Infrared Atmospheric Sounding Interferometer Measurements Research Articles

A satellite chronology of plumes from the April 2021 eruption of La Soufrière, St Vincent

Abstract. Satellite instruments play a valuable role in detecting, monitoring and characterising emissions of ash and gas into the atmosphere during volcanic eruptions. This study uses two satellite instruments, the Infrared Atmospheric Sounding Interferometer (IASI) and the Advanced Baseline Imager (ABI), to examine the plumes of ash and sulfur dioxide (SO2) from the April 2021 eruption of La Soufrière, St Vincent. The frequent ABI data have been used to construct a 14 d chronology of a series of explosive events at La Soufrière, which is then complemented by measurements of SO2 from IASI, which is able to track the plume as it is transported around the globe. A minimum of 35 eruptive events were identified using true, false and brightness temperature difference maps produced with the ABI data. The high temporal resolution images were used to identify the approximate start and end times, as well as the duration and characteristics of each event. From this analysis, four distinct phases within the 14 d eruption have been defined, each consisting of multiple explosive events with similar characteristics: (1) an initial explosive event, (2) a sustained event lasting over 9 h, (3) a pulsatory phase with 25 explosive events in a 65.3 h period and (4) a waning sequence of explosive events. It is likely that the multiple explosive events during the April 2021 eruption contributed to the highly complex plume structure that can be seen in the IASI measurements of the SO2 column amounts and heights. The bulk of the SO2 from the first three phases of the eruption was transported eastwards, which based on the wind direction at the volcano implies that the SO2 was largely in the upper troposphere. Some of the SO2 was carried to the south and west of the volcano, suggesting a smaller emission of the gas into the stratosphere, there being a shift in wind direction around the height of the tropopause. The retrieved SO2 heights show that the plume had multiple layers but was largely concentrated between 13 and 19 km, with the majority of the SO2 being located in the upper troposphere and around the height of the tropopause, with some emission into the stratosphere. An average e-folding time of 6.07±4.74 d was computed based on the IASI SO2 results: similar to other tropical eruptions of this magnitude and height. The SO2 was trackable for several weeks after the eruption and is shown to have circulated the globe, with parts of it reaching as far as 45∘ S and 45∘ N. Using the IASI SO2 measurements, a time series of the total SO2 mass loading was produced, with this peaking on 13 April (descending orbits) at 0.31±0.09 Tg. Converting these mass values to a temporally varying SO2 flux demonstrated that the greatest emission occurred on 10 April with that measurement incorporating SO2 from the second phase of the eruption (sustained emission) and the beginning of the pulsatory phase. The SO2 flux is then shown to fall during the later stages of the eruption: suggesting a reduction in eruptive energy, something also reflected in ash height estimates obtained with the ABI instrument. A total SO2 emission of 0.63±0.5 Tg of SO2 has been derived, although due to limitations associated with the retrieval, particularly in the first few days after the eruption began, this, the retrieved column amounts and the total SO2 mass on each day should be considered minimum estimates. There are a number of similarities between the 1979 and 2021 eruptions at La Soufrière, with both eruptions consisting of a series of explosive events with varied heights and including some emission into the stratosphere. These similarities highlight the importance of in-depth investigations into eruptions and the valuable contribution of satellite data for this purpose; as these studies aid in learning about a volcano's behaviour, which may allow for better preparation for future eruptive activity.

