration levels, the sites with high HCHO concentrations being crucial for the determination of the satellite bias in the regions of emissions and the clean sites allowing a small TROPOMI offset to be determined. The wide range of sampled HCHO levels within the network allows the robust determination of the significant constant and proportional TROPOMI HCHO biases (TROPOMI =+1.10±0.05 ×1015+0.64±0.03 × FTIR; in molecules per square centimetre). Second, the precision of TROPOMI HCHO data is estimated by the median absolute deviation (MAD) of the relative differences between TROPOMI and FTIR ground-based data. The clean sites are especially useful for minimizing a possible additional collocation error. The precision requirement of 1.2×1016 molec. cm−2 for a single pixel is reached at most of the clean sites, where it is found that the TROPOMI precision can even be 2 times better (0.5–0.8×1015 molec. cm−2 for a single pixel). However, we find that the provided TROPOMI random uncertainties may be underestimated by a factor of 1.6 (for clean sites) to 2.3 (for high HCHO levels). The correlation is very good between TROPOMI and FTIR data (R=0.88 for 3 h mean coincidences; R=0.91 for monthly means coincidences). Using about 17 months of data (from May 2018 to September 2019), we show that the TROPOMI seasonal variability is in very good agreement at all of the FTIR sites. The FTIR network demonstrates the very good quality of the TROPOMI HCHO products, which is well within the pre-launch requirements for both accuracy and precision. This paper makes suggestions for the refinement of the TROPOMI random uncertainty budget and TROPOMI quality assurance values for a better filtering of the remaining outliers.

The El Niño–Southern Oscillation (ENSO) has been suggested as a strong forcing in the methane cycle and as a driver of recent trends in global atmospheric methane mole fractions [CH4]. Such a sensitivity of the global CH4 budget to climate events would have important repercussions for climate change mitigation strategies and the accuracy of projections for future greenhouse forcing. Here, we test the impact of ENSO on atmospheric CH4 in a correlation analysis. We use local and global records of [CH4], as well as stable carbon isotopic records of atmospheric CH4 (δ13CH4), which are particularly sensitive to the combined ENSO effects on CH4 production from wetlands and biomass burning. We use a variety of nominal, smoothed, and detrended time series including growth rate records. We find that at most 36 % of the variability in [CH4] and δ13CH4 is attributable to ENSO, but only for detrended records in the southern tropics. Trend-bearing records from the southern tropics, as well as all studied hemispheric and global records, show a minor impact of ENSO, i.e. CH4 production that responds less to ENSO than previously suggested. Dynamics of the removal by hydroxyl likely counteract the variation in emissions, but the expected isotope signal is not evident. It is possible that other processes obscure the ENSO signal, which itself indicates a minor influence of the latter on global CH4 emissions. Trends like the recent rise in atmospheric [CH4] can therefore not be attributed to ENSO. This leaves anthropogenic methane sources as the likely driver, which must be mitigated to reduce anthropogenic climate change.

Among the more than 20 ground-based FTIR (Fourier transform infrared) stations currently operating around the globe, only a few have provided formaldehyde (HCHO) total column time series until now. Although several independent studies have shown that the FTIR measurements can provide formaldehyde total columns with good precision, the spatial coverage has not been optimal for providing good diagnostics for satellite or model validation. Furthermore, these past studies used different retrieval settings, and biases as large as 50 % can be observed in the HCHO total columns depending on these retrieval choices, which is also a weakness for validation studies combining data from different ground-based stations.For the present work, the HCHO retrieval settings have been optimized based on experience gained from past studies and have been applied consistently at the 21 participating stations. Most of them are either part of the Network for the Detection of Atmospheric Composition Change (NDACC) or under consideration for membership. We provide the harmonized settings and a characterization of the HCHO FTIR products. Depending on the station, the total systematic and random uncertainties of an individual HCHO total column measurement lie between 12 % and 27 % and between 1 and 11×1014 molec cm−2, respectively. The median values among all stations are 13 % and 2.9×1014 molec cm−2 for the total systematic and random uncertainties.This unprecedented harmonized formaldehyde data set from 21 ground-based FTIR stations is presented and its comparison with a global chemistry transport model shows consistency in absolute values as well as in seasonal cycles. The network covers very different concentration levels of formaldehyde, from very clean levels at the limit of detection (few 1013 molec cm−2) to highly polluted levels (7×1016 molec cm−2). Because the measurements can be made at any time during daylight, the diurnal cycle can be observed and is found to be significant at many stations. These HCHO time series, some of them starting in the 1990s, are crucial for past and present satellite validation and will be extended in the coming years for the next generation of satellite missions.

Presented here is the validation of the CrIS (Cross-track Infrared Sounder) fast physical NH3 retrieval (CFPR) column and profile measurements using ground-based Fourier transform infrared (FTIR) observations. We use the total columns and profiles from seven FTIR sites in the Network for the Detection of Atmospheric Composition Change (NDACC) to validate the satellite data products. The overall FTIR and CrIS total columns have a positive correlation of r = 0.77 (N = 218) with very little bias (a slope of 1.02). Binning the comparisons by total column amounts, for concentrations larger than 1.0 × 1016 molecules cm−2, i.e. ranging from moderate to polluted conditions, the relative difference is on average ∼ 0–5 % with a standard deviation of 25–50 %, which is comparable to the estimated retrieval uncertainties in both CrIS and the FTIR. For the smallest total column range (

We report on the ground-based FTIR (Fourier transform infrared) tropospheric water vapour isotopologue remote sensing data that have been recently made available via the database of NDACC (Network for the Detection of Atmospheric Composition Change; ftp://ftp.cpc.ncep.noaa.gov/ndacc/MUSICA/) and via doi:10.5281/zenodo.48902. Currently, data are available for 12 globally distributed stations. They have been centrally retrieved and quality-filtered in the framework of the MUSICA project (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water). We explain particularities of retrieving the water vapour isotopologue state (vertical distribution of H216O, H218O, and HD16O) and reveal the need for a new metadata template for archiving FTIR isotopologue data. We describe the format of different data components and give recommendations for correct data usage. Data are provided as two data types. The first type is best-suited for tropospheric water vapour distribution studies disregarding different isotopologues (comparison with radiosonde data, analyses of water vapour variability and trends, etc.). The second type is needed for analysing moisture pathways by means of H2O, δD-pair distributions.

