IASI Measurements Research Articles

Is the recovery of stratospheric O<sub>3</sub> speeding up in the Southern Hemisphere? An evaluation from the first IASI decadal record (2008–2017)

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

Tracking down global NH<sub>3</sub> point sources with wind-adjusted superresolution

Abstract. 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 classification of industries into five categories – fertilizer, coking, soda ash, geothermal and explosives industries – and introduced a new urban category for isolated NH3 hotspots over cities. The latter mainly consists of African megacities, as clear isolation of such urban hotspots is almost never possible elsewhere due to the presence of a diffuse background with higher concentrations. The techniques presented in this paper can most likely be exploited in the study of point sources of other short-lived atmospheric pollutants such as SO2 and NO2.

Comparison of dust-layer heights from active and passive satellite sensors

Abstract. Aerosol-layer height is essential for understanding the impact of aerosols on the climate system. As part of the European Space Agency Aerosol_cci project, aerosol-layer height as derived from passive thermal and solar satellite sensors measurements have been compared with aerosol-layer heights estimated from CALIOP measurements. The Aerosol_cci project targeted dust-type aerosol for this study. This ensures relatively unambiguous aerosol identification by the CALIOP processing chain. Dust-layer height was estimated from thermal IASI measurements using four different algorithms (from BIRA-IASB, DLR, LMD, LISA) and from solar GOME-2 (KNMI) and SCIAMACHY (IUP) measurements. Due to differences in overpass time of the various satellites, a trajectory model was used to move the CALIOP-derived dust heights in space and time to the IASI, GOME-2 and SCIAMACHY dust height pixels. It is not possible to construct a unique dust-layer height from the CALIOP data. Thus two CALIOP-derived layer heights were used: the cumulative extinction height defined as the height where the CALIOP extinction column is half of the total extinction column, and the geometric mean height, which is defined as the geometrical mean of the top and bottom heights of the dust layer. In statistical average over all IASI data there is a general tendency to a positive bias of 0.5–0.8 km against CALIOP extinction-weighted height for three of the four algorithms assessed, while the fourth algorithm has almost no bias. When comparing geometric mean height there is a shift of −0.5 km for all algorithms (getting close to zero for the three algorithms and turning negative for the fourth). The standard deviation of all algorithms is quite similar and ranges between 1.0 and 1.3 km. When looking at different conditions (day, night, land, ocean), there is more detail in variabilities (e.g. all algorithms overestimate more at night than during the day). For the solar sensors it is found that on average SCIAMACHY data are lower by −1.097 km (−0.961 km) compared to the CALIOP geometric mean (cumulative extinction) height, and GOME-2 data are lower by −1.393 km (−0.818 km).

Spatio-temporal variations of nitric acid total columns from 9 years of IASI measurements – a driver study

Abstract. This study aims to understand the spatial and temporal variability of HNO3 total columns in terms of explanatory variables. To achieve this, multiple linear regressions are used to fit satellite-derived time series of HNO3 daily averaged total columns. First, an analysis of the IASI 9-year time series (2008–2016) is conducted based on various equivalent latitude bands. The strong and systematic denitrification of the southern polar stratosphere is observed very clearly. It is also possible to distinguish, within the polar vortex, three regions which are differently affected by the denitrification. Three exceptional denitrification episodes in 2011, 2014 and 2016 are also observed in the Northern Hemisphere, due to unusually low arctic temperatures. The time series are then fitted by multivariate regressions to identify what variables are responsible for HNO3 variability in global distributions and time series, and to quantify their respective influence. Out of an ensemble of proxies (annual cycle, solar flux, quasi-biennial oscillation, multivariate ENSO index, Arctic and Antarctic oscillations and volume of polar stratospheric clouds), only the those defined as significant (p value < 0.05) by a selection algorithm are retained for each equivalent latitude band. Overall, the regression gives a good representation of HNO3 variability, with especially good results at high latitudes (60–80 % of the observed variability explained by the model). The regressions show the dominance of annual variability in all latitudinal bands, which is related to specific chemistry and dynamics depending on the latitudes. We find that the polar stratospheric clouds (PSCs) also have a major influence in the polar regions, and that their inclusion in the model improves the correlation coefficients and the residuals. However, there is still a relatively large portion of HNO3 variability that remains unexplained by the model, especially in the intertropical regions, where factors not included in the regression model (such as vegetation fires or lightning) may be at play.

