Partial Column Research Articles

Intercomparison of long-term ground-based measurements of total, tropospheric, and stratospheric ozone at Lauder, New Zealand

Abstract. Long-term, 21st century ground-based ozone measurements are crucial to study the recovery of stratospheric ozone as well as the trends of tropospheric ozone. This study is performed in the context of the LOTUS (Long-term Ozone Trends and Uncertainties in the Stratosphere) and TOAR-II (Tropospheric Ozone Assessment Report, phase II) initiatives. Within LOTUS, we want to know why different trends have been observed by different ground-based measurements at Lauder. In TOAR-II, intercomparison studies among the different ground-based datasets are needed to evaluate their quality and relevance for trend studies. To achieve these goals, we perform an intercomparison study of total column ozone and its vertical distribution among the ground-based measurement instruments available at the Lauder station from 2000 to 2022, which are a Fourier transform infrared (FTIR) spectrometer, a Dobson spectrophotometer, a UV2 (ultraviolet double monochromator), a microwave radiometer (MWR), ozonesondes, and a stratospheric lidar. Because only the latter two provide high-vertical-resolution profiles, the vertical ozone distribution is validated using partial columns, defined to provide independent information: one tropospheric column and three stratospheric columns. Because FTIR provides total columns and vertical information covering all partial columns as well as high temporal sampling, the intercomparisons (bias, scatter, and drift) are analyzed using FTIR as the reference. Very good agreement between the FTIR and Dobson (FTIR and UV2) total column ozone records is apparent in the high Pearson correlation of 0.97 (0.93), low biases of −3 % (−2 %), and 2 % (3 %) dispersions, which are within the respective systematic and random uncertainties. The small observed drifts 0.4 % (0.3 %) per decade are “non-significant” (or rather a low certainty in a 95 % confidence interval) and show good stability of the three ozone total column series at Lauder. In the troposphere we find a small bias of −1.9 % with the ozonesondes but a larger one (+10.7 %) with Umkehr, which can be explained by the low degrees of freedom for signal (0.5) of Umkehr in the troposphere. However, no significant drift is found among the three instruments in the troposphere, which proves their relevance for trend studies within TOAR-II. The negative bias observed in total columns is confirmed by negative biases in all stratospheric columns for all instruments with respect to FTIR (between −1.2 % and −6.8 %). This, confirmed by the total column biases, points to a 2 %–3 % underestimation of the infrared spectroscopic line intensities. Nevertheless, the dispersion between FTIR and all techniques is typically within 5 % for the stratospheric partial columns, in close agreement with the given random uncertainty budgets. We observe no significant drift in the stratosphere between ozonesondes and FTIR for all partial columns, with ozonesonde trends being less negative than in LOTUS (Godin-Beekmann et al., 2022, further referred to as the LOTUS22). The only significant drift in the lower-stratospheric columns is obtained between FTIR and Umkehr, as was already found in LOTUS22. Two significant positive drifts are observed in the middle stratosphere (2 % and 3 % per decade) with lidar and MWR, respectively, while two significant negative drifts are observed in the upper stratosphere (−3 % and −4 % per decade) with Umkehr and lidar, respectively. While remaining drifts are still present, our study explains roughly half of the differences in observed trends in LOTUS22 by the different sampling, vertical sensitivity, or time periods and gaps. In addition, the FTIR data in the present work have been improved since LOTUS22, reducing the differences in the upper-stratospheric and tropospheric trends. This shows the necessity for continuous review and improvement of the measurement and retrieval processes. This study also reflects the importance of super sites such as Lauder for cross-validating the long-term ozone measurements. Our study demonstrated that well-harmonized, optimized, well-characterized instruments that show very good agreement in terms of bias, dispersion, and correlation are capable of detecting trends that agree within their respective measurement uncertainties.

The impact of El Niño–Southern Oscillation on the total column ozone over the Tibetan Plateau

