Detection Of Atmospheric Composition Change Research Articles

Nonlinear and Non‐Gaussian Ensemble Assimilation of MOPITT CO

AbstractSatellite retrievals of carbon monoxide (CO) are routinely assimilated in atmospheric chemistry models to improve air quality forecasts, produce reanalyzes and to estimate emissions. This study applies the quantile‐conserving ensemble filter framework, a novel assimilation algorithm that can deal with non‐Gaussian and modestly nonlinear distributions. Instead of assuming normal distributions like the Ensemble Adjustments Kalman Filter (EAKF), we now apply a bounded normal rank histogram (BNRH) distribution for the prior. The goal is to efficiently estimate bounded quantities such as CO atmospheric mixing ratios and emission fluxes while maintaining the good performance achieved by the EAKF. We contrast assimilating meteorological and MOPITT (Measurement of Pollution in the Troposphere) observations for May 2018. We evaluate the results with the fourth deployment of the NASA Atmospheric Tomography Mission (ATom‐4) airborne field campaign. We also compare simulations with CO tropospheric columns from the network for the detection of atmospheric composition change and surface in‐situ observations from NOAA carbon cycle greenhouse gases. While the differences remain small, the BNRH approach clearly works better than the EAKF in comparison to all observation data sets.

Evaluating modelled tropospheric columns of CH4, CO, and O3 in the Arctic using ground-based Fourier transform infrared (FTIR) measurements

Abstract. This study evaluates tropospheric columns of methane, carbon monoxide, and ozone in the Arctic simulated by 11 models. The Arctic is warming at nearly 4 times the global average rate, and with changing emissions in and near the region, it is important to understand Arctic atmospheric composition and how it is changing. Both measurements and modelling of air pollution in the Arctic are difficult, making model validation with local measurements valuable. Evaluations are performed using data from five high-latitude ground-based Fourier transform infrared (FTIR) spectrometers in the Network for the Detection of Atmospheric Composition Change (NDACC). The models were selected as part of the 2021 Arctic Monitoring and Assessment Programme (AMAP) report on short-lived climate forcers. This work augments the model–measurement comparisons presented in that report by including a new data source: column-integrated FTIR measurements, whose spatial and temporal footprint is more representative of the free troposphere than in situ and satellite measurements. Mixing ratios of trace gases are modelled at 3-hourly intervals by CESM, CMAM, DEHM, EMEP MSC-W, GEM-MACH, GEOS-Chem, MATCH, MATCH-SALSA, MRI-ESM2, UKESM1, and WRF-Chem for the years 2008, 2009, 2014, and 2015. The comparisons focus on the troposphere (0–7 km partial columns) at Eureka, Canada; Thule, Greenland; Ny Ålesund, Norway; Kiruna, Sweden; and Harestua, Norway. Overall, the models are biased low in the tropospheric column, on average by −9.7 % for CH4, −21 % for CO, and −18 % for O3. Results for CH4 are relatively consistent across the 4 years, whereas CO has a maximum negative bias in the spring and minimum in the summer and O3 has a maximum difference centered around the summer. The average differences for the models are within the FTIR uncertainties for approximately 15 % of the model–location comparisons.

Atmospheric N2O and CH4 total columns retrieved from low-resolution Fourier transform infrared (FTIR) spectra (Bruker VERTEX 70) in the mid-infrared region

Abstract. Nitrous oxide (N2O) and methane (CH4) are two important greenhouse gases in the atmosphere. In 2019, mid-infrared (MIR) solar absorption spectra were recorded by a Bruker VERTEX 70 spectrometer and a Bruker IFS 125HR spectrometer at Sodankylä, Finland, at spectral resolutions of 0.2 and 0.005 cm−1, respectively. The N2O and the CH4 retrievals from high-resolution MIR spectra have been well investigated within the Network for the Detection of Atmospheric Composition Change (NDACC) but not for MIR spectra gathered with instruments operating at low spectral resolution. In this study, N2O and CH4 retrieval strategies and retrieval uncertainties from the VERTEX 70 MIR low-resolution spectra are discussed and presented. The accuracy and precision of the VERTEX 70 N2O and CH4 retrievals are assessed by comparing them with the coincident 125HR retrievals and AirCore measurements. The relative differences between the N2O total columns retrieved from 125HR and VERTEX 70 spectra are −0.3 ± 0.7 (1σ) % with a correlation coefficient (R) of 0.93. Regarding the CH4 total column, we first used the same retrieval microwindows for 125HR and VERTEX 70 spectra, but there is an underestimation in the VERTEX 70 retrievals, especially in summer. The relative differences between the CH4 total columns retrieved from the 125HR and VERTEX 70 spectra are -1.3±1.1 (1σ) % with a R value of 0.77. To improve the VERTEX 70 CH4 retrievals, we propose alternative retrieval microwindows. The relative differences between the CH4 total columns retrieved from the 125HR and VERTEX 70 spectra in these new windows become 0.0±0.8 (1σ) %, along with an increase in the R value to 0.87. The coincident AirCore measurements confirm that the VERTEX 70 CH4 retrievals using the latter window choice are better, with relative mean differences between the VERTEX 70 CH4 retrievals and AirCore measurements of −1.9 % for the standard NDACC microwindows and of 0.13 % for the alternative microwindows. This study provides insight into the N2O and CH4 retrievals from the low-resolution (0.2 cm−1) MIR spectra observed with a VERTEX 70 spectrometer, and it demonstrates the suitability of this kind of instrument for contributing to satellite validation, model verification, and other scientific campaigns with the advantage of its transportability and lower cost compared to standard NDACC-type Fourier-transform infrared (FTIR) instruments.

