Suchergebnisse

As a precursor of atmospheric aerosols, ammonia ( NH3 ) is one of the primary gaseous air pollutants. Given its short atmospheric lifetime, ambient NH3 concentrations are dominated by local sources. In a recent study, Van Damme et al. ( 2018 ) have highlighted the importance of NH3 point sources, especially those associated with feedlots and industrial ammonia production. Their emissions were shown to be largely underestimated in bottom-up emission inventories. The discovery was made possible thanks to the use of oversampling techniques applied to 9 years of global daily IASI NH3 satellite measurements. Oversampling allows one to increase the spatial resolution of averaged satellite data beyond what the satellites natively offer. Here we apply for the first time superresolution techniques, which are commonplace in many fields that rely on imaging, to measurements of an atmospheric sounder, whose images consist of just single pixels. We demonstrate the principle on synthetic data and on IASI measurements of a surface parameter. Superresolution is a priori less suitable to be applied on measurements of variable atmospheric constituents, in particular those affected by transport. However, by first applying the wind-rotation technique, which was introduced in the study of other primary pollutants, superresolution becomes highly effective in mapping NH3 at a very high spatial resolution. We show that plume transport can be revealed in greater detail than what was previously thought to be possible. Next, using this wind-adjusted superresolution technique, we introduce a new type of NH3 map that allows tracking down point sources more easily than the regular oversampled average. On a subset of known emitters, the source could be located within a median distance of 1.5 km. We subsequently present a new global point-source catalog consisting of more than 500 localized and categorized point sources. Compared to our previous catalog, the number of identified sources more than doubled. In addition, we refined the ...

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 nearsurface 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). ; SCOPUS: ar.j ; info:eu-repo/semantics/published

Ammonia (NH3) is a major source of nitrates in the atmosphere and a major source of fine particulate matter. As such, there have been increasing efforts to measure the atmospheric abundance of NH3 and its spatial and temporal variability. In this study, long-Term measurements of NH3 derived from multiscale datasets are examined. These NH3 datasets include 16 years of total column measurements using Fourier transform infrared (FTIR) spectroscopy, 3 years of surface in situ measurements, and 10 years of total column measurements from the Infrared Atmospheric Sounding Interferometer (IASI). The datasets were used to quantify NH3 temporal variability over Toronto, Canada. The multiscale datasets were also compared to assess the representativeness of the FTIR measurements. All three time series showed positive trends in NH3 over Toronto: 3.34-0.89 %/yr from 2002 to 2018 in the FTIR columns, 8.88-5.08 %/yr from 2013 to 2017 in the surface in situ data, and 8.38-1.54 %/yr from 2008 to 2018 in the IASI columns. To assess the representative scale of the FTIR NH3 columns, correlations between the datasets were examined. The best correlation between FTIR and IASI was obtained with coincidence criteria of-25 km and-20 min, with r D 0:73 and a slope of 1.14-0.06. Additionally, FTIR column and in situ measurements were standardized and correlated. Comparison of 24 d averages and monthly averages resulted in correlation coefficients of r D 0:72 and r D 0:75, respectively, although correlation without averaging to reduce high-frequency variability led to a poorer correlation, with r D 0:39. The GEOS-Chem model, run at 22.5 resolution, was compared to FTIR and IASI to assess model performance and investigate the correlation of observational data and model output, both with local column measurements (FTIR) and measurements on a regional scale (IASI). Comparisons on a regional scale (a domain spanning 35 to 53-N and 93.75 to 63.75-W) resulted in r D 0:57 and thus a coefficient of determination, which is indicative of the ...