Extending the HIRS Data Record with IASI Measurements

The High-Resolution Infrared Radiation Sounder (HIRS) on the NOAA and the MetOp satellite series have provided global sounding measurements since the late 1970s, spanning over 40 years. These measurements have been useful in climate change detection, numerical weather prediction, and development of long-term climate data records of profiles of atmospheric temperature and humidity, cloud climatology, upper tropospheric water vapor, outgoing longwave radiation, etc. However, the HIRS instrument is being replaced by the new generation of sounders such as the hyperspectral Infrared Atmospheric Sounding Interferometer (IASI) on recently launched satellites. In order to continue and extend the HIRS record, we use IASI measurements to simulate and derive HIRS-like data for the 12 HIRS longwave channels. The MetOp satellite operated by EUMETSAT carries both the HIRS and the hyper-spectral IASI instrument with accurate spectral and radiometric calibration, providing a great opportunity to consistently calibrate the measurements. The IASI radiances are convolved with the HIRS spectral response functions to produce IASI-simulated HIRS (IHIRS) for the longwave channels. In the present work, IHIRS data are collocated and compared with HIRS observed radiances on the same satellite to develop a calibration table for each of the ascending/descending orbits and cloudy and clear categories. The resulting inter-instrument calibrated IHIRS data was found to agree with HIRS brightness temperatures within 0.05 K for all longwave channels.

Measurement report: Evolution and distribution of NH3 over Mexico City from ground-based and satellite infrared spectroscopic measurements

Abstract. Ammonia (NH3) is the most abundant alkaline compound in the atmosphere, with consequences for the environment, human health, and radiative forcing. In urban environments, it is known to play a key role in the formation of secondary aerosols through its reactions with nitric and sulfuric acids. However, there are only a few studies about NH3 in Mexico City. In this work, atmospheric NH3 was measured over Mexico City between 2012 and 2020 by means of ground-based solar absorption spectroscopy using Fourier transform infrared (FTIR) spectrometers at two sites (urban and remote). Total columns of NH3 were retrieved from the FTIR spectra and compared with data obtained from the Infrared Atmospheric Sounding Interferometer (IASI) satellite instrument. The diurnal variability of NH3 differs between the two FTIR stations and is strongly influenced by the urban sources. Most of the NH3 measured at the urban station is from local sources, while the NH3 observed at the remote site is most likely transported from the city and surrounding areas. The evolution of the boundary layer and the temperature play a significant role in the recorded seasonal and diurnal patterns of NH3. Although the vertical columns of NH3 are much larger at the urban station, the observed annual cycles are similar for both stations, with the largest values in the warm months, such as April and May. The IASI measurements underestimate the FTIR NH3 total columns by an average of 32.2±27.5 % but exhibit similar temporal variability. The NH3 spatial distribution from IASI shows the largest columns in the northeast part of the city. In general, NH3 total columns over Mexico City measured at the FTIR stations exhibited an average annual increase of 92±3.9×1013 molecules cm−2 yr−1 (urban, from 2012 to 2019) and 8.4±1.4×1013 molecules cm−2 yr−1 (remote, from 2012 to 2020), while IASI data within 20 km of the urban station exhibited an average annual increase of 38±7.6×1013 molecules cm−2 yr−1 from 2008 to 2018.

