scholarly journals Error sources in the retrieval of aerosol information over bright surfaces from satellite measurements in the oxygen A-band

2017 ◽  
Author(s):  
Swadhin Nanda ◽  
Martin de Graaf ◽  
Maarten Sneep ◽  
Johan F. de Haan ◽  
Piet Stammes ◽  
...  
Keyword(s):  
Optical Thickness ◽  
Surface Albedo ◽  
High Surface ◽  
Aerosol Optical Thickness ◽  
Radiative Transfer Model ◽  
Retrieval Algorithm ◽  
Transfer Model ◽  
Aerosol Layer ◽  
Critical Surface ◽  
Layer Height

Abstract. Retrieving aerosol optical thickness and aerosol layer height over a bright surface from measured top of atmosphere reflectance spectrum in the oxygen A-band is known to be challenging, often resulting in large errors. In certain atmospheric conditions and viewing geometries, a loss of sensitivity to aerosol optical thickness has been reported in literature. This loss of sensitivity has been attributed to a phenomenon known as critical surface albedo regime, which is a range of surface albedos for which the top of atmosphere reflectance has minimal sensitivity to aerosol optical thickness. This paper extends the concept of critical surface albedo for aerosol layer height retrievals in the oxygen A-band, and discusses its implications. The underlying physics are introduced by analysing top of atmosphere reflectance spectra obtained using a radiative transfer model. Furthermore, error analysis of the aerosol layer height retrieval algorithm are conducted over dark and bright surfaces to show the dependency on surface reflectance. The analysis shows that the information on aerosol layer height from atmospheric path contribution and the surface contribution to the top of atmosphere are opposite in sign – an increase in surface brightness results in a decrease in information content. In the case of aerosol optical thickness, these contributions are anti-correlated, leading to large retrieval errors in high surface albedo regimes. The consequence of this anti-correlation is demonstrated with measured spectra in the oxygen A-band from GOME-2A instrument on board the Metop-A satellite over the 2010 Russian wildfires incident.

scholarly journals Error sources in the retrieval of aerosol information over bright surfaces from satellite measurements in the oxygen A band

2018 ◽  
Vol 11 (1) ◽  
pp. 161-175 ◽  
Author(s):  
Swadhin Nanda ◽  
Martin de Graaf ◽  
Maarten Sneep ◽  
Johan F. de Haan ◽  
Piet Stammes ◽  
...  
Keyword(s):  
Optical Thickness ◽  
Surface Albedo ◽  
Reflectance Spectrum ◽  
Aerosol Optical Thickness ◽  
Retrieval Algorithm ◽  
Transfer Model ◽  
Aerosol Layer ◽  
Critical Surface ◽  
Layer Height ◽  
Atmospheric Path

Abstract. Retrieving aerosol optical thickness and aerosol layer height over a bright surface from measured top-of-atmosphere reflectance spectrum in the oxygen A band is known to be challenging, often resulting in large errors. In certain atmospheric conditions and viewing geometries, a loss of sensitivity to aerosol optical thickness has been reported in the literature. This loss of sensitivity has been attributed to a phenomenon known as critical surface albedo regime, which is a range of surface albedos for which the top-of-atmosphere reflectance has minimal sensitivity to aerosol optical thickness. This paper extends the concept of critical surface albedo for aerosol layer height retrievals in the oxygen A band, and discusses its implications. The underlying physics are introduced by analysing the top-of-atmosphere reflectance spectrum as a sum of atmospheric path contribution and surface contribution, obtained using a radiative transfer model. Furthermore, error analysis of an aerosol layer height retrieval algorithm is conducted over dark and bright surfaces to show the dependence on surface reflectance. The analysis shows that the derivative with respect to aerosol layer height of the atmospheric path contribution to the top-of-atmosphere reflectance is opposite in sign to that of the surface contribution – an increase in surface brightness results in a decrease in information content. In the case of aerosol optical thickness, these derivatives are anti-correlated, leading to large retrieval errors in high surface albedo regimes. The consequence of this anti-correlation is demonstrated with measured spectra in the oxygen A band from the GOME-2 instrument on board the Metop-A satellite over the 2010 Russian wildfires incident.