The three infrared atmospheric sounding interferometers (IASIs), launched in 2006, 2012, and 2018, are key instruments to weather forecasting, and most meteorological centres assimilate IASI nadir radiance data into atmospheric models to feed their forecasts. The European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) recently released a reprocessed homogeneous radiance record for the whole IASI observation period, from which 13 years (2008-2020) of temperature profiles can be obtained. In this work, atmospheric temperatures at different altitudes are retrieved from IASI radiances measured in the carbon dioxide absorption bands (654-800 and 2250-2400gcm-1) by selecting the channels that are the most sensitive to the temperature at different altitudes. We rely on an artificial neural network (ANN) to retrieve atmospheric temperatures from a selected set of IASI radiances. We trained the ANN with IASI radiances as input and the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis version 5 (ERA5) as output. The retrieved temperatures were validated with ERA5, with in situ radiosonde temperatures from the Analysed RadioSoundings Archive (ARSA) network and with EUMETSAT temperatures retrieved from IASI radiances using a different method. Between 750 and 7ghPa, where IASI is most sensitive to temperature, a good agreement is observed between the three datasets: the differences between IASI on one hand and ERA5, ARSA, or EUMETSAT on the other hand are usually less than 0.5gK at these altitudes. At 2ghPa, as the IASI sensitivity decreases, we found differences up to 2gK between IASI and the three validation datasets. We then computed atmospheric temperature linear trends from atmospheric temperatures between 750 and 2ghPa. We found that in the past 13 years, there is a general warming trend of the troposphere that is more important at the poles and at mid-latitudes (0.5gK/decade at mid-latitudes, 1gK/decade at the North Pole). The stratosphere is globally cooling on average, ...

Carbon monoxide (CO) is a key atmospheric compound that can be remotely sensed by satellite on the global scale. Fifteen years of continuous observations are now available from the MOPITT/Terra mission (2000 to present). Another 15 and more years of observations will be provided by the IASI/MetOp instrument series (2007-2023 >). In order to study long-term variability and trends, a homogeneous record is required, which is not straightforward as the retrieved quantities are instrument and processing dependent. The present study aims at evaluating the consistency between the CO products derived from the MOPITT and IASI missions, both for total columns and vertical profiles, during a 6-year overlap period (2008-2013). The analysis is performed by first comparing the available 2013 versions of the retrieval algorithms (v5T for MOPITT and v20100815 for IASI), and second using a dedicated reprocessing of MOPITT CO profiles and columns using the same a priori information as the IASI product. MOPITT total columns are generally slightly higher over land (bias ranging from 0 to 13 %) than IASI data. When IASI and MOPITT data are retrieved with the same a priori constraints, correlation coefficients are slightly improved. Large discrepancies (total column bias over 15 %) observed in the Northern Hemisphere during the winter months are reduced by a factor of 2 to 2.5. The detailed analysis of retrieved vertical profiles compared with collocated aircraft data from the MOZAIC-IAGOS network, illustrates the advantages and disadvantages of a constant vs. a variable a priori. On one hand, MOPITT agrees better with the aircraft profiles for observations with persisting high levels of CO throughout the year due to pollution or seasonal fire activity (because the climatology-based a priori is supposed to be closer to the real atmospheric state). On the other hand, IASI performs better when unexpected events leading to high levels of CO occur, due to a larger variability associated with the a priori. ; SCOPUS: ar.j ...

We apply the Tropospheric Emission Spectrometer (TES) ozone retrieval algorithm to Infrared Atmospheric Sounding Instrument (IASI) radiances and characterise the uncertainties and information content of the retrieved ozone profiles. This study focuses on mid-latitudes for the year 2008. We validate our results by comparing the IASI ozone profiles to ozone sondes. In the sonde comparisons, we find a negative bias (1-10%) in the IASI profiles in the lower to mid-troposphere and a positive bias (up to 14%) in the upper troposphere/lower stratosphere (UTLS) region. For the described cases, the degrees of freedom for signal are on average 3.2, 0.3, 0.8, and 0.9 for the columns 0 km - top of atmosphere, (0-6), (0-11), and (8-16) km, respectively. We find that our biases with respect to sondes and our degrees of freedom for signal for ozone are comparable to previously published results from other IASI ozone algorithms. In addition to evaluating biases, we validate the retrieval errors by comparing predicted errors to the sample covariance matrix of the IASI observations themselves. For the predicted versus empirical error comparison, we find that these errors are consistent and that the measurement noise and the interference of temperature and water vapour on the retrieval together mostly explain the empirically derived random errors. In general, the precision of the IASI ozone profiles is better than 20%. ; SCOPUS: ar.j ; info:eu-repo/semantics/published

