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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.

In Australia, bushfires are a natural part of the country’s landscape and essential for the regeneration of plant species; however, the 2019–20 bushfires were unprecedented in their extent and intensity. This paper is focused on the 2019–20 Australian bushfires and the resulting surface and column atmospheric carbon monoxide (CO) anomalies around Wollongong. Column CO data from the ground-based Total Carbon Column Observing Network (TCCON) and Network for the Detection of Atmospheric Composition Change (NDACC) site in Wollongong are used together with surface in situ measurements. A systematic comparison was performed between the surface in situ and column measurements of CO to better understand whether column measurements can be used as an estimate of the surface concentrations. If so, satellite column measurements of CO could be used to estimate the exposure of humans to CO and other fire-related pollutants. We find that the enhancements in the column measurements are not always significantly evident in the corresponding surface measurements. Topographical features play a key role in determining the surface exposures from column abundance especially in a coastal city like Wollongong. The topography at Wollongong, combined with meteorological effects, potentially exacerbates differences in the column and surface. Hence, satellite column amounts are unlikely to provide an accurate reflection of exposure at the ground during major events like the 2019–2020 bushfires.

We present findings from the Measurements of Urban, Marine and Biogenic Air (MUMBA) campaign, which took place in the coastal city of Wollongong in New South Wales, Australia. We focus on a few key air quality indicators, along with a comparison to regional scale chemical transport model predictions at a spatial resolution of 1 km by 1 km. We find that the CSIRO chemical transport model provides accurate simulations of ozone concentrations at most times, but underestimates the ozone enhancements that occur during extreme temperature events. The model also meets previously published performance standards for fine particulate matter less than 2.5 microns in diameter (PM2.5), and the larger aerosol fraction (PM10). We explore the observed composition of the atmosphere within this urban air-shed during the MUMBA campaign and discuss the different influences on air quality in the city. Our findings suggest that further improvements to our ability to simulate air quality in this coastal city can be made through more accurate anthropogenic and biogenic emissions inventories and better understanding of the impact of extreme temperatures on air quality. The challenges in modelling air quality within the urban air-shed of Wollongong, including difficulties in accurate simulation of the local meteorology, are likely to be replicated in many other coastal cities in the Southern Hemisphere.

We investigate the Australian methane budget from 2005–2008 using the GEOS‐Chem 3D chemistry transport model, focusing on the relative contribution of emissions from different sectors and the influence of long‐range transport. To evaluate the model, we use in situ surface measurements of methane, methane dry air column average (XCH4) from ground‐based Fourier transform spectrometers (FTSs), and train‐borne surface concentration measurements from an in situ FTS along the north–south continental transect. We use gravity anomaly data from Gravity Recovery and Climate Experiment to describe the spatial and temporal distribution of wetland emissions and scale it to a prior emission estimate, which better describes observed atmospheric methane variability at tropical latitudes. The clean air sites of Cape Ferguson and Cape Grim are the least affected by local emissions, while Wollongong, located in the populated southeast with regional coal mining, samples the most locally polluted air masses (2.5% of the total air mass versus <1% at other sites). Averaged annually, the largest single source above background of methane at Darwin is long‐range transport, mainly from Southeast Asia, accounting for ∼25% of the change in surface concentration above background. At Cape Ferguson and Cape Grim, emissions from ruminant animals are the largest source of methane above background, at approximately 20% and 30%, respectively, of the surface concentration. At Wollongong, emissions from coal mining are the largest source above background representing 60% of the surface concentration. The train data provide an effective way of observing transitions between urban, desert, and tropical landscapes. Key Points We investigate the Australian methane budget from 2005–2008 Darwin, in tropical Australia, is most influenced by intercontinental transport Other Australian measurement sites are most influenced by anthropogenic sources