Design and description of the MUSICA IASI full retrieval product

Abstract. IASI (Infrared Atmospheric Sounding Interferometer) is the core instrument of the currently three Metop (Meteorological operational) satellites of EUMETSAT (European Organization for the Exploitation of Meteorological Satellites). The MUSICA IASI processing has been developed in the framework of the European Research Council project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water). The processor performs an optimal estimation of the vertical distributions of water vapour (H2O), the ratio between two water vapour isotopologues (the HDO/H2O ratio), nitrous oxide (N2O), methane (CH4), and nitric acid (HNO3) and works with IASI radiances measured under cloud-free conditions in the spectral window between 1190 and 1400 cm−1. The retrieval of the trace gas profiles is performed on a logarithmic scale, which allows the constraint and the analytic treatment of ln [HDO]−ln [H2O] as a proxy for the HDO/H2O ratio. Currently, the MUSICA IASI processing has been applied to all IASI measurements available between October 2014 and June 2021 and about two billion individual retrievals have been performed. Here we describe the MUSICA IASI full retrieval product data set. The data set is made available in the form of netCDF data files that are compliant with version 1.7 of the CF (Climate and Forecast) metadata convention. For each individual retrieval these files contain information on the a priori usage and constraint, the retrieved atmospheric trace gas and temperature profiles, profiles of the leading error components, and information on vertical representativeness in the form of the averaging kernels as well as averaging kernel metrics, which are more handy than the full kernels. We discuss data filtering options and give examples of the high horizontal and continuous temporal coverage of the MUSICA IASI data products. For each orbit an individual standard output data file is provided with comprehensive information for each individual retrieval, resulting in a rather large data volume (about 40 TB for the almost 7 years of data with global daily coverage). This, at a first glance, apparent drawback of large data files and data volume is counterbalanced by multiple possibilities of data reuse, which are briefly discussed. Examples of standard data output files and a README .pdf file informing users about access to the total data set are provided via https://doi.org/10.35097/408 (Schneider et al., 2021b). In addition, an extended output data file is made available via https://doi.org/10.35097/412 (Schneider et al., 2021a). It contains the same variables as the standard output files together with Jacobians (and spectral responses) for many different uncertainty sources and gain matrices (due to this additional variables it is called the extended output). We use these additional data for assessing the typical impact of different uncertainty sources – like surface emissivity or spectroscopic parameters – and different cloud types on the retrieval results. The extended output file is limited to 74 example observations (over a polar, mid-latitudinal, and tropical site); its data volume is only 73 MB, and it is thus recommended to users for having a quick look at the data.

Ash particle refractive index model for simulating the brightness temperature spectrum of volcanic ash clouds from satellite infrared sounder measurements

Abstract. Using data from the Infrared Atmospheric Sounding Interferometer (IASI) measurements of volcanic ash clouds (VACs) and radiative transfer calculations, we attempt to simulate the measured brightness temperature spectra (BTS) of volcanic ash aerosols in the infrared region. In particular, the dependence on the ash refractive index (RI) model is investigated. We apply 21 RI models for the optical properties of ash particles, including recently published models. The results of BTS simulations are evaluated using the root mean square (rms) of the brightness temperature difference between measurements and simulations for channels in the wavenumber range of 750–1400 cm−1. The results of numerical simulations for 156 pixels of IASI measurements for ash plumes from seven volcanoes indicated that some newly established RI models have smaller rms than those obtained with the conventional ash RI model. For some eruption events, the RI models deduced from the chemical composition of ash samples for the same volcanic eruption events simulate the measured BTS well. The results suggest that infrared sounder measurements and precise BTS simulations of the VACs contribute to estimating the appropriate RI model in satellite VAC analysis.

Accuracy of Vaisala RS41 and RS92 Upper Tropospheric Humidity Compared to Satellite Hyperspectral Infrared Measurements

Radiosondes are important for calibrating satellite sensors and assessing sounding retrievals. Vaisala RS41 radiosondes have mostly replaced RS92 in the Global Climate Observing System (GCOS) Reference Upper Air Network (GRUAN) and the conventional network. This study assesses RS41 and RS92 upper tropospheric humidity (UTH) accuracy by comparing with Infrared Atmospheric Sounding Interferometer (IASI) upper tropospheric water vapor absorption spectrum measurements. Using single RS41 and RS92 soundings at three GRUAN and DOE Atmospheric Radiation Measurement (ARM) sites and dual RS92/RS41 launches at three additional GRUAN sites, collocated with cloud-free IASI radiances (OBS), we compute Line-by-Line Radiative Transfer Model radiances for radiosonde profiles (CAL). We analyze OBS-CAL differences from 2015 to 2020, for daytime, nighttime, and dusk/dawn separately if data is available, for standard (STD) RS92 and RS41 processing, and RS92 GRUAN Data Processing (GDP; RS41 GDP is in development). We find that daytime RS41 (even without GDP) has ~1% smaller UTH errors than GDP RS92. RS41 may still have a dry bias of 1–1.5% for both daytime and nighttime, and a similar error for nighttime RS92 GDP, while standard RS92 may have a dry bias of 3–4%. These sonde humidity biases are probably upper limits since “cloud-free” scenes could still be cloud contaminated. Radiances computed from European Centre for Medium-Range Weather Forecasts (ECMWF) analyses match better than radiosondes with IASI measurements, perhaps because ECMWF assimilates IASI measurements. Relative differences between RS41 STD and RS92 GDP, or between radiosondes and ECMWF humidity profiles obtained from the radiance analysis, are consistent with their differences obtained directly from the RH measurements.