A regional atmospheric inversion method has been developed to determine the spatial and temporal distribution of CO2 sinks and sources across New Zealand for 2011–2013. This approach infers net air–sea and air–land CO2 fluxes from measurement records, using back-trajectory simulations from the Numerical Atmospheric dispersion Modelling Environment (NAME) Lagrangian dispersion model, driven by meteorology from the New Zealand Limited Area Model (NZLAM) weather prediction model. The inversion uses in situ measurements from two fixed sites, Baring Head on the southern tip of New Zealand's North Island (41.408° S, 174.871° E) and Lauder from the central South Island (45.038° S, 169.684° E), and ship board data from monthly cruises between Japan, New Zealand, and Australia. A range of scenarios is used to assess the sensitivity of the inversion method to underlying assumptions and to ensure robustness of the results. The results indicate a strong seasonal cycle in terrestrial land fluxes from the South Island of New Zealand, especially in western regions covered by indigenous forest, suggesting higher photosynthetic and respiratory activity than is evident in the current a priori land process model. On the annual scale, the terrestrial biosphere in New Zealand is estimated to be a net CO2 sink, removing 98 (±37) Tg CO2 yr−1 from the atmosphere on average during 2011–2013. This sink is much larger than the reported 27 Tg CO2 yr−1 from the national inventory for the same time period. The difference can be partially reconciled when factors related to forest and agricultural management and exports, fossil fuel emission estimates, hydrologic fluxes, and soil carbon change are considered, but some differences are likely to remain. Baseline uncertainty, model transport uncertainty, and limited sensitivity to the northern half of the North Island are the main contributors to flux uncertainty.

Nitrous oxide (N2O) is an important greenhouse gas and it can also generate nitric oxide, which depletes ozone in the stratosphere. It is a common target species of ground-based Fourier transform infrared (FTIR) near-infrared (TCCON) and mid-infrared (NDACC) measurements. Both TCCON and NDACC networks provide a long-term global distribution of atmospheric N2O mole fraction. In this study, the dry-air column-averaged mole fractions of N2O (XN2O) from the TCCON and NDACC measurements are compared against each other at seven sites around the world (Ny-Ålesund, Sodankylä, Bremen, Izaña, Réunion, Wollongong, Lauder) in the time period of 2007–2017. The mean differences in XN2O between TCCON and NDACC (NDACC–TCCON) at these sites are between −3.32 and 1.37 ppb (−1.1 %–0.5 %) with standard deviations between 1.69 and 5.01 ppb (0.5 %–1.6 %), which are within the uncertainties of the two datasets. The NDACC N2O retrieval has good sensitivity throughout the troposphere and stratosphere, while the TCCON retrieval underestimates a deviation from the a priori in the troposphere and overestimates it in the stratosphere. As a result, the TCCON XN2O measurement is strongly affected by its a priori profile. Trends and seasonal cycles of XN2O are derived from the TCCON and NDACC measurements and the nearby surface flask sample measurements and compared with the results from GEOS-Chem model a priori and a posteriori simulations. The trends and seasonal cycles from FTIR measurement at Ny-Ålesund and Sodankylä are strongly affected by the polar winter and the polar vortex. The a posteriori N2O fluxes in the model are optimized based on surface N2O measurements with a 4D-Var inversion method. The XN2O trends from the GEOS-Chem a posteriori simulation (0.97±0.02 (1σ) ppb yr−1) are close to those from the NDACC (0.93±0.04 ppb yr−1) and the surface flask sample measurements (0.93±0.02 ppb yr−1). The XN2O trend from the TCCON measurements is slightly lower (0.81±0.04 ppb yr−1) due to the underestimation of the trend in TCCON a priori simulation. The XN2O trends from the GEOS-Chem a priori simulation are about 1.25 ppb yr−1, and our study confirms that the N2O fluxes from the a priori inventories are overestimated. The seasonal cycles of XN2O from the FTIR measurements and the model simulations are close to each other in the Northern Hemisphere with a maximum in August–October and a minimum in February–April. However, in the Southern Hemisphere, the modeled XN2O values show a minimum in February–April while the FTIR XN2O retrievals show different patterns. By comparing the partial column-averaged N2O from the model and NDACC for three vertical ranges (surface–8, 8–17, 17–50 km), we find that the discrepancy in the XN2O seasonal cycle between the model simulations and the FTIR measurements in the Southern Hemisphere is mainly due to their stratospheric differences.

Knowing the spatial and seasonal distributions of nitric acid (HNO3) around the globe is of great interest and allows us to comprehend the processes regulating stratospheric ozone, especially in the polar regions. Due to its unprecedented spatial and temporal sampling, the nadir-viewing Infrared Atmospheric Sounding Interferometer (IASI) is capable of sounding the atmosphere twice a day globally, with good spectral resolution and low noise. With the Fast Optimal Retrievals on Layers for IASI (FORLI) algorithm, we are retrieving, in near real time, columns as well as vertical profiles of several atmospheric species, among which is HNO3. We present in this paper the first characterization of the FORLI-HNO3 profile products, in terms of vertical sensitivity and error budgets. We show that the sensitivity of IASI to HNO3 is highest in the lower stratosphere (10–20 km), where the largest amounts of HNO3 are found, but that the vertical sensitivity of IASI only allows one level of information on the profile (degrees of freedom for signal, DOFS; ∼ 1). The sensitivity near the surface is negligible in most cases, and for this reason, a partial column (5–35 km) is used for the analyses. Both vertical profiles and partial columns are compared to FTIR ground-based measurements from the Network for the Detection of Atmospheric Composition Change (NDACC) to characterize the accuracy and precision of the FORLI-HNO3 product. The profile validation is conducted through the smoothing of the raw FTIR profiles by the IASI averaging kernels and gives good results, with a slight overestimation of IASI measurements in the upper troposphere/lower stratosphere (UTLS) at the six chosen stations (Thule, Kiruna, Jungfraujoch, Izaña, Lauder and Arrival Heights). The validation of the partial columns (5–35 km) is also conclusive with a mean correlation of 0.93 between IASI and the FTIR measurements. An initial survey of the HNO3 spatial and seasonal variabilities obtained from IASI measurements for a 1-year (2011) data set shows that the expected latitudinal gradient of concentrations from low to high latitudes and the large seasonal variability in polar regions (cycle amplitude around 30 % of the seasonal signal, peak to peak) are well represented by IASI data.

