Infrared Atmospheric Sounding Interferometer Retrievals Research Articles

How well are aerosol–cloud interactions represented in climate models? – Part 1: Understanding the sulfate aerosol production from the 2014–15 Holuhraun eruption

Abstract. For over 6 months, the 2014–2015 effusive eruption at Holuhraun, Iceland, injected considerable amounts of sulfur dioxide (SO2) into the lower troposphere with a daily rate of up to one-third of the global emission rate, causing extensive air pollution across Europe. The large injection of SO2, which oxidises to form sulfate aerosol (SO42-), provides a natural experiment offering an ideal opportunity to scrutinise state-of-the-art general circulation models' (GCMs) representation of aerosol–cloud interactions (ACIs). Here we present Part 1 of a two-part model inter-comparison using the Holuhraun eruption as a framework to analyse ACIs. We use SO2 retrievals from the Infrared Atmospheric Sounding Interferometer (IASI) instrument and ground-based measurements of SO2 and SO42- mass concentrations across Europe, in conjunction with a trajectory analysis using the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model, to assess the spatial and chemical evolution of the volcanic plume as simulated by five GCMs and a chemical transport model (CTM). IASI retrievals of plume altitude and SO2 column load reveal that the volcanic perturbation is largely contained within the lower troposphere. Compared to the satellite observations, the models capture the spatial evolution and vertical variability of the plume reasonably well, although the models often overestimate the plume altitude. HYSPLIT trajectories are used to attribute to Holuhraun emissions 111 instances of elevated sulfurous surface mass concentrations recorded at European Monitoring and Evaluation Programme (EMEP) stations during September and October 2014. Comparisons with the simulated concentrations show that the modelled ratio of SO2 to SO42- during these pollution episodes is often underestimated and overestimated for the young and mature plume, respectively. Models with finer vertical resolutions near the surface are found to better capture these elevated sulfurous ground-level concentrations. Using an exponential function to describe the decay of observed surface mass concentration ratios of SO2 to SO42- with plume age, the in-plume oxidation rate constant is estimated as 0.032 ± 0.002 h−1 (1.30 ± 0.08 d e-folding time), with a near-vent ratio of 25 ± 5 (µg m−3 of SO2 / µg m−3 of SO42-). The majority of the corresponding derived modelled oxidation rate constants are lower than the observed estimate. This suggests that the representation of the oxidation pathway/s in the simulated plumes is too slow. Overall, despite their coarse spatial resolutions, the six models show reasonable skill in capturing the spatial and chemical evolution of the Holuhraun plume. This capable representation of the underlying aerosol perturbation is essential to enable the investigation of the eruption's impact on ACIs in the second part of this study.

An Improved IASI Temperature and Humidity Retrieval Method Based on Double Channel Differences

AbstractDue to surface emissivity, the retrieval accuracy of hyperspectral infrared temperature and humidity profiles is typically poor in the lower atmosphere. To solve this problem, we use the double channel differences method (DCDM) to retrieve the temperature and humidity profiles of the Infrared Atmospheric Sounding Interferometer (IASI) with different surfaces, zenith angles, and data sources. Results show that DCDM can effectively improve IASI retrieval performance. The root mean square error (RMSE) reductions are large and exhibit no marked change with the zenithal angle. Compared with prior profiles, prior near‐surface temperatures can markedly improve the retrieval performance of temperature profiles. Humidity profile retrieval using both humidity and temperature channels can reduce the RMSE and the dependence on the precision of the prior inputs. The DCDM can markedly reduce errors in temperature and relative humidity retrievals, and the retrievals agree with ERA‐Interim better than IASI L2. With the DCDM, the lower temperature and relative humidity RMSE can be ∼3.5 K/14% (land), ∼3 K/13% (coast), ∼1.4 K/7% (sea). Compared with radiosonde observations and ERA‐Interim, the DCDM can reduce errors in temperature and humidity retrievals, and the improvement in performance is equivalent.