Abstract. The Tibetan Plateau (TP; approximately 27.5–37.5° N, 75.5–105.5° E) is the highest and largest plateau on Earth with a mean elevation of over 4 km. This special geography causes strong surface solar ultraviolet radiation (UV), with potential risks to human and ecosystem health, which is mainly controlled by the local stratospheric ozone concentration. The El Niño–Southern Oscillation (ENSO), the dominant mode of interannual variability on Earth, is characterised by the tropical Pacific Ocean sea surface temperature anomalies (SSTAs) and sea level pressure change for the warm-phase El Niño and cold-phase La Niña events. Although some studies have suggested the existence of positive correlation between ENSO and the total column ozone (TCO) over the TP, the mechanism underlying this effect is not fully understood. Here we use the Copernicus Climate Change Service (C3S) merged satellite dataset, the Stratospheric Water and OzOne Satellite Homogenized (SWOOSH) dataset and the TOMCAT three-dimensional (3D) offline chemical transport model forced by ERA5 meteorological reanalyses from the European Centre for Medium-Range Weather Forecasts (ECMWF) over the period 1979–2021 to investigate the influence of ENSO on the TCO over the TP. We find that the El Niño (La Niña) events favour positive (negative) TCO anomalies over the TP from wintertime of its mature phase to springtime of its decaying phase. Through studying the ozone profile, we attribute the positive (negative) TCO anomalies mainly to the increased (decreased) ozone at the 200–70 hPa levels, i.e. in the upper troposphere and lower stratosphere (UTLS) regions. Our results suggest that the El Niño events impact the TP TCO via the following potential processes: (1) a negative upper-level geopotential height anomaly associated with El Niño is responsible for a decrease in air column thickness; (2) the thickness decrease modulates reduced tropospheric temperature and thus favours a decrease in the tropopause height (TH); and (3) such a TH decrease tends to induce a change in the relative amounts of ozone-poor tropospheric and ozone-rich stratospheric air in the profile, which increases the partial column ozone in the UTLS and hence corresponds to the TP TCO increase. The La Niña events affect TP TCO in a manner resembling the El Niño events, except with anomalies of opposite sign. This work provides a systematic understanding of the influence of ENSO on ozone over the TP, which has implications for the interannual variability of ozone.

Surface snow bromide and nitrate at Eureka, Canada, in early spring and implications for polar boundary layer chemistry

Abstract. This study explores the role of snowpack in polar boundary layer chemistry, especially as a direct source of reactive bromine (BrOx = BrO + Br) and nitrogen (NOx = NO + NO2) in the Arctic springtime. Surface snow samples were collected daily from a Canadian high Arctic location at Eureka, Nunavut (80° N, 86° W) from the end of February to the end of March in 2018 and 2019. The snow was sampled at several sites representing distinct environments: sea ice, inland close to sea level, and a hilltop ∼ 600 m above sea level (a.s.l.). At the inland sites, surface snow salinity has a double-peak distribution with the first and lowest peak at 0.001–0.002 practical salinity unit (psu), which corresponds to the precipitation effect, and the second peak at 0.01–0.04 psu, which is likely related to the salt accumulation effect (due to loss of water vapour by sublimation). Snow salinity on sea ice has a triple-peak distribution; its first and second peaks overlap with the inland peaks, and the third peak at 0.2–0.4 psu is likely due to the sea water effect (a result of upward migration of brine). At all sites, snow sodium and chloride concentrations increase by almost 10-fold from the top 0.2 to ∼ 1.5 cm. Surface snow bromide at sea level is significantly enriched, indicating a net sink of atmospheric bromine. Moreover, surface snow bromide at sea level has an increasing trend over the measurement period, with mean slopes of 0.024 µM d−1 in the 0–0.2 cm layer and 0.016 µM d−1 in the 0.2–0.5 cm layer. Surface snow nitrate at sea level also shows a significant increasing trend, with mean slopes of 0.27, 0.20, and 0.07 µM d−1 in the top 0.2, 0.2–0.5, and 0.5–1.5 cm layers, respectively. Using these trends, an integrated net deposition flux of bromide of (1.01 ± 0.48) × 107 molec.cm-2s-1 and an integrated net deposition flux of nitrate of (2.6 ± 0.37) × 108 molec.cm-2s-1 were derived. In addition, the surface snow nitrate and bromide at inland sites were found to be significantly correlated (R = 0.48–0.76) with the [NO3-]/[Br-] ratio of 4–7 indicating a possible acceleration effect of reactive bromine in atmospheric NOx-to-nitrate conversion. This is the first time such an effect has been seen in snow chemistry data obtained with a sampling frequency as short as 1 d. BrO partial column (0–4 km) data measured by MAX-DOAS show a decreasing trend in early spring, which generally agrees with the derived surface snow bromide deposition flux indicating that bromine in Eureka atmosphere and surface snow did not reach a photochemical equilibrium state. Through mass balance analysis, we conclude that the average release flux of reactive bromine from snow over the campaign period must be smaller than the derived bromide deposition flux of ∼ 1 × 107 molec.cm-2s-1. Note that the net mean fluxes observed do not completely rule out larger bidirectional fluxes over shorter timescales.

Solar FTIR measurements of NOx vertical distributions – Part 1: First observational evidence of a seasonal variation in the diurnal increasing rates of stratospheric NO2 and NO