In order to recognize the importance of ozone (O3) in the troposphere and lower stratosphere in the tropics, a DIAL (differential absorption lidar) tropospheric O3 lidar system (LIO3TUR) was developed and installed at the Université de la Réunion campus site (close to the sea) on Reunion Island (southern tropics) in 1998. From 1998 to 2010, it acquired 427 O3 profiles from the low to the upper troposphere and has been central to several studies. In 2012, the system was moved up to the new Maïdo Observatory facility (2160-l. - metres above mean sea level) where it started operation in February 2013. The current system (LIO3T) configuration generates a 266 beam obtained with the fourth harmonic of a Nd:YAG laser sent into a Raman cell filled up with deuterium (using helium as buffer gas), generating the 289 and 316 beams to enable the use of the DIAL method for O3 profile measurements. The optimal range for the actual system is 6-19ga.m.s.l. depending on the instrumental and atmospheric conditions. For a 1gh integration time, vertical resolution varies from 0.7gkm at 6ga.m.s.l. to 1.3gkm at 19ga.m.s.l. and mean uncertainty within the 6-19gkm range is between 6 and 13g%. Comparisons with eight electrochemical concentration cell (ECC) sondes simultaneously launched from the Maïdo Observatory show good agreement between data sets with a 6.8g% mean absolute relative difference ( D ) between 6 and 17ga.m.s.l. (LIO3T lower than ECC). Comparisons with 37 ECC sondes launched from the nearby Gillot site during the daytime in a ±24gh window around lidar shooting result in a 9.4g% D between 6 and 19ga.m.s.l. (LIO3T lower than ECC). Comparisons with 11 ground-based Network for Detection of Atmospheric Composition Change (NDACC) Fourier transform infrared (FTIR) spectrometer measurements acquired during the daytime in a ±24gh window around lidar shooting show good agreement between data sets with a D of 11.8g% for the 8.5-16gkm partial column (LIO3T higher than FTIR), and comparisons with 39 simultaneous Infrared Atmospheric ...

This paper assesses the quality of IASI (Infrared Atmospheric Sounding Interferometer)/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 9 years (2008-July 2017) through an extensive intercomparison and validation exercise using independent observations (satellite, ground-based and ozonesonde). Compared with the previous version of FORLI-O3 (v20140922), several improvements have been introduced in FORLI-O3 v20151001, including absorbance look-up tables recalculated to cover a larger spectral range, with additional numerical corrections. This leads to a change of ĝ1/4 4 % in the total ozone column (TOC) product, which is mainly associated with a decrease in the retrieved O3 concentration in the middle stratosphere (above 30 hPa/25 km). IASI-A and IASI-B TOCs are consistent, with a global mean difference of less than 0.3 % for both daytime and nighttime measurements; IASI-A is slightly higher than IASI-B. A global difference of less than 2.4 % is found for the tropospheric (TROPO) O3 column product (IASI-A is lower than IASI-B), which is partly due to a temporary issue related to the IASI-A viewing angle in 2015. Our validation shows that IASI-A and IASI-B TOCs are consistent with GOME-2 (Global Ozone Monitoring Experiment-2), Dobson, Brewer, SAOZ (Système d'Analyse par Observation Zénithale) and FTIR (Fourier transform infrared) TOCs, with global mean differences in the range of 0.1 %-2 % depending on the instruments compared. The worst agreement with UV-vis retrieved TOC (satellite and ground) is found at the southern high latitudes. The IASI-A and ground-based TOC comparison for the period from 2008 to July 2017 shows the long-Term stability of IASI-A, with insignificant or small negative drifts of 1 %-3 % decadeĝ'1. The comparison results of IASI-A and IASI-B against smoothed FTIR and ozonesonde partial O3 columns vary with altitude and latitude, with the maximum ...