A retrieval of xCO2 from ground-based mid-infrared NDACC solar absorption spectra and comparison to TCCON

Abstract. Two global networks of ground-based Fourier transform spectrometers are measuring abundances of atmospheric trace gases that absorb in the near infrared and mid-infrared: the Network for the Detection of Atmospheric Composition Change (NDACC) and the Total Carbon Column Observing Network (TCCON). The first lacks a CO2 product; therefore, this study focuses on developing an xCO2 retrieval method for NDACC from a spectral window in the 4800 cm−1 region. This retrieval will allow extending ground-based measurements back in time, which we will demonstrate with historical data available from Ny-Ålesund, Svalbard. At this site, both TCCON and NDACC measurements are routinely performed, which is an advantage for collocated comparisons. The results are compared with collocated TCCON measurements of column-averaged dry-air mole fractions of CO2 (denoted by xCO2) in Ny-Ålesund, Svalbard, and only TCCON in Burgos, Philippines. We found that it is possible to retrieve xCO2 from NDACC spectra with a precision of 0.2 %. The comparison between the new retrieval and TCCON showed that the sensitivity of the new retrieval is high in the troposphere and lower in the upper stratosphere, similar to TCCON, as seen in the averaging kernels, and that the seasonality is well captured as seen in the retrieved time series. Additionally, we have included a retrieval strategy suggestion to improve the quality of the xCO2 product.

Network for the Detection of Atmospheric Composition Change (NDACC) Fourier transform infrared (FTIR) trace gas measurements at the University of Toronto Atmospheric Observatory from 2002 to 2020

Abstract. Nineteen years of atmospheric composition measurements made at the University of Toronto Atmospheric Observatory (TAO; 43.66∘ N, 79.40∘ W; 174 m a.s.l.) are presented. These are retrieved from Fourier transform infrared (FTIR) solar absorption spectra recorded with an ABB Bomem DA8 spectrometer from May 2002 to December 2020. The retrievals have been performed for 14 species: O3, HCl, HF, HNO3, CH4, C2H6, CO, HCN, N2O, C2H2, H2CO, CH3OH, HCOOH, and NH3 using the SFIT4 algorithm. The measurements have been archived in the Network for the Detection of Atmospheric Composition Change (NDACC) data repository in Hierarchical Data Format version 4 (HDF4) files following the Generic Earth Observation Metadata Standard (GEOMS) and are also publicly available on Borealis, the Canadian Dataverse Repository (https://doi.org/10.5683/SP2/VC8JMC, Yamanouchi et al., 2022). In this paper, we describe the instrumentation, the retrieval strategy, the vertical sensitivity of the retrievals, the quality assurance process, and the error analysis of the TAO FTIR measurements and present the current version of the time series.

Validation of OMPS Suomi NPP and OMPS NOAA‐20 Formaldehyde Total Columns With NDACC FTIR Observations