Abstract. Observations of nitrogen dioxide (NO2) and nitrogen oxide (NO) in the stratosphere are relevant to understand long-term changes and variabilities in stratospheric nitrogen oxide (NOx) and ozone (O3) concentrations. Due to the versatile role of NO2 and NO in stratospheric O3 photochemistry, they are important for recovery and build-up of O3 holes in the stratosphere and therefore can indirectly affect human life. Thus, we present in this work the evaluation of NO2 and NO stratospheric partial columns (> 16 km altitude) retrieved from ground-based Fourier-transform infrared (FTIR) measurements of over 25 years at Zugspitze (47.42° N, 10.98° E; 2964 m a.s.l.) and 18 years at Garmisch (47.47° N, 11.06° E; 745 m a.s.l.), Germany. The obtained stratospheric columns are only weakly influenced by tropospheric pollution and show only a very small bias of 2.5 ± 0.2 % when comparing NO2 above Zugspitze and Garmisch. Stratospheric columns of both NO2 and NO show a diurnal increase that depends on local solar time (LST). We quantified this behavior by calculating diurnal increasing rates. Here, we find mean values for the NO2 diurnal increasing rate of (0.89 ± 0.14) × 1014 and (0.94 ± 0.14) × 1014 cm−2 h−1 at Zugspitze and Garmisch, respectively. The mean NO morning diurnal increasing rate above Zugspitze is found to be (1.42 ± 0.12) × 1014 cm−2 h−1. Regarding the seasonal dependency of these increasing rates, for the first time, we were able to experimentally detect a significant seasonal variation in both NO2 diurnal increasing rates and NO morning diurnal increasing rates with a maximum of (1.13 ± 0.04) × 1014 cm−1 h−1 for NO2 and (1.76 ± 0.25) × 1014 cm−1 h−1 for NO in September and a minimum of (0.71 ± 0.18) × 1014 cm−1 h−1 in December for NO2 and a minimum of (1.18 ± 0.41) × 1014 cm−1 h−1 in November for NO. This similar behavior may be explained by the interconnection of both species in stratospheric photochemistry. The outcome of this work is a retrieval and analysis strategy of FTIR data for NOx stratospheric columns, which can help to further validate photochemical models or improve satellite validations. The first use of this data set is shown in the companion paper (Nürnberg et al., 2023) wherein experiment-based NOx scaling factors describing the diurnal increase in the retrieved partial columns are extracted and recently published model-based scaling factors are validated.

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.

Inferring the vertical distribution of CO and CO2 from TCCON total column values using the TARDISS algorithm

Abstract. We describe an approach for determining limited information about the vertical distribution of carbon monoxide (CO) and carbon dioxide (CO2) from total column ground-based Total Carbon Column Observation Network (TCCON) observations. For CO and CO2, it has been difficult to retrieve information about their vertical distribution from spectral line shapes because of the errors in the spectroscopy and the atmospheric temperature profile that mask the effects of variations in their mixing ratio with altitude. For CO2 the challenge is especially difficult given that these variations are typically 2 % or less. Nevertheless, if sufficient accuracy can be obtained, such information would be highly valuable for evaluation of retrievals from satellites and more generally for improving the estimate of surface sources and sinks of these trace gases. We present here the Temporal Atmospheric Retrieval Determining Information from Secondary Scaling (TARDISS) retrieval algorithm. TARDISS uses several simultaneously obtained total column observations of the same gas from different absorption bands with distinctly different vertical averaging kernels. The different total column retrievals are combined in TARDISS using a Bayesian approach where the weights and temporal covariance applied to the different retrievals include additional constraints on the diurnal variation in the vertical distribution for these gases. We assume that the near-surface part of the column varies rapidly over the course of a day (from surface sources and sinks, for example) and that the upper part of the column has a larger temporal covariance over the course of a day. Using measurements from the five North American TCCON sites, we find that the retrieved lower partial column (between the surface and ∼ 800 hPa) of the CO and CO2 dry mole fractions (DMFs) have slopes of 0.999 ± 0.002 and 1.001 ± 0.003 with respect to lower column DMF from integrated in situ data measured directly from aircraft and in AirCores. The average error for our lower column CO retrieval is 1.51 ppb (∼ 2 %) while the average error for our CO2 retrieval is 5.09 ppm (∼ 1.25 %). Compared with classical line-shape-derived vertical profile retrievals, our algorithm reduces the influence of forward model errors such as imprecision in spectroscopy (line shapes and intensities) and in the instrument line shape. In addition, because TARDISS uses the existing retrieved column abundances from TCCON (which themselves are computationally much less intensive than profile retrieval algorithms), it is very fast and processes years of data in minutes. We anticipate that this approach will find broad application for use in carbon cycle science.

South Pole Station ozonesondes: variability and trends in the springtime Antarctic ozone hole 1986–2021