International audience ; Monitoring Atmospheric Composition and Climate (MACC/MACCII) currently represents the European Union's Copernicus Atmosphere Monitoring Service (CAMS) (http://www.copernicus.eu), which will become fully operational in the course of 2015. The global near-real-time MACC model production run for aerosol and reactive gases provides daily analyses and 5 day forecasts of atmospheric composition fields. It is the only assimilation system world-wide that is operational to produce global analyses and forecasts of reactive gases and aerosol fields. We have investigated the ability of the MACC analysis system to simulate tropospheric concentrations of reactive gases (CO, O3, and NO2) covering the period between 2009 and 2012. A validation was performed based on CO and O3 surface observations from the Global Atmosphere Watch (GAW) network, O3 surface observations from the European Monitoring and Evaluation Programme (EMEP) and furthermore, NO2 tropospheric columns derived from the satellite sensors SCIAMACHY and GOME-2, and CO total columns derived from the satellite sensor MOPITT. The MACC system proved capable of reproducing reactive gas concentrations in consistent quality, however, with a seasonally dependent bias compared to surface and satellite observations: for northern hemispheric surface O3 mixing ratios, positive biases appear during the warm seasons and negative biases during the cold parts of the years, with monthly Modified Normalised Mean Biases (MNMBs) ranging between −30 and 30% at the surface. Model biases are likely to result from difficulties in the simulation of vertical mixing at night and deficiencies in the model's dry deposition parameterization. Observed tropospheric columns of NO2 and CO could be reproduced correctly during the warm seasons, but are mostly underestimated by the model during the cold seasons, when anthropogenic emissions are at a highest, especially over the US, Europe and Asia. Monthly MNMBs of the satellite data evaluation range between −110 and 40% for ...

International audience ; Monitoring Atmospheric Composition and Climate (MACC/MACCII) currently represents the European Union's Copernicus Atmosphere Monitoring Service (CAMS) (http://www.copernicus.eu), which will become fully operational in the course of 2015. The global near-real-time MACC model production run for aerosol and reactive gases provides daily analyses and 5 day forecasts of atmospheric composition fields. It is the only assimilation system world-wide that is operational to produce global analyses and forecasts of reactive gases and aerosol fields. We have investigated the ability of the MACC analysis system to simulate tropospheric concentrations of reactive gases (CO, O3, and NO2) covering the period between 2009 and 2012. A validation was performed based on CO and O3 surface observations from the Global Atmosphere Watch (GAW) network, O3 surface observations from the European Monitoring and Evaluation Programme (EMEP) and furthermore, NO2 tropospheric columns derived from the satellite sensors SCIAMACHY and GOME-2, and CO total columns derived from the satellite sensor MOPITT. The MACC system proved capable of reproducing reactive gas concentrations in consistent quality, however, with a seasonally dependent bias compared to surface and satellite observations: for northern hemispheric surface O3 mixing ratios, positive biases appear during the warm seasons and negative biases during the cold parts of the years, with monthly Modified Normalised Mean Biases (MNMBs) ranging between −30 and 30% at the surface. Model biases are likely to result from difficulties in the simulation of vertical mixing at night and deficiencies in the model's dry deposition parameterization. Observed tropospheric columns of NO2 and CO could be reproduced correctly during the warm seasons, but are mostly underestimated by the model during the cold seasons, when anthropogenic emissions are at a highest, especially over the US, Europe and Asia. Monthly MNMBs of the satellite data evaluation range between −110 and 40% for NO2 and at most −20% for CO, over the investigated regions. The underestimation is likely to result from a combination of errors concerning the dry deposition parameterization and certain limitations in the current emission inventories, together with an insufficiently established seasonality in the emissions.