Global distributions of atmospheric ammonia (NH3) measured with satellite instruments such as the Infrared Atmospheric Sounding Interferometer (IASI) contain valuable information on NH3 concentrations and variability in regions not yet covered by ground-based instruments. Due to their large spatial coverage and (bi-)daily overpasses, the satellite observations have the potential to increase our knowledge of the distribution of NH3 emissions and associated seasonal cycles. However the observations remain poorly validated, with only a handful of available studies often using only surface measurements without any vertical information. In this study, we present the first validation of the IASI-NH3 product using ground-based Fourier transform infrared spectroscopy (FTIR) observations. Using a recently developed consistent retrieval strategy, NH3 concentration profiles have been retrieved using observations from nine Network for the Detection of Atmospheric Composition Change (NDACC) stations around the world between 2008 and 2015. We demonstrate the importance of strict spatio-temporal collocation criteria for the comparison. Large differences in the regression results are observed for changing intervals of spatial criteria, mostly due to terrain characteristics and the short lifetime of NH3 in the atmosphere. The seasonal variations of both datasets are consistent for most sites. Correlations are found to be high at sites in areas with considerable NH3 levels, whereas correlations are lower at sites with low atmospheric NH3 levels close to the detection limit of the IASI instrument. A combination of the observations from all sites (Nobs = 547) give a mean relative difference of −32.4 ± (56.3) %, a correlation r of 0.8 with a slope of 0.73. These results give an improved estimate of the IASI-NH3 product performance compared to the previous upper-bound estimates (−50 to +100 %).

Atmospheric non-methane hydrocarbon concentrations began declining in the 1970s. Surface and column measurements show that Northern Hemisphere ethane concentrations are now rising, probably due to North American oil and natural gas emissions. Non-methane hydrocarbons such as ethane are important precursors to tropospheric ozone and aerosols. Using data from a global surface network and atmospheric column observations we show that the steady decline in the ethane mole fraction that began in the 1970s1,2,3 halted between 2005 and 2010 in most of the Northern Hemisphere and has since reversed. We calculate a yearly increase in ethane emissions in the Northern Hemisphere of 0.42 (±0.19) Tg yr−1 between mid-2009 and mid-2014. The largest increases in ethane and the shorter-lived propane are seen over the central and eastern USA, with a spatial distribution that suggests North American oil and natural gas development as the primary source of increasing emissions. By including other co-emitted oil and natural gas non-methane hydrocarbons, we estimate a Northern Hemisphere total non-methane hydrocarbon yearly emission increase of 1.2 (±0.8) Tg yr−1. Atmospheric chemical transport modelling suggests that these emissions could augment summertime mean surface ozone by several nanomoles per mole near oil and natural gas production regions. Methane/ethane oil and natural gas emission ratios could suggest a significant increase in associated methane emissions; however, this increase is inconsistent with observed leak rates in production regions and changes in methane’s global isotopic ratio.

We present a 10-year (January 2007–December 2016) time series of continuous in situ measurements of methane ( CH4 ), carbon monoxide (CO) and nitrous oxide ( N2O ) made by an in situ Fourier transform infrared trace gas and isotope analyser (FTIR) operated at Lauder, New Zealand (45.04 S, 169.68 E, 370 m a. m. s. l.). Being the longest continuous deployed operational FTIR system of this type, we are in an ideal position to perform a practical evaluation of the multi-year performance of the analyser. The operational methodology, measurement precision, reproducibility, accuracy and instrument reliability are reported. We find the FTIR has a measurement repeatability of the order of 0.37 ppb (1 σ standard deviation) for CH4 , 0.31 ppb for CO and 0.12 ppb for N2O . Regular target cylinder measurements provide a reproducibility estimate of 1.19 ppb for CH4 , 0.74 ppb for CO and 0.27 ppb for N2O . FTIR measurements are compared to co-located ambient air flask samples acquired at Lauder since May 2009, which allows a long-term assessment of the FTIR data set across annual and seasonal composition changes. Comparing FTIR and co-located flask measurements show that the bias (FTIR minus flask) for CH4 of −1.02 ± 2.61 ppb and CO of −0.43 ± 1.60 ppb are within the Global Atmospheric Watch (GAW)-recommended compatibility goals of 2 ppb. The N2O FTIR flask bias of −0.01 ± 0.77 ppb is within the GAW-recommended compatibility goals of 0.1 ppb and should be viewed as a serendipitous result due to the large standard deviation along with known systematic differences in the measurement sets. Uncertainty budgets for each gas are also constructed based on instrument precision, reproducibility and accuracy. In the case of CH4 , systematic uncertainty dominates, whilst for CO and N2O it is comparable to the random uncertainty component. The long-term instrument stability, precision estimates and flask comparison results indicate the FTIR CH4 and CO time series meet the GAW compatibility recommendations across multiple years of operation (and instrument changes) and are sufficient to capture annual trends and seasonal cycles observed at Lauder. The differences between FTIR and flask N2O measurements need to be reconciled. Trend analysis of the 10-year time series captures seasonal cycles and the secular upward trend of CH4 and N2O . The CH4 and CO time series have the required precision and accuracy at a high enough temporal resolution to be used in inversion models in a data-sparse region of the world.

Atmospheric remote sensing by instruments such as spectrometers and interferometers often requires scheduling that is dependent on external factors, for example; time and solar (or lunar) zenith angle. Such instruments manufactured by Bruker often use the software package OPUS, which, while useful, is not flexible enough for automatic, repeated, atmospheric measurements of this nature. In this brief paper, we describe ASAP, a Python tool developed to run our network of Fourier transform interferometers in New Zealand and Antarctica. It allows the automated scheduling of measurements by time, lunar, or solar zenith angle while accounting for weather or other external parameters. There is a wide range of useful functions, all packaged in a simple graphical user interface; it is available on request.

Transport of carbonyl sulfide (OCS) from the troposphere to the stratosphere contributes sulfur to the stratospheric aerosol layer, which reflects incoming short-wave solar radiation, cooling the climate system. Previous analyses of OCS observations have shown no significant trend, suggesting that OCS is unlikely to be a major contributor to the reported increases in stratospheric aerosol loading and indicating a balanced OCS budget. Here we present analyses of ground-based Fourier transform spectrometer measurements of OCS at three Southern Hemisphere sites spanning 34.45°S to 77.80°S. At all three sites statistically significant positive trends are seen from 2001 to 2014 with an observed overall trend in total column OCS at Wollongong of 0.73 ± 0.03%/yr, at Lauder of 0.43 ± 0.02%/yr, and at Arrival Heights of 0.45 ± 0.05%/yr. These observed trends in OCS imply that the OCS budget is not balanced and could contribute to constraints on current estimates of sources and sinks.