Abstract. Balloon-borne ozonesondes launched weekly from South Pole Station (1986–2021) measure high-vertical-resolution profiles of ozone and temperature from the surface to 30–35 km altitude. The launch frequency is increased in late winter before the onset of rapid stratospheric ozone loss in September. Ozone hole metrics show that the yearly total column ozone and 14–21 km partial column ozone minimum values and September loss rate trends have been improving (less severe) since 2001. The 36-year record also shows interannual variability, especially in recent years (2019–2021). Here we show additional details of these 3 years by comparing annual minimum profiles observed on the date when the lowest integrated total column ozone occurs. We also compare the July–December time series of the 14–21 km partial column ozone values to the 36-year median with percentile intervals. The 2019 anomalous vortex breakdown showed stratospheric temperatures began warming in early September followed by reduced ozone loss. The minimum total column ozone of 180 Dobson units (DU) was observed on 24 September. This was followed by two stable and cold polar vortex years during 2020 and 2021 with total column ozone minimums at 104 DU (1 October) and 102 DU (7 October), respectively. These years also showed broad near-zero-ozone (loss saturation) regions within the 14–21 km layer by the end of September which persisted into October. Validation of the ozonesonde observations is conducted through the ongoing comparison of total column ozone measurements with the South Pole ground-based Dobson spectrophotometer. The ozonesondes show a more positive bias of 2 ± 3 % (higher) than the Dobson following a thorough evaluation and homogenization of the long-term ozonesonde record completed in 2018.

Design of Implicit Partial Product-LDPC Codes and Low Complexity Decoding Algorithm

In this letter, we are concerned with a recently proposed class of product codes, called implicit partial product low-density parity-check (IP-LDPC) codes, which consist of LDPC codes for rows and Bose-Chaudhuri-Hocquenghem (BCH) codes for columns. Distinguished from the conventional product codes, only partial columns are doubly-protected and the column checks are transmitted implicitly rather than explicitly. For any given LDPC code, we present three heuristic rules to design an IP-LDPC code with the same code rate, showing how to select the number of doubly-protected columns and the BCH code (for columns). The stringent constraint is that the product of the number of doubly-protected columns and the length of syndrome per column must be less than or equal to the product of the number of the rows and the length of extra bits that can be carried reliably and implicitly per row (LDPC codeword). We also propose a simple bit-flipping algorithm for the column decoding in the case when the number of unsuccessfully decoded rows is relatively small, which occurs often especially when the iterative decoding is implemented. The simulation results show that IP-LDPC codes can lower down the word error rate (WER) of a (3,6)-regular LDPC code with length 1024 from 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">−2</sup> to 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">−6</sup> at the SNR around 2.0 dB but without any code rate loss.

Multi-axis differential optical absorption spectroscopy (MAX-DOAS) observations of formaldehyde and nitrogen dioxide at three sites in Asia and comparison with the global chemistry transport model CHASER

Abstract. Formaldehyde (HCHO) and nitrogen dioxide (NO2) concentrations and profiles were retrieved from ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) observations during January 2017–December 2018 at three sites in Asia: (1) Phimai (15.18∘ N, 102.5∘ E), Thailand; (2) Pantnagar (29∘ N, 78.90∘ E) in the Indo-Gangetic Plain (IGP), India; and (3) Chiba (35.62∘ N, 140.10∘ E), Japan. Retrievals were performed using the Japanese MAX-DOAS profile retrieval algorithm ver. 2 (JM2). The observations were used to evaluate the NO2 and HCHO partial columns and profiles (0–4 km) simulated using the global chemistry transport model (CTM) CHASER (Chemical Atmospheric General Circulation Model for Study of Atmospheric Environment and Radiative Forcing). The NO2 and HCHO concentrations at all three sites showed consistent seasonal variation throughout the investigated period. Biomass burning affected the HCHO and NO2 variations at Phimai during the dry season and at Pantnagar during spring (March–May) and post-monsoon (September–November). Results found for the HCHO-to-NO2 ratio (RFN), an indicator of high ozone sensitivity, indicate that the transition region (i.e., 1 &lt; RFN &lt; 2) changes regionally, echoing the recent finding for RFN effectiveness. Moreover, reasonable estimates of transition regions can be derived, accounting for the NO2–HCHO chemical feedback. The model was evaluated against global NO2 and HCHO columns data retrieved from Ozone Monitoring Instrument (OMI) observations before comparison with ground-based datasets. Despite underestimation, the model well simulated the satellite-observed global spatial distribution of NO2 and HCHO, with respective spatial correlations (r) of 0.73 and 0.74. CHASER demonstrated good performance, reproducing the MAX-DOAS-retrieved HCHO and NO2 abundances at Phimai, mainly above 500 m from the surface. Model results agree with the measured variations within the 1-sigma (1σ) standard deviation of the observations. Simulations at higher resolution improved the modeled NO2 estimates for Chiba, reducing the mean bias error (MBE) for the 0–2 km height by 35 %, but resolution-based improvements were limited to surface layers. Sensitivity studies show that at Phimai, pyrogenic emissions contribute up to 50 % and 35 % to HCHO and NO2 concentrations, respectively.