Decrease in tropospheric O<sub>3</sub> levels in the Northern Hemisphere observed by IASI

Abstract. In this study, we describe the recent changes in the tropospheric ozone (O3) 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 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 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 O3 trends having been reached from the available independent datasets (UV or IR satellites, O3 sondes, aircrafts, ground-based measurements, etc.) for the reasons that are discussed in the text, this finding is consistent with the reported decrease in O3 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 O3–CO relationship (in terms of correlation coefficient, regression slope and covariance) that we found to be the strongest at northern midlatitudes in summer.

Global height-resolved methane retrievals from the Infrared Atmospheric Sounding Interferometer (IASI) on MetOp

Abstract. This paper describes the global height-resolved methane (CH4) retrieval scheme for the Infrared Atmospheric Sounding Interferometer (IASI) on MetOp, developed at the Rutherford Appleton Laboratory (RAL). The scheme precisely fits measured spectra in the 7.9 micron region to allow information to be retrieved on two independent layers centred in the upper and lower troposphere. It also uses nitrous oxide (N2O) spectral features in the same spectral interval to directly retrieve effective cloud parameters to mitigate errors in retrieved methane due to residual cloud and other geophysical variables. The scheme has been applied to analyse IASI measurements between 2007 and 2015. Results are compared to model fields from the MACC greenhouse gas inversion and independent measurements from satellite (GOSAT), airborne (HIPPO) and ground (TCCON) sensors. The estimated error on methane mixing ratio in the lower- and upper-tropospheric layers ranges from 20 to 100 and from 30 to 40 ppbv, respectively, and error on the derived column-average ranges from 20 to 40 ppbv. Vertical sensitivity extends through the lower troposphere, though it decreases near to the surface. Systematic differences with the other datasets are typically < 10 ppbv regionally and < 5 ppbv globally. In the Southern Hemisphere, a bias of around 20 ppbv is found with respect to MACC, which is not explained by vertical sensitivity or found in comparison of IASI to TCCON. Comparisons to HIPPO and MACC support the assertion that two layers can be independently retrieved and provide confirmation that the estimated random errors on the column- and layer-averaged amounts are realistic. The data have been made publically available via the Centre for Environmental Data Analysis (CEDA) data archive (Siddans, 2016).

The Application of PCRTM Physical Retrieval Methodology for IASI Cloudy Scene Analysis

This paper applies a physical inversion approach to retrieve geophysical properties from the single instrumental field-of-view (FOV) spectral radiances measured by the Infrared Atmospheric Sounding Interferometer (IASI) under all-sky conditions. We demonstrate the use of a principal-component-based radiative transfer model (PCRTM) and a physical inversion methodology to simultaneously retrieve cloud radiative and microphysical properties along with atmospheric thermodynamic parameters. By using a fast parameterization scheme, the PCRTM can include the cloud scattering properties simulation in radiative transfer calculations without incurring much more computational cost. The computational speed achieved for a single FOV forward simulation under cloudy skies is similar to that normally achieved for clear skies. The retrieval algorithm introduced herein adopts a novel cloud phase determination scheme, to stabilize and/or constrain retrieval iterations, based on characteristics of the reflectance and transmittance of ice and water clouds. A modified Gaussian-Newton minimization technique is employed in the iterative inversion process in order to overcome a highly nonlinear cost function introduced by the cloud parameters. We carry out a rigorous error analysis for the retrieval of temperature, moisture, ozone (O3), and carbon monoxide (CO) from IASI measurements under cloudy-sky conditions. Our algorithm is applied to real IASI observations. Retrieval results are validated using European Center for Medium-Range Weather Forecasting data and collocated Lidar/Radar measurements, and the dependence of retrieval accuracy on cloud optical depth is illustrated.