International audience ; Monitoring Atmospheric Composition and Climate (MACC/MACCII) currently represents the European Union's Copernicus Atmosphere Monitoring Service (CAMS) (http://www.copernicus.eu), which will become fully operational in the course of 2015. The global near-real-time MACC model production run for aerosol and reactive gases provides daily analyses and 5 day forecasts of atmospheric composition fields. It is the only assimilation system world-wide that is operational to produce global analyses and forecasts of reactive gases and aerosol fields. We have investigated the ability of the MACC analysis system to simulate tropospheric concentrations of reactive gases (CO, O3, and NO2) covering the period between 2009 and 2012. A validation was performed based on CO and O3 surface observations from the Global Atmosphere Watch (GAW) network, O3 surface observations from the European Monitoring and Evaluation Programme (EMEP) and furthermore, NO2 tropospheric columns derived from the satellite sensors SCIAMACHY and GOME-2, and CO total columns derived from the satellite sensor MOPITT. The MACC system proved capable of reproducing reactive gas concentrations in consistent quality, however, with a seasonally dependent bias compared to surface and satellite observations: for northern hemispheric surface O3 mixing ratios, positive biases appear during the warm seasons and negative biases during the cold parts of the years, with monthly Modified Normalised Mean Biases (MNMBs) ranging between −30 and 30% at the surface. Model biases are likely to result from difficulties in the simulation of vertical mixing at night and deficiencies in the model's dry deposition parameterization. Observed tropospheric columns of NO2 and CO could be reproduced correctly during the warm seasons, but are mostly underestimated by the model during the cold seasons, when anthropogenic emissions are at a highest, especially over the US, Europe and Asia. Monthly MNMBs of the satellite data evaluation range between −110 and 40% for NO2 and at most −20% for CO, over the investigated regions. The underestimation is likely to result from a combination of errors concerning the dry deposition parameterization and certain limitations in the current emission inventories, together with an insufficiently established seasonality in the emissions.

International audience ; Monitoring Atmospheric Composition and Climate (MACC/MACCII) currently represents the European Union's Copernicus Atmosphere Monitoring Service (CAMS) (http://www.copernicus.eu), which will become fully operational in the course of 2015. The global near-real-time MACC model production run for aerosol and reactive gases provides daily analyses and 5 day forecasts of atmospheric composition fields. It is the only assimilation system world-wide that is operational to produce global analyses and forecasts of reactive gases and aerosol fields. We have investigated the ability of the MACC analysis system to simulate tropospheric concentrations of reactive gases (CO, O3, and NO2) covering the period between 2009 and 2012. A validation was performed based on CO and O3 surface observations from the Global Atmosphere Watch (GAW) network, O3 surface observations from the European Monitoring and Evaluation Programme (EMEP) and furthermore, NO2 tropospheric columns derived from the satellite sensors SCIAMACHY and GOME-2, and CO total columns derived from the satellite sensor MOPITT. The MACC system proved capable of reproducing reactive gas concentrations in consistent quality, however, with a seasonally dependent bias compared to surface and satellite observations: for northern hemispheric surface O3 mixing ratios, positive biases appear during the warm seasons and negative biases during the cold parts of the years, with monthly Modified Normalised Mean Biases (MNMBs) ranging between −30 and 30% at the surface. Model biases are likely to result from difficulties in the simulation of vertical mixing at night and deficiencies in the model's dry deposition parameterization. Observed tropospheric columns of NO2 and CO could be reproduced correctly during the warm seasons, but are mostly underestimated by the model during the cold seasons, when anthropogenic emissions are at a highest, especially over the US, Europe and Asia. Monthly MNMBs of the satellite data evaluation range between −110 and 40% for NO2 and at most −20% for CO, over the investigated regions. The underestimation is likely to result from a combination of errors concerning the dry deposition parameterization and certain limitations in the current emission inventories, together with an insufficiently established seasonality in the emissions.

