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The pixel size of the Infrared Atmospheric Sounding Interferometer (IASI) remote sensor is much smaller than the horizontal grid size of current Chemical Transport Models (CTMs). In order to assimilate the maximum of information from the IASI retrievals, we have increased the horizontal resolution of our model MOCAGE to be consistent with the IASI pixel size. Experiments are carried out with the Valentina data assimilation system using the standard and the high resolution versions of the model. Two resolutions of the horizontal Gaussian grid have been used for the model: with a T42 and a T170 triangular truncations. Our study is based on the combination of data from the IASI instrument and from the Microwave Limb Sounder (MLS), since this latter dataset allows the information to be spread through the whole atmospheric columns at a low computational cost. Two datasets of ozone super-observations have been constructed by averaging the IASI data on the two model grids. Direct model simulations without data assimilation first show that the increase of the horizontal resolution modifies the ozone smallest scale structures as well as the ozone meridional distribution. This modification results from a better representation of the vertical velocity with the T170 configuration. When the ozone assimilation is performed there is less influence of the horizontal resolution of the model. Nevertheless, in a general way, comparisons with independent data show large reductions of the ozone standard deviations when the resolution is increased. When the ozone assimilation is performed with the high resolution dataset, the high resolution model does not improve the ozone analysis compared to the one obtained with the same model resolution but with the low resolution IASI dataset. This result is due to the difficulty to combine IASI data and MLS data. For assimilating IASI data at high resolution the horizontal correlation length-scale has to be decreased to catch the small scale structures present in the dataset. By doing so the influence of the coarser resolution MLS data is decreased and part of the information brought on the vertical shape of the ozone profile is lost. It is concluded that it is essential to add information on the vertical distribution of ozone column when the IASI data is assimilated at a resolution close to the pixel size. Using IASI averaging kernels would likely improve the simulations, but the computational cost would be much higher. Alternatively, better results might be obtained by a careful tuning of the horizontal correlation length-scale.

Satellite measurements play an increasingly important role in the study of atmospheric ammonia (NH3). Here, we present version 4 of the Artificial Neural Network for IASI (ANNI) retrieval of NH3. The main change is the introduction of total column averaging kernels (AVKs), which can be used to undo the effect of the vertical profile shape assumption of the retrieval. While the main equations can be matched term for term with analogous ones used in UV/Vis retrievals for other minor absorbers, we derive the formalism from the ground up, as its applicability to thermal infrared measurements is non-trivial. A large number of other smaller changes were introduced in ANNI v4, most of which improve the consistency of the measurements, across time and across the series of IASI instruments. This includes a more robust way of calculating the hyperspectral range index (HRI), explicitly accounting for long-term changes in CO2 in the HRI calculation and the use of a reprocessed cloud product that was specifically developed for climate applications. The NH3 distributions derived with ANNI v4 are very similar to the ones derived with v3, although values are about 15–20 % larger due to the improved setup of the HRI. We exclude further large biases of the same nature, by showing the consistency between ANNI v4 derived NH3 columns with columns obtained with an optimal estimation approach. Finally, with v4, we revised the uncertainty budget and now report systematic uncertainty estimates alongside random uncertainties, allowing realistic mean uncertainties to be estimated.

In this paper, we exploit the first 10-year data record (2008–2017) of nitric acid (HNO3) total columns measured by the IASI-A/MetOp infrared sounder, characterized by an exceptional daily sampling and a good vertical sensitivity in the lower-to-mid stratosphere (around 50 hPa), to monitor the relationship between the temperature decrease and the observed HNO3 loss that occurs each year in the Antarctic stratosphere during the polar night. Since the HNO3 depletion results from the formation of polar stratospheric clouds (PSCs), which trigger the development of the ozone (O3) hole, its continuous monitoring is of high importance. We verify here, from the 10-year time evolution of HNO3 together with temperature (taken from reanalysis at 50 hPa), the recurrence of specific regimes in the annual cycle of IASI HNO3 and identify (for each year) the day and the 50 hPa temperature (“drop temperature”) corresponding to the onset of strong HNO3 depletion in the Antarctic winter. Although the measured HNO3 total column does not allow for the uptake of HNO3 by different types of PSC particles along the vertical profile to be differentiated, an average drop temperature of 194.2 ± 3.8 K, close to the nitric acid trihydrate (NAT) existence threshold (∼ 195 K at 50 hPa), is found in the region of potential vorticity lower than −10 × 10−5 Km2kg-1s-1 (similar to the 70–90∘ S equivalent latitude region during winter). The spatial distribution and interannual variability of the drop temperature are investigated and discussed. This paper highlights the capability of the IASI sounder to monitor the evolution of polar stratospheric HNO3, a key player in the processes involved in the depletion of stratospheric O3.

Space-based measurements of the outgoing longwave radiation (OLR) are essential for the study of Earth's climate system. While the CERES instrument provides accurate measurements of this quantity, its measurements are not spectrally resolved. Here we present a high-resolution OLR product (sampled at 0.25 cm21), derived from measurements of the IASI satellite sounder. The applied methodology relies on precalculated angular distribution models (ADMs). These are usually calculated for tens to hundreds of different scene types (characterized by surface and atmosphere parameters). To guarantee accurate results in the range 645-2300 cm21 covered by IASI, we constructed ADMs for over 140 000 scenes. These were selected from one year of CAMS reanalysis data. A dissimilarity-based selection algorithm was applied to choose scenes as different from each other as possible, thereby maximizing the performance on real data, while keeping the number of scenes manageable. A comparison of the IASI OLR integrated over the 645-2300 cm21 range was performed with the longwave broadband OLR products from CERES and the AIRS instrument. The latter are systematically higher due to the contribution of the far infrared to the total IR spectral range, but as expected exhibit generally high spatial correlations with the IASI OLR, except for some areas in the tropical region. We also compared the IASI OLR against the spectrally resolved OLR derived from AIRS. A good agreement was found above 1200 cm21 while AIRS OLR appeared to be systematically higher in the atmospheric window region, likely related to differences in overpass time or to the use of a different cloud detection algorithm., SCOPUS: ar.j, info:eu-repo/semantics/published

In this paper, we present the global fingerprint of recent changes in middle–upper stratosphere (MUSt; hPa) ozone ( O3 ) in comparison with lower stratosphere (LSt; 150–25 hPa) O3 derived from the first 10 years of the IASI/Metop-A satellite measurements (January 2008–December 2017). The IASI instrument provides vertically resolved O3 profiles with very high spatial and temporal (twice daily) samplings, allowing O3 changes to be monitored in these two regions of the stratosphere. By applying multivariate regression models with adapted geophysical proxies on daily mean O3 time series, we discriminate anthropogenic trends from various modes of natural variability, such as the El Nino–Southern Oscillation (ENSO). The representativeness of the O3 response to its natural drivers is first examined. One important finding relies on a pronounced contrast between a positive LSt O3 response to ENSO in the extratropics and a negative one in the tropics, with a delay of 3 months, which supports a stratospheric pathway for the ENSO influence on lower stratospheric and tropospheric O3 . In terms of trends, we find an unequivocal O3 recovery from the available period of measurements in winter–spring at middle to high latitudes for the two stratospheric layers sounded by IASI ( > ∼ 35 ∘ N–S in the MUSt and > ∼ 45 ∘ S in the LSt) as well as in the total columns at southern latitudes ( > ∼ 45 ∘ S) where the increase reaches its maximum. These results confirm the effectiveness of the Montreal Protocol and its amendments and represent the first detection of a significant recovery of O3 concurrently in the lower, in the middle–upper stratosphere and in the total column from one single satellite dataset. A significant decline in O3 at northern mid-latitudes in the LSt is also detected, especially in winter–spring of the Northern Hemisphere. Given counteracting trends in the LSt and MUSt at these latitudes, the decline is not categorical in total O3 . When freezing the regression coefficients determined for each natural driver over the whole IASI period but adjusting a trend, we calculate a significant speeding up in the O3 response to the decline of O3 -depleting substances (ODSs) in the total column, in the LSt and, to a lesser extent, in the MUSt, at high southern latitudes over the year. Results also show a small significant acceleration of the O3 decline at northern mid-latitudes in the LSt and in the total column over the last few years. That, specifically, needs urgent investigation to identify its exact origin and apprehend its impact on climate change. Additional years of IASI measurements would, however, be required to confirm the O3 change rates observed in the stratospheric layers over the last few years.