Importance of depth and intensity of convection on the isotopic composition of water vapor as seen from IASI and TES δD observations

We use tropical observations of the water vapor isotopic composition, derived from IASI and TES spaceborne measurements, to show that the isotopic composition of water vapor in the free troposphere is sensitive to both the depth and the intensity of convection. We find that for any given precipitation intensity, vapor associated with deep convection is isotopically depleted relative to vapor associated with shallow convection. The intensity of precipitation also plays a role as for any given depth of convection, the relative enrichment of water vapor decreases as the intensity of precipitation increases. Shallow convection, via the uplifting of enriched boundary layer air into the free troposphere and the convective detrainment, enriches the free troposphere. In contrast, deep convection is associated with processes that deplete the water vapor in the free troposphere, such as rain re-evaporation. The results of this study allow for a better identification of the parameters controlling the isotopic composition of the free troposphere and indicate that the isotopic composition of water vapor can be used to evaluate the relative contributions of shallow and deep convection in global models.

Empirical assessment of errors in total ozone measurements with different instruments and methods

Knowledge of measurement errors is one of the most important issues for assessing the quality of experimental data. In this paper, we compared various methods and instruments for measuring the total ozone content (TOC) near St. Petersburg in the period from 2009 to 2015. We considered the TOC datasets of ground-based measurements at Voyeykovo (Dobson spectrophotometer and M-124 ozonometer) and Peterhof (Bruker 125HR spectrometer), as well as OMI and IASI satellite measurements. To assess the errors intrinsic to each of these instruments three ensembles of the TOC measurements were formed containing different numbers of comparisons and based on different selection criteria. At the first stage, we determined the means and standard deviations between the ensembles of the TOC measurements. Then, assuming a horizontally homogeneous and stationary ozone field, the random and systematic errors of individual methods were evaluated. The average random errors of the TOC measurements for all tree ensembles were 2.9 ± 0.5%, 2.8 ± 0.7%, 1.2 ± 0.2%, and 1.4 ± 0.1% for IASI, M-124, OMI, and Bruker 125HR, respectively. The systematic error of the standard Dobson measurements is–1.7% and–2.1% for OMI and IASI, respectively, and amounts to + 0.5% and + 2.1% for M-124 and Bruker 125HR, respectively. The OMI and Bruker 125HR TOC measurement errors are most resistant to atmospheric conditions, whereas errors in IASI and M-124 TOC measurements depend to a large extent on the state of the atmosphere.

Probing into the aging dynamics of biomass burning aerosol by using satellite measurements of aerosol optical depth and carbon monoxide

Abstract. Carbonaceous aerosol released into the atmosphere from open biomass burning (BB) is known to undergo considerable chemical and physical transformations (aging). However, there is substantial controversy about the nature and observable effects of these transformations. A shortage of consistent observational evidence on BB aerosol aging processes under different environmental conditions and at various temporal scales hinders development of their adequate representations in chemistry transport models (CTMs). In this study, we obtain insights into the BB aerosol dynamics by using available satellite measurements of aerosol optical depth (AOD) and carbon monoxide (CO). The basic concept of our method is to consider AOD as a function of the BB aerosol photochemical age (that is, the time period characterizing the exposure of BB aerosol emissions to atmospheric oxidation reactions) predicted by means of model tracers. We evaluate the AOD enhancement ratio (ER) defined as the ratio of optical depth of actual BB aerosol with respect to that of a modeled aerosol tracer that is assumed to originate from the same fires as the real BB aerosol but that is not affected by any aging processes. To limit possible effects of model transport errors, the AOD measurements are normalized to CO column amounts that are also retrieved from satellite measurements. The method is applied to the analysis of the meso- and synoptic-scale evolution of aerosol in smoke plumes from major wildfires that occurred in Siberia in summer 2012. AOD and CO retrievals from MODIS and IASI measurements, respectively, are used in combination with simulations performed with the CHIMERE CTM. The analysis indicates that aging processes strongly affected the evolution of BB aerosol in the situation considered, especially in dense plumes (with spatial average PM2. 5 concentration exceeding 100 µg m−3). For such plumes, the ER is found to increase almost 2-fold on the scale of ∼ 10 h of daytime aerosol evolution (after a few first hours of the evolution that are not resolved in our analysis). The robustness of this finding is corroborated by sensitivity tests and Monte Carlo experiments. Furthermore, a simulation using the volatility basis set framework suggests that a large part of the increase in the ER can be explained by atmospheric processing of semi-volatile organic compounds. Our results are consistent with findings of a number of earlier studies reporting considerable underestimation of AOD by CTMs in which BB aerosol aging processes have either been disregarded or simulated in a highly simplified way. In general, this study demonstrates the feasibility of using satellite measurements of AOD in biomass burning plumes in combination with aerosol tracer simulations for the investigation of BB aerosol evolution and validation of BB aerosol aging schemes in atmospheric models.