scholarly journals A neural network radiative transfer model approach applied to the Tropospheric Monitoring Instrument aerosol height algorithm

2019 ◽  
Vol 12 (12) ◽  
pp. 6619-6634 ◽  
Author(s):  
Swadhin Nanda ◽  
Martin de Graaf ◽  
J. Pepijn Veefkind ◽  
Mark ter Linden ◽  
Maarten Sneep ◽  
...  
Keyword(s):  
Neural Network ◽  
Radiative Transfer ◽  
European Space Agency ◽  
Forward Model ◽  
Radiative Transfer Model ◽  
Retrieval Algorithm ◽  
Transfer Model ◽  
Aerosol Layer ◽  
Layer Height ◽  
Monitoring Instrument

Abstract. To retrieve aerosol properties from satellite measurements of the oxygen A-band in the near-infrared, a line-by-line radiative transfer model implementation requires a large number of calculations. These calculations severely restrict a retrieval algorithm's operational capability as it can take several minutes to retrieve the aerosol layer height for a single ground pixel. This paper proposes a forward modelling approach using artificial neural networks to speed up the retrieval algorithm. The forward model outputs are trained into a set of neural network models to completely replace line-by-line calculations in the operational processor. Results comparing the forward model to the neural network alternative show an encouraging outcome with good agreement between the two when they are applied to retrieval scenarios using both synthetic and real measured spectra from TROPOMI (TROPOspheric Monitoring Instrument) on board the European Space Agency (ESA) Sentinel-5 Precursor mission. With an enhancement of the computational speed by 3 orders of magnitude, TROPOMI's operational aerosol layer height processor is now able to retrieve aerosol layer heights well within operational capacity.

scholarly journals An exploratory study on the aerosol height retrieval from OMI measurements of the 477 nm O<sub>2</sub>–O<sub>2</sub> spectral band, using a Neural Network approach

2016 ◽  
Author(s):  
Julien Chimot ◽  
Joris Pepijn Veefkind ◽  
Tim Vlemmix ◽  
Johan de Haan ◽  
Vassilis Amiridis ◽  
...  
Keyword(s):  
Neural Network ◽  
Air Quality ◽  
Optical Thickness ◽  
Exploratory Study ◽  
Surface Albedo ◽  
Spectral Band ◽  
Aerosol Optical Thickness ◽  
Aerosol Layer ◽  
Layer Height ◽  
North East

Abstract. This paper presents an exploratory study on the retrieval of aerosol layer height (ALH) from the OMI 477 nm O2–O2 spectral band. We have developed algorithms based on the Multilayer Perceptron (MLP) Neural Network (NN) approach and applied them on 3-year (2005–2007) OMI cloud-free scenes over North-East Asia, collocated with MODIS-Aqua aerosol product. In addition to the importance of aerosol altitude for climate and air quality objectives, the main motivation of this study is to evaluate the possibility of retrieving ALH for potential future improvements of trace gas retrievals (e.g. NO2, HCHO, SO2, etc..) from UV-Vis air quality satellite measurements over scenes including high aerosol concentrations. ALH retrieval relies on the analysis of the O2–O2 slant column density (SCD) and requires an accurate knowledge of the aerosol optical thickness τ. Using the MODIS-Aqua aerosol optical thickness at 550 nm as a prior information, comparison with the LIdar climatology of vertical Aerosol Structure for space-based lidar simulation (LIVAS) shows that ALH average biases over scenes with MODIS τ ≥ are in the range of 260–800 m. These results depend on the assumed aerosol single scattering albedo (sensitivity up to 600 m) and the chosen surface albedo (variation less than 200 m). Scenes with τ ≤ 0.5 are expected to show too large biases due to the little impacts of particles on the O2–O2 SCD changes. In addition, NN algorithms also enable aerosol optical thickness retrieval by exploring the OMI reflectance in the continuum. Comparisons with collocated MODIS-Aqua show agreements between −0.02 ± 0.45 and −0.18 ± 0.24 depending on the season. Improvements may be obtained from a better knowledge of the surface albedo, and higher accuracy of the aerosol model. This study shows the first encouraging aerosol layer height retrieval results over land from satellite observations of the 477 nm O2–O2 spectral band.