International audience; Limiting excess atmospheric ammonia (NH3) is one of the great challenges for humanity in the 21th century, but can only be achieved with adequate monitoring means in place. Here, we report the first NH3 measurements from the Geostationary Interferometric Infrared Sounder (GIIRS) onboard the Chinese FY-4A satellite. The instrument scans almost all of Asia ten times per day. We show that GIIRS’ unprecedented temporal sampling can be exploited to measure diurnal and nocturnal variations of NH3 and demonstrate this on two case studies over Punjab and the North China Plain. Day–night variations are found to be almost absent in winter, but can reach a factor 2–3 in the warmer months. These case studies are very promising given the future landscape of geostationary sounders, but also show that improved knowledge on lower tropospheric air temperatures and the vertical profile of NH3 is key to better exploit their measurements.

Atmospheric sounding in the infrared has, for a long time, mainly been dedicated to meteorology. The operation of hyperspectral sounders has remarkably served this application area in the last two decades, up to the level that these instruments have become the dominant contributors to numerical weather forecast. Even more remarkable is, however, how the hyperspectral infrared sounders have fostered the fields of atmospheric chemistry and climate, thanks to the measurements of a large series of trace gases in the troposphere and stratosphere (see infographics in Figure 1 and e.g. [1]). In Europe, major advances have been made by exploiting radiance record of the Infrared Atmospheric Sounding Interferometer (IASI) onboard the Metop platform series, which started in 2006 and is expected to continue until 2024 at least. The long time series of available IASI measurements and its remarkable stability over time has in particular allowed characterizing the inter-annual variability of several reactive species (ozone -O 3 -, carbon monoxide -CO-, ammonia -NH 3 -), to isolate significant trends in the troposphere and the stratosphere (for 03), and to trace these to emission reductions or to changes in our environment and climate (e.g. [2], [3]). Another key achievement made with IASI lies in the detection and characterization of local point sources from agriculture and industry in averaged distributions [4].

Excess atmospheric ammonia (NH3) leads to deleterious effects on biodiversity, ecosystems, air quality and health, and it is therefore essential to monitor its budget and temporal evolution. Hyperspectral infrared satellite sounders provide daily NH3 observations at global scale for over a decade. Here we use the version 3 of the Infrared Atmospheric Sounding Interferometer (IASI) NH3 dataset to derive global, regional and national trends from 2008 to 2018. We find a worldwide increase of 12.8 ± 1.3 % over this 11-year period, driven by large increases in east Asia (5.80 ± 0.61% increase per year), western and central Africa (2.58 ± 0.23 % yr−1), North America (2.40 ± 0.45 % yr−1) and western and southern Europe (1.90 ± 0.43 % yr−1). These are also seen in the Indo-Gangetic Plain, while the southwestern part of India exhibits decreasing trends. Reported national trends are analyzed in the light of changing anthropogenic and pyrogenic NH3 emissions, meteorological conditions and the impact of sulfur and nitrogen oxides emissions, which alter the atmospheric lifetime of NH3. We end with a short case study dedicated to the Netherlands and the ‘Dutch Nitrogen crisis' of 2019., info:eu-repo/semantics/published

Following past studies to quantify decadal trends in global carbon monoxide (CO) using satellite observations, we update estimates and find a CO trend in column amounts of about −0.50 % per year between 2002 to 2018, which is a deceleration compared to analyses performed on shorter records that found −1 % per year. Aerosols are co-emitted with CO from both fires and anthropogenic sources but with a shorter lifetime than CO. A combined trend analysis of CO and aerosol optical depth (AOD) measurements from space helps to diagnose the drivers of regional differences in the CO trend. We use the long-term records of CO from the Measurements of Pollution in the Troposphere (MOPITT) and AOD from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument. Other satellite instruments measuring CO in the thermal infrared, AIRS, TES, IASI, and CrIS, show consistent hemispheric CO variability and corroborate results from the trend analysis performed with MOPITT CO. Trends are examined by hemisphere and in regions for 2002 to 2018, with uncertainties quantified. The CO and AOD records are split into two sub-periods (2002 to 2010 and 2010 to 2018) in order to assess trend changes over the 16 years. We focus on four major population centers: Northeast China, North India, Europe, and Eastern USA, as well as fire-prone regions in both hemispheres. In general, CO declines faster in the first half of the record compared to the second half, while AOD trends show more variability across regions. We find evidence of the atmospheric impact of air quality management policies. The large decline in CO found over Northeast China is initially associated with an improvement in combustion efficiency, with subsequent additional air quality improvements from 2010 onwards. Industrial regions with minimal emission control measures such as North India become more globally relevant as the global CO trend weakens. We also examine the CO trends in monthly percentile values to understand seasonal implications and find that local changes in biomass burning are sufficiently strong to counteract the global downward trend in atmospheric CO, particularly in late summer., SCOPUS: ar.j, info:eu-repo/semantics/published

The Infrared Atmospheric Sounding Interferometer (IASI) mission consists of a suite of three infrared sounders providing today over 13 years of consistent global measurements (from end of 2007 up to now). In this work we use the recently developed version 3 of the IASI NH3 dataset to derive global, regional and national trends from 2008 to 2018. Reported national trends are analysed in the light of changing anthropogenic and pyrogenic NH3 emissions, meteorological conditions and the impact of sulphur and nitrogen oxides emissions. A case study is dedicated to the Netherlands. Temporal variation on shorter timescales will also be investigated.

In this paper, we exploit the first 10-year data-record (2008–2017) of nitric acid (HNO3) total columns measured by the IASI-A/Metop infrared sounder, characterized by an exceptional daily sampling and a good vertical sensitivity in the mid-stratosphere (around 50 hPa), to monitor the causal relationship between the temperature decrease and the observed HNO3 loss that occurs each year in the Antarctic stratosphere during the polar night. Since the HNdepletion results from the formation of polar stratospheric clouds (PSCs) which trigger the development of the ozone (O3) hole, its continuous monitoring is of high importance. We verify here, from the 10-year time evolution of the pair HNO3-temperature (taken from reanalysis at 50 hPa), the recurrence of specific regimes in the cycle of IASI HNO3 and identify, for each year, the day and the 50 hPa-temperature (drop temperature) corresponding to the onset of denitrification in Antarctic winter. Although the measured HNO3 total column does not allow differentiating the uptake of HNO3 by different types of PSC particles along the vertical profile, an average drop temperature of ∼ 191 ± 3 K, consistent with the nitric acid trihydrate (NAT) formation temperature (close to 195 K at 50 hPa), is found. The spatial distribution and inter-annual variability of the drop temperature are briefly investigated and discussed in the context of previous PSCs studies. This paper highlights the capability of the IASI sounder to monitor the long-term evolution of the polar stratospheric composition and processes involved in the depletion of stratospheric O3.