The global and multi-annual MUSICA IASI {H<sub>2</sub>O, <i>δ</i>D} pair dataset

Abstract. We present a global and multi-annual space-borne dataset of tropospheric {H2O, δD} pairs that is based on radiance measurements from the nadir thermal infrared sensor IASI (Infrared Atmospheric Sounding Interferometer) on board the Metop satellites of EUMETSAT (European Organisation for the Exploitation of Meteorological Satellites). This dataset is an a posteriori processed extension of the MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water) IASI full product dataset as presented in Schneider et al. (2021b). From the independently retrieved H2O and δD proxy states, their a priori settings and constraints, and their error covariances provided by the IASI full product dataset, we generate an optimal estimation product for pairs of H2O and δD. Here, this standard MUSICA method for deriving {H2O, δD} pairs is extended using an a posteriori reduction of the constraints for improving the retrieval sensitivity at dry conditions. By applying this improved water isotopologue post-processing for all cloud-free MUSICA IASI retrievals, this yields a {H2O, δD} pair dataset for the whole period from October 2014 to December 2020 with global coverage twice per day (local morning and evening overpass times). In total, the dataset covers more than 1500 million individually processed observations. The retrievals are most sensitive to variations in {H2O, δD} pairs within the free troposphere, with up to 30 % of all retrievals containing vertical profile information in the {H2O, δD} pair product. After applying appropriate quality filters, the largest number of reliable pair data arises for tropical and subtropical summer regions, but higher latitudes also show a considerable amount of reliable data. Exemplary time series over the tropical Atlantic and West Africa are chosen to illustrate the potential of the MUSICA IASI {H2O, δD} pair data for atmospheric moisture pathway studies. Furthermore, in order to facilitate the application of this rather comprehensive MUSICA IASI {H2O, δD} pair dataset (referred to as Level-2), we additionally provide the data in a re-gridded and simplified format (Level-3) with focus on the quality-filtered {H2O, δD} pairs in the free troposphere. A technical documentation for guiding the use of both datasets is attached as the Supplement. Finally, the Level-2 dataset is referenced with the DOI https://doi.org/10.35097/415 (Diekmann et al., 2021a) and the Level-3 dataset with DOI https://doi.org/10.35097/495 (Diekmann et al., 2021b).

Source attribution of carbon monoxide and ozone over the Indian subcontinent using MOZART-4 chemistry transport model

Daily simulations of tropospheric carbon monoxide (CO) and ozone (O3) have been made using MOZART-4 (Model for OZone And Related chemical Tracers version 4) during 2007–08. The model simulated CO and O3 are evaluated against MOZAIC (Measurement of Ozone and Water Vapor by Airbus In-Service Aircraft) airborne observations over Hyderabad and IASI (Infrared Atmospheric Sounding Interferometer) retrievals over five most populous cities of India i.e. Mumbai, Delhi, Bangalore, Hyderabad, and Ahmedabad. The MOZAIC tropospheric column showed winter maxima and summer minima for CO whereas spring maxima and summer minima for O3. These seasonal features are reproduced well by model over Hyderabad. Model lower and middle tropospheric CO (O3) columns are positively biased by about 14 (8) ppbv as compared to MOZAIC observations. Model underestimated (overestimated) IASI CO columns during pre-monsoon (post-monsoon) while it overestimated IASI O3 columns throughout the year. Model simulated column of CO and O3 are positively biased by 4–13% and 23–33% respectively as compared to the IASI retrievals over five most populous cities. Tagged and sensitivity simulations of MOZART-4 have been used to quantify the contribution of different sources to the tropospheric CO and O3 distribution over the Indian landmass region. At surface, anthropogenic contribution varies from 55% to 81% during different seasons with an annual average contribution of 67%. This contribution decreases with increasing altitude up to 35% at 300 hPa. The contribution of photochemically produced CO is found to be 9–33% at surface. Unlike ANT-CO, the photochemically produced CO increases with altitude as it reaches up to 48% at 300 hPa. Surface BB-CO contributes upto 30% over parts of North East India during pre-monsoon season. Contribution of NAT-CO is found to be negligible (Approximately 6%) near surface as well as at the higher altitudes. Sensitivity simulations are used to decompose the total ozone (TO) into contributions from enhancement of ozone from Indian anthropogenic emissions, referred as Indian pollution ozone (IPO) and from the total background ozone (TBO). Annual total ozone is found to be 30 to 70 ppbv at surface and 77 to 85 ppbv at 300 hPa over the Indian landmass region. IPO and TBO contribute annually 58% and 42% at surface while 45% and 55% at 300 hPa respectively. The IPO contributes strongly at surface, with maximum (68%) impact during pre-monsoon season.