Within the NDACC (Network for the Detection of Atmospheric Composition Change), more than 20 FTIR (Fourier-transform infrared) spectrometers, spread worldwide, provide long-term data records of many atmospheric trace gases. We present a method that uses measured and modelled XCO2 for assessing the consistency of these NDACC data records. Our XCO2 retrieval setup is kept simple so that it can easily be adopted for any NDACC/FTIR-like measurement made since the late 1950s. By a comparison to coincident TCCON (Total Carbon Column Observing Network) measurements, we empirically demonstrate the useful quality of this suggested NDACC XCO2 product (empirically obtained scatter between TCCON and NDACC is about 4‰ for daily mean as well as monthly mean comparisons, and the bias is 25‰). Our XCO2 model is a simple regression model fitted to CarbonTracker results and the Mauna Loa CO2 in situ records. A comparison to TCCON data suggests an uncertainty of the model for monthly mean data of below 3‰. We apply the method to the NDACC/FTIR spectra that are used within the project MUSICA (multi-platform remote sensing of isotopologues for investigating the cycle of atmospheric water) and demonstrate that there is a good consistency for these globally representative set of spectra measured since 1996: the scatter between the modelled and measured XCO2 on a yearly time scale is only 3‰.

Ground-based Fourier transform infrared (FTIR) measurements of solar absorption spectra can provide ozone total columns with a precision of 2% but also independent partial column amounts in about four vertical layers, one in the troposphere and three in the stratosphere up to about 45km, with a precision of 5–6%. We use eight of the Network for the Detection of Atmospheric Composition Change (NDACC) stations having a long-term time series of FTIR ozone measurements to study the total and vertical ozone trends and variability, namely, Ny-Ålesund (79° N), Thule (77° N), Kiruna (68° N), Harestua (60° N), Jungfraujoch (47° N), Izaña (28° N), Wollongong (34° S) and Lauder (45° S). The length of the FTIR time series varies by station but is typically from about 1995 to present. We applied to the monthly means of the ozone total and four partial columns a stepwise multiple regression model including the following proxies: solar cycle, quasi-biennial oscillation (QBO), El Niño–Southern Oscillation (ENSO), Arctic and Antarctic Oscillation (AO/AAO), tropopause pressure (TP), equivalent latitude (EL), Eliassen–Palm flux (EPF), and volume of polar stratospheric clouds (VPSC). At the Arctic stations, the trends are found mostly negative in the troposphere and lower stratosphere, very mixed in the middle stratosphere, positive in the upper stratosphere due to a large increase in the 1995–2003 period, and non-significant when considering the total columns. The trends for mid-latitude and subtropical stations are all non-significant, except at Lauder in the troposphere and upper stratosphere and at Wollongong for the total columns and the lower and middle stratospheric columns where they are found positive. At Jungfraujoch, the upper stratospheric trend is close to significance (+0.9 ± 1.0% decade−1). Therefore, some signs of the onset of ozone mid-latitude recovery are observed only in the Southern Hemisphere, while a few more years seem to be needed to observe it at the northern mid-latitude station.

The Measurements of Pollution in the Troposphere (MOPITT) satellite instrument provides the longest continuous dataset of carbon monoxide (CO) from space. We perform the first validation of MOPITT version 6 retrievals using total column CO measurements from ground-based remote-sensing Fourier transform infrared spectrometers (FTSs). Validation uses data recorded at 14 stations, that span a wide range of latitudes (80° N to 78° S), in the Network for the Detection of Atmospheric Composition Change (NDACC). MOPITT measurements are spatially co-located with each station, and different vertical sensitivities between instruments are accounted for by using MOPITT averaging kernels (AKs). All three MOPITT retrieval types are analyzed: thermal infrared (TIR-only), joint thermal and near infrared (TIR–NIR), and near infrared (NIR-only). Generally, MOPITT measurements overestimate CO relative to FTS measurements, but the bias is typically less than 10 %. Mean bias is 2.4 % for TIR-only, 5.1 % for TIR–NIR, and 6.5 % for NIR-only. The TIR–NIR and NIR-only products consistently produce a larger bias and lower correlation than the TIR-only. Validation performance of MOPITT for TIR-only and TIR–NIR retrievals over land or water scenes is equivalent. The four MOPITT detector element pixels are validated separately to account for their different uncertainty characteristics. Pixel 1 produces the highest standard deviation and lowest correlation for all three MOPITT products. However, for TIR-only and TIR–NIR, the error-weighted average that includes all four pixels often provides the best correlation, indicating compensating pixel biases and well-captured error characteristics. We find that MOPITT bias does not depend on latitude but rather is influenced by the proximity to rapidly changing atmospheric CO. MOPITT bias drift has been bound geographically to within ±0.5 % yr−1 or lower at almost all locations.

Changes of atmospheric methane (CH4) since 2005 have been evaluated using Fourier Transform Infrared (FTIR) solar observations performed at ten ground-based sites, all members of the Network for Detection of Atmospheric Composition Change (NDACC). From this, we find an increase of atmospheric methane total columns that amounts to 0.31 ± 0.03 % year−1 (2-sigma level of uncertainty) for the 2005–2014 period. Comparisons with in situ methane measurements at both local and global scales show good agreement. We used the GEOS-Chem Chemical Transport Model tagged simulation that accounts for the contribution of each emission source and one sink in the total methane, simulated over the 2005–2012 time period and based on emissions inventories and transport. After regridding according to NDACC vertical layering using a conservative regridding scheme and smoothing by convolving with respective FTIR seasonal averaging kernels, the GEOS-Chem simulation shows an increase of atmospheric methane of 0.35 ± 0.03 % year−1 between 2005 and 2012, which is in agreement with NDACC measurements over the same time period (0.30 ± 0.04 % year−1, averaged over ten stations). Analysis of the GEOS-Chem tagged simulation allows us to quantify the contribution of each tracer to the global methane change since 2005. We find that natural sources such as wetlands and biomass burning contribute to the inter-annual variability of methane. However, anthropogenic emissions such as coal mining, and gas and oil transport and exploration, which are mainly emitted in the Northern Hemisphere and act as secondary contributors to the global budget of methane, have played a major role in the increase of atmospheric methane observed since 2005. Based on the GEOS-Chem tagged simulation, we discuss possible cause(s) for the increase of methane since 2005, which is still unexplained.