Massive wildfires erupted in Amazonia and through the subarctic region in summer 2019, and in Australia in winter 2019-2020. During such biomass burning events, sizeable amounts of volatile organic compounds (VOCs) can be emitted directly by the fires as well as rapidly produced in plumes via the degradation of short-lived gas precursors. The VOCs have a significant impact on tropospheric chemistry by, e.g., affecting the oxidative capacity of the atmosphere. Nadir-viewing infrared sensors onboard meteorological satellites provide global and spatially dense observations that are very useful to track biomass burning events throughout the globe and to provide trace gas quantification in fire plumes.We apply a general retrieval framework, based on an artificial neural network, to derive the integrated abundance (total column) of several major VOCs from the infrared radiance spectra recorded by IASI (Infrared Atmospheric Sounding Interferometer) embarked on the Metop platforms. Quasi-global distributions of methanol (CH3OH), formic (HCOOH) and acetic (CH3COOH) acids, PAN, acetone (CH3COCH3), acetylene (C2H2) and hydrogen cyanide (HCN) column abundance are produced twice-daily from the a.m. and p.m. overpasses of the satellite instrument. In particular, we use the IASI data to produce daily regional snapshots over biomass burning areas of interest and to quantify the VOC enhancements in the plumes from the recent Amazonian, Australian and subarctic wildfires. Finally, the abundance ratios of these VOCs to IASI carbon monoxide (CO) are presented and discussed.

IASI satellite ammonia (NH3) measurements are used to identify, categorise and quantify world's NH3 emission hotspots. In particular, applying spatial oversampling and supersampling techniques on more than 10 years of IASI measurements, we are able to track-down more than 500 localized point sources of agricultural, industrial (fertilizer, coking, soda ash, geothermal and explosives industries), urban and natural origin. We present an on-line global NH3 point sources catalogue, consisting of an interactive global map, visualizing the distribution, type and time evolution of the different point sources (http://www.ulb.ac.be/cpm/NH3-IASI.html). Calculated satellite-based emissions of NH3 suggest a drastic underestimation of point sources in bottom-up inventories, especially those of industrial emitters. Temporal analysis revealed rapid shifts in anthropogenic activities, such as the opening or closure of industrial plants. These results demonstrate that using NH3 satellite data will be hugely beneficial for improving bottom-up emission inventories.A recently obtained homogeneous data record of NH3 total columns from IASI (ANNI-NH3-v3R) is also used to derive trends over the last decade. We apply a bootstrap resampling method to determine the trends and to assess whether the calculated values are significant or not. We obtain the first global distribution (0.5°×0.5°) of atmospheric NH3 trends based on 11 years (2008-2018) of IASI/Metop-A observations. Distinct temporal patterns are extracted and are analysed in light of anthropogenic activities and biomass burning events. National absolute and relative trends are also calculated and discussed.

Hydrogen Chloride (HCl) is an important but still poorly understood magmatic volatile species. Degassed HCl and ratios with other volatiles can be used to monitor, understand and forecast volcanic activity. As the dominant chlorine reservoir species in the stratosphere, and a source of reactive halogens, HCl also plays an important role in the depletion of ozone. The contribution of volcanic HCl to the stratospheric budget is however somewhat debated, but it is generally accepted that scavenging by hydrometeors is a dominant process. Unlike the less soluble SO2, this prevents the majority of volcanically emitted HCl from reaching the stratosphere. Currently HCl measurements have only been reported from limb sounders (MLS and ACE-FTS in particular), but given their viewing geometry, their vertical sensitivity is limited to the upper troposphere/lower stratosphere. In the past ten years, MLS was able to measure traces of HCl in a number of large volcanic plumes such as those originating from Sarychev Peak, Nabro and Calbuco.Here, we report the first measurements from IASI of HCl in volcanic plumes. We provide unambiguous spectroscopic identification of HCl in the 2670-2760 cm-1 spectral region in several IASI observed spectra. A survey of 12 years of IASI data was carried out, and revealed several large plumes of volcanic HCl. We show two notably large plumes of HCl identified in the eruptions of Calbuco (2015) and Raikoke (2019). For these two eruptions, we show that HCl is detected in the lower altitude plumes emitted towards the end of the eruptions (and not in the main, higher-altitude and SO2-rich plumes). This finding could be a result of the greater scavenging of HCl relative to SO2 in rapidly rising plumes, but could also be related to particular degassing mechanics of different volatile components in the erupted melt. First quantitative estimates indicate that for the analysed plumes, the HCl/SO2 molar ratios exceed one, which is much higher than the typical ratios measured by MLS (typically below 0.05) and also higher than reported from petrological data or in situ measurements (typically in the range 0.1-0.3).

Formic (HCOOH) and acetic acids (CH3COOH) are the most abundant carboxylic acids in the Earth's atmosphere and key compounds to aqueous-phase chemistry. Here we present the first distributions of CH3COOH retrieved from the 2007–2018 satellite observations of the nadir-looking infrared atmospheric sounding interferometer (IASI), using a neural network-based retrieval approach. A joint analysis with the IASI HCOOH product reveals that the two species exhibit similar distributions, seasonality, and atmospheric burden, pointing to major common sources. We show that their abundance is highly correlated to isoprene and monoterpenes emissions, as well as to biomass burning. Over Africa, evidence is provided that residual smoldering combustion might be a major driver of the HCOOH and CH3COOH seasonality. Earlier seasonal enhancement of HCOOH at Northern Hemisphere middle and high latitudes and late seasonal secondary peaks of CH3COOH in the tropics suggest that sources and production pathways specific to each species are also at play., SCOPUS: ar.j, info:eu-repo/semantics/published

International audience; We analyze the 2019 sudden stratospheric warming event that occurred in the Southern Hemisphere through its impact on the Antarctic ozone. Using temperature, ozone, and nitric acid data from the Infrared Atmospheric Sounding Interferometer (IASI), our results show that the average increase in stratospheric temperature reached a maximum of 34.4° on September 20th in the [60‐90]°S latitude range when compared to the past three years. Dynamical parameters suggest a locally‐reversed and weakened zonal winds and a shift in the location of the polar jet vortex. This led to air masses mixing, to a reduced polar stratospheric clouds formation detected at a ground station, and as such to lower ozone and nitric acid depletion. 2019 total ozone columns for the months of September, October, and November, were on average higher by 29%, 28%, and 26% respectively when compared to the 11‐year average of the same months.

Biomass burning emissions are a major source of trace gases and aerosols. Wildfires being highly variable in time and space, calculating emissions requires a numerical tool able to estimate fluxes at the kilometer scale and with an hourly time step. Here, the APIFLAME model version 2.0 is presented. It is structured to be modular in terms of input databases and processing methods. The main evolution compared to version 1.0 is the possibility of merging burned area and fire radiative power (FRP) satellite observations to modulate the temporal variations of fire emissions and to integrate small fires that may not be detected in the burned area product. Accounting for possible missed detection due to small fire results in an increase in burned area ranging from ∼5% in Africa and Australia to ∼30% in North America on average over the 2013-2017 time period based on the Moderate-Resolution Imaging Spectroradiometer (MODIS) Collection 6 fire products. An illustration for the case of southwestern Europe during the summer of 2016, marked by large wildfires in Portugal, is presented. Emissions calculated using different possible configurations of APIFLAME show a dispersion of 80% on average over the domain during the largest wildfires (8-14 August 2016), which can be considered as an estimate of uncertainty of emissions. The main sources of uncertainty studied, by order of importance, are the emission factors, the calculation of the burned area, and the vegetation attribution. The aerosol (PM10) and carbon monoxide (CO) concentrations simulated with the CHIMERE regional chemistry transport model (CTM) are consistent with observations (good timing for the beginning and end of the events, ±1d for the timing of the peak values) but tend to be overestimated compared to observations at surface stations. On the contrary, vertically integrated concentrations tend to be underestimated compared to satellite observations of total column CO by the Infrared Atmospheric Sounding Interferometer (IASI) instrument and aerosol optical depth (AOD) by MODIS. This underestimate is lower close to the fire region (5%-40% for AOD depending on the configuration and 8%-18% for total CO) but rapidly increases downwind. For all comparisons, better agreement is achieved when emissions are injected higher into the free troposphere using a vertical profile as estimated from observations of aerosol plume height by the Multi-angle Imaging SpectroRadiometer (MISR) satellite instrument (injection up to 4km). Comparisons of aerosol layer heights to observations by the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) show that some parts of the plume may still be transported at too low an altitude. The comparisons of the different CTM simulations to observations point to uncertainties not only on emissions (total mass and daily variability) but also on the simulation of their transport with the CTM and mixing with other sources. Considering the uncertainty of the emission injection profile and of the modeling of the transport of these dense plumes, it is difficult to fully validate emissions through comparisons between model simulations and atmospheric observations., SCOPUS: ar.j, info:eu-repo/semantics/published