Evaluation of MUSICA IASI tropospheric water vapour profiles using theoretical error assessments and comparisons to GRUAN Vaisala RS92 measurements

Abstract. Volume mixing ratio water vapour profiles have been retrieved from IASI (Infrared Atmospheric Sounding Interferometer) spectra using the MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water) processor. The retrievals are done for IASI observations that coincide with Vaisala RS92 radiosonde measurements performed in the framework of the GCOS (Global Climate Observing System) Reference Upper-Air Network (GRUAN) in three different climate zones: the tropics (Manus Island, 2° S), mid-latitudes (Lindenberg, 52° N), and polar regions (Sodankylä, 67° N). The retrievals show good sensitivity with respect to the vertical H2O distribution between 1 km above ground and the upper troposphere. Typical DOFS (degrees of freedom for signal) values are about 5.6 for the tropics, 5.1 for summertime mid-latitudes, 3.8 for wintertime mid-latitudes, and 4.4 for summertime polar regions. The errors of the MUSICA IASI water vapour profiles have been theoretically estimated considering the contribution of many different uncertainty sources. For all three climate regions, unrecognized cirrus clouds and uncertainties in atmospheric temperature have been identified as the most important error sources and they can reach about 25 %. The MUSICA IASI water vapour profiles have been compared to 100 individual coincident GRUAN water vapour profiles. The systematic difference between the data is within 11 % below 12 km altitude; however, at higher altitudes the MUSICA IASI data show a dry bias with respect to the GRUAN data of up to 21 %. The scatter is largest close to the surface (30 %), but never exceeds 21 % above 1 km altitude. The comparison study documents that the MUSICA IASI retrieval processor provides H2O profiles that capture the large variations in H2O volume mixing ratio profiles well from 1 km above ground up to altitudes close to the tropopause. Above 5 km the observed scatter with respect to GRUAN data is in reasonable agreement with the combined MUSICA IASI and GRUAN random errors. The increased scatter at lower altitudes might be explained by surface emissivity uncertainties at the summertime continental sites of Lindenberg and Sodankylä, and the upper tropospheric dry bias might suggest deficits in correctly modelling the spectroscopic line shapes of water vapour.

Assessing the impacts of assimilating IASI and MOPITT CO retrievals using CESM‐CAM‐chem and DART

AbstractWe show the results and evaluation with independent measurements from assimilating both MOPITT (Measurements Of Pollution In The Troposphere) and IASI (Infrared Atmospheric Sounding Interferometer) retrieved profiles into the Community Earth System Model (CESM). We used the Data Assimilation Research Testbed ensemble Kalman filter technique, with the full atmospheric chemistry CESM component Community Atmospheric Model with Chemistry. We first discuss the methodology and evaluation of the current data assimilation system with coupled meteorology and chemistry data assimilation. The different capabilities of MOPITT and IASI retrievals are highlighted, with particular attention to instrument vertical sensitivity and coverage and how these impact the analyses. MOPITT and IASI CO retrievals mostly constrain the CO fields close to the main anthropogenic, biogenic, and biomass burning CO sources. In the case of IASI CO assimilation, we also observe constraints on CO far from the sources. During the simulation time period (June and July 2008), CO assimilation of both instruments strongly improves the atmospheric CO state as compared to independent observations, with the higher spatial coverage of IASI providing better results on the global scale. However, the enhanced sensitivity of multispectral MOPITT observations to near surface CO over the main source regions provides synergistic effects at regional scales.

Validation of IASI-Retrieved Atmospheric Water Vapor Data over the Tibetan Plateau Region

AbstractThe Infrared Atmospheric Sounding Interferometer (IASI) is a new-generation ultraspectral atmospheric sounding instrument mounted on the MetOp-A, the first operational polar-orbiting satellite developed by the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT). It is an ultrahigh spectral-resolution atmospheric detector which can detect atmospheric chemical composition, temperature, and humidity profiles with high accuracy and resolution. In the present study, through comparative analyses of the similarities and differences between the IASI and the radiosonde observation (RAOB) water vapor data, and between the IASI and the Aqua-AIRS water vapor retrievals, a detailed and systematic assessment of the credibility of the IASI water vapor retrievals over the plateau region was made. A comparison of the IASI retrievals with the AIRS retrievals and the RAOB measurements over the Tibetan Plateau revealed that the IASI retrieval data are reliable and can be used for conduc...