AbstractWe validate formaldehyde (HCHO) vertical column densities (VCDs) from Ozone Mapping and Profiler Suite Nadir Mapper (OMPS‐NM) instruments onboard the Suomi National Polar‐orbiting Partnership (Suomi NPP) satellite for 2012–2020 and National Oceanic and Atmospheric Administration‐20 (NOAA‐20) satellite for 2018–2020, hereafter referred to as OMPS‐NPP and OMPS‐N20, with ground‐based Fourier‐Transform Infrared (FTIR) observations of the Network for the Detection of Atmospheric Composition Change (NDACC). OMPS‐NPP/N20 HCHO products reproduce seasonal variability at 24 FTIR sites. Monthly variability of OMPS‐NPP/N20 has a very good agreement with FTIR, showing correlation coefficients of 0.83 and 0.88, respectively. OMPS‐NPP (N20) biases averaged over all sites are −0.9 (4) ± 3 (6)%. However, at clean sites (with VCDs < 4.0 × 1015 molecules cm−2), positive biases of 20 (32) ± 6 (18)% occur for OMPS‐NPP (N20). At sites with HCHO VCDs > 4.0 × 1015 molecules cm−2, negative biases of −15% ± 4% appear for OMPS‐NPP, but OMPS‐N20 shows smaller bias of 0.5% ± 6% due to its smaller ground pixel footprints. Therefore, smaller satellite footprint sizes are important in distinguishing small‐scale plumes. In addition, we discuss a bias correction and provide lower limit for the monthly uncertainty of OMPS‐NPP/N20 HCHO products. The total uncertainty for OMPS‐NPP (N20) at clean sites is 0.7 (0.8) × 1015 molecules cm−2, corresponding to a relative uncertainty of 32 (30)%. In the case of HCHO VCDs > 4.0 × 1015 molecules cm−2, however, the relative uncertainty in HCHO VCDs for OMPS‐NPP (N20) decreases to 31 (18)%.

Atmospheric distribution of HCN from satellite observations and 3-D model simulations

Abstract. Hydrogen cyanide (HCN) is an important tracer of biomass burning, but there are significant uncertainties in its atmospheric budget, especially its photochemical and ocean sinks. Here we use a tracer version of the TOMCAT global 3-D chemical transport model to investigate the physical and chemical processes driving the abundance of HCN in the troposphere and stratosphere over the period 2004–2016. The modelled HCN distribution is compared with version 4.1 of the Atmospheric Chemistry Experiment Fourier transform spectrometer (ACE-FTS) HCN satellite data, which provide profiles up to around 42 km, and with ground-based column measurements from the Network for the Detection of Atmospheric Composition Change (NDACC). The long-term ACE-FTS measurements reveal the strong enhancements in upper-tropospheric HCN due to large wildfire events in Indonesia in 2006 and 2015. Our 3-D model simulations confirm previous lower-altitude balloon comparisons that the currently recommended NASA Jet Propulsion Laboratory (JPL) reaction rate coefficient of HCN with OH greatly overestimates the HCN loss. The use of the rate coefficient proposed by Kleinböhl et al. (2006) in combination with the HCN oxidation by O(1D) gives good agreement between ACE-FTS observations and the model. Furthermore, the model photochemical loss terms show that the reduction in the HCN mixing ratio with height in the middle stratosphere is mainly driven by the O(1D) sink with only a small contribution from a reaction with OH. From comparisons of the model tracers with ground-based HCN observations we test the magnitude of the ocean sink in two different published schemes (Li et al., 2000, 2003). We find that in our 3-D model the two schemes produce HCN abundances which are very different to the NDACC observations but in different directions. A model HCN tracer using the Li et al. (2000) scheme overestimates the HCN concentration by almost a factor of 2, while a HCN tracer using the Li et al. (2003) scheme underestimates the observations by about one-third. To obtain good agreement between the model and observations, we need to scale the magnitudes of the global ocean sinks by factors of 0.25 and 2 for the schemes of Li et al. (2000) and Li et al. (2003), respectively. This work shows that the atmospheric photochemical sinks of HCN now appear well constrained but improvements are needed in parameterizing the major ocean uptake sink.

Retrieval of atmospheric CFC-11 and CFC-12 from high-resolution FTIR observations at Hefei and comparisons with other independent datasets