Biomass burning emissions are a major source of trace gases and aerosols. Wildfires being highly variable in time and space, calculating emissions requires a numerical tool able to estimate fluxes at the kilometer scale and with an hourly time-step. Here, the APIFLAME model version 2.0 is presented. It is structured to be modular in terms of input databases and processing methods. The main evolution compared to the version v1.0 is the possibility to merge burned area and fire radiative power (FRP) satellite observations to modulate the temporal variations of fire emissions and to integrate small fires that may not be detected in the burned area product. Accounting for possible missed detection due to small fires results in an increase ranging from ∼ 5 % in Africa and Australia to ∼ 30 % in North America, on average over the 2013–2017 time period based on the Moderate-Resolution Imaging Spectroradiometer (MODIS) collection 6 fire products. An illustration for the case of south-western Europe during the summer of 2016, marked by large wildfires in Portugal, is presented. Emissions calculated using different possible configurations of APIFLAME show a dispersion of 75% on average over the domain during the largest wildfires (8–14/08/2016), which can be considered as an estimate of uncertainty on emissions (excluding the uncertainty on emission factors). Corresponding enhancements of aerosols and carbon monoxide (CO) simulated with the regional chemistry transport model CHIMERE are consistent with observations (good timing for the beginning and end of the events, ± 1 day for the timing of the peak values) but tend to be overestimated compared to observations at surface stations. On the contrary, vertically integrated concentrations tend to be underestimated compared to satellite observations of total column CO by the Infrared Atmospheric Sounding Interferometer (IASI) instrument and aerosol optical depth (AOD) by MODIS, which allow regional scale evaluation. This underestimate is lower close to the fire region (5 % to 40 % for AOD depending on the configuration, and 8–18 % for total CO) but rapidly increases downwind. For all comparisons, better agreement is achieved when emissions are injected higher into the free troposphere using a vertical profile as estimated from observations of aerosol plume height by the MISR satellite instrument (injection up to 4 km). The overestimate compared to surface sites and underestimate compared to satellite observations point to uncertainties not only on emissions (total mass and daily variability) but also on their injection profile and on the modelling of the transport of these dense plumes.

In this study, we describe the recent changes in the tropospheric ozone (O 3 ) columns measured by the Infrared Atmospheric Sounding Interferometer (IASI), onboard the Metop satellite, during the first 9 years of operation (January 2008 to May 2017). Using appropriate multivariate regression methods, we differentiate significant linear trends from other sources of O 3 variations captured by IASI. The geographical patterns of the adjusted O 3 trends are provided and discussed on the global scale. Given the large contribution of the natural variability in comparison with that of the trend (25–85 % vs. 15–50 %, respectively) to the total O 3 variations, we estimate that additional years of IASI measurements are generally required to detect the estimated O 3 trends with high precision. Globally, additional 6 months to 6 years of measurements, depending on the regions and the seasons, are needed to detect a trend of | 5 | DU decade −1 . An exception is interestingly found during summer at mid- and high latitudes of the Northern Hemisphere (NH; ∼ 40 to ∼ 75 ∘ N), where the large absolute fitted trend values ( ∼ | 0.5 | DU yr −1 on average) combined with the small model residuals ( ∼ 10 %) allow for detection of a band-like pattern of significant negative trends. Despite no consensus in terms of tropospheric O 3 trends having been reached from the available independent datasets (UV or IR satellites, O 3 sondes, aircrafts, ground-based measurements, etc.) for the reasons that are discussed in the text, this finding is consistent with the reported decrease in O 3 precursor emissions in recent years, especially in Europe and USA. The influence of continental pollution on that latitudinal band is further investigated and supported by the analysis of the O 3 –CO relationship (in terms of correlation coefficient, regression slope and covariance) that we found to be the strongest at northern midlatitudes in summer.

This study aims to understand the spatial and temporal variability of HNO3 total columns in terms of explanatory variables. To achieve this, multiple linear regressions are used to fit satellite-derived time series of HNO3 daily averaged total columns. First, an analysis of the IASI 9-year time series (2008-2016) is conducted based on various equivalent latitude bands. The strong and systematic denitrification of the southern polar stratosphere is observed very clearly. It is also possible to distinguish, within the polar vortex, three regions which are differently affected by the denitrification. Three exceptional denitrification episodes in 2011, 2014 and 2016 are also observed in the Northern Hemisphere, due to unusually low arctic temperatures. The time series are then fitted by multivariate regressions to identify what variables are responsible for HNO3 variability in global distributions and time series, and to quantify their respective influence. Out of an ensemble of proxies (annual cycle, solar flux, quasi-biennial oscillation, multivariate ENSO index, Arctic and Antarctic oscillations and volume of polar stratospheric clouds), only the those defined as significant (p value, SCOPUS: ar.j, info:eu-repo/semantics/published

Recently, Whitburn et al.(2016) presented a neural-network-based algorithm for retrieving atmospheric ammonia (NH3) columns from Infrared Atmospheric Sounding Interferometer (IASI) satellite observations. In the past year, several improvements have been introduced, and the resulting new baseline version, Artificial Neural Network for IASI (ANNI)-NH3-v2.1, is documented here. One of the main changes to the algorithm is that separate neural networks were trained for land and sea observations, resulting in a better training performance for both groups. By reducing and transforming the input parameter space, performance is now also better for observations associated with favourable sounding conditions (i.e. enhanced thermal contrasts). Other changes relate to the introduction of a bias correction over land and sea and the treatment of the satellite zenith angle. In addition to these algorithmic changes, new recommendations for post-filtering the data and for averaging data in time or space are formulated. We also introduce a second dataset (ANNI-NH3-v2.1R-I) which relies on ERA-Interim ECMWF meteorological input data, along with surface temperature retrieved from a dedicated network, rather than the operationally provided Eumetsat IASI Level 2 (L2) data used for the standard near-real-time version. The need for such a dataset emerged after a series of sharp discontinuities were identified in the NH3 time series, which could be traced back to incremental changes in the IASI L2 algorithms for temperature and clouds. The reanalysed dataset is coherent in time and can therefore be used to study trends. Furthermore, both datasets agree reasonably well in the mean on recent data, after the date when the IASI meteorological L2 version 6 became operational (30 September 2014).

Vegetation fires are a major source of ammonia (NH3) in the atmosphere. Their emissions are mainly estimated using bottom-up approaches that rely on uncertain emission factors. In this study, we derive new biome-specific NH3 enhancement ratios relative to carbon monoxide (CO), ERNH3 ∕ CO (directly related to the emission factors), from the measurements of the IASI sounder onboard the Metop-A satellite. This is achieved for large tropical regions and for an 8-year period (2008–2015). We find substantial differences in the ERNH3 ∕ CO ratios between the biomes studied, with calculated values ranging from 7 × 10−3 to 23 × 10−3. For evergreen broadleaf forest these are typically 50–75 % higher than for woody savanna and savanna biomes. This variability is attributed to differences in fuel types and size and is in line with previous studies. The analysis of the spatial and temporal distribution of the ERNH3 ∕ CO ratio also reveals a (sometimes large) within-biome variability. On a regional level, woody savanna shows, for example, a mean ERNH3 ∕ CO ratio for the region of Africa south of the Equator that is 40–75 % lower than in the other five regions studied, probably reflecting regional differences in fuel type and burning conditions. The same variability is also observed on a yearly basis, with a peak in the ERNH3 ∕ CO ratio observed for the year 2010 for all biomes. These results highlight the need for the development of dynamic emission factors that take into better account local variations in fuel type and fire conditions. We also compare the IASI-derived ERNH3 ∕ CO ratio with values reported in the literature, usually calculated from ground-based or airborne measurements. We find general good agreement in the referenced ERNH3 ∕ CO ratio except for cropland, for which the ERNH3 ∕ CO ratio shows an underestimation of about 2–2.5 times.