AIRS, IASI, and CrIS Retrieval Records at Climate Scales: An Investigation into the Propagation of Systematic Uncertainty

AbstractUncertainty requirements for climate observations are more stringent than for weather observations because of the scale dependency of natural variation. At present there is no space-based climate observing system, so weather observations have to be aggregated for the study of large-scale change. The management and minimization of uncertainty sources in weather observations are, therefore, a high priority. This work is a first attempt at investigating if a single long-term record can be assembled with temperature retrievals from three hyperspectral satellite sounders in polar orbit: the Atmospheric Infrared Sounder (AIRS) on Aqua in afternoon orbit since 2002, the Infrared Atmospheric Sounding Interferometer (IASI) on MetOp-A in morning orbit since 2006, and the Cross-track Infrared Sounder (CrIS) on board the Suomi National Polar-Orbiting Partnership in afternoon orbit since 2011. These instruments measure not only the vertical atmospheric structure but also atmospheric composition, thus providing coincident observations of many essential climate variables. Two main sources of known systematic differences, namely local sampling time (LST) and instrument type (i.e., interferometer vs grating spectrometer), are characterized. For a 5-yr record it is shown that differences among these temperature soundings are height dependent; a multi-instrument data record could be assembled from measurements of the stratosphere but this is not yet possible for the troposphere, where cloud effects are shown to be dominant and dependent on instrument type. Moreover, LST differences are limited to regional systematic effects in the lower troposphere and boundary layer. This research is a step toward the development of transparent and geophysically consistent methods with which to assemble weather measurements into climate observations.

Operational Monitoring of Trace Gases over the Mediterranean Sea

This paper describes the operational implementation of the processorφ-IASI over the Mediterranean sea. Theφ-IASI model implements two physically based inversion algorithms for the sequential retrieval of (a) the thermodynamic state of the atmosphere and (b) the tropospheric content of CO, CO2, CH4, and N2O from hyperspectral radiance observations of the Infrared Atmospheric Sounding Interferometer (IASI). The retrieval algorithm for trace gases exploits the concept ofpartially scanned interferogramtechnique, which is a tool mostly suited for Fourier transform spectrometers in the infrared. Minor and trace gases retrievals for July 2010 are presented and compared to in situ observations from five Mediterranean, permanent, stations of the Global Atmospheric Watch (GAW) network. The comparison evidences a good general consistency between satellite and in situ observations. IASI retrievals show a marked southeastern gradient, which is shown to be consistent with the general tropospheric circulation over the Mediterranean basin. These patterns are barely seen from in situ observations, a fact which stresses the importance of satellite (trace gases) data assimilation to improve the performance and quality of trace gases transport models.

Partially scanned interferogram methodology applied to IASI for the retrieval of CO, CO_2, CH_4 and N_2O

The technique of partially scanned interferograms is applied to the retrieval of trace gases from Infrared Atmospheric Sounding Interferometer (IASI) observations. For the specific case of CO, CO₂, CH₄ and N₂O, we show that this methodology allows us to retrieve trace gases column abundances at an unprecedented accuracy at the level of the single IASI footprint. The technique consists in transforming the IASI spectra back to the interferogram domain where we identify small regions that are mostly sensitive to single gas species. The retrieval is then performed by directly applying Least Squares estimation to these small segments of interferometric radiances. One of the main advantages of the technique is that it allows the efficient use of the information contained in all the IASI channels that are available in the absorption bands of a specific gas species. The retrieval technique has been applied to IASI radiances measured over the Mediterranean sea during the month of July 2010, one of the hottest months on record. Results have been validated against ground-based measurements. We have also carried out a comparison with Atmospheric Infrared Radiometer Sounder data and IASI retrievals obtained with usual variational approaches in the spectral domain.