scholarly journals A neural network radiative transfer model approach applied to TROPOMI’s aerosol height algorithm

2019 ◽  
Author(s):  
Swadhin Nanda ◽  
Martin de Graaf ◽  
J. Pepijn Veefkind ◽  
Mark ter Linden ◽  
Maarten Sneep ◽  
...  
Keyword(s):  
Neural Network ◽  
Radiative Transfer ◽  
Near Infrared ◽  
Forward Model ◽  
Radiative Transfer Model ◽  
Retrieval Algorithm ◽  
Transfer Model ◽  
Aerosol Layer ◽  
Neural Network Models ◽  
Layer Height

Abstract. To retrieve aerosol properties from satellite measurements of the oxygen A-band in the near infrared, a line-by-line radiative transfer model implementation requires a large number of calculations. These calculations severely restrict a retrieval algorithm's operational capability as it can take several minutes to retrieve aerosol layer height for a single ground pixel. This paper proposes a forward modeling approach using artificial neural networks to speed up the retrieval algorithm. The forward model outputs are trained into a set of neural network models to completely replace line-by-line calculations in the operational processor. Results of comparing the forward model to the neural network alternative show encouraging results with good agreements between the two when applied to retrieval scenarios using both synthetic and real measured spectra from TROPOMI (TROPOspheric Monitoring Instrument) on board the ESA Sentinel-5 Precursor mission. With an enhancement of the computational speed by three orders of magnitude, TROPOMI's operational aerosol layer height processor is now able to retrieve aerosol layer heights well within operational capacity.

Consistent retrieval of cloud/aerosol single scattering properties and surface reflectance

2021 ◽  
Author(s):  
Marta Luffarelli ◽  
Yves Govaerts
Keyword(s):  
Radiative Transfer ◽  
Optical Thickness ◽  
Solution Space ◽  
Single Scattering ◽  
Aerosol Optical Thickness ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Surface Reflectance ◽  
Earth System ◽  
System Components

&lt;p&gt;The CISAR (Combined Inversion of Surface and AeRosols) algorithm is exploited in the framework of the ESA Aerosol Climate Change Initiatiave (CCI) project, aiming at providing a set of atmospheric (cloud and aerosol) and surface reflectance products derived from S3A/SLSTR observations using the same radiative transfer physics and assumptions. CISAR is an advance algorithm developed by Rayference originally designed for the retrieval of aerosol single scattering properties and surface reflectance from both geostationary and polar orbiting satellite observations. &amp;#160;It is based on the inversion of a fast radiative transfer model (FASTRE). The retrieval mechanism allows a continuous variation of the aerosol and cloud single scattering properties in the solution space.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;Traditionally, different approaches are exploited to retrieve the different Earth system components, which could lead to inconsistent data sets. The simultaneous retrieval of different atmospheric and surface variables over any type of surface (including bright surfaces and water bodies) with the same forward model and inversion scheme ensures the consistency among the retrieved Earth system components. Additionally, pixels located in the transition zone between pure clouds and pure aerosols are often discarded from both cloud and aerosol algorithms. This &amp;#8220;twilight zone&amp;#8221; can cover up to 30% of the globe. A consistent retrieval of both cloud and aerosol single scattering properties with the same algorithm could help filling this gap.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;The CISAR algorithm aims at overcoming the need of an external cloud mask, discriminating internally between aerosol and cloud properties. This approach helps reducing the overestimation of aerosol optical thickness in cloud contaminated pixels. The surface reflectance product is delivered both for cloud-free and cloudy observations. &amp;#160;&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;Global maps obtained from the processing of S3A/SLSTR observations will be shown. The SLSTR/CISAR products over events such as, for instance, the Australian fire in the last months of 2019, will be discussed in terms of aerosol optical thickness, aerosol-cloud discrimination and fine/coarse mode fraction.&lt;/p&gt;