Abstract. Synthetic halogenated organic chlorofluorocarbons (CFCs) play an important role in stratospheric ozone depletion and contribute significantly to the greenhouse effect. In this work, the mid-infrared solar spectra measured by ground-based high-resolution Fourier transform infrared spectroscopy (FTIR) were used to retrieve atmospheric CFC-11 (CCl3F) and CFC-12 (CCl2F2) at Hefei, China. The CFC-11 columns observed from January 2017 to December 2020 and CFC-12 columns from September 2015 to December 2020 show a similar annual decreasing trend and seasonal cycle, with an annual rate of -0.47±0.06 % yr−1 and -0.68±0.03 % yr−1, respectively. So the decline rate of CFC-11 is significantly lower than that of CFC-12. CFC-11 total columns were higher in summer, and CFC-12 total columns were higher in summer and autumn. Both CFC-11 and CFC-12 total columns reached the lowest in spring. Further, FTIR data of NDACC (Network for the Detection of Atmospheric Composition Change) candidate station Hefei were compared with the ACE-FTS (Atmospheric Chemistry Experiment Fourier transform spectrometer) satellite data, WACCM (Whole Atmosphere Community Climate Model) data, and the data from other NDACC-IRWG (InfraRed Working Group) stations (St. Petersburg, Jungfraujoch, and Réunion). The mean relative difference between the vertical profiles observed by FTIR and ACE-FTS is -5.6±3.3 % and 4.8±0.9 % for CFC-11 and CFC-12 for an altitude of 5.5 to 17.5 km, respectively. The results demonstrate that our FTIR data agree relatively well with the ACE-FTS satellite data. The annual decreasing rate of CFC-11 measured from ACE-FTS and calculated by WACCM is -1.15±0.22 % yr−1 and -1.68±0.18 % yr−1, respectively. The interannual decreasing rates of atmospheric CFC-11 obtained from ACE-FTS and WACCM data are higher than that from FTIR observations. Also, the annual decreasing rate of CFC-12 from ACE-FTS and WACCM is -0.85±0.15 % yr−1 and -0.81±0.05 % yr−1, respectively, close to the corresponding values from the FTIR measurements. The total columns of CFC-11 and CFC-12 at the Hefei and St. Petersburg stations are significantly higher than those at the Jungfraujoch and Réunion (Maïdo) stations, and the two values reached the maximum in local summer or autumn and the minimum in local spring or winter at the four stations. The seasonal variability at the three stations in the Northern Hemisphere is higher than that at the station in the Southern Hemisphere.

Measurements of Mesospheric Water Vapor From 1992 to 2021 at Three Stations From the Network for the Detection of Atmospheric Composition Change

AbstractWe present ground‐based microwave measurements of mesospheric water vapor made by the Water Vapor Millimeter‐wave Spectrometer (WVMS) instruments since the early 1990s from sites in California, Hawaii, and New Zealand. These measurements are compared with coincident measurements from the Halogen Occultation Experiment, the Aura Microwave Limb Sounder, and Sounding of the Atmosphere using Broadband Emission Radiometry; all of which combine to cover the entire time period of the ground‐based measurements. Comparisons are presented both on ∼weekly timescales in order to better identify discontinuities in the relative differences and on annual timescales in order to better study geophysical variations. The WVMS retrievals shown here are available on the Network for the Detection of Atmospheric Composition Change database. The range of WVMS trends and the differences from the satellite trends, with the latter varying over a range of ∼3%/decade, provide an estimate of how accurately it would be possible to determine multidecadal trends using ground‐based microwave instruments in a postsatellite era. This uncertainty is comparable to the trend in mesospheric water vapor that is expected to have occurred since the early 1990s.

Ozone depletion in the Arctic and Antarctic stratosphere induced by wildfire smoke

Abstract. A record-breaking stratospheric ozone loss was observed over the Arctic and Antarctica in 2020. Strong ozone depletion occurred over Antarctica in 2021 as well. The ozone holes developed in smoke-polluted air. In this article, the impact of Siberian and Australian wildfire smoke (dominated by organic aerosol) on the extraordinarily strong ozone reduction is discussed. The study is based on aerosol lidar observations in the North Pole region (October 2019–May 2020) and over Punta Arenas in southern Chile at 53.2∘ S (January 2020–November 2021) as well as on respective NDACC (Network for the Detection of Atmospheric Composition Change) ozone profile observations in the Arctic (Ny-Ålesund) and Antarctica (Neumayer and South Pole stations) in 2020 and 2021. We present a conceptual approach on how the smoke may have influenced the formation of polar stratospheric clouds (PSCs), which are of key importance in the ozone-depleting processes. The main results are as follows: (a) the direct impact of wildfire smoke below the PSC height range (at 10–12 km) on ozone reduction seems to be similar to well-known volcanic sulfate aerosol effects. At heights of 10–12 km, smoke particle surface area (SA) concentrations of 5–7 µm2 cm−3 (Antarctica, spring 2021) and 6–10 µm2 cm−3 (Arctic, spring 2020) were correlated with an ozone reduction in terms of ozone partial pressure of 0.4–1.2 mPa (about 30 % further ozone reduction over Antarctica) and of 2–3.5 mPa (Arctic, 20 %–30 % reduction with respect to the long-term springtime mean). (b) Within the PSC height range, we found indications that smoke was able to slightly increase the PSC particle number and surface area concentration. In particular, a smoke-related additional ozone loss of 1–2 mPa (10 %–20 % contribution to the total ozone loss over Antarctica) was observed in the 14–23 km PSC height range in September–October 2020 and 2021. Smoke particle number concentrations ranged from 10 to 100 cm−3 and were about a factor of 10 (in 2020) and 5 (in 2021) above the stratospheric aerosol background level. Satellite observations indicated an additional mean column ozone loss (deviation from the long-term mean) of 26–30 Dobson units (9 %–10 %, September 2020, 2021) and 52–57 Dobson units (17 %–20 %, October 2020, 2021) in the smoke-polluted latitudinal Antarctic belt from 70–80∘ S.