Satellite observation of lowermost tropospheric ozone by multispectral synergism of IASI thermal infrared and GOME-2 ultraviolet measurements over Europe

Abstract. We present a new multispectral approach for observing lowermost tropospheric ozone from space by synergism of atmospheric radiances in the thermal infrared (TIR) observed by IASI (Infrared Atmospheric Sounding Interferometer) and earth reflectances in the ultraviolet (UV) measured by GOME-2 (Global Ozone Monitoring Experiment-2). Both instruments are onboard the series of MetOp satellites (in orbit since 2006 and expected until 2022) and their scanning capabilities offer global coverage every day, with a relatively fine ground pixel resolution (12 km-diameter pixels spaced by 25 km for IASI at nadir). Our technique uses altitude-dependent Tikhonov–Phillips-type constraints, which optimize sensitivity to lower tropospheric ozone. It integrates the VLIDORT (Vector Linearized Discrete Ordinate Radiative Transfer) and KOPRA (Karlsruhe Optimized and Precise Radiative transfer Algorithm) radiative transfer codes for simulating UV reflectance and TIR radiance, respectively. We have used our method to analyse real observations over Europe during an ozone pollution episode in the summer of 2009. The results show that the multispectral synergism of IASI (TIR) and GOME-2 (UV) enables the observation of the spatial distribution of ozone plumes in the lowermost troposphere (LMT, from the surface up to 3 km a.s.l., above sea level), in good agreement with the CHIMERE regional chemistry-transport model. In this case study, when high ozone concentrations extend vertically above 3 km a.s.l., they are similarly observed over land by both the multispectral and IASI retrievals. On the other hand, ozone plumes located below 3 km a.s.l. are only clearly depicted by the multispectral retrieval (both over land and over ocean). This is achieved by a clear enhancement of sensitivity to ozone in the lowest atmospheric layers. The multispectral sensitivity in the LMT peaks at 2 to 2.5 km a.s.l. over land, while sensitivity for IASI or GOME-2 only peaks at 3 to 4 km a.s.l. at lowest (above the LMT). The degrees of freedom for the multispectral retrieval increase by 0.1 (40% in relative terms) with respect to IASI only retrievals for the LMT. Validations with ozonesondes (over Europe during summer 2009) show that our synergetic approach for combining IASI (TIR) and GOME-2 (UV) measurements retrieves lowermost tropospheric ozone with a mean bias of 1% and a precision of 16%, when smoothing by the retrieval vertical sensitivity (1% mean bias and 21% precision for direct comparisons).

Validating IASI Temperature and Moisture Sounding Retrievals over East Asia Using Radiosonde Observations

Abstract Temperature and moisture profiles retrieved from Infrared Atmospheric Sounding Interferometer (IASI) data are evaluated using collocated radiosonde data from September 2008 to August 2009 over East Asia. The level-2 products used in this study were provided by the National Oceanic and Atmospheric Administration/National Environmental Satellite, Data, and Information Service. By using radiosonde observations as a reference, the bias and root-mean-square error (RMSE) of the temperature and water vapor profiles are obtained to examine the performance of the IASI retrievals depending on surface types and the degree of atmospheric moisture. Overall, retrievals over the land or under drier atmospheric conditions show degraded performance for both the temperature and the moisture, especially for the boundary layer temperature. It is further shown that the vertical distributions of the RMSEs and the biases of the IASI retrievals resemble the variability pattern of the radiosonde observations from the mean profiles. These retrieval aspects are thought to be related to the surface emissivity effect on the IASI retrieval and the difficulties of accounting for large atmospheric variability in the retrieval process. Although the retrieval performance appears to degrade under cloudy conditions, cloudy- and clear-sky retrievals show similar statistical behaviors varying with surface type and atmospheric moisture. Furthermore, the similar statistical behaviors between first guess and final retrievals suggest that error characteristics inherent to the first guess were not sufficiently resolved by the physical retrieval process, leaving a need to improve the first guess for the better retrieval.