Ammonia emissions in tropical biomass burning regions: Comparison between satellite-derived emissions and bottom-up fire inventories

Vegetation fires emit large amounts of nitrogen compounds in the atmosphere, including ammonia (NH3). These emissions are still subject to large uncertainties. In this study, we analyze time series of monthly NH3 total columns (molec cm−2) from the IASI sounder on board MetOp-A satellite and their relation with MODIS fire radiative power (MW) measurements. We derive monthly NH3 emissions estimates for four regions accounting for a major part of the total area affected by fires (two in Africa, one in central South America and one in Southeast Asia), using a simplified box model, and we compare them to the emissions from both the GFEDv3.1 and GFASv1.0 biomass burning emission inventories. In order to strengthen the analysis, we perform a similar comparison for carbon monoxide (CO), also measured by IASI and for which the emission factors used in the inventories to convert biomass burned to trace gas emissions are thought to be more reliable. In general, a good correspondence between NH3 and CO columns and the FRP is found, especially for regions in central South America with correlation coefficients of 0.82 and 0.66, respectively. The comparison with the two biomass burning emission inventories GFASv1.0 and GFEDv3.1 shows good agreements, particularly in the time of the maximum of emissions for the central South America region and in the magnitude for the region of Africa south of the equator. We find evidence of significant non-pyrogenic emissions for the regions of Africa north of the equator (for NH3) and Southeast Asia (for NH3 and CO). On a yearly basis, total emissions calculated from IASI measurements for the four regions reproduce fairly well the interannual variability from the GFEDv3.1 and GFASv1.0 emissions inventories for NH3 but show values about 1.5–2 times higher than emissions given by the two biomass burning emission inventories, even when assuming a fairly long lifetime of 36 h for that species.

Spectral Signatures of Earth’s Climate Variability over 5 Years from IASI

Abstract Interannual variability in spectrally resolved longwave radiances is quantified at a variety of spatial scales using 5 yr of IASI observations. Maximum variability is seen at the smallest scales investigated (10° zonal means) at northern and southern high latitudes across the center of the 15-µm CO2 band. As the spatial scale increases, the overall magnitude of interannual variability is reduced across the spectrum and the spectral shape of the variability changes. In spectral regions sensitive to conditions in the upper troposphere, the effect of increasing spatial scale is relatively small and at the global scale these parts of the spectrum show the greatest year-to-year variability. Conversely, the atmospheric window (8–12 µm), which is sensitive to variations in surface temperature and cloud, shows a marked reduction in interannual variability with increasing spatial scale. Over the 5 yr studied, at global scales the standard deviation in annual mean brightness temperature is less than 0.17 K across the spectrum, dropping to less than 0.05 K across the window. Spectrally integrating the IASI measurements to create pseudobroadband and window channels indicates a variation about the mean that is higher for the broadband channel than for the window channel at the global and quasi-global scales and over the Southern Hemisphere. These findings are in agreement with observations from CERES Terra over the same period and imply that at the largest spatial scales, over the period considered here, fluctuations in mid- to upper-tropospheric temperatures and water vapor, and not cloud or surface temperature, play the dominant role in determining the level of interannual variability in all-sky outgoing longwave radiation.

Optimal Estimation Method retrievals with IASI, AMSU and MHS measurements: Final Report

Optimal Estimation Method retrievals with IASI, AMSU and MHS measurements: Final Report

Assimilation of satellite infrared sounding measurements in the presence of heterogeneous cloud fields