Impact of instrumental line shape characterization on ozone monitoring by FTIR spectrometry

Abstract. Retrieving high-precision concentrations of atmospheric trace gases from FTIR (Fourier transform infrared) spectrometry requires a precise knowledge of the instrumental performance. In this context, this paper examines the impact on the ozone (O3) retrievals of several approaches used to characterize the instrumental line shape (ILS) function of ground-based FTIR spectrometers within NDACC (Network for the Detection of Atmospheric Composition Change). The analysis has been carried out at the subtropical Izaña Observatory (IZO, Spain) by using the 20-year time series of the high-resolution FTIR solar absorption spectra acquired between 1999 and 2018. The theoretical quality assessment and the comparison to independent O3 observations available at IZO (Brewer O3 total columns and electrochemical concentration cell, ECC, sondes) reveal consistent findings. The inclusion of a simultaneous retrieval of the ILS parameters in the O3 retrieval strategy allows, on the one hand, a rough instrumental characterization to be obtained and, on the other hand, the precision of the FTIR O3 products to be slightly improved. The improvement is of special relevance above the lower stratosphere, where the cross-interference between the O3 vertical distribution and the instrumental performance is more significant. However, it has been found that the simultaneous ILS retrieval leads to a misinterpretation of the O3 variations on daily and seasonal scales. Therefore, in order to ensure the independence of the O3 retrievals and the instrumental response, the optimal approach to deal with the FTIR instrumental characterization is found to be the continuous monitoring of the ILS function by means of independent observations, such as gas cell measurements.

Variability of Water Vapor in Central Mexico from Two Remote Sensing Techniques: FTIR Spectroscopy and GPS

Abstract Total column H2O is measured by two remote sensing techniques at the Altzomoni Atmospheric Observatory (19°12′N, 98°65′W, 4000 m above sea level), a high-altitude, tropical background site in central Mexico. A ground-based solar absorption FTIR spectrometer that is part of the Network for Detection of Atmospheric Composition Change (NDACC) is used to retrieve water vapor in three spectral regions (6074–6471, 2925–2941, and 1110–1253 cm−1) and is compared to data obtained from a global positioning system (GPS) receiver that is part of the TLALOCNet GPS-meteorological network. Strong correlations are obtained between the coincident hourly means from the three FTIR products and small relative bias and correction factors could be determined for each when compared to the more consistent GPS data. Retrievals from the 2925–2941 cm−1 spectral region have the highest correlation with GPS [coefficient of determination (R2) = 0.998, standard deviation (STD) = 0.18 cm (78.39%), mean difference = 0.04 cm (8.33%)], although the other products are also highly correlated [R2 ≥ 0.99, STD ≤ 0.20 cm (<90%), mean difference ≤ 0.1 cm (<24%)]. Clear-sky dry bias (CSDB) values are reduced to <10% (<0.20 cm) when coincident hourly means are used in the comparison. The use of GPS and FTIR water vapor products simultaneously leads to a more complete and better description of the diurnal and seasonal cycles of water vapor. We describe the water vapor climatology with both complementary datasets, nevertheless, pointing out the importance of considering the clear-sky dry bias arising from the large diurnal and seasonal variability of water vapor at this high-altitude tropical site.