The stratospheric climate and variability from simulations of sixteen chemistry-climate models is evaluated. On average the polar night jet is well reproduced though its variability is less well reproduced with a large spread between models. Polar temperature biases are less than 5 K except in the Southern Hemisphere (SH) lower stratosphere in spring. The accumulated area of low temperatures responsible for polar stratospheric cloud formation is accurately reproduced for the Antarctic but underestimated for the Arctic. The shape and position of the polar vortex is well simulated, as is the tropical upwelling in the lower stratosphere. There is a wide model spread in the frequency of major sudden stratospheric warnings (SSWs), late biases in the breakup of the SH vortex, and a weak annual cycle in the zonal wind in the tropical upper stratosphere. Quantitatively, "metrics" indicate a wide spread in model performance for most diagnostics with systematic biases in many, and poorer performance in the SH than in the Northern Hemisphere (NH). Correlations were found in the SH between errors in the final warming, polar temperatures, the leading mode of variability, and jet strength, and in the NH between errors in polar temperatures, frequency of major SSWs, and jet strength. Models with a stronger QBO have stronger tropical upwelling and a colder NH vortex. Both the qualitative and quantitative analysis indicate a number of common and long-standing model problems, particularly related to the simulation of the SH and stratospheric variability. Copyright 2011 by the American Geophysical Union.

Global distributions of atmospheric ammonia (NH3) measured with satellite instruments such as the Infrared Atmospheric Sounding Interferometer (IASI) contain valuable information on NH3 concentrations and variability in regions not yet covered by ground based instruments. Due to their large spatial coverage and daily observations, the satellite observations have the potential to increase our knowledge of the distribution of NH3 emissions, and associated seasonal cycles. However the observations remain poorly validated, with only a handful of available studies often using only surface observations without any vertical information. In this study, we present the first validation of the IASI-NH3 product using ground-based Fourier Transform InfraRed (FTIR) observations. Using a recently developed consistent retrieval strategy, NH3 concentration profiles have been retrieved using observations from nine Network for the Detection of Atmospheric Composition Change (NDACC) stations around the world between 2008–2015. We demonstrate the importance of strict spatio-temporal collocation criteria for the comparison. Large differences in the regression results are observed for changing intervals of spatial criteria, mostly due to terrain characteristics and the short lifetime of NH3 in the atmosphere. The seasonal variations of both datasets are consistent for most sites. Correlations are found to be high at sites in areas with considerable NH3 levels, whereas correlations are lower at sites with low atmospheric NH3 levels close to the detection limit of the IASI instrument. A combination of the observations from all sites (Nobs = 547) give a MRD of −32.4 ± (56.3) %, a correlation r of 0.8 with a slope of 0.73. These results indicate that the IASI-NH3 product performs better than previous upper bound estimates (-50% – +100 %).

Time series of total column abundances of hydrogen chloride (HCl), chlorine nitrate (ClONO2), and hydrogen fluoride (HF) were determined from ground-based Fourier transform infrared (FTIR) spectra recorded at 17 sites belonging to the Network for the Detection of Atmospheric Composition Change (NDACC) and located between 80.05° N and 77.82° S. By providing such a near-global overview on ground-based measurements of the two major stratospheric chlorine reservoir species, HCl and ClONO2, the present study is able to confirm the decrease of the atmospheric inorganic chlorine abundance during the last few years. This decrease is expected following the 1987 Montreal Protocol and its amendments and adjustments, where restrictions and a subsequent phase-out of the prominent anthropogenic chlorine source gases (solvents, chlorofluorocarbons) were agreed upon to enable a stabilisation and recovery of the stratospheric ozone layer. The atmospheric fluorine content is expected to be influenced by the Montreal Protocol, too, because most of the banned anthropogenic gases also represent important fluorine sources. But many of the substitutes to the banned gases also contain fluorine so that the HF total column abundance is expected to have continued to increase during the last few years. The measurements are compared with calculations from five different models: the two-dimensional Bremen model, the two chemistry-transport models KASIMA and SLIMCAT, and the two chemistry-climate models EMAC and SOCOL. Thereby, the ability of the models to reproduce the absolute total column amounts, the seasonal cycles, and the temporal evolution found in the FTIR measurements is investigated and inter-compared. This is especially interesting because the models have different architectures. The overall agreement between the measurements and models for the total column abundances and the seasonal cycles is good. Linear trends of HCl, ClONO2, and HF are calculated from both measurement and model time series data, with a focus on the time range 2000–2009. This period is chosen because from most of the measurement sites taking part in this study, data are available during these years. The precision of the trends is estimated with the bootstrap resampling method. The sensitivity of the trend results with respect to the fitting function, the time of year chosen and time series length is investigated, as well as a bias due to the irregular sampling of the measurements. The measurements and model results investigated here agree qualitatively on a decrease of the chlorine species by around 1% yr−1. The models simulate an increase of HF of around 1% yr−1. This also agrees well with most of the measurements, but some of the FTIR series in the Northern Hemisphere show a stabilisation or even a decrease in the last few years. In general, for all three gases, the measured trends vary more strongly with latitude and hemisphere than the modelled trends. Relative to the FTIR measurements, the models tend to underestimate the decreasing chlorine trends and to overestimate the fluorine increase in the Northern Hemisphere. At most sites, the models simulate a stronger decrease of ClONO2 than of HCl. In the FTIR measurements, this difference between the trends of HCl and ClONO2 depends strongly on latitude, especially in the Northern Hemisphere.