Analysis of IASI tropospheric O<sub>3</sub> data over the Arctic during POLARCAT campaigns in 2008

Abstract. Ozone data retrieved in the Arctic region from infrared radiance spectra recorded by the Infrared Atmospheric Sounding Interferometer (IASI) on board the MetOp-A European satellite are presented. They are compared with in situ and lidar observations obtained during a series of aircraft measurement campaigns as part of the International Polar Year POLARCAT activities in spring and summer 2008. Different air masses were sampled during the campaigns including clean air, polluted plumes originating from anthropogenic sources, forest fire plumes from the three northern continents, and stratospheric-influenced air masses. The comparison between IASI O3 [0–8 km], [0–12 km] partial columns and profiles with collocated aircraft observations is achieved by taking into account the different sensitivity and geometry of the sounding instruments. A detailed analysis is provided and the agreement is discussed in terms of vertical sensitivity and surface properties at the location of the observations. Overall, IASI O3 profiles are found to be in relatively good agreement with smoothed in situ and lidar profiles in the free troposphere with differences of less than 40% (25% over sea for both seasons) and 10%, respectively. The correlation between IASI O3 retrieved partial columns and the smoothed aircraft partial columns is good with DC-8 in situ data in spring over North America (r = 0.68), and over Greenland with ATR-42 lidar measurements in summer (r = 0.67). Correlations with other data are less significant highlighting the difficulty of IASI to capture precisely the O3 variability in the Arctic upper troposphere and lower stratosphere (UTLS). This is particularly noted in comparison with the [0–12 km] partial columns. The IASI [0–8 km] partial columns display a low negative bias (by less than 26% over snow) compared to columns derived from in situ measurements. Despite the relatively high biases of the IASI retrievals in the Arctic UTLS, our analysis shows that IASI can be used to identify, using O3 / CO ratios, stratospheric intrusions.

A comparison of OEM CO retrievals from the IASI and MOPITT instruments

Abstract. Observations of atmospheric carbon monoxide (CO) can only be made on continental and global scales by remote sensing instruments situated in space. One such instrument is the Infrared Atmospheric Sounding Interferometer (IASI), producing spectrally resolved, top-of-atmosphere radiance measurements from which CO vertical layers and total columns can be retrieved. This paper presents a technique for intercomparisons of satellite data with low vertical resolution. The example in the paper also generates the first intercomparison between an IASI CO data set, in this case that produced by the University of Leicester IASI Retrieval Scheme (ULIRS), and the V3 and V4 operationally retrieved CO products from the Measurements Of Pollution In The Troposphere (MOPITT) instrument. The comparison is performed for a localised region of Africa, primarily for an ocean day-time configuration, in order to develop the technique for instrument intercomparison in a region with well defined a priori. By comparing both the standard data and a special version of MOPITT data retrieved using the ULIRS a priori for CO, it is shown that standard intercomparisons of CO are strongly affected by the differing a priori data of the retrievals, and by the differing sensitivities of the two instruments. In particular, the differing a priori profiles for MOPITT V3 and V4 data result in systematic retrieved profile changes as expected. An application of averaging kernels is used to derive a difference quantity which is much less affected by smoothing error, and hence more sensitive to systematic error. These conclusions are confirmed by simulations with model profiles for the same region. This technique is used to show that for the data that has been processed the systematic bias between MOPITT V4 and ULIRS IASI data, at MOPITT vertical resolution, is less than 7 % for the comparison data set, and on average appears to be less than 4 %. The results of this study indicate that intercomparisons of satellite data sets with low vertical resolution should ideally be performed with: retrievals using a common a priori appropriate to the geographic region studied; the application of averaging kernels to compute difference quantities with reduced a priori influence; and a comparison with simulated differences using model profiles for the target gas in the region.

ULIRS, an optimal estimation retrieval scheme for carbon monoxide using IASI spectral radiances: sensitivity analysis, error budget and simulations

Abstract. This paper presents a new retrieval scheme for tropospheric carbon monoxide (CO), using measured radiances from the Infrared Atmospheric Sounding Interferometer (IASI) onboard the MetOp-A satellite. The University of Leicester IASI Retrieval Scheme (ULIRS) is an optimal estimation retrieval scheme, which utilises equidistant pressure levels and a floating pressure grid based on topography. It makes use of explicit digital elevation and emissivity information, and incorporates a correction for solar surface reflection in the daytime with a high resolution solar spectrum. The retrieval scheme has been assessed through a formal error analysis, via the simulation of surface effects and by an application to real IASI data over a region in Southern Africa. The ULIRS enables the retrieval of between 1 and 2 pieces of information about the tropospheric CO vertical profiles, with peaks in the sensitivity at approximately 5 and 12 km. Typical errors for the African region relating to the profiles are found to be ~20% at 5 and 12 km, and on the total columns to range from 18 to 34%. Finally the performance of the ULIRS is shown for a range of simulated geophysical conditions.