We retrieved lower stratospheric vertical profiles of O3, HNO3, and HCl from solar spectra taken with a ground-based Fourier transform infrared spectrometer (FTIR) installed at Syowa Station, Antarctica (69.0∘ S, 39.6∘ E), from March to December 2007 and September to November 2011. This was the first continuous measurement of chlorine species throughout the ozone hole period from the ground in Antarctica. We analyzed temporal variation of these species combined with ClO, HCl, and HNO3 data taken with the Aura MLS (Microwave Limb Sounder) satellite sensor and ClONO2 data taken with the Envisat MIPAS (the Michelson Interferometer for Passive Atmospheric Sounding) satellite sensor at 18 and 22 km over Syowa Station. An HCl and ClONO2 decrease occurred from the end of May at both 18 and 22 km, and eventually, in early winter, both HCl and ClONO2 were almost depleted. When the sun returned to Antarctica in spring, enhancement of ClO and gradual O3 destruction were observed. During the ClO-enhanced period, a negative correlation between ClO and ClONO2 was observed in the time series of the data at Syowa Station. This negative correlation was associated with the relative distance between Syowa Station and the edge of the polar vortex. We used MIROC3.2 chemistry–climate model (CCM) results to investigate the behavior of whole chlorine and related species inside the polar vortex and the boundary region in more detail. From CCM model results, the rapid conversion of chlorine reservoir species (HCl and ClONO2) into Cl2, gradual conversion of Cl2 into Cl2O2, increase in HOCl in the winter period, increase in ClO when sunlight became available, and conversion of ClO into HCl were successfully reproduced. The HCl decrease in the winter polar vortex core continued to occur due to both transport of ClONO2 from the subpolar region to higher latitudes, providing a flux of ClONO2 from more sunlit latitudes into the polar vortex, and the heterogeneous reaction of HCl with HOCl. The temporal variation of chlorine species over Syowa Station was affected by both heterogeneous chemistries related to polar stratospheric cloud (PSC) occurrence inside the polar vortex and transport of a NOx-rich air mass from the polar vortex boundary region, which can produce additional ClONO2 by reaction of ClO with NO2. The deactivation pathways from active chlorine into reservoir species (HCl and/or ClONO2) were confirmed to be highly dependent on the availability of ambient O3. At 18 km, where most ozone was depleted, most ClO was converted to HCl. At 22 km where some O3 was available, an additional increase in ClONO2 from the prewinter value occurred, similar to the Arctic.

In this study, an extension on the previously reported status of the COllaborative Carbon Column Observing Network's (COCCON) calibration procedures incorporating refined methods is presented. COCCON is a global network of portable Bruker EM27/SUN FTIR spectrometers for deriving column-averaged atmospheric abundances of greenhouse gases. The original laboratory open-path lamp measurements for deriving the instrumental line shape (ILS) of the spectrometer from water vapour lines have been refined and extended to the secondary detector channel incorporated in the EM27/SUN spectrometer for detection of carbon monoxide (CO). The refinements encompass improved spectroscopic line lists for the relevant water lines and a revision of the laboratory pressure measurements used for the analysis of the spectra. The new results are found to be in good agreement with those reported by Frey et al. (2019) and discussed in detail. In addition, a new calibration cell for ILS measurements was designed, constructed and put into service. Spectrometers calibrated since January 2020 were tested using both methods for ILS characterization, open-path (OP) and cell measurements. We demonstrate that both methods can detect the small variations in ILS characteristics between different spectrometers, but the results of the cell method indicate a systematic bias of the OP method. Finally, a revision and extension of the COCCON network instrument-to-instrument calibration factors for XCO2, XCO and XCH4 is presented, incorporating 47 new spectrometers (of 83 in total by now). This calibration is based on the reference EM27/SUN spectrometer operated by the Karlsruhe Institute of Technology (KIT) and spectra collected by the collocated TCCON station Karlsruhe. Variations in the instrumental characteristics of the reference EM27/SUN from 2014 to 2017 were detected, probably arising from realignment and the dual-channel upgrade performed in early 2018. These variations are considered in the evaluation of the instrument-specific calibration factors in order to keep all tabulated calibration results consistent.

Correct determination of the phase spectrum is a highly relevant task in Fourier transform spectrometry for concluding which spectral distribution most likely gave rise to the measured interferogram. We present implementation of an improved scheme for phase determination in the operational Collaborative Carbon Column Observing Network (COCCON) processor. We introduce a robust unwrapping scheme for retrieving a spectrally smooth phase spectrum at intermediate spectral resolution, which uses all spectral positions carrying enough signal to allow a significant determination of the phase. In the second step, we perform a least-squares fit of model parameters of a suitable analytical phase spectrum model through all reliable phase values constructed in the first step. The model fit exploits the fact that we expect the phase to be spectrally smooth. Still, it can be refined to reflect specific characteristics inherent to the optical and electronic layout of the interferometer. The proposed approach avoids the problems of the classical phase reconstruction method, which enforces a spectrally smooth phase by directly limiting spectral resolution when calculating the complex phase. Thereby, the phase is created from a very low number of interferogram points around the centerburst of the interferogram, which results in a suboptimal noise propagation from the interferogram into the spectral domain. Moreover, the interpolation of the phase spectrum across spectral subsections with reduced spectral signal is not well behaved, and results depend strongly on the numerical apodization function used for creating the low-resolution phase.