TROPESS/CrIS carbon monoxide profile validation with NOAA GML and ATom in situ aircraft observations

Abstract. The new single-pixel TROPESS (TRopospheric Ozone and its Precursors from Earth System Sounding) profile retrievals of carbon monoxide (CO) from the Cross-track Infrared Sounder (CrIS) are evaluated using vertical profiles of in situ observations from the National Oceanic and Atmospheric Administration (NOAA) Global Monitoring Laboratory (GML) aircraft program and from the Atmospheric Tomography Mission (ATom) campaigns. The TROPESS optimal estimation retrievals are produced using the MUSES (MUlti-SpEctra, MUlti-SpEcies, MUlti-Sensors) algorithm, which has heritage from retrieval algorithms developed for the EOS/Aura Tropospheric Emission Spectrometer (TES). TROPESS products provide retrieval diagnostics and error covariance matrices that propagate instrument noise as well as the uncertainties from sequential retrievals of parameters such as temperature and water vapor that are required to estimate the carbon monoxide profiles. The validation approach used here evaluates biases in column and profile values as well as the validity of the retrieval error estimates using the mean and variance of the compared satellite and aircraft observations. CrIS–NOAA GML comparisons had biases of 0.6 % for partial column average volume mixing ratios (VMRs) and (2.3, 0.9, −4.5) % for VMRs at (750, 511, 287) hPa vertical levels, respectively, with standard deviations from 9 % to 14 %. CrIS–ATom comparisons had biases of −0.04 % for partial column and (2.2, 0.5, −3.0) % for (750, 511, 287) hPa vertical levels, respectively, with standard deviations from 6 % to 10 %. The reported observational errors for TROPESS/CrIS CO profiles have the expected behavior with respect to the vertical pattern in standard deviation of the comparisons. These comparison results give us confidence in the use of TROPESS/CrIS CO profiles and error characterization for continuing the multi-decadal record of satellite CO observations.

Synergetic use of IASI profile and TROPOMI total-column level 2 methane retrieval products

Abstract. The thermal infrared nadir spectra of IASI (Infrared Atmospheric Sounding Interferometer) are successfully used for retrievals of different atmospheric trace gas profiles. However, these retrievals offer generally reduced information about the lowermost tropospheric layer due to the lack of thermal contrast close to the surface. Spectra of scattered solar radiation observed in the near-infrared and/or shortwave infrared, for instance by TROPOMI (TROPOspheric Monitoring Instrument), offer higher sensitivity near the ground and are used for the retrieval of total-column-averaged mixing ratios of a variety of atmospheric trace gases. Here we present a method for the synergetic use of IASI profile and TROPOMI total-column level 2 retrieval products. Our method uses the output of the individual retrievals and consists of linear algebra a posteriori calculations (i.e. calculation after the individual retrievals). We show that this approach has strong theoretical similarities to applying the spectra of the different sensors together in a single retrieval procedure but with the substantial advantage of being applicable to data generated with different individual retrieval processors, of being very time efficient, and of directly benefiting from the high quality and most recent improvements of the individual retrieval processors. We demonstrate the method exemplarily for atmospheric methane (CH4). We perform a theoretical evaluation and show that the a posteriori combination method yields a total-column-averaged CH4 product (XCH4) that conserves the good sensitivity of the corresponding TROPOMI product while merging it with the high-quality upper troposphere–lower stratosphere (UTLS) CH4 partial-column information of the corresponding IASI product. As a consequence, the combined product offers additional sensitivity for the tropospheric CH4 partial column, which is not provided by the individual TROPOMI nor the individual IASI product. The theoretically predicted synergetic effect is verified by comparisons to CH4 reference data obtained from collocated XCH4 measurements at 14 globally distributed TCCON (Total Carbon Column Observing Network) stations, CH4 profile measurements made by 36 individual AirCore soundings, and tropospheric CH4 data derived from continuous ground-based in situ observations made at two nearby Global Atmospheric Watch (GAW) mountain stations. The comparisons clearly demonstrate that the combined product can reliably detect the actual variations of atmospheric XCH4, CH4 in the UTLS, and CH4 in the troposphere. A similar good reliability for the latter is not achievable by the individual TROPOMI and IASI products.

Retrieving H&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt;O/HDO columns over cloudy and clear-sky scenes from the Tropospheric Monitoring Instrument (TROPOMI)