Retrieval of ash properties from IASI measurements

Abstract. A new optimal estimation algorithm for the retrieval of volcanic ash properties has been developed for use with the Infrared Atmospheric Sounding Interferometer (IASI). The retrieval method uses the wave number range 680–1200 cm−1, which contains window channels, the CO2 ν2 band (used for the height retrieval), and the O3 ν3 band.Assuming a single infinitely (geometrically) thin ash plume and combining this with the output from the radiative transfer model RTTOV, the retrieval algorithm produces the most probable values for the ash optical depth (AOD), particle effective radius, plume top height, and effective radiating temperature. A comprehensive uncertainty budget is obtained for each pixel. Improvements to the algorithm through the use of different measurement error covariance matrices are explored, comparing the results from a sensitivity study of the retrieval process using covariance matrices trained on either clear-sky or cloudy scenes. The result showed that, due to the smaller variance contained within it, the clear-sky covariance matrix is preferable. However, if the retrieval fails to pass the quality control tests, the cloudy covariance matrix is implemented.The retrieval algorithm is applied to scenes from the Eyjafjallajökull eruption in 2010, and the retrieved parameters are compared to ancillary data sources. The ash optical depth gives a root mean square error (RMSE) difference of 0.46 when compared to retrievals from the MODerate-resolution Imaging Spectroradiometer (MODIS) instrument for all pixels and an improved RMSE of 0.2 for low optical depths (AOD < 0.1). Measurements from the Facility for Airborne Atmospheric Measurements (FAAM) and Deutsches Zentrum für Luft- und Raumfahrt e.V. (DLR) flight campaigns are used to verify the retrieved particle effective radius, with the retrieved distribution of sizes for the scene showing excellent consistency. Further, the plume top altitudes are compared to derived cloud-top altitudes from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument and show agreement with RMSE values of less than 1 km.

First characterization and validation of FORLI-HNO<sub>3</sub> vertical profiles retrieved from IASI/Metop

Abstract. 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.

An Observationally Based Global Band-by-Band Surface Emissivity Dataset for Climate and Weather Simulations

Abstract While current atmospheric general circulation models (GCMs) still treat the surface as a blackbody in their longwave radiation scheme, recent studies suggest the need for taking realistic surface spectral emissivity into account. There have been few measurements available for the surface emissivity in the far IR (<650 cm−1). Based on first-principle calculation, the authors compute the spectral emissivity over the entire longwave spectrum for a variety of surface types. MODIS-retrieved mid-IR surface emissivity at 0.05° × 0.05° spatial resolution is then regressed against the calculated spectral emissivity to determine the surface type for each grid. The derived spectral emissivity data are then spatially averaged onto 0.5° × 0.5° grids and spectrally integrated onto the bandwidths used by the RRTMG_LW—a longwave radiation scheme widely used in current climate and numerical weather models. The band-by-band surface emissivity dataset is then compared with retrieved surface spectral emissivities from Infrared Atmospheric Sounding Interferometer (IASI) measurements. The comparison shows favorable agreement between two datasets in all the bands covered by the IASI measurements. The authors further use the dataset in conjunction with ERA-Interim to evaluate its impact on the top-of-atmosphere radiation budget. Depending on the blackbody surface assumptions used in the original calculation, the globally averaged difference caused by the inclusion of realistic surface emissivity ranges from −1.2 to −1.5 W m−2 for clear-sky OLR and from −0.67 to −0.94 W m−2 for all-sky OLR. Moreover, the difference is not spatially uniform and has a distinct spatial pattern.