This paper presents an extensive intercomparison and validation for the ozone (O3) product measured by the two Infrared Atmospheric Sounding Interferometers (IASIs) launched on board the MetOp-A and MetOp-B satellites in 2006 and in 2012 respectively. IASI O3 total columns and vertical profiles obtained from Fast Optimal Retrievals on Layers for IASI (FORLI) v20140922 software (running up until recently) are validated against independent observations during the period 2008-2014 on a global scale. On average for the period 2013-2014, IASI-A and IASI-B total ozone columns (TOCs) retrieved using FORLI are consistent, with IASI-B providing slightly lower values with a global difference of only 0.2±0.8%. The comparison between IASI-A and IASI-B O3 vertical profiles shows differences within ±2% over the entire altitude range. Global validation results for 7 years of IASI TOCs from FORLI against the Global Ozone Monitoring Experiment-2 (GOME-2) launched on board MetOp-A and Brewer-Dobson data show that, on average, IASI overestimates the ultraviolet (UV) data by 5-6% with the largest differences found in the southern high latitudes. The comparison with UV-visible SAOZ (Système d'Analyse par Observation Zénithale) measurements shows a mean bias between IASI and SAOZ TOCs of 2-4% in the midlatitudes and tropics and 7% at the polar circle. Part of the discrepancies found at high latitudes can be attributed to the limited information content in the observations due to low brightness temperatures. The comparison with ozonesonde vertical profiles (limited to 30km) shows that on average IASI with FORLI processing underestimates O3 by ∼ 5-15% in the troposphere while it overestimates O3 by ∼ 10-40% in the stratosphere, depending on the latitude. The largest relative differences are found in the tropical tropopause region; this can be explained by the low O3 amounts leading to large relative errors. In this study, we also evaluate an updated version of FORLI-O3 retrieval software (v20151001), using look-up tables recalculated ...

Atmospheric ozone plays a key role in air quality and the radiation budget of the Earth, both directly and through its chemical influence on other trace gases. Assessments of the atmospheric ozone distribution and associated climate change therefore demand accurate vertically resolved ozone observations with both stratospheric and tropospheric sensitivity, on both global and regional scales, and both in the long term and at shorter timescales. Such observations have been acquired by two series of European nadir-viewing ozone profilers, namely the scattered-light UV-visible spectrometers of the GOME family, launched regularly since 1995 (GOME, SCIAMACHY, OMI, GOME-2A/B, TROPOMI, and the upcoming Sentinel-5 series), and the thermal infrared emission sounders of the IASI type, launched regularly since 2006 (IASI on Metop platforms and the upcoming IASI-NG on Metop-SG). In particular, several Level-2 retrieved, Level-3 monthly gridded, and Level-4 assimilated nadir ozone profile data products have been improved and harmonized in the context of the ozone project of the European Space Agency's Climate Change Initiative (ESA Ozone-cci). To verify their fitness for purpose, these ozone datasets must undergo a comprehensive quality assessment (QA), including (a) detailed identification of their geographical, vertical, and temporal domains of validity; (b) quantification of their potential bias, noise, and drift and their dependences on major influence quantities; and (c) assessment of the mutual consistency of data from different sounders. For this purpose we have applied to the Ozone-cci Climate Research Data Package (CRDP) released in 2017 the versatile QA and validation system Multi-TASTE, which has been developed in the context of several heritage projects (ESA's Multi-TASTE, EUMETSAT's O3M-SAF, and the European Commission's FP6 GEOmon and FP7 QA4ECV). This work, as the second in a series of four Ozone-cci validation papers, reports for the first time on data content studies, information content studies and ...