Evaluation of AIRS, IASI, and OMI ozone profile retrievals in the extratropical tropopause region using in situ aircraft measurements

We evaluate ozone profile retrievals from the Atmospheric Infrared Sounder (AIRS), the Infrared Atmospheric Sounding Interferometer (IASI), and the Ozone Monitoring Instrument (OMI) using in situ measurements collected on board the NSF/NCAR Gulfstream‐V aircraft during the Stratosphere‐Troposphere Analyses of Regional Transport 2008 (START08) experiment. The focus of this study is to examine how well the satellite retrieval products capture the ozone gradients and variability in the extratropical upper troposphere lower stratosphere (UTLS). The AIRS retrieval examined is version 5, while IASI and OMI retrievals are research products. All satellite instruments show excellent ability in capturing synoptic‐scale ozone gradients associated with strong potential vorticity (PV) gradients. The positive ozone‐PV correlation near the tropopause is also well represented in the satellite data in comparison to collocated aircraft measurements. During aircraft cruise legs, more than 90% of collocated satellite retrievals agree with aircraft measurements within ±50% for ozone mixing ratios greater than 200 ppbv. Below 200 ppbv, AIRS and IASI retrievals show significant positive biases, while OMI shows both positive and negative biases. Ozone gradients across the tropopause are well‐captured, with median values within 30% (positive for AIRS and IASI, negative for OMI) and variances within ±50%. Ozone variability in the UTLS is captured by the satellite retrievals at the 80% level. In the presence of high clouds, however, the infrared retrievals show the largest positive biases. Despite the limited vertical information content, the high horizontal coverage and long‐term data availability make these satellite data sets a valuable asset for UTLS research.

IASI temperature and water vapor retrievals – error assessment and validation

Abstract. The METOP-A satellite Infrared Atmospheric Sounding Interferometer (IASI) Level 2 products comprise retrievals of vertical profiles of temperature and water vapor. The error covariance matrices and biases of the most recent version (4.3.1) of the L2 data were assessed, and the assessment was validated using radiosonde data for reference. The radiosonde data set includes dedicated and synoptic time launches at the Lindenberg station in Germany. For optimal validation, the linear statistical Validation Assessment Model (VAM) was used. The VAM uses radiosonde profiles as input and provides optimal estimate of the nominal IASI retrieval by utilizing IASI averaging kernels and statistical characteristics of the ensembles of the reference radiosondes. For temperatures above 900 mb and water retrievals above 700 mb, level expected and assessed errors are in good agreement. Below those levels, noticeable excess in assessed error is observed, possibly due to inaccurate surface parameters and undetected clouds/haze.

Measurements of total and tropospheric ozone from IASI: comparison with correlative satellite, ground-based and ozonesonde observations

Abstract. In this paper, we present measurements of total and tropospheric ozone, retrieved from infrared radiance spectra recorded by the Infrared Atmospheric Sounding Interferometer (IASI), which was launched on board the MetOp-A European satellite in October 2006. We compare IASI total ozone columns to Global Ozone Monitoring Experiment-2 (GOME-2) observations and ground-based measurements from the Dobson and Brewer network for one full year of observations (2008). The IASI total ozone columns are shown to be in good agreement with both GOME-2 and ground-based data, with correlation coefficients of about 0.9 and 0.85, respectively. On average, IASI ozone retrievals exhibit a positive bias of about 9 DU (3.3%) compared to both GOME-2 and ground-based measurements. In addition to total ozone columns, the good spectral resolution of IASI enables the retrieval of tropospheric ozone concentrations. Comparisons of IASI tropospheric columns to 490 collocated ozone soundings available from several stations around the globe have been performed for the period of June 2007–August 2008. IASI tropospheric ozone columns compare well with sonde observations, with correlation coefficients of 0.95 and 0.77 for the [surface–6 km] and [surface–12 km] partial columns, respectively. IASI retrievals tend to overestimate the tropospheric ozone columns in comparison with ozonesonde measurements. Positive average biases of 0.15 DU (1.2%) and 3 DU (11%) are found for the [surface–6 km] and for the [surface–12 km] partial columns respectively.