In this paper, we present the global fingerprint of recent changes in the mid-upper stratospheric (MUSt; > 25 hPa) ozone (O3) in comparison with the lower stratospheric (LSt, 150–25 hPa) O3 derived from the first 10 years of the IASI/Metop-A satellite measurements (January 2008–December 2017). The IASI instrument provides vertically-resolved O3 profiles with very high spatial and temporal (twice daily) samplings, allowing to monitor O3 changes in these two regions of the stratosphere. By applying multivariate regression models with adapted geophysical proxies on daily mean O3 time series, we discriminate anthropogenic trends from various modes of natural variability, such as the El Niño/Southern Oscillation – ENSO. The representativeness of the O3 response to its natural drivers is first examined. One important finding relies on a pronounced contrast between a positive LSt O3 response to ENSO in the extra-tropics and a negative one in the tropics, with a delay of 3 months, which supports a stratospheric pathway for the ENSO influence on lower stratospheric and tropospheric O3. In terms of trends, we find an unequivocal O3 recovery from the available period of measurements in winter/spring at mid-high latitudes for the two stratospheric layers sounded by IASI (>∼35° N/S in the MUSt and >∼45° S in the LSt) as well as in the total columns at southern latitudes (>∼45° S) where the increase reaches its maximum. These results confirm the effectiveness of the Montreal protocol and its amendments, and represent the first detection of a significant recovery of O3 concurrently in the lower, in the mid-upper stratosphere and in the total column from one single satellite dataset. A significant decline in O3 at northern mid-latitudes in the LSt is also detected, especially in winter/spring of the northern hemisphere. Given counteracting trends in LSt and MUSt at these latitudes, the decline is not categorical in total O3. When freezing the regression coefficients determined for each natural driver over the whole IASI period but adjusting a trend, we calculate a significant speeding up in the O3 response to the decline of O3 depleting substances (ODS) in the total column, in the LSt and, in a lesser extent, in the MUSt, at high southern latitudes over the year. A significant acceleration of the O3 decline at northern mid-latitudes in the LSt and in the total column is also highlighted over the last years. That, specifically, needs urgent investigation for identifying its exact origin and apprehending its impact on climate change.

Aerosol is an important component of the Earth's atmosphere, affecting weather, climate, and diverse elements of the biosphere. Satellite sounders are an essential tool for measuring the highly variable distributions of atmospheric aerosol. Here we present a new algorithm for estimating atmospheric dust optical depths and associated retrieval uncertainties from spectral radiance measurements of the Infrared Atmospheric Sounding Interferometer (IASI). The retrieval is based on the calculation of a dust index and on a neural network trained with synthetic IASI spectra. It has an inherent high sensitivity to dust and efficiently discriminates dust from other aerosols. In particular, over remote dust-free areas, the retrieved levels of optical depth have a low bias. Over sea, noise levels are markedly lower than over land. Performance over deserts is comparable to that of other land surfaces. We use ground-based coarse mode aerosol measurements from the AErosol RObotic NETwork to validate the new product. The overall assessment is favorable, with standard deviations in line with estimated uncertainties, low biases, and high correlation coefficients. However, a systematic relative bias occurs between sites dominated by African and Asian dust sources respectively, likely linked to differences in mineralogy. The retrieval has been performed on over a decade of IASI data, and the resulting data set is now publicly available. We present a global seasonal dust climatology based on this record and compare it with those obtained from independent satellite measurements (Moderate Resolution Imaging Spectroradiometer and a third-party IASI product) and dust optical depth from the ECMWF model., SCOPUS: ar.j, info:eu-repo/semantics/published

In a recent global analysis of satellite-derived atmospheric NH 3 data, a hotspot was observed in the vicinity of Lake Natron, Tanzania. The lake is in the centre of an endorheic (limited drainage) basin and has shallow, saline-alkaline waters. Its remote location and the absence of nearby large anthropogenic sources suggest that the observed NH 3 is mainly of natural origin. Here we explore 10 years of IASI NH 3 satellite data and other publicly available datasets over the area to characterize the natural NH 3 emissions in this unique ecosystem. Temporal analysis reveals that the emissions are episodic and linked with the lake’s surface area. The largest NH 3 column loadings generally occur at the end of the dry season in September–November over Lake Natron’s largest mudflat, that is exposed with receding water levels. The timing is different from the agricultural dominated NH 3 emissions in the wider Natron area, which peak early in the year, after the first wet season. The likely source of NH 3 at Lake Natron is decomposition of organic material, either from rivers and springs or produced in the lake (plankton, bird excreta). High temperatures and alkalinity are known to promote NH 3 losses from soda lakes. We formulate six processes that may explain why the largest losses are observed specifically over concentrated brines and/or exposed sediments. As a by-product, we also show that hyperspectral infrared sounders such as IASI are capable of mapping different types of evaporative minerals such as trona and thermonatrite., SCOPUS: ar.j, info:eu-repo/semantics/published

As one of the most abundant oxygenated volatile organic compounds in the atmosphere, acetone (CH 3 C[O]CH 3 ) influences atmospheric oxidants levels and ozone formation. Here we report the first unambiguous identification of acetone from the nadir-viewing satellite sounder Infrared Atmospheric Sounding Interferometer (IASI). Via a neural network-based retrieval approach that was previously applied to the retrieval of other weak absorbers, we obtain daily global acetone retrievals. A first intercomparison with independent measurements is conducted. As the retrieval method is computationally fast, it allowed the full reprocessing of the 2007–2018 IASI time series. Analysis of the retrieved global product and its seasonality suggests that emissions of acetone and precursors from the terrestrial biosphere at Northern Hemisphere middle and high latitudes are the main contributors to the atmospheric acetone abundance, more than year-round oxidation of anthropogenic isoalkanes. Remarkably, biomass burning does not appear to be a strong global source of acetone., SCOPUS: ar.j, info:eu-repo/semantics/published

International audience; Through its important role in the formation of particulate matter, atmospheric ammonia affects air quality and has implications for human health and life expectancy1,2. Excess ammonia in the environment also contributes to the acidification and eutrophication of ecosystems3,4,5 and to climate change6. Anthropogenic emissions dominate natural ones and mostly originate from agricultural, domestic and industrial activities7. However, the total ammonia budget and the attribution of emissions to specific sources remain highly uncertain across different spatial scales7,8,9. Here we identify, categorize and quantify the world’s ammonia emission hotspots using a high-resolution map of atmospheric ammonia obtained from almost a decade of daily IASI satellite observations. We report 248 hotspots with diameters smaller than 50 kilometres, which we associate with either a single point source or a cluster of agricultural and industrial point sources—with the exception of one hotspot, which can be traced back to a natural source. The state-of-the-art EDGAR emission inventory10 mostly agrees with satellite-derived emission fluxes within a factor of three for larger regions. However, it does not adequately represent the majority of point sources that we identified and underestimates the emissions of two-thirds of them by at least one order of magnitude. Industrial emitters in particular are often found to be displaced or missing. Our results suggest that it is necessary to completely revisit the emission inventories of anthropogenic ammonia sources and to account for the rapid evolution of such sources over time. This will lead to better health and environmental impact assessments of atmospheric ammonia and the implementation of suitable nitrogen management strategies.