Abstract. This paper presents an extended scientific HDO/H2O total column data product from short-wave infrared (SWIR) measurements by the Tropospheric Monitoring Instrument (TROPOMI) including clear-sky and cloudy scenes. The retrieval employs a forward model which accounts for scattering, and the algorithm infers the trace gas column information, surface properties, and effective cloud parameters from the observations. Compared to the previous clear-sky-only data product, coverage is greatly enhanced by including scenes over low clouds, particularly enabling data over oceans as the albedo of water in the SWIR spectral range is too low to retrieve under cloud-free conditions. The new dataset is validated against co-located ground-based Fourier transform infrared (FTIR) observations by the Total Carbon Column Observing Network (TCCON). The median bias for clear-sky scenes is 1.4×1021 molec cm−2 (2.9 %) in H2O columns and 1.1×1017 molec cm−2 (−0.3 %) in HDO columns, which corresponds to −17 ‰ (9.9 %) in a posteriori δD. The bias for cloudy scenes is 4.9×1021 molec cm−2 (11 %) in H2O, 1.1×1018 molec cm−2 (7.9 %) in HDO, and −20 ‰ (9.7 %) in a posteriori δD. At low-altitude stations, the bias is small at low and middle latitudes and has a larger value at high latitudes. At high-altitude stations, an altitude correction is required to compensate for different partial columns seen by the station and the satellite. The bias in a posteriori δD after altitude correction depends on sensitivity due to shielding by clouds and on realistic a priori profile shapes for both isotopologues. Cloudy scenes generally involve low sensitivity below the clouds, and since the information is filled up by the prior, a realistic shape of the prior is important for realistic total column estimation in these cases. Over oceans, aircraft measurements with the Water Isotope System for Precipitation and Entrainment Research (WISPER) instrument from a field campaign in 2018 are used for validation, yielding biases of −3.9 % in H2O and −3 ‰ in δD over clouds. To demonstrate the added value of the new dataset, a short case study of a cold air outbreak over the Atlantic Ocean in January 2020 is presented, showing the daily evolution of the event with single-overpass results.

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.

Ozone pollution during the COVID-19 lockdown in the spring of 2020 over Europe, analysed from satellite observations, in situ measurements, and models

Abstract. We present a comprehensive study integrating satellite observations of ozone pollution, in situ measurements, and chemistry-transport model simulations for quantifying the role of anthropogenic emission reductions during the COVID-19 lockdown in spring 2020 over Europe. Satellite observations are derived from the IASI+GOME2 (Infrared Atmospheric Sounding Interferometer + Global Ozone Monitoring Experiment 2) multispectral synergism, which provides better sensitivity to near-surface ozone pollution. These observations are mainly analysed in terms of differences between the average on 1–15 April 2020, when the strictest lockdown restrictions took place, and the same period in 2019. They show clear enhancements of near-surface ozone in central Europe and northern Italy, as well as some other hotspots, which are typically characterized by volatile organic compound (VOC)-limited chemical regimes. An overall reduction of ozone is observed elsewhere, where ozone chemistry is limited by the abundance of NOx. The spatial distribution of positive and negative ozone concentration anomalies observed from space is in relatively good quantitative agreement with surface in situ measurements over the continent (a correlation coefficient of 0.55, a root-mean-squared difference of 11 ppb, and the same standard deviation and range of variability). An average difference of ∼ 8 ppb between the two observational datasets is observed, which can partly be explained by the fact the satellite approach retrieves partial columns of ozone with a peak sensitivity above the surface (near 2 km of altitude over land and averaging kernels reaching the middle troposphere over ocean). For assessing the impact of the reduction of anthropogenic emissions during the lockdown, we adjust the satellite and in situ surface observations for subtracting the influence of meteorological conditions in 2020 and 2019. This adjustment is derived from the chemistry-transport model simulations using the meteorological fields of each year and identical emission inventories. Using adjustments adapted for the altitude and sensitivity of each observation, both datasets show consistent estimates of the influence of lockdown emission reduction. They both show lockdown-associated ozone enhancements in hotspots over central Europe and northern Italy, with a reduced amplitude with respect to the total changes observed between the 2 years and an overall reduction elsewhere over Europe and the ocean. Satellite observations additionally provide the ozone anomalies in the regions remote from in situ sensors, an enhancement over the Mediterranean likely associated with maritime traffic emissions, and a marked large-scale reduction of ozone elsewhere over ocean (particularly over the North Sea), in consistency with previous assessments done with ozone sonde measurements in the free troposphere. These observational assessments are compared with model-only estimations, using the CHIMERE chemistry-transport model. Whereas a general qualitative consistency of positive and negative ozone anomalies is observed with respect to observational estimates, significant changes are seen in their amplitudes. Models underestimate the range of variability of the ozone changes by at least a factor 2 with respect to the two observational datasets, both for enhancements and decreases of ozone. Moreover, a significant ozone decrease observed at a large hemispheric scale is not simulated since the modelling domain is the European continent. As simulations only consider the troposphere, the influence from stratospheric ozone is also missing. Sensitivity analyses also show an important role of vertical mixing of atmospheric constituents, which depends on the meteorological fields used in the simulation and significantly modify the amplitude of the changes of ozone pollution during the lockdown.

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.