IASI measurements of reactive trace species in biomass burning plumes

Abstract. This work presents observations of a series of short-lived species in biomass burning plumes from the Infrared Atmospheric Sounding Interferometer (IASI), launched onboard the MetOp-A platform in October 2006. The strong fires that have occurred in the Mediterranean Basin – and particularly Greece – in August 2007, and those in Southern Siberia and Eastern Mongolia in the early spring of 2008 are selected to support the analyses. We show that the IASI infrared spectra in these fire plumes contain distinctive signatures of ammonia (NH3), ethene (C2H4), methanol (CH3OH) and formic acid (HCOOH) in the atmospheric window between 800 and 1200 cm−1, with some noticeable differences between the plumes. Peroxyacetyl nitrate (CH3COOONO2, abbreviated as PAN) was also observed with good confidence in some plumes and a tentative assignment of a broadband absorption spectral feature to acetic acid (CH3COOH) is made. For several of these species these are the first reported measurements made from space in nadir geometry. The IASI measurements are analyzed for plume height and concentration distributions of NH3, C2H4 and CH3OH. The Greek fires are studied in greater detail for the days associated with the largest emissions. In addition to providing information on the spatial extent of the plume, the IASI retrievals allow an estimate of the total mass emissions for NH3, C2H4 and CH3OH. Enhancement ratios are calculated for the latter relative to carbon monoxide (CO), giving insight in the chemical processes occurring during the transport, the first day after the emission.

Comparison of active and passive water vapor remote sensing from space: An analysis based on the simulated performance of IASI and space borne differential absorption lidar

Two remote sensing systems, which are considered to be operated in space, the Infrared Atmospheric Sounding Interferometer (IASI) and the Water Vapour Lidar Experiment in Space (WALES) are compared with respect to their measurement methodologies and their performance. The focus is the retrieval of water vapor, which is determined by the inversion of the radiative transfer equation in case of IASI and by the differential absorption lidar (DIAL) technique in case of WALES. It is realized that different techniques and definitions for the specification of errors exist which are subject of confusion in the remote sensing community. After a clarification of this issue, a comparison of IASI and WALES water vapor retrievals is performed using the same water vapor climatologies and the same 2-d water vapor fields provided by a global numerical weather prediction (NWP) model. The methodologies and the capabilities of each instrument are compared in regions without clouds. Using end-to-end simulations for both instruments, which are to our knowledge performed for the first time, systematic errors are compared up to 16 km. It is found that the dependence of IASI retrievals on a variety of atmospheric parameters leads to compensating effects. Due to the multiwavelength retrieval, errors in the water vapor spectroscopy can partly cancel. The residual error is quantified by inversion of the radiative transfer equation in dependence of several atmospheric variables. In contrast, errors in water vapor DIAL are very sensitive to laser spectral properties as well as to the accuracy of water vapor spectroscopy, as single water vapor absorption lines are used for each vertical segment of the retrieval. As laser transmitters with excellent spectral specifications are feasible, this can still lead to very low systematic errors under all atmospheric conditions. Noise errors are determined using analytical models and are compared up to 16 km. At the same vertical (1–2 km) and horizontal (100–200 km) resolutions, respectively, the average noise errors in each profile are of the order of 10% for both methods. Depending on the climatology, the vertical range of IASI measurements is always several kilometers lower than that of DIAL. The performance of IASI degrades in dry atmospheres whereas the DIAL performance remains nearly independent of the climatology chosen. Bias errors show a similar behavior. Neglecting bias errors in the spectral measurements, from mid-latitudes to the tropics, IASI biases are <2 % in the vertical range where the noise errors remain <20%. In the sub-arctic winter atmosphere, the bias increases to about −4% close to the ground. Space borne DIAL bias profiles range between −2–1% under all conditions plus an additional height independent bias of about ±2 due to remaining uncertainties in absorption line spectroscopy. Operation in the region of clouds are not a focus of this publication but it is worth to mention that the results demonstrate that space borne DIAL can perform measurements down to cloud tops and often through optically thin clouds. Particularly powerful is the synergistic combinations of both sensors in the future. Iteration between IASI temperature and DIAL water vapor retrievals will increase both accuracies.