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

This paper studies the seasonal variation of surface and column CO at three different sites (Paris, Jungfraujoch and Wollongong), with an emphasis on establishing a link between the CO vertical distribution and the nature of CO emission sources. We find the first evidence of a time lag between surface and free tropospheric CO seasonal variations in the Northern Hemisphere. The CO seasonal variability obtained from the total columns and free tropospheric partial columns shows a maximum around March-April and a minimum around September-October in the Northern Hemisphere (Paris and Jungfraujoch). In the Southern Hemisphere (Wollongong) this seasonal variability is shifted by about 6 months. Satellite observations by the IASI-MetOp (Infrared Atmospheric Sounding Interferometer) and MOPITT (Measurements Of Pollution In The Troposphere) instruments confirm this seasonality. Ground-based FTIR (Fourier transform infrared) measurements provide useful complementary information due to good sensitivity in the boundary layer. In situ surface measurements of CO volume mixing ratios at the Paris and Jungfraujoch sites reveal a time lag of the near-surface seasonal variability of about 2 months with respect to the total column variability at the same sites. The chemical transport model GEOS-Chem (Goddard Earth Observing System chemical transport model) is employed to interpret our observations. GEOS-Chem sensitivity runs identify the emission sources influencing the seasonal variation of CO. At both Paris and Jungfraujoch, the surface seasonality is mainly driven by anthropogenic emissions, while the total column seasonality is also controlled by air masses transported from distant sources. At Wollongong, where the CO seasonality is mainly affected by biomass burning, no time shift is observed between surface measurements and total column data., SCOPUS: ar.j, info:eu-repo/semantics/published

International audience; In this paper, we describe a new flexible and robust NH3 retrieval algorithm from measurements of the Infrared Atmospheric Sounding Interferometer (IASI). The method is based on the calculation of a spectral hyperspectral range index (HRI) and subsequent conversion to NH3 columns via a neural network. It is an extension of the method presented in Van Damme et al. (2014a) who used lookup tables (LUT) for the radiance-concentration conversion. The new method inherits the advantages of the LUT-based method while providing several significant improvements. These include the following: (1) Complete temperature and humidity vertical profiles can be accounted for. (2) Third-party NH3 vertical profile information can be used. (3) Reported positive biases of LUT retrieval are reduced, and finally (4) a full measurement uncertainty characterization is provided. A running theme in this study, related to item (2), is the importance of the assumed vertical NH3 profile. We demonstrate the advantages of allowing variable profile shapes in the retrieval. As an example, we analyze how the retrievals change when all NH3 is assumed to be confined to the boundary layer. We analyze different averaging procedures in use for NH3 in the literature, introduced to cope with the variable measurement sensitivity and derive global averaged distributions for the year 2013. A comparison with a GEOS-Chem modeled global distribution is also presented, showing a general good correspondence (within ±3 × 1015 molecules.cm−2) over most of the Northern Hemisphere. However, IASI finds mean columns about 1–1.5 × 1016 molecules.cm−2 (∼50–60%) lower than GEOS-Chem for India and the North China plain.

This paper assesses the quality of IASI/Metop-A (IASI-A) and IASI/Metop-B (IASI-B) ozone (O3) products (total and partial O3 columns) retrieved with the Fast Optimal Retrievals on Layers for IASI Ozone (FORLI-O3) v20151001 software for nine years (2008–2017) through an extensive inter-comparison and validation exercise using independent observations (satellite, ground-based and ozonesonde). IASI-A and IASI-B Total O3 Columns (TOCs) are generally consistent, with a global mean difference less than 0.3 % for both day- and nighttime measurements, IASI-A being slightly higher than IASI-B. A global difference less than 2.4 % is found for the tropospheric (TROPO) O3 column product (IASI-A being lower than IASI-B), which is partly due to a temporary issue related to IASI-A viewing angle in 2015. Our validation shows that IASI-A and IASI-B TOCs are consistent with GOME-2, Dobson, Brewer and SAOZ retrieved ones, with global mean differences in the range 0.1–2 % depending on the instruments. The IASI-A and ground-based TOC comparison for the period 2008–July 2017 shows good long-term stability (negative trends within 3 % decade−1). The comparison results between IASI-A and IASI-B against smoothed ozonesonde partial O3 columns vary in altitude and latitude, with maximum standard deviation for the 300–150 hPa column (20–40 %) due to strong ozone variability and a priori uncertainty. The worst agreement with the ozonesondes and with UV-vis retrieved TOC [satellite and ground] is found at the southern high latitudes. Compared to ozonesonde data, IASI-A and IASI-B O3 products overestimate the O3 abundance in the stratosphere (up to 20 % for the 150–25 hPa column) and underestimates the O3 abundance in the troposphere (within 10 % for the mid-latitudes and ~ 18 % for the tropics). Based on the period 2011–2016, non-significant drift is found for the northern hemispheric tropospheric columns while a small drift prevails for the period before 2011.

The IASI (Infrared Atmospheric Sounding Interferometer) nadir-looking thermal infrared sounder onboard MetOp-A enables the monitoring of atmospheric constituents on a global scale. This paper presents a quality assessment of IASI CO profiles retrieved by the two different retrieval algorithms SOFRID and FORLI, by an intercomparison with airborne in-situ CO profiles from the MOZAIC program for the 2008-2009 period. Lower (surface-480 hPa) and upper tropospheric partial column (480-225 hPa) comparisons as well as profile comparisons are made. The retrieval errors of the IASI products are less than 21% in the lower troposphere and less than 10% in the upper troposphere. A statistical analysis shows similar correlation coefficients for the two retrieval algorithms and smoothed MOZAIC of r ∼ 0.8 and r ∼ 0.7 in the lower and upper troposphere respectively. Comparison with smoothed MOZAIC data of the temporal variation of the CO profiles at the airports of Frankfurt and Windhoek demonstrates that the IASI products are able to capture the seasonal variability at these sites. At Frankfurt SOFRID (respectively FORLI) is positively biased by 10.5% (13.0%) compared to smoothed MOZAIC in the upper (lower) troposphere, and the limited sensitivity of the IASI instrument to the boundary layer when thermal contrast is low is identified. At Windhoek, the impact of the vegetation fires in Southern Africa from July to November is captured by both SOFRID and FORLI, with an overestimation of the CO background values (fire maxima) by SOFRID (FORLI) by 12.8% (10%). Profile comparisons at Frankfurt and Windhoek show that the largest discrepancies are found between the two IASI products and MOZAIC for the nighttime retrievals. © 2012 Author(s)., SCOPUS: ar.j, info:eu-repo/semantics/published

Retrieving concentrations of minor atmospheric trace gases from satellite observations is challenging due to their weak spectral signature. Here we present a new version of the ANNI (Artificial Neural Network for Infrared Atmospheric Sounding Interferometer, IASI) retrieval framework, which relies on a hyperspectral range index (HRI) for the quantification of the gas spectral signature and on an artificial feedforward neural network to convert the HRI into a gas total column. We detail the different steps of the retrieval method, especially where they differ from previous work, and apply the retrieval to three important volatile organic compounds: methanol (CH3OH), formic acid (HCOOH), and peroxyacetyl nitrate (PAN). The comparison of the retrieved columns with those from an optimal estimation inversion retrieval shows an overall excellent agreement: differences occur mainly when the sensitivity to the target gas is low and are consistent with the conceptual differences between the two approaches. We present retrieval examples over selected regions, comparison with previously developed products, and the global seasonal distributions including the first global distributions of PAN on a daily basis. The ANNI retrieval has been carried out on the whole time series of IASI observations (2007–2018), so that currently over 10 years of twice-daily global CH3OH, HCOOH, and PAN total column distributions have been produced. This unique data set opens avenues for tackling important questions related to sources, transport, and transformation of volatile organic compounds in the global atmosphere., SCOPUS: ar.j, info:eu-repo/semantics/published

International audience; Assessments of carbon monoxide emissions through inverse modeling are dependent on the modeled abundance of the hydroxyl radical (OH) which controls both the primary sink of CO and its photochemical source through hydrocarbon oxidation. However, most chemistry-transport models (CTMs) fall short of reproducing constraints on hemispherically-averaged OH levels derived from methylchloroform (MCF) observations. Here we construct five different OH fields compatible with MCF-based analyses, and we prescribe those fields in a global CTM to infer CO fluxes based on IASI CO columns. Each OH field leads to a different set of optimized emissions. Comparisons with independent data (surface, ground-based remotely-sensed, aircraft) indicate that the inversion adopting the lowest average OH level in the Northern Hemisphere (7.8 × 105molec. cm−3, ca. 18% lower than the best estimate based on MCF measurements) provides the best overall agreement with all tested observation datasets.