Radiative forcing over the Arctic of aerosols from the August 2017 Canadian and Greenlandic wildfires

2021 ◽  
Author(s):  
Filippo Calì Quaglia ◽  
Daniela Meloni ◽  
Alcide Giorgio di Sarra ◽  
Tatiana Di Iorio ◽  
Virginia Ciardini ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Radiative Forcing ◽  
Solar Zenith Angle ◽  
Surface Albedo ◽  
High Arctic ◽  
The Arctic ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Aerosol Layer ◽  
Radiative Effect

&lt;p&gt;Extended and intense wildfires occurred in Northern Canada and, unexpectedly, on the Greenlandic West coast during summer 2017. The thick smoke plume emitted into the atmosphere was transported to the high Arctic, producing one of the largest impacts ever observed in the region. Evidence of Canadian and Greenlandic wildfires was recorded at the Thule High Arctic Atmospheric Observatory (THAAO, 76.5&amp;#176;N, 68.8&amp;#176;W, www.thuleatmos-it.it) by a suite of instruments managed by ENEA, INGV, Univ. of Florence, and NCAR. Ground-based observations of the radiation budget have allowed quantification of the surface radiative forcing at THAAO.&amp;#160;&lt;/p&gt;&lt;p&gt;Excess biomass burning chemical tracers such as CO, HCN, H2CO, C2H6, and NH3 were&amp;#160; measured in the air column above Thule starting from August 19 until August 23. The aerosol optical depth (AOD) reached a peak value of about 0.9 on August 21, while an enhancement of wildfire compounds was&amp;#160; detected in PM10. The measured shortwave radiative forcing was -36.7 W/m2 at 78&amp;#176; solar zenith angle (SZA) for AOD=0.626.&lt;/p&gt;&lt;p&gt;MODTRAN6.0 radiative transfer model (Berk et al., 2014) was used to estimate the aerosol radiative effect and the heating rate profiles at 78&amp;#176; SZA. Measured temperature profiles, integrated water vapour, surface albedo, spectral AOD and aerosol extinction profiles from CALIOP onboard CALIPSO were used as model input. The peak&amp;#160; aerosol heating rate (+0.5 K/day) was&amp;#160; reached within the aerosol layer between 8 and 12 km, while the maximum radiative effect (-45.4 W/m2) is found at 3 km, below the largest aerosol layer.&lt;/p&gt;&lt;p&gt;The regional impact of the event that occurred on August 21 was investigated using a combination of atmospheric radiative transfer modelling with measurements of AOD and ground surface albedo from MODIS. The aerosol properties used in the radiative transfer model were constrained by in situ measurements from THAAO. Albedo data over the ocean have been obtained from Jin et al. (2004). Backward trajectories produced through HYSPLIT simulations (Stein et al., 2015) were also employed to trace biomass burning plumes.&lt;/p&gt;&lt;p&gt;The radiative forcing efficiency (RFE) over land and ocean was derived, finding values spanning from -3 W/m2 to -132 W/m2, depending on surface albedo and solar zenith angle. The fire plume covered a vast portion of the Arctic, with large values of the daily shortwave RF (&lt; -50 W/m2) lasting for a few days. This large amount of aerosol is expected to influence cloud properties in the Arctic, producing significant indirect radiative effects.&lt;/p&gt;

scholarly journals MISR Calibration and Implications for Low-Light-Level Aerosol Retrieval over Dark Water