In this article, a possible way to improve one of the techniques currently used by the numerical weather prediction (NWP) community to assimilate observations from hyperspectral infrared sounders (e.g. the Infrared Atmospheric Sounding Interferometer, IASI) in the presence of clouds is investigated. In particular, attention is focused on increasing the complexity of the cloud radiative model – where clouds are considered as single-layer grey bodies of negligible depth – used by a one-dimensional variational retrieval (1D-Var) cloud analysis that provides cloud parameters used in forward calculations within the global data assimilation system. A new two-layer cloud scheme is tested in the 1D-Var and results are compared with a single layer approach. In the new scheme four cloud-analysis control variables are included and are analysed simultaneously with temperature and humidity profiles. A validation of the new scheme using both simulated and observed IASI radiances shows that the two-layer cloud representation reduces significantly the bias in the mean profiles of retrieved minus background temperature differences, particularly in less homogeneous scenes. However, the bias is still too large to allow useful assimilation of channels below the cloud. Nevertheless, providing a better estimate of cloud position is valuable as it helps to prevent the assimilation of channels sensitive to the atmosphere below the cloud. Furthermore, the statistical analysis of the retrievals from IASI measurements – complemented by the Advanced Very High Resolution Radiometer cluster information – shows that the new scheme is more accurate in more heterogeneous scenes. This suggests that an a priori assessment of the degree of inhomogeneity in a scene may be useful to constrain the data appropriately, leading to a more effective use of cloudy radiances within the global 4D-Var assimilation.

On the effect of dust aerosols on AIRS and IASI operational level 2 products

Satellite retrievals of environmental parameters can enable a global scale understanding of various atmospheric phenomena. Validation of these retrievals using in situ and other correlative measurements is critical to the success of our accurate interpretation of such phenomena. In this paper, we analyze the effect of dust on AIRS and IASI operational level 2 profiles using data obtained from the 2009–2011 AEROSE campaigns. We find that the presence of dust in the AIRS and IASI measurements biases the cloud‐cleared radiances by as much as 4 K. In addition, we find that the temperature and surface temperature retrievals resultant from these cloud‐cleared radiances show 2 to 3 K spurious oscillations throughout the troposphere.

Physical analysis and recalibration of MetOp HIRS using IASI for cloud studies

The HIRS long‐wave CO2 channels (702 cm−1, 716.5 cm−1, 731.7 cm−1, and 748.8 cm−1) have been used by scientists for estimating cloud height and amount. However, spectral and radiometric biases in these HIRS channels significantly affect the accuracy and consistency of the level‐1b data used. This study utilizes the MetOp IASI measurements to calibrate the long‐wave CO2 channels of the HIRS on the same satellite. The radiance bias characteristics are displayed for a sample MetOp orbit. Detailed analysis is performed in an attempt to find the causes of the bias. The analysis consists of three steps. First, a thermal‐equilibrium analysis of blackbody using the HIRS window channel reveals the blackbody of MetOp HIRS has a 0.14 K bias. Then, the effective Spectral Response Function (SRF) corrections are estimated for the three long‐wave CO2 channels by minimizing the orbital bias variation, which is −0.13 cm−1 for channel 4, 0.09 cm−1 for channel 5, and −0.15 cm−1 for channel 7. Channel brightness temperature dynamic range is found to be important for separating SRF versus nonlinearity effects. Finally, the nonlinearity effect is evaluated and the nonlinearity term is derived to reduce the orbital mean biases toward zero. The improved radiometric and spectral recalibration parameters are validated using 16 months of independent MetOp data, with very positive results, showing consistent performance. It is found that the HIRS biases relative IASI are generally within 0.1 K after the recalibration.

Matching radiative transfer models and radiosonde data from the EPS/Metop Sodankylä campaign to IASI measurements

Abstract. Radiances observed from IASI are compared to calculated ones. Calculated radiances are obtained using several radiative transfer models (OSS, LBLRTM v11.3 and v11.6) on best estimates of the atmospheric state vectors. The atmospheric state vectors are derived from cryogenic frost point hygrometer and humidity dry bias corrected RS92 measurements flown on sondes launched 1 h and 5 min before IASI overpass time. The temperature and humidity best estimate profiles are obtained by interpolating or extrapolating these measurements to IASI overpass time. The IASI observed and calculated radiances match to within one sigma IASI instrument noise in the spectral region where water vapour is a strong absorber (wavenumber, ν, in the range of 1500 ≤ ν ≤ 1570 and 1615 ≤ ν ≤ 1800 cm−1).

Technical Note: An assessment of the accuracy of the RTTOV fast radiative transfer model using IASI data

Abstract. IASI measurements of spectral radiances made between the 1st April 2008 and the 15th April 2008 are compared with simulations performed using the RTTOV fast radiative transfer model utilizing regression coefficients based on different line-by-line models. The comparisons are performed within the framework of the European Centre for Medium-Range Weather Forecasts Integrated Forecast System using fields of temperature, water vapour and ozone obtained from short-range forecasts. Simulations are performed to assess the accuracy of the RTTOV computations and investigate relative differences between the line-by-line models and the quality of the spectroscopic databases on which the RTTOV coefficients are based.