HCOOH distributions from IASI for 2008–2014: comparison with ground-based FTIR measurements and a global chemistry-transport model

Abstract. Formic acid (HCOOH) is one of the most abundant volatile organic compounds in the atmosphere. It is a major contributor to rain acidity in remote areas. There are, however, large uncertainties on the sources and sinks of HCOOH and therefore HCOOH is misrepresented by global chemistry-transport models. This work presents global distributions from 2008 to 2014 as derived from the measurements of the Infrared Atmospheric Sounding Interferometer (IASI), based on conversion factors between brightness temperature differences and representative retrieved total columns over seven regions: Northern Africa, southern Africa, Amazonia, Atlantic, Australia, Pacific, and Russia. The dependence of the measured HCOOH signal on the thermal contrast is taken into account in the conversion method. This conversion presents errors lower than 20 % for total columns ranging between 0.5 and 1 × 1016 molec cm−2 but reaches higher values, up to 78 %, for columns that are lower than 0.3 × 1016 molec cm−2. Signatures from biomass burning events are highlighted, such as in the Southern Hemisphere and in Russia, as well as biogenic emission sources, e.g., over the eastern USA. A comparison between 2008 and 2014 with ground-based Fourier transform infrared spectroscopy (FTIR) measurements obtained at four locations (Maido and Saint-Denis at La Réunion, Jungfraujoch, and Wollongong) is shown. Although IASI columns are found to correlate well with FTIR data, a large bias (> 100 %) is found over the two sites at La Réunion. A better agreement is found at Wollongong with a negligible bias. The comparison also highlights the difficulty of retrieving total columns from IASI measurements over mountainous regions such as Jungfraujoch. A comparison of the retrieved columns with the global chemistry-transport model IMAGESv2 is also presented, showing good representation of the seasonal and interannual cycles over America, Australia, Asia, and Siberia. A global model underestimation of the distribution and a misrepresentation of the seasonal cycle over India are also found. A small positive trend in the IASI columns is observed over Australia, Amazonia, and India over the 2008–2014 period (from 0.7 to 1.5 % year−1), while a decrease of ∼ 0.8 % year−1 is measured over Siberia.

Ash and ice clouds during the Mt Kelud February 2014 eruption as interpreted from IASI and AVHRR/3 observations

Abstract. During the Mt Kelud February 2014 eruption the ash cloud was detectable on 13–14 February in the infrared with the reverse absorption technique by, for example, the Advanced Very High Resolution Radiometer (AVHRR/3). The Infrared Atmospheric Sounding Interferometer (IASI) observed the ash cloud also on 15 February when AVHRR did not detect any ash signal. The differences between ash detection with AVHRR/3 and IASI are discussed along with the reasons for the differences, supported by radiative transfer modelling. The effect of concurrent ice clouds on the ash detection and the ash signal in the IASI measurements is demonstrated. Specifically, a radiative transfer model is used to simulate IASI spectra with ash-only, with ice cloud only and with both ash and ice clouds. It is shown that modelled IASI spectra with ash and ice clouds reproduce the measured IASI spectra better than ash-only- or ice-only-modelled spectra. The ash and ice modelled spectra that best reproduce the IASI spectra contain about a factor of 12 less ash than the ash-only spectra that come closest to reproducing the measured spectra.

Ozone variability in the troposphere and the stratosphere from the first 6 years of IASI observations (2008–2013)