This study aims at understanding the spatial and temporal variability of HNO 3 total columns in terms of explanatory variables. To achieve this, multiple linear regressions are used to fit satellite-derived time series of HNO 3 daily averaged total columns. First, an analysis of the IASI 9-year time series (2008–2016) is conducted based on various equivalent latitude bands. The strong and systematic denitrification of the southern polar stratosphere is observed very clearly. It is also possible to distinguish, within the polar vortex, three regions wich are differently affected by the denitrification. Three exceptional denitrification episodes in 2011, 2014 and 2016 are also observed in the northern hemisphere, due to unusually low arctic temperatures. The time series are then fitted by multivariate regressions to identify what variables are responsible for HNO 3 variability in global distributions and time series, and to quantify their respective influence. Out of an ensemble of proxies (annual cycle, solar flux, quasi-biennial oscillation, multivariate ENSO index, Arctic and Antarctic oscillations and volume of polar stratospheric clouds), only the ones defined as significant (p-value 3 variability, with especially good results at high latitudes (60–80 % of the observed variability explained by the model). The regressions show everywhere the dominance of the annual variability, which is related to specific chemistry and dynamic depending on the latitudes. We find that the PSCs also have a major influence in the polar regions, and that their inclusion in the model improves the correlation coefficients and the residuals. However, there is still a relatively large part of the HNO 3 variability that remains unexplained by the model, especially in the intertropical regions, where factors not included in the regression model (such as vegetation fires or lightning) may be at play.

In this study, we describe the recent changes in the tropospheric ozone (O3) columns (TOCs) measured by the Infrared Atmospheric Sounding Interferometer (IASI) onboard the Metop satellite during the first 9 years of the IASI operation (January 2008 to May 2017). Using appropriate multivariate regression methods, we discriminate significant linear trends from other sources of O3 variations captured by IASI. The geographical patterns of the adjusted O3 trends are provided and discussed on the global scale. Given the large contribution of the natural variability in comparison with that of the trend (25–85 % vs 15–50 %, respectively) to the total O3 variations, we estimate that additional years of IASI measurements are generally required to detect the estimated O3 trends with a high precision. Globally, additional 6 months to 6 years of measurements, depending on the regions and the seasons, are needed to detect a trend of |5| DU/decade. An exception is interestingly found during summer in the mid-high latitudes of the North Hemisphere (N.H.; ~ 40° N–75° N) where the large absolute fitted trend values (~ |0.5| DU/yr on average) combined with the small model residuals (~ 10 %) allow the detection of a band-like pattern of significant negative trends. This finding supports the reported decrease in O3 precursor emissions in recent years, especially in Europe and US. The influence of continental pollution on that latitudinal band is further investigated and supported by the analysis of the O3–CO relationship (in terms of correlation coefficient, regression slope and covariance) that we found to be the strongest at the northern mid-latitudes in summer.

The GOME-type Total Ozone Essential Climate Variable (GTO-ECV) is a Level-3 data record, which combines individual sensor products into one single cohesive record covering the 22 year period from 1995 to 2017, generated in the frame of the European Space Agency's Climate Change Initiative Phase-II. It is based on Level-2 total ozone data produced by the GODFIT v4 algorithm as applied to the GOME/ERS-2, OMI/Aura, SCIAMACHY/Envisat and GOME-2/MetopA and /MetopB observations. In this paper we examine whether GTO-ECV meets the specific requirements set by the international climate-chemistry modelling community for decadal stability, long-term and short term accuracy. In the following, we present the validation of the 2017 release of the Climate Research Data Package Total Ozone Column (CRDP TOC), both at Level-2 and Level-3. The individual Level-2 data sets show excellent inter-sensor consistency with mean differences generally within 0.5 % at moderate latitudes (±50°), whereas the Level-3 data sets show mean differences with respect to the OMI reference data record that span between −0.2 ± 0.9 % (for GOME-2B) and 1.0 ± 1.4&htinsp;% (for SCIAMACHY). Very similar findings are reported for the Level-2 validation against independent ground-based TOC observations reported by Brewer, Dobson and SAOZ instruments; the mean bias between GODFIT v4 satellite TOC and ground instrument is well within 1.0 ± 1.0 % for all sensors, the drift per decade spans between −0.5 % to 1.0 ± 1.0 % depending on the sensor, and the peak-to-peak seasonality of the differences ranges between ~ 1 % for GOME and OMI, to ~ 2 % for SCIAMACHY. For the Level-3 validation, as a first step the aim was to show that the Level-3 CRDP produces consistent findings as the Level-2 individual sensor comparisons. We show an excellent agreement with 0.5 to 2 % peak-to-peak amplitude for the monthly mean difference time series and a negligible drift per decade in the Northern Hemisphere differences at −0.11 ± 0.10 % per decade for Dobson and +0.22 ± 0.08 % per decade for Brewer collocations. The exceptional quality of the Level-3 GTO-ECV v3 TOC record temporal stability well satisfies the requirements for the total ozone measurement decadal stability of between 1–3 % and the short term and long-term accuracy requirements of 2 % and 3 % respectively, showing an excellent inter-sensor consistency both in the Level-2 GODFIT v4 as well as in the Level-3 GTO-ECV v3 datasets and thus can be used for longer term analysis of the ozone layer, such as decadal trend studies, chemistry-climate model evaluation and data assimilation applications.

We present global distributions of C2H2 and hydrogen cyanide (HCN) total columns derived from the Infrared Atmospheric Sounding Interferometer (IASI) for the years 2008–2010. These distributions are obtained with a fast method allowing to retrieve C2H2 abundance globally with a 5 % precision and HCN abundance in the tropical (subtropical) belt with a 10 % (25 %) precision. IASI data are compared for validation purposes with ground-based Fourier transform infrared (FTIR) spectrometer measurements at four selected stations. We show that there is an overall agreement between the ground-based and space measurements with correlation coefficients for daily mean measurements ranging from 0.28 to 0.81, depending on the site. Global C2H2 and subtropical HCN abundances retrieved from IASI spectra show the expected seasonality linked to variations in the anthropogenic emissions and seasonal biomass burning activity, as well as exceptional events, and are in good agreement with previous spaceborne studies. Total columns simulated by the Model for Ozone and Related Chemical Tracers, version 4 (MOZART-4) are compared to the ground-based FTIR measurements at the four selected stations. The model is able to capture the seasonality in the two species in most of the cases, with correlation coefficients for daily mean measurements ranging from 0.50 to 0.86, depending on the site. IASI measurements are also compared to the distributions from MOZART-4. Seasonal cycles observed from satellite data are reasonably well reproduced by the model with correlation coefficients ranging from −0.31 to 0.93 for C2H2 daily means, and from 0.09 to 0.86 for HCN daily means, depending on the considered region. However, the anthropogenic (biomass burning) emissions used in the model seem to be overestimated (underestimated), and a negative global mean bias of 1 % (16 %) of the model relative to the satellite observations was found for C2H2 (HCN).