Hydrogen chloride (HCl) and hydrogen fluoride (HF) are respectively the main chlorine and fluorine reservoirs in the Earth's stratosphere. Their buildup resulted from the intensive use of man-made halogenated source gases, in particular CFC-11 (CCl3F) and CFC-12 (CCl2F2), during the second half of the 20th century. It is important to continue monitoring the evolution of these source gases and reservoirs, in support of the Montreal Protocol and also indirectly of the Kyoto Protocol. The Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS) is a space-based instrument that has been performing regular solar occultation measurements of over 30 atmospheric gases since early 2004. In this validation paper, the HCl, HF, CFC-11 and CFC-12 version 2.2 profile data products retrieved from ACE-FTS measurements are evaluated. Volume mixing ratio profiles have been compared to observations made from space by MLS and HALOE, and from stratospheric balloons by SPIRALE, FIRS-2 and Mark-IV. Partial columns derived from the ACE-FTS data were also compared to column measurements from ground-based Fourier transform instruments operated at 12 sites. ACE-FTS data recorded from March 2004 to August 2007 have been used for the comparisons. These data are representative of a variety of atmospheric and chemical situations, with sounded air masses extending from the winter vortex to summer sub-tropical conditions. Typically, the ACE-FTS products are available in the 10–50 km altitude range for HCl and HF, and in the 7–20 and 7–25 km ranges for CFC-11 and -12, respectively. For both reservoirs, comparison results indicate an agreement generally better than 5–10% above 20 km altitude, when accounting for the known offset affecting HALOE measurements of HCl and HF. Larger positive differences are however found for comparisons with single profiles from FIRS-2 and SPIRALE. For CFCs, the few coincident measurements available suggest that the differences probably remain within ±20%.

Harmonized time series of column-averaged mole fractions of atmospheric methane and ethane over the period 1999–2014 are derived from solar Fourier transform infrared (FTIR) measurements at the Zugspitze summit (47° N, 11° E; 2964 m a.s.l.) and at Lauder (45° S, 170° E; 370 m a.s.l.). Long-term trend analysis reveals a consistent renewed methane increase since 2007 of 6.2 [5.6, 6.9] ppb yr−1 (parts-per-billion per year) at the Zugspitze and 6.0 [5.3, 6.7] ppb yr−1 at Lauder (95 % confidence intervals). Several recent studies provide pieces of evidence that the renewed methane increase is most likely driven by two main factors: (i) increased methane emissions from tropical wetlands, followed by (ii) increased thermogenic methane emissions due to growing oil and natural gas production. Here, we quantify the magnitude of the second class of sources, using long-term measurements of atmospheric ethane as a tracer for thermogenic methane emissions. In 2007, after years of weak decline, the Zugspitze ethane time series shows the sudden onset of a significant positive trend (2.3 [1.8, 2.8] × 10−2 ppb yr−1 for 2007–2014), while a negative trend persists at Lauder after 2007 (−0.4 [−0.6, −0.1] × 10−2 ppb yr−1). Zugspitze methane and ethane time series are significantly correlated for the period 2007–2014 and can be assigned to thermogenic methane emissions with an ethane-to-methane ratio (EMR) of 12–19 %. We present optimized emission scenarios for 2007–2014 derived from an atmospheric two-box model. From our trend observations we infer a total ethane emission increase over the period 2007–2014 from oil and natural gas sources of 1–11 Tg yr−1 along with an overall methane emission increase of 24–45 Tg yr−1. Based on these results, the oil and natural gas emission contribution (C) to the renewed methane increase is deduced using three different emission scenarios with dedicated EMR ranges. Reference scenario 1 assumes an oil and gas emission combination with EMR = 7.0–16.2 %, which results in a minimum contribution C > 39 % (given as lower bound of 95 % confidence interval). Beside this most plausible scenario 1, we consider two less realistic limiting cases of pure oil-related emissions (scenario 2 with EMR = 16.2–31.4 %) and pure natural gas sources (scenario 3 with EMR = 4.4–7.0 %), which result in C > 18 % and C > 73 %, respectively. Our results suggest that long-term observations of column-averaged ethane provide a valuable constraint on the source attribution of methane emission changes and provide basic knowledge for developing effective climate change mitigation strategies.

Recently, it was shown that of the ozone-depleting substances currently emitted, N2O emissions (the primary source of stratospheric NOx) dominate, and are likely to do so throughout the 21st century. To investigate the links between N2O and NOx concentrations, and the effects of NOx on ozone in a changing climate, the evolution of stratospheric ozone from 1960 to 2100 was simulated using the NIWA-SOCOL chemistry-climate model. The yield of NOx from N2O is reduced due to stratospheric cooling and a strengthening of the Brewer-Dobson circulation. After accounting for the reduced NOx yield, additional weakening of the primary NOx cycle is attributed to reduced availability of atomic oxygen, due to a) stratospheric cooling decreasing the atomic oxygen/ozone ratio, and b) enhanced rates of chlorine-catalyzed ozone loss cycles around 2000 and enhanced rates of HOx-induced ozone depletion. Our results suggest that the effects of N2O on ozone depend on both the radiative and chemical environment of the upper stratosphere, specifically CO2-induced cooling of the stratosphere and elevated CH4 emissions which enhance HOx-induced ozone loss and remove the availability of atomic oxygen to participate in NOx ozone loss cycles.

The goal of this study is to determine how H2O and HDO measurements in water vapor can be used to detect and diagnose biases in the representation of processes controlling tropospheric humidity in atmospheric general circulation models (GCMs). We analyze a large number of isotopic data sets (four satellite, sixteen ground-based remote-sensing, five surface in situ and three aircraft data sets) that are sensitive to different altitudes throughout the free troposphere. Despite significant differences between data sets, we identify some observed HDO/H2O characteristics that are robust across data sets and that can be used to evaluate models. We evaluate the isotopic GCM LMDZ, accounting for the effects of spatiotemporal sampling and instrument sensitivity. We find that LMDZ reproduces the spatial patterns in the lower and mid troposphere remarkably well. However, it underestimates the amplitude of seasonal variations in isotopic composition at all levels in the subtropics and in midlatitudes, and this bias is consistent across all data sets. LMDZ also underestimates the observed meridional isotopic gradient and the contrast between dry and convective tropical regions compared to satellite data sets. Comparison with six other isotope-enabled GCMs from the SWING2 project shows that biases exhibited by LMDZ are common to all models. The SWING2 GCMs show a very large spread in isotopic behavior that is not obviously related to that of humidity, suggesting water vapor isotopic measurements could be used to expose model shortcomings. In a companion paper, the isotopic differences between models are interpreted in terms of biases in the representation of processes controlling humidity. Copyright © 2012 by the American Geophysical Union.