Abstract. In this paper, we assess how daily ozone (O3) measurements from the Infrared Atmospheric Sounding Interferometer (IASI) on the MetOp-A platform can contribute to the analyses of the processes driving O3 variability in the troposphere and the stratosphere and, in the future, to the monitoring of long-term trends. The temporal evolution of O3 during the first 6 years of IASI (2008–2013) operation is investigated with multivariate regressions separately in four different layers (ground–300, 300–150, 150–25, 25–3 hPa), by adjusting to the daily time series averaged in 20° zonal bands, seasonal and linear trend terms along with important geophysical drivers of O3 variation (e.g. solar flux, quasi-biennial oscillation (QBO)). The regression model is shown to perform generally very well with a strong dominance of the annual harmonic terms and significant contributions from O3 drivers, in particular in the equatorial region where the QBO and the solar flux contribution dominate. More particularly, despite the short period of the IASI data set available up to now, two noticeable statistically significant apparent trends are inferred from the daily IASI measurements: a positive trend in the upper stratosphere (e.g. 1.74 ± 0.77 DU year−1 between 30 and 50° S), which is consistent with other studies suggesting a turnaround for stratospheric O3 recovery, and a negative trend in the troposphere at the mid-latitudes and high northern latitudes (e.g. −0.26 ± 0.11 DU year−1 between 30 and 50° N), especially during summer and probably linked to the impact of decreasing ozone precursor emissions. The impact of the high temporal sampling of IASI on the uncertainty in the determination of O3 trend has been further explored by performing multivariate regressions on IASI monthly averages and on ground-based Fourier transform infrared (FTIR) measurements.

Assimilation of transformed retrievals obtained from clear‐sky IASI measurements

A recent study, which provided theoretical justifications to show that the assimilation of radiances and retrievals can be equivalent when some key requirements are met – namely when remote‐sounding data are related to model variable perturbations in an approximately linear way and when the same prior constraints are used to solve the inverse problem – has brought new insight into the problem of how to assimilate satellite measurements in numerical weather prediction. In this article, we explore this new theoretical framework in practical terms and investigate the viability of assimilating transformed retrievals from hyperspectral infrared sounders such as the Infrared Atmospheric Sounding Interferometer (IASI) in an optimal way. First, the dependence of a measure of information content of temperature‐ and humidity‐sensitive observations from IASI in clear‐sky conditions on the forecast (or ‘background’) uncertainty used to constrain the retrievals is assessed. Subsequently, numerical comparisons between profiles obtained from direct radiance assimilation and those obtained from assimilating appropriately transformed retrievals are performed, for different atmospheric conditions. By making use of the new concept of degrees‐of‐freedom (DFS) weighting function, it is shown that the background error covariance matrix plays a crucial role in determining the conditions for equivalence between assimilation of radiances and transformed retrievals. The numerical comparisons confirm the theoretical results stating that the temperature and humidity profiles obtained from both the direct assimilation of radiances and the assimilation of transformed retrievals are equal within the analysis error as long as the same prior constraints are used. Finally, when the prior differs, it is shown how the characteristics of background error matrices are crucial to guarantee the numerical equivalence between the two methods; the best is when the background matrix utilised to calculate the transformed retrievals is characterised by larger variances than the one utilised in the assimilation.

Retrieval of near-surface sulfur dioxide (SO<sub>2</sub>) concentrations at a global scale using IASI satellite observations

Abstract. SO2 from volcanic eruptions is now operationally monitored from space in both the ultraviolet (UV) and thermal infrared (TIR) spectral range, but anthropogenic SO2 has almost solely been measured from UV sounders. Indeed, TIR instruments are well known to have a poor sensitivity to the planetary boundary layer (PBL), due to generally low thermal contrast (TC) between the ground and the air above it. Recent studies have demonstrated the capability of the Infrared Atmospheric Sounding Interferometer (IASI) to measure near-surface SO2 locally, for specific atmospheric conditions. In this work, we develop a retrieval method allowing the inference of SO2 near-surface concentrations from IASI measurements at a global scale. This method consists of two steps. Both are based on the computation of radiance indexes representing the strength of the SO2 ν3 band in IASI spectra. The first step allows the peak altitude of SO2 to be retrieved and near-surface SO2 to be selected. In the second step, 0–4 km columns of SO2 are inferred using a look-up table (LUT) approach. Using this new retrieval method, we obtain the first global distribution of near-surface SO2 from IASI-A, and identify the dominant anthropogenic hotspot sources and volcanic degassing. The 7-year daily time evolution of SO2 columns above two industrial source areas (Beijing in China and Sar Cheshmeh in Iran) is investigated and correlated to the seasonal variations of the parameters that drive the IASI sensitivity to the PBL composition. Apart from TC, we show that humidity is the most important parameter which determines IR sensitivity to near-surface SO2 in the ν3 band. As IASI provides global measurements twice daily, the differences between the retrieved columns for the morning and evening orbits are investigated. This paper finally presents a first intercomparison of the measured 0–4 km columns with an independent iterative retrieval method and with observations of the Ozone Monitoring Instrument (OMI).