Ground-based validation of the MetOp-A and MetOp-B GOME-2 OClO measurements

Abstract. This paper reports on ground-based validation of the atmospheric OClO data record produced within the framework of EUMETSAT's Satellite Application Facility on Atmospheric Chemistry Monitoring (AC SAF) using the Global Ozone Monitoring Experiment (GOME)-2A and GOME-2B instrument measurements, covering the 2007–2016 and 2013–2016 periods, respectively. OClO slant column densities are compared to correlative measurements collected from nine Zenith-Scattered-Light Differential Optical Absorption Spectroscopy (ZSL-DOAS) instruments from the Network for the Detection of Atmospheric Composition Change (NDACC) distributed in both the Arctic and Antarctic. Sensitivity tests are performed on the ground-based data to estimate the impact of the different OClO DOAS analysis settings. On this basis, we infer systematic uncertainties of about 25 % (i.e., about 3.75×1013 molec. cm−2) between the different ground-based data analyses, reaching total uncertainties ranging from about 26 % to 33 % for the different stations (i.e., around 4 to 5×1013 molec. cm−2). Time series at the different sites show good agreement between satellite and ground-based data for both the inter-annual variability and the overall OClO seasonal behavior. GOME-2A results are found to be noisier than those of GOME-2B, especially after 2011, probably due to instrumental degradation effects. Daily linear regression analysis for OClO-activated periods yield correlation coefficients of 0.8 for GOME-2A and 0.87 for GOME-2B, with slopes with respect to the ground-based data ensemble of 0.64 and 0.72, respectively. Satellite minus ground-based offsets are within 8×1013 molec. cm−2, with some differences between GOME-2A and GOME-2B depending on the station. Overall, considering all the stations, a median offset of about -2.2×1013 molec. cm−2 is found for both GOME-2 instruments.

Three decades of remote sensing of NO2 vertical distribution and column content at the A. M. Obukhov Institute of Atmospheric Physics

The paper reviews the results of 30-year spectrometric measurements of vertical distribution and column content of NO2 at the Zvenigorod Scientific Station (ZSS) of the A. M. Obukhov Institute of Atmospheric Physics and presents analysis of NO2 long-term trends and interannual variations. The station is located in the western Moscow region. It is part of the Network for the Detection of Atmospheric Composition Change (NDACC). Measurements are done in the morning and evening twilight by zenith-scattered visible solar radiation. Vertical NO2 profiles are retrieved and column NO2 contents are calculated by profile integration. Long term trends and inter-annual variations of NO2 are analysed by multivariate regression method taking into account autocorrelation of data in a wide range of time scales. Seasonally dependent estimates of NO2 trends and interannual variations due to the quasi-biennial oscillation, El Nino–Southern oscillation, North Atlantic Oscillation, and the 11-year solar cycle are obtained. Most pronounced (in per cent units) trends and circulation and solar cycle effects are peculiar to the winter–spring period of the year. Mutual influence is assessed between the estimates of the trend and the solar cycle effect in stratospheric NO2.

Improved ozone monitoring by ground-based FTIR spectrometry

Abstract. Accurate observations of atmospheric ozone (O3) are essential to monitor in detail its key role in atmospheric chemistry. The present paper examines the performance of different O3 retrieval strategies from FTIR (Fourier transform infrared) spectrometry by using the 20-year time series of the high-resolution solar spectra acquired from 1999 to 2018 at the subtropical Izaña Observatory (IZO, Spain) within NDACC (Network for the Detection of Atmospheric Composition Change). In particular, the effects of two of the most influential factors have been investigated: the inclusion of a simultaneous atmospheric temperature profile fit and the spectral O3 absorption lines used for the retrievals (the broad spectral region of 1000–1005 cm−1 and single micro-windows between 991 and 1014 cm−1). Additionally, the water vapour (H2O) interference in O3 retrievals has been evaluated, with the aim of providing an improved O3 strategy that minimises its impact and, therefore, could be applied at any NDACC FTIR station under different humidity conditions. The theoretical and experimental quality assessments of the different FTIR O3 products (total column (TC) amounts and volume mixing ratio (VMR) profiles) provide consistent results. Combining a simultaneous temperature retrieval with the optimal selection of single O3 micro-windows results in superior FTIR O3 products, with a precision of better than 0.6 %–0.7 % for O3 TCs as compared to coincident NDACC Brewer observations taken as a reference. However, this improvement can only be achieved provided the FTIR spectrometer is properly characterised and stable over time. For unstable instruments, the temperature fit is found to exhibit a strong negative influence on O3 retrievals due to the increase in the cross-interference between the temperature retrieval and instrumental performance (given by the instrumental line shape function and measurement noise), which leads to a worsening of the precision of FTIR O3 TCs of up to 2 %. This cross-interference becomes especially noticeable beyond the upper troposphere/lower stratosphere, as documented theoretically as well as experimentally by comparing FTIR O3 profiles to those measured using electrochemical concentration cell (ECC) sondes within NDACC. Consequently, it should be taken into account for the reliable monitoring of the O3 vertical distribution, especially over long-term timescales.