First Airborne Measurements With a G-Band Differential Absorption Radar

Observations and analysis from the first airborne deployment of a G-band atmospheric radar, the Jet Propulsion Laboratory&#x2019;s vapor in-cloud profiling radar (VIPR), are presented with a focus on ocean surface scatterometry and water vapor retrievals using the differential absorption radar (DAR) technique. We assess transceiver cross-calibration stability between the two DAR frequency channels using a combination of ground-based calibration measurements and airborne cloud observations that are validated by independent sensors. By comparing calibrated, unattenuated ocean surface backscatter measurements with existing models, we demonstrate the need for improvements in treating ocean surface scattering at G-band frequencies for future in-flight radar calibration applications. During science-oriented flights off the coast of California, we demonstrate partial column integrated water vapor (IWV) measurement capabilities with 0.3-mm precision in clear sky by performing a descent maneuver over an operational radiosonde (RS) launching site and comparing with the coincident <i>in situ</i> profiles to find a root mean square error (RMSE) of 0.5 mm. Furthermore, we present water vapor profiling and IWV measurements in the presence of clouds and precipitation when flying through a frontal weather system in the vicinity of Bodega Bay. By comparing with coincident RS profiles, we find an RMSE for in-cloud humidity profile retrievals of 1.1 <inline-formula> <tex-math notation="LaTeX">${\rm gm}^{-3}$ </tex-math></inline-formula> and precision of 0.6 <inline-formula> <tex-math notation="LaTeX">${\rm gm}^{-3}$ </tex-math></inline-formula> while the IWV retrievals reveal a bias from differential hydrometeor extinction of 5 mm. We provide a critical assessment of cloud-scattering-induced biases in the water vapor retrievals, as well as discuss a potential method for eliminating systematic error from the DAR measurements.

Intercomparison of CO measurements from TROPOMI, ACE-FTS, and a high-Arctic ground-based Fourier transform spectrometer

Abstract. The TROPOspheric Monitoring Instrument (TROPOMI) provides a daily, spatially resolved (initially 7×7 km2, upgraded to 7×5.6 km2 in August 2019) global dataset of CO columns; however, due to the relative sparseness of reliable ground-based data sources, it can be challenging to characterize the validity and accuracy of satellite data products in remote regions such as the high Arctic. In these regions, satellite intercomparisons can supplement model- and ground-based validation efforts and serve to verify previously observed differences. In this paper, we compare the CO products from TROPOMI, the Atmospheric Chemistry Experiment (ACE) Fourier transform spectrometer (FTS), and a high-Arctic ground-based FTS located at the Polar Environment Atmospheric Research Laboratory (PEARL) in Eureka, Nunavut (80.05∘ N, 86.42∘ W). A global comparison of TROPOMI reference profiles scaled by the retrieved total column with ACE-FTS CO partial columns for the period from 28 November 2017 to 31 May 2020 displays excellent agreement between the two datasets (R=0.93) and a small relative bias of -0.83±0.26% (bias ± standard error of the mean). Additional comparisons were performed within five latitude bands: the north polar region (60 to 90∘ N), northern mid-latitudes (20 to 60∘ N), the equatorial region (20∘ S to 20∘ N), southern mid-latitudes (60 to 20∘ S), and the south polar region (90 to 60∘ S). Latitudinal comparisons of the TROPOMI and ACE-FTS CO datasets show strong correlations ranging from R=0.93 (southern mid-latitudes) to R=0.86 (equatorial region) between the CO products but display a dependence of the mean differences on latitude. Positive mean biases of 7.93±0.61 % and 7.21±0.52 % were found in the northern and southern polar regions, respectively, while a negative bias of -9.41±0.55% was observed in the equatorial region. To investigate whether these differences are introduced by cloud contamination, which is reflected in the TROPOMI averaging kernel shape, the latitudinal comparisons were repeated for cloud-covered pixels and clear-sky pixels only, as well as for the unsmoothed and smoothed cases. Clear-sky pixels were found to be biased higher with poorer correlations on average than clear+cloudy scenes and cloud-covered scenes only. Furthermore, the latitudinal dependence on the biases was observed in both the smoothed and unsmoothed cases. To provide additional context to the global comparisons of TROPOMI with ACE-FTS in the Arctic, both satellite datasets were compared against measurements from the ground-based PEARL-FTS. Comparisons of TROPOMI with smoothed PEARL-FTS total columns in the period of 3 March 2018 to 27 March 2020 display a strong correlation (R=0.88); however, a positive mean bias of 14.7±0.16 % was also found. A partial column comparison of ACE-FTS with the PEARL-FTS in the period from 25 February 2007 to 18 March 2020 shows good agreement (R=0.79) and a mean positive bias of 7.89±0.21 % in the ACE-FTS product relative to the ground-based FTS. The magnitude and sign of the mean relative differences are consistent across all intercomparisons in this work, as well as with recent ground-based validation efforts, suggesting that the current TROPOMI CO product exhibits a positive bias in the high-Arctic region. However, the observed bias is within the TROPOMI mission accuracy requirement of ±15 %, providing further confirmation that the data quality in these remote high-latitude regions meets this specification.