Within the project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water), long-term tropospheric water vapour isotopologue data records are provided for ten globally distributed ground-based mid-infrared remote sensing stations of the NDACC (Network for the Detection of Atmospheric Composition Change). We present a new method allowing for an extensive and straightforward characterisation of the complex nature of such isotopologue remote sensing datasets. We demonstrate that the MUSICA humidity profiles are representative for most of the troposphere with a vertical resolution ranging from about 2 km (in the lower troposphere) to 8 km (in the upper troposphere) and with an estimated precision of better than 10%. We find that the sensitivity with respect to the isotopologue composition is limited to the lower and middle troposphere, whereby we estimate a precision of about 30‰ for the ratio between the two isotopologues HD16O and H216O. The measurement noise, the applied atmospheric temperature profiles, the uncertainty in the spectral baseline, and the cross-dependence on humidity are the leading error sources. We introduce an a posteriori correction method of the cross-dependence on humidity, and we recommend applying it to isotopologue ratio remote sensing datasets in general. In addition, we present mid-infrared CO2 retrievals and use them for demonstrating the MUSICA network-wide data consistency. In order to indicate the potential of long-term isotopologue remote sensing data if provided with a well-documented quality, we present a climatology and compare it to simulations of an isotope incorporated AGCM (Atmospheric General Circulation Model). We identify differences in the multi-year mean and seasonal cycles that significantly exceed the estimated errors, thereby indicating deficits in the modeled atmospheric water cycle.

International audience; We use observations of N2O and mean age to identify realistic transport in models in order to explain their ozone predictions. The results are applied to 15 chemistry climate models (CCMs) participating in the 2010 World Meteorological Organization ozone assessment. Comparison of the observed and simulated N2O, mean age and their compact correlation identifies models with fast or slow circulations and reveals details of model ascent and tropical isolation. This process-oriented diagnostic is more useful than mean age alone because it identifies models with compensating transport deficiencies that produce fortuitous agreement with mean age. The diagnosed model transport behavior is related to a model's ability to produce realistic lower stratosphere (LS) O3 profiles. Models with the greatest tropical transport problems compare poorly with O3 observations. Models with the most realistic LS transport agree more closely with LS observations and each other. We incorporate the results of the chemistry evaluations in the Stratospheric Processes and their Role in Climate (SPARC) CCMVal Report to explain the range of CCM predictions for the return-to-1980 dates for global (60°S-60°N) and Antarctic column ozone. Antarctic O3 return dates are generally correlated with vortex Cly levels, and vortex Cly is generally correlated with the model's circulation, although model Cl chemistry and conservation problems also have a significant effect on return date. In both regions, models with good LS transport and chemistry produce a smaller range of predictions for the return-to-1980 ozone values. This study suggests that the current range of predicted return dates is unnecessarily broad due to identifiable model deficiencies.

International audience; We address the question of how ozone and long-lived greenhouse gas changes impact the Northern Annular Mode (NAM). Using reanalyses and results from the Chemistry-Climate Model Validation 2 (CCMVal-2) initiative, we calculate seasonal NAM indices from geopotential height for winter and spring. From these, we determine the strength of stratosphere-troposphere coupling in the model simulations and the reanalyses. For both seasons, we find a large spread in the ability of models to represent the vertical coherence of the NAM, although most models are within the 95% confidence interval. In winter, many models underestimate the vertical coherence derived from the reanalyses. Some models exhibit substantial differences in vertical coherence between simulations driven with modeled and observed ocean conditions. In spring, in the simulations using modeled ocean conditions, models with poorer horizontal or vertical resolution tend to underestimate the vertical coupling, and vice versa for models with better resolution. Accounting for model deficits in producing an appropriate troposphere-stratosphere coupling, we show significant correlations of the NAM in winter with three indices representing the anthropogenic impact. Analysis of cross-correlations between these indices suggests that increasing CO2 is the main reason for these correlations in this season. In the CCMVal-2 simulations, CO2 increases are associated with a weakening of the NAM in winter. For spring, we show that the dominant effect is chemical ozone depletion leading to a transient strengthening of the NAM, with CO2 changes playing an insignificant role.

International audience; Coupled chemistry-climate model simulations covering the recent past and continuing throughout the 21st century have been completed with a range of different models. Common forcings are used for the halogen amounts and greenhouse gas concentrations, as expected under the Montreal Protocol (with amendments) and Intergovernmental Panel on Climate Change A1b Scenario. The simulations of the Antarctic ozone hole are compared using commonly used diagnostics: the minimum ozone, the maximum area of ozone below 220 DU, and the ozone mass deficit below 220 DU. Despite the fact that the processes responsible for ozone depletion are reasonably well understood, a wide range of results is obtained. Comparisons with observations indicate that one of the reasons for the model underprediction in ozone hole area is the tendency for models to underpredict, by up to 35%, the area of low temperatures responsible for polar stratospheric cloud formation. Models also typically have species gradients that are too weak at the edge of the polar vortex, suggesting that there is too much mixing of air across the vortex edge. Other models show a high bias in total column ozone which restricts the size of the ozone hole (defined by a 220 DU threshold). The results of those models which agree best with observations are examined in more detail. For several models the ozone hole does not disappear this century but a small ozone hole of up to three million square kilometers continues to occur in most springs even after 2070.

A multimodel assessment of the performance of chemistry-climate models (CCMs) in the extratropical upper troposphere/lower stratosphere (UTLS) is conducted for the first time. Process-oriented diagnostics are used to validate dynamical and transport characteristics of 18 CCMs using meteorological analyses and aircraft and satellite observations. The main dynamical and chemical climatological characteristics of the extratropical UTLS are generally well represented by the models, despite the limited horizontal and vertical resolution. The seasonal cycle of lowermost stratospheric mass is realistic, however with a wide spread in its mean value. A tropopause inversion layer is present in most models, although the maximum in static stability is located too high above the tropopause and is somewhat too weak, as expected from limited model resolution. Similar comments apply to the extratropical tropopause transition layer. The seasonality in lower stratospheric chemical tracers is consistent with the seasonality in the Brewer-Dobson circulation. Both vertical and meridional tracer gradients are of similar strength to those found in observations. Models that perform less well tend to use a semi-Lagrangian transport scheme and/or have a very low resolution. Two models, and the multimodel mean, score consistently well on all diagnostics, while seven other models score well on all diagnostics except the seasonal cycle of water vapor. Only four of the models are consistently below average. The lack of tropospheric chemistry in most models limits their evaluation in the upper troposphere. Finally, the UTLS is relatively sparsely sampled by observations, limiting our ability to quantitatively evaluate many aspects of model performance. Copyright © 2010 by the American Geophysical Union.