Nitrous Oxide Profiling from Infrared Radiances (NOPIR): Algorithm Description, Application to 10 Years of IASI Observations and Quality Assessment

Nitrous oxide (N2O) is the third most abundant anthropogenous greenhouse gas (after carbon dioxide and methane), with a long atmospheric lifetime and a continuously increasing concentration due to human activities, making it an important gas to monitor. In this work, we present a new method to retrieve N2O concentration profiles (with up to two degrees of freedom) from each cloud-free satellite observation by the Infrared Atmospheric Sounding Interferometer (IASI), using spectral micro-windows in the N2O ν3 band, the Radiative Transfer for TOVS (RTTOV) tools and the Tikhonov regularization scheme. A time series of ten years (2011–2020) of IASI N2O profiles and integrated partial columns has been produced and validated with collocated ground-based Network for the Detection of Atmospheric Composition Change (NDACC) and Total Carbon Column Observing Network (TCCON) data. The importance of consistency in the ancillary data used for the retrieval for generating consistent time series has been demonstrated. The Nitrous Oxide Profiling from Infrared Radiances (NOPIR) N2O partial columns are of very good quality, with a positive bias of 1.8 to 4% with respect to the ground-based data, which is less than the sum of uncertainties of the compared values. At high latitudes, the comparisons are a bit worse, due to either a known bias in the ground-based data, or to a higher uncertainty in both ground-based and satellite retrievals.

Evaluation and Global-Scale Observation of Nitrous Oxide from IASI on Metop-A

Nitrous oxide (N2O) is a greenhouse gas difficult to estimate by satellite because of its weak spectral signature in the infra-red band and its low variability in the troposphere. Nevertheless, this study presents the evaluation of new tropospheric N2O observations from the Infrared Atmospheric Sounder Interferometer (IASI) on Metop-A using the Toulouse N2O Retrieval Version 2.0 tool. This tool is based on the Radiative Transfer for Tiros Operational Vertical sounder (RTTOV) model version 12.3 coupled to the Levenberg-Marquardt optimal estimation method enabling the simultaneous retrieval of methane, water vapour, temperature profiles together with surface temperature and emissivity within the 1240–1350 cm−1 window. In this study, we focused on the upper troposphere (300 hPa) where the sensitivity of IASI is significant. The IASI N2O data has been evaluated using aircraft N2O observations from the High-performance Instrumented Airborne Platform for Environmental Research Pole-to-Pole Observations (HIPPO) campaigns in 2009, 2010, and 2011 and from the National Oceanic and Atmospheric Administration’s (NOAA) Global Greenhouse Gas Reference Network (GGGRN) in 2011. In addition, we evaluated the IASI N2O using ground-based N2O measurements from 9 stations belonging to the Network for the Detection of Atmospheric Composition Change (NDACC). We found a total random error of ∼2 ppbv (0.6%) for one single retrieval at 300 hPa. Under favorable conditions, this error is also found in the vertical level pressure range 300–500 hPa. It decreases rapidly to ∼0.4 ppbv (0.1%) when we average on a 1° × 1° box. In addition, independent observations allows the estimation of bias with the IASI TN2OR v2.0 N2O. The bias between IASI and aircraft N2O data at 300 hPa is ∼1.0 ppbv (∼0.3%). We found an estimated random error of ∼2.3 ppbv (∼0.75%). This study also shows relatively high correlations between IASI data and aircraft in situ profiles but more varying correlations over the year 2011 depending on the location between IASI and NDACC remote sensing data. Finally, we present daily, monthly, and seasonal IASI N2O horizontal distributions in the upper troposphere as well as cross sections for different seasons that exhibit maxima in the Tropical band especially over Africa and South America.

Global Atmospheric OCS Trend Analysis From 22 NDACC Stations

AbstractCarbonyl sulfide (OCS) is a non‐hygroscopic trace species in the free troposphere and a large sulfur reservoir maintained by both direct oceanic, geologic, biogenic, and anthropogenic emissions and the oxidation of other sulfur‐containing source species. It is the largest source of sulfur transported to the stratosphere during volcanically quiescent periods. Data from 22 ground‐based globally dispersed stations are used to derive trends in total and partial column OCS. Middle infrared spectral data are recorded by solar‐viewing Fourier transform interferometers that are operated as part of the Network for the Detection of Atmospheric Composition Change between 1986 and 2020. Vertical information in the retrieved profiles provides analysis of discreet altitudinal regions. Trends are found to have well‐defined inflection points. In two linear trend time periods ∼2002 to 2008 and ∼2008 to 2016 tropospheric trends range from ∼0.0 to (1.55 ± 0.30%/yr) in contrast to the prior period where all tropospheric trends are negative. Regression analyses show strongest correlation in the free troposphere with anthropogenic emissions. Stratospheric trends in the period ∼2008 to 2016 are positive up to (1.93 ± 0.26%/yr) except notably low latitude stations that have negative stratospheric trends. Since ∼2016, all stations show a free tropospheric decrease to 2020. Stratospheric OCS is regressed with simultaneously measured N2O to derive a trend accounting for dynamical variability. Stratospheric lifetimes are derived and range from (54.1 ± 9.7)yr in the sub‐tropics to (103.4 ± 18.3)yr in Antarctica. These unique long‐term measurements provide new and critical constraints on the global OCS budget.