Tropospheric and stratospheric NO retrieved from ground-based Fourier-transform infrared (FTIR) measurements

Abstract. Nitric oxide (NO) is a key active trace gas in the atmosphere, which contributes to form harmful ozone in the troposphere and to the destruction of ozone in the stratosphere. In this study, we present the NO retrieval from ground-based Fourier-transform infrared (FTIR) solar absorption spectrometry measurements at a polluted site (Xianghe, China) and a background site (Maïdo, Reunion Island). The degree of freedom (DOF) of the NO retrieval is 2.3±0.4 (1σ) at Xianghe and 1.3±0.1 at Maïdo. By looking at the FTIR NO retrievals at Xianghe and Maïdo, we find that the stratospheric NO partial column is large in summer as compared to winter at both sites, and the seasonal variation in the FTIR stratospheric NO partial columns is consistent with that observed by the co-located Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) satellite measurements. A large diurnal variation in the stratospheric NO partial column is observed by the FTIR measurements at Maïdo, with an increase from the early morning to about 14:00 local time and a decrease thereafter. Due to the low NO concentration near the surface, the FTIR NO retrieval is only sensitive to the stratosphere at Maïdo. The high NO mole fraction near the surface at Xianghe allows us to derive tropospheric and stratospheric NO partial columns separately, although the tropospheric column is very difficult to retrieve in summer (June–August) because of the high water vapor abundance. A good correlation is found between the NO observed by the FTIR measurements and other air pollutants (NO2 and CO) in the troposphere at Xianghe. It is the first study of a successful analysis of NO in the troposphere from a ground-based FTIR site. The tropospheric and stratospheric NO retrieval might be possible at other potential FTIR sites inside or near large cities with enhanced levels of NO near the surface.

Variabilities in PM2.5 and Black Carbon Surface Concentrations Reproduced by Aerosol Optical Properties Estimated by In-Situ Data, Ground Based Remote Sensing and Modeling

Because of the increased temporal and spatial resolutions of the sensors onboard recently launched satellites, satellite-based surface aerosol concentration, which is usually estimated from the aerosol optical depth (AOD), is expected to become a strategic tool for air quality studies in the future. By further exploring the relationships of aerosol concentrations and their optical properties using ground observations, the accuracies of these products can be improved. Here, we analyzed collocated observations of surface mass concentrations of fine particulate matter (PM2.5) and black carbon (BC), as well as columnar aerosol optical properties from a sky radiometer and aerosol extinction profiles obtained by multi-axis differential optical absorption spectroscopy (MAX-DOAS), during the 2019–2020 period. We focused the analyses on a daily scale, emphasizing the role of the ultraviolet (UV) spectral region. Generally, the correlation between the AOD of the fine fraction (i.e., fAOD) and the PM2.5 surface concentration was moderately strong, regardless of considerations of boundary layer humidity and altitude. In contrast, the fAOD of the partial column below 1 km, which was obtained by combining sky radiometer and MAX-DOAS retrievals, better reproduced the variability of the PM2.5 and resulted in a linear relationship. In the same manner, we demonstrated that the absorption AOD of the fine fraction (fAAOD) of the partial column was related to the variability of the BC concentration. Analogous analyses based on aerosol products from the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) confirmed these findings and highlighted the importance of the shape of the aerosol profile. Overall, our results indicated a remarkable consistency among the retrieved datasets, and between the datasets and MERRA-2 products. These results confirmed the well-known sensitivity to aerosol absorption in the UV spectral region; they also highlighted the efficacy of combined MAX-DOAS and sky radiometer observations.

Rapid eruptive transitions from low to high intensity explosions and effusive activity: insights from textural analysis of a small-volume trachytic eruption, Ascension Island, South Atlantic

Proximal deposits of small-volume trachytic eruptions are an under-studied record of eruption dynamics despite being common across a range of settings. The 59 ± 4 ka Echo Canyon deposits, Ascension Island, resulted from a small-volume explosive-effusive trachytic eruption. Variations in juvenile clast texture reveal changes in ascent dynamics and transitions in eruption style. Five dominant textural types are identified within the pumice lapilli population. Early Strombolian-Vulcanian eruption phases are typified by macro- and micro-vesicular equant clast types. Sheared clasts are most abundant at the eruption peak, transitioning to dense clasts in later phases due to shear-induced coalescence, outgassing and vesicle collapse. Melt densification and outgassing via tuffisite veins increased plume density, contributing to partial column collapse and the explosive-effusive transition. Bulk vesicularity distributions indicate a shift in dominant fragmentation mechanism during the eruption, from early-stage bubble interference and rupture to late-stage transient fragmentation, with a transient peak of Plinian activity. Dome and lava groundmass crystallinities of up to 70% indicate near-complete degassing during effusive phases, followed by shallow over pressurisation and a final less explosive phase. We provide textural evidence for high-intensity explosive phases and rapid transitions in eruptive style during small-volume trachytic eruptions and consider the impact of trachytic melt compositions on underlying dynamics of these short-lived, explosive events. This analysis demonstrates the value of detailed stratigraphy in understanding critical changes in eruption dynamics and the timescales over which they may occur which is of particular value in anticipating future eruptions of this type.