In this study, we present ground-based measurements of column-averaged dry-air mole fractions (DMFs) of CO2 (or XCO2) taken in a semiarid region of Australia with an EM27/SUN portable spectrometer equipped with an automated clamshell cover. We compared these measurements to space-based XCO2 retrievals from the Greenhouse Gases Observing Satellite (GOSAT). Side-by-side measurements of EM27/SUN with the Total Carbon Column Observing Network (TCCON) instrument at the University of Wollongong were conducted in 2015–2016 to derive an XCO2 scaling factor of 0.9954 relative to TCCON. Although we found a slight drift of 0.13 % over 3 months in the calibration curve of the EM27/SUN vs. TCCON XCO2, the alignment of the EM27/SUN proved stable enough for a 2-week campaign, keeping the retrieved Xair values, another measure of stability, to within 0.5 % and the modulation efficiency to within 2 %. From the measurements in Alice Springs, we confirm a small bias of around 2 ppm in the GOSAT M-gain to H-gain XCO2 retrievals, as reported by the NIES GOSAT validation team. Based on the reported random errors from GOSAT, we estimate the required duration of a future campaign in order to better understand the estimated bias between the EM27/SUN and GOSAT. The dataset from the Alice Springs measurements is accessible at 10.4225/48/5b21f16ce69bc .

In this study, we present ground-based measurements of column-averaged dry-air mole fractions (DMFs) of CO.sub.2 (or XCO.sub.2) taken in a semiarid region of Australia with an EM27/SUN portable spectrometer equipped with an automated clamshell cover. We compared these measurements to space-based XCO.sub.2 retrievals from the Greenhouse Gases Observing Satellite (GOSAT). Side-by-side measurements of EM27/SUN with the Total Carbon Column Observing Network (TCCON) instrument at the University of Wollongong were conducted in 2015-2016 to derive an XCO.sub.2 scaling factor of 0.9954 relative to TCCON. Although we found a slight drift of 0.13 % over 3 months in the calibration curve of the EM27/SUN vs. TCCON XCO.sub.2, the alignment of the EM27/SUN proved stable enough for a 2-week campaign, keeping the retrieved X.sub.air values, another measure of stability, to within 0.5 % and the modulation efficiency to within 2 %. From the measurements in Alice Springs, we confirm a small bias of around 2 ppm in the GOSAT M-gain to H-gain XCO.sub.2 retrievals, as reported by the NIES GOSAT validation team. Based on the reported random errors from GOSAT, we estimate the required duration of a future campaign in order to better understand the estimated bias between the EM27/SUN and GOSAT. The dataset from the Alice Springs measurements is accessible at

We use Fourier transform infrared ground‐based measurements and satellite and model data to assess long‐range correlations in tropospheric carbon monoxide. We find that CO columns measured in New Zealand correlate well with those measured in Antarctica, if a transport‐related lag is taken into account. The model suggests that this long‐range correlation is part of a mode of anomalous CO comprising almost the whole southern extratropics, which is linked to biomass burning in the southern continents. No such mode is modeled for the Northern Hemisphere. The area of long‐range correlations maximizes for the southern subtropical Pacific, which is identified as an advantageous location for a hypothetical new measurement station. The satellite data (produced by the Measurements of Pollution in the Troposphere (MOPITT) instrument) partially confirm these findings but with generally reduced correlations. In particular, the satellite data suggest no long‐range correlation at high latitudes. This is partially explained in terms of retrieval limitations and partially reflects a model deficiency. Key Points Southern Hemisphere CO exhibits long‐range correlations MOPITT CO exhibits reduced long‐range correlations versus FTIR and model The southern subtropical Pacific would be a good site for a new FTIR instrument