The Relationship between Clouds Containing Multiple Layers 7.5–30 m Thick and Surface Weather Conditions

Previous studies have identified finely laminated, or layered, features within Arctic clouds. This study focuses on quasi-horizontal layers that are 7.5 to 30 m thick, within clouds from 0 to 5 km altitude. No pre-selection for any particular cloud types was made prior to the identification of laminations. We capitalize on the 4-year measurement record available from Eureka, Nunavut (79.6∘ N, 85.6∘ W), using the Canadian Network for the Detection of Atmospheric Composition Change (CANDAC) Rayleigh–Mie–Raman Lidar (CRL; 1 min, 7.5 m resolution). Laminated features are identified on 18% of all days, from 2016–2019. Their presence is conclusively excluded on 12% of days. March, April, and May have a higher measurement cadence and show laminations on 41% of days. Individual months show laminations on up to 50% of days. Our results suggest that laminations are not rare phenomena at Eureka. To determine laminations’ likely contribution to Arctic weather and climate, local weather reports were obtained from the nearby Environment and Climate Change Canada (ECCC) weather station. Days with laminated clouds are strongly correlated with precipitating snow (r = 0.63), while days with non-laminated clouds (r = −0.40) and clear sky days (r = −0.43) are moderately anti-correlated with snow precipitation.

Advanced NO<sub>2</sub> retrieval technique for the Brewer spectrophotometer applied to the 20-year record in Rome, Italy

Abstract. A re-evaluated data set of nitrogen dioxide (NO2) column densities over Rome for the years 1996 to 2017 is here presented. This long-term record is obtained from ground-based direct sun measurements with a MkIV Brewer spectrophotometer (serial number #067) and further reprocessed using a novel algorithm. Compared to the original Brewer algorithm, the new method includes updated NO2 absorption cross sections and Rayleigh scattering coefficients, and it accounts for additional atmospheric compounds and instrumental artefacts, such as the spectral transmittance of the filters, the alignment of the wavelength scale, and internal temperature. Moreover, long-term changes in the Brewer radiometric sensitivity are tracked using statistical methods for in-field calibration. The resulting series presents only a few (about 30) periods with missing data longer than 1 week and features NO2 retrievals for more than 6100 d, covering nearly 80 % of the considered 20-year period. The high quality of the data is demonstrated by two independent comparisons. In the first intensive campaign, Brewer #067 is compared against another Brewer (#066), recently calibrated at the Izaña Atmospheric Observatory through the Langley method and there compared to reference instrumentation from the Network for the Detection of Atmospheric Composition Change (NDACC). Data from this campaign show a highly significant Pearson's correlation coefficient of 0.90 between the two series of slant column densities (SCDs), slope 0.98 and offset 0.05 DU (Dobson units; 1.3×1015 molec.cm-2). The average bias between the vertical column densities is 0.03 DU (8.1×1014 molec.cm-2), well within the combined uncertainty of both instruments. Brewer #067 is also independently compared with new-generation instrumentation, a co-located Pandora spectrometer (#117), over a 1-year-long period (2016–2017) at Sapienza University of Rome, showing linear correlation indices above 0.96 between slant column densities, slope of 0.97, and offset of 0.02 DU (5.4×1014 molec.cm-2). The average bias between vertical column densities is negligible (−0.002 DU or -5.4×1013 molec.cm-2). This, incidentally, represents the first intercomparison of NO2 retrievals between a MkIV Brewer and a Pandora instrument. Owing to its accuracy and length, the Brewer data set collected in Rome can be useful for satellite calibration/validation exercises, comparison with photochemical models, and better aerosol optical depth estimates (NO2 optical depth climatology). In addition, it can be employed to identify long-term trends in NO2 column densities in a metropolitan environment, over two decades witnessing important changes in environmental policies, emission loads and composition, and the effect of a worldwide economic recession, to offer just a few examples. The method can be replicated on the more than 80 MkIV spectrophotometers operating worldwide in the frame of the international Brewer network. The NO2 data set described in this paper can be freely accessed at https://doi.org/10.5281/zenodo.4715219 (Diémoz and Siani, 2021).