Recently, Whitburn et al. (2016) presented a neural network-based algorithm for retrieving atmospheric ammonia (NH3) columns from IASI satellite observations. In the past year, several improvements have been introduced and the resulting new baseline version, ANNI-NH3-v2, is documented here. One of the main changes to the algorithm is that separate neural networks were trained for land and sea observations, resulting in a better training performance for both groups. By reducing and transforming the input parameter space, performance is now also better for observations associated with favourable sounding conditions (i.e. enhanced thermal contrasts). Other changes relate to the introduction of a bias correction over sea and the treatment of the satellite zenith angle. In addition to these algorithmic changes, new recommendations for post-filtering the data and for averaging data in time or space are formulated. We also introduce a second dataset (ANNI-NH3-v2R-I) which relies on ERA-Interim ECMWF meteorological input data, along with built-in surface temperature, rather than the operationally provided Eumetsat IASI L2 data used for the standard near-real time version. The need for such a dataset emerged after a series of sharp discontinuities were identified in the NH3 timeseries, which could be traced back to incremental changes in the IASI L2 algorithms for temperature and clouds. The reanalysed dataset is coherent in time and can therefore be used to study trends. Furthermore, both datasets agree reasonably well in the mean on recent data, after the date when the IASI meteorological L2 version 6 became operational (30 September 2014).

Part of the ISSI Scientific Report Series volume 16; International audience; In this chapter we describe what is achievable in terms of pollutant tracking from space using observations provided by thermal infrared remote sensors. After a general introduction on infrared remote sensing, we exploit the data provided by the Infrared Atmospheric Sounding Interferometer (IASI) missions onboard the Metop series of satellite to illustrate pollution detection at various spatial and temporal scales. Then, we focus on air pollution over China and discuss three case studies involving different pollutants. The first example discusses the geophysical conditions for detection of ammonia (NH3) and sulfur dioxide (SO2), both precursors of particulate matter (PM). The second case illustrates the seasonal variation of ozone (O3), in particular during the monsoon period. The third case shows the local accumulation of enhanced levels of carbon monoxide (CO) when pollution episodes occur.

International audience; Separating concentrations of carbon monoxide (CO) in the boundary layer from the rest of the atmosphere with nadir satellite measurements is of particular importance to differentiate emission from transport. Although thermal infrared (TIR) satellite sounders are considered to have limited sensitivity to the composition of the near-surface atmosphere, previous studies show that they can provide information on CO close to the ground in case of high thermal contrast. In this work we investigate the capability of IASI (Infrared Atmospheric Sounding Interferometer) to retrieve near-surface CO concentrations, and we quantitatively assess the influence of thermal contrast on such retrievals. We present a 3-part analysis, which relies on both theoretical forward simulations and retrievals on real data, performed for a large range of negative and positive thermal contrast situations. First, we derive theoretically the IASI detection threshold of CO enhancement in the boundary layer, and we assess its dependence on thermal contrast. Then, using the optimal estimation formalism, we quantify the role of thermal contrast on the error budget and information content of near-surface CO retrievals. We demonstrate that, contrary to what is usually accepted, large negative thermal contrast values (ground cooler than air) lead to a better decorrelation between CO concentrations in the low and the high troposphere than large positive thermal contrast (ground warmer than the air). In the last part of the paper we use Mexico City and Barrow as test cases to contrast our theoretical predictions with real retrievals, and to assess the accuracy of IASI surface CO retrievals through comparisons to ground-based in-situ measurements.

International audience; We analyze the ozone (O3) variability in the troposphere (from ground to 300 hPa) using eight years (January 2008 – March 2016) of O3 profile measurements provided by the Infrared Atmospheric Sounding Interferometer (IASI) onboard the MetOp satellite. The capability of IASI to monitor the year-to-year variability in that layer is examined first in terms of vertical sensitivity, a priori contribution and correlations in the deseasonalized anomalies with the upper layers. We present global patterns of the main geophysical drivers (e.g. solar flux - SF, Quasi-Biennial Oscillations - QBO, North Atlantic Oscillation - NAO, El Niño/Southern Oscillation - ENSO) of IASI O3 variations, obtained by applying appropriate annual and seasonal multivariate regression models on time series of spatially gridded averaged O3. The results show that the models are able to explain most of the O3 variability captured by IASI. Large O3 changes in the North Arctic/Euro-Atlantic sector and over the equatorial band are attributed to the NAO and the QBO effects, respectively. ENSO is modeled as the main contributor to the O3 variations in the tropical band where direct effects of warm and cool ENSO phases are highlighted with a clear tropical-extratropical gradient. A strong West-East gradient in the tropics is also found and likely reflects an indirect effect related to ENSO dry conditions. Finally, we also show that the ENSO perturbs the O3 variability far from the tropics into mid- and high latitudes where a significant 4-month time-lag in the response of O3 to ENSO is identified for the first time.

In the wake of the June 2011 Nabro eruption, large stratospheric plumes were observed by several instruments up to altitudes of 21 km, much higher than initial reported injection heights. It has been debated whether deep convection associated with the Asian Summer Monsoon anticyclone played a vital role in the vertical transport of the plume. Here we present a new and fast SO2 height retrieval algorithm for observations of the Infrared Atmospheric Sounding Interferometer (IASI). A comprehensive validation with forward trajectories and coincident CALIOP measurements is presented which indicates an accuracy better than 2 km for plumes below 20 km and SO2 columns up to the 1 DU level. We use this new product to analyse the Nabro eruption. Our findings indicate an initial plume located mainly between 15 and 17 km for which the lower parts underwent in succession rapid descent and uplift, within the Asian Monsoon anticyclone circulation, up to the stable thermal tropopause between 16 and 18 km, from where it slowly ascended further into the stratosphere. Evidence is presented that emissions in the first week of the eruption also contributed to the stratospheric sulfur input. This includes a second eruption between 15 and 17 km on the 16th and continuous emissions in the mid-troposphere of which some were also entrained and lifted within the anticyclonic circulation.

Ammonia (NH3) emissions in the atmosphere have increased substantially over the past decades, largely because of intensive livestock production and use of fertilizers. As a short-lived species, NH3 is highly variable in the atmosphere and its concentration is generally small, except near local sources. While ground-based measurements are possible, they are challenging and sparse. Advanced infrared sounders in orbit have recently demonstrated their capability to measure NH3, offering a new tool to refine global and regional budgets. In this paper we describe an improved retrieval scheme of NH3 total columns from the measurements of the Infrared Atmospheric Sounding Interferometer (IASI). It exploits the hyperspectral character of this instrument by using an extended spectral range (800–1200 cm−1) where NH3 is optically active. This scheme consists of the calculation of a dimensionless spectral index from the IASI level1C radiances, which is subsequently converted to a total NH3 column using look-up tables built from forward radiative transfer model simulations. We show how to retrieve the NH3 total columns from IASI quasi-globally and twice daily above both land and sea without large computational resources and with an improved detection limit. The retrieval also includes error characterization of the retrieved columns. Five years of IASI measurements (1 November 2007 to 31 October 2012) have been processed to acquire the first global and multiple-year data set of NH3 total columns, which are evaluated and compared to similar products from other retrieval methods. Spatial distributions from the five years data set are provided and analyzed at global and regional scales. In particular, we show the ability of this method to identify smaller emission sources than those previously reported, as well as transport patterns over the ocean. The five-year time series is further examined in terms of seasonality and interannual variability (in particular as a function of fire activity) separately for the Northern and Southern Hemispheres.

In this paper we investigate a severe pollution episode that occurred in Beijing, Tianjin, and the Hebei province in January 2013. The episode was caused by the combination of anthropogenic emissions and a high-pressure system that trapped pollutants in the boundary layer. Using IASI (Infrared Atmospheric Sounding Interferometer) satellite measurements, high concentrations of key trace gases such as carbon monoxide (CO), sulfur dioxide (SO2), and ammonia (NH3) along with ammonium sulfate aerosol ((NH4)2SO4) are found. We show that IASI is able to detect boundary layer pollution in case of large negative thermal contrast combined with high levels of pollution. Our findings demonstrate that anthropogenic key pollutants, such as CO and SO2, can be monitored by IASI in the North China Plain during wintertime in support of air quality evaluation and management.