Moist processes during MJO events as diagnosed from water isotopic measurements from the IASI satellite

This study aims to investigate some characteristics of the moist processes of the Madden-Julian oscillation (MJO), by making use of joint HDO (or δD) and H2O vapor measurements. The MJO is the main intraseasonal mode of the tropical climate, but is hard to properly simulate in global atmospheric models. The joint use of δD-H2O diagnostics yields additional information compared to sole humidity measurements. We use mid-tropospheric Infrared Atmospheric Sounding Interferometer (IASI) satellite δD and H2O measurements to determine the mean MJO humidity and δD evolution. Moreover, by making use of high temporal resolution data, we determine the variability in this evolution during about eight MJO events from 2010 to 2012 (including those monitored during the CINDY/DYNAMO campaign). This data has a higher spatio-temporal coverage than previous δD measurements, enabling the sampling of individual MJO events. IASI measurements over the Indian Ocean confirm earlier findings that the moistening before the precipitation peak of an MJO event is due to water vapor slightly enriched in HDO. There is then a HDO depletion around the precipitation peak that also corresponds to the moister environment. Most inter-event variability determined in the current study occurs 5 to 10 days after the MJO event. In 75% of the events, humidity decreases while the atmosphere remains depleted. In a quarter of the events, humidity increases simultaneously with an increase in δD. After this, the advection of relatively dry and enriched air brings back the state to the mean. Over the maritime continent, δD-H2O cycles are more variable on timescales shorter than the MJO and the inter-event variability is larger than over the Indian Ocean. The sequence of moistening and drying processes as revealed by the q-δD cycles can be used as a benchmark to evaluate the representation of moist processes in models. This is done here by comparing observations to simulations of the isotope enabled LMDZ GCM nudged with reanalysis wind fields. These simulations also give informations to investigate possible physical origins of the observed q-δD cycles.

Acetylene (C<sub>2</sub>H<sub>2</sub>) and hydrogen cyanide (HCN) from IASI satellite observations: global distributions, validation, and comparison with model

Abstract. 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).

Proposal for Infrared Atmospheric Sounding Interferometer on-board data compression

The Infrared Atmospheric Sounding Interferometer (IASI) system provides infrared soundings of moisture and temperature profiles, as well as soundings of chemical components. These measurements play a key role in atmospheric chemistry, global change, and climate monitoring. The instrument, developed by a cooperating agreement between European Organisation for the Exploitation of Meteorological Satellites and Centre National d'Études Spatiales, is implemented on the Metop satellite series. The instrument data production rate is 45 Mb/s while the transmission rate allocated to IASI measurements is 1.5 Mb/s. It is thus necessary to implement a significant part of the IASI data processing on-board the instrument. We investigate the information statistics of IASI L0 data once the on-board processing chain is finished. We analyze order-0 entropy, and order-1, order-2 and order-3 conditional entropies, where conditional entropies assess both the spectral and the spatial joint information. According to the simple order-0 entropy, at least one bit per sample could be spared if a variable-length code was employed. We also investigate the actual performance of different lossless compression techniques on IASI L0 data. The CCSDS-123, JPEG-LS, and JPEG2000 standards, as well as M-CALIC coding technique are evaluated. Experimental results reveal that IASI Level 0 data can be coded by a compression ratio above 2.6:1.