International audience; The internal variability and coupling between the stratosphere and troposphere in CCMVal-2 chemistry-climate models are evaluated through analysis of the annular mode patterns of variability. Computation of the annular modes in long data sets with secular trends requires refinement of the standard definition of the annular mode, and a more robust procedure that allows for slowly varying trends is established and verified. The spatial and temporal structure of the models' annular modes is then compared with that of reanalyses. As a whole, the models capture the key features of observed intraseasonal variability, including the sharp vertical gradients in structure between stratosphere and troposphere, the asymmetries in the seasonal cycle between the Northern and Southern hemispheres, and the coupling between the polar stratospheric vortices and tropospheric midlatitude jets. It is also found that the annular mode variability changes little in time throughout simulations of the 21st century. There are, however, both common biases and significant differences in performance in the models. In the troposphere, the annular mode in models is generally too persistent, particularly in the Southern Hemisphere summer, a bias similar to that found in CMIP3 coupled climate models. In the stratosphere, the periods of peak variance and coupling with the troposphere are delayed by about a month in both hemispheres. The relationship between increased variability of the stratosphere and increased persistence in the troposphere suggests that some tropospheric biases may be related to stratospheric biases and that a well-simulated stratosphere can improve simulation of tropospheric intraseasonal variability.

International audience; The impact of stratospheric ozone on the tropospheric general circulation of theSouthern Hemisphere (SH) is examined with a set of chemistry‐climate models participatingin the Stratospheric Processes and their Role in Climate (SPARC)/Chemistry‐ClimateModel Validation project phase 2 (CCMVal‐2). Model integrations of both the past andfuture climates reveal the crucial role of stratospheric ozone in driving SH circulationchange: stronger ozone depletion in late spring generally leads to greater polewarddisplacement and intensification of the tropospheric midlatitude jet, and greater expansion ofthe SH Hadley cell in the summer. These circulation changes are systematic as polewarddisplacement of the jet is typically accompanied by intensification of the jet and expansion ofthe Hadley cell. Overall results are compared with coupled models participating in theIntergovernmental Panel on Climate Change Fourth Assessment Report (IPCC AR4), andpossible mechanisms are discussed. While the tropospheric circulation response appearsquasi‐linearly related to stratospheric ozone changes, the quantitative response to a givenforcing varies considerably from one model to another. This scatter partly results fromdifferences in model climatology. It is shown that poleward intensification of the westerly jetis generally stronger in models whose climatological jet is biased toward lower latitudes.This result is discussed in the context of quasi‐geostrophic zonal mean dynamics.

The goal of the Chemistry-Climate Model Validation (CCMVal) activity is to improve understanding of chemistry-climate models (CCMs) through process-oriented evaluation and to provide reliable projections of stratospheric ozone and its impact on climate. An appreciation of the details of model formulations is essential for understanding how models respond to the changing external forcings of greenhouse gases and ozone-depleting substances, and hence for understanding the ozone and climate forecasts produced by the models participating in this activity. Here we introduce and review the models used for the second round (CCMVal-2) of this intercomparison, regarding the implementation of chemical, transport, radiative, and dynamical processes in these models. In particular, we review the advantages and problems associated with approaches used to model processes of relevance to stratospheric dynamics and chemistry. Furthermore, we state the definitions of the reference simulations performed, and describe the forcing data used in these simulations. We identify some developments in chemistry-climate modeling that make models more physically based or more comprehensive, including the introduction of an interactive ocean, online photolysis, troposphere-stratosphere chemistry, and non-orographic gravity-wave deposition as linked to tropospheric convection. The relatively new developments indicate that stratospheric CCM modeling is becoming more consistent with our physically based understanding of the atmosphere. Copyright 2010 by the American Geophysical Union.

Spectral measurements of UV irradiances at Tokyo are compared with corresponding measurements at a pristine site (Lauder New Zealand) to identify the causes of the reductions in urban UV irradiances, and to quantify their effects. Tropospheric extinctions in Tokyo were found to be up to ~40% greater than at Lauder. Most of these differences can be explained by differences in cloud and aerosols, but ozone differences are also important in the summer. Examining spectral signatures of tropospheric transmission of both sites shows that reductions due to mean NO2 and SO2 amounts are generally small. However, at times the amount of NO2 can be 10 times higher than the mean amount, and on these days it can decrease the UVA irradiance up to 40%. If SO2 shows comparable day to day variability, it would contribute to significant reductions in UVB irradiances. The results indicate that at Tokyo, interactions between the larger burden of tropospheric ozone and aerosols also have a significant effect. These results have important implications for our ability to accurately retrieve surface UV irradiances at polluted sites from satellites that use backscattered UV. Supplementary data characterising these boundary layer effects are probably needed.

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.

International audience; The performance of 18 coupled Chemistry Climate Models (CCMs) in the Tropical Tropopause Layer (TTL) is evaluated using qualitative and quantitative diagnostics. Trends in tropopause quantities in the tropics and the extratropical Upper Troposphere and Lower Stratosphere (UTLS) are analyzed. A quantitative grading methodology for evaluating CCMs is extended to include variability and used to develop four different grades for tropical tropopause temperature and pressure, water vapor and ozone. Four of the 18 models and the multi‐model mean meet quantitative and qualitative standards for reproducing key processes in the TTL. Several diagnostics are performed on a subset of the models analyzing the Tropopause Inversion Layer (TIL), Lagrangian cold point and TTL transit time. Historical decreases in tropical tropopause pressure and decreases in water vapor are simulated, lending confidence to future projections. The models simulate continued decreases in tropopause pressure in the 21st century, along with ∼1K increases per century in cold point tropopause temperature and 0.5–1 ppmv per century increases in water vapor above the tropical tropopause. TTL water vapor increases below the cold point. In two models, these trends are associated with 35% increases in TTL cloud fraction. These changes indicate significant perturbations to TTL processes, specifically to deep convective heating and humidity transport. Ozone in the extratropical lowermost stratosphere has significant and hemispheric asymmetric trends. O3 is projected to increase by nearly 30% due to ozone recovery in the Southern Hemisphere (SH) and due to enhancements in the stratospheric circulation. These UTLS ozone trends may have significant effects in the TTL and the troposphere.