2005 ◽  
Vol 62 (4) ◽  
pp. 1032-1052 ◽  
Author(s):  
Ralph Kahn ◽  
Wen-Hao Li ◽  
John V. Martonchik ◽  
Carol J. Bruegge ◽  
David J. Diner ◽  
...  
Keyword(s):  
Optical Thickness ◽  
Near Infrared ◽  
Light Level ◽  
Single Scattering ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Aerosol Layer ◽  
Radiometric Calibration ◽  
Low Light ◽  
Vicarious Calibration

Abstract Studying aerosols over ocean is one goal of the Multiangle Imaging Spectroradiometer (MISR) and other spaceborne imaging systems. But top-of-atmosphere equivalent reflectance typically falls in the range of 0.03 to 0.12 at midvisible wavelengths and can be below 0.01 in the near-infrared, when an optically thin aerosol layer is viewed over a dark ocean surface. Special attention must be given to radiometric calibration if aerosol optical thickness, and any information about particle microphysical properties, are to be reliably retrieved from such observations. MISR low-light-level vicarious calibration is performed in the vicinity of remote islands hosting Aerosol Robotic Network (AERONET) sun- and sky-scanning radiometers, under low aerosol loading, low wind speed, relatively cloud free conditions. MISR equivalent reflectance is compared with values calculated from a radiative transfer model constrained by coincident, AERONET-retrieved aerosol spectral optical thickness, size distribution, and single scattering albedo, along with in situ wind measurements. Where the nadir view is not in sun glint, MISR equivalent reflectance is also compared with Moderate Resolution Imaging Spectroradiometer (MODIS) reflectance. The authors push the limits of the vicarious calibration method’s accuracy, aiming to assess absolute, camera-to-camera, and band-to-band radiometry. Patterns repeated over many well-constrained cases lend confidence to the results, at a few percent accuracy, as do additional vicarious calibration tests performed with multiplatform observations taken during the Chesapeake Lighthouse and Aircraft Measurements for Satellites (CLAMS) campaign. Conclusions are strongest in the red and green bands, but are too uncertain to accept for the near-infrared. MISR nadir-view and MODIS low-light-level absolute reflectances differ by about 4% in the blue and green bands, with MISR reporting higher values. In the red, MISR agrees with MODIS band 14 to better than 2%, whereas MODIS band 1 is significantly lower. Compared to the AERONET-constrained model, the MISR aft-viewing cameras report reflectances too high by several percent in the blue, green, and possibly the red. Better agreement is found in the nadir- and the forward-viewing cameras, especially in the blue and green. When implemented on a trial basis, calibration adjustments indicated by this work remove 40% of a 0.05 bias in retrieved midvisible aerosol optical depth over dark water scenes, produced by the early postlaunch MISR algorithm. A band-to-band correction has already been made to the MISR products, and the remaining calibration adjustments, totaling no more than a few percent, are planned.

scholarly journals Global stratospheric aerosol extinction profile retrievals from SCIAMACHY limb-scatter observations

2012 ◽  
Vol 5 (4) ◽  
pp. 5993-6035 ◽  
Author(s):  
F. Ernst ◽  
C. von Savigny ◽  
A. Rozanov ◽  
V. Rozanov ◽  
K.-U. Eichmann ◽  
...  
Keyword(s):  
Surface Albedo ◽  
Optimal Estimation ◽  
Stratospheric Aerosol ◽  
Visible Spectral Range ◽  
Radiative Transfer Model ◽  
Retrieval Algorithm ◽  
Transfer Model ◽  
Aerosol Extinction ◽  
Index Approach ◽  
The Impact

Abstract. Stratospheric aerosol extinction profiles are retrieved from SCIAMACHY/Envisat limb-scatter observations in the visible spectral range. The retrieval algorithm is based on a colour-index approach using the normalized limb-radiance profiles at 470 nm and 750 nm wavelength. The optimal estimation approach in combination with the radiative transfer model SCIATRAN is employed for the retrievals. This study presents a detailed description of the retrieval algorithm, and a sensitivity analysis investigating the impact of the most important parameters that affect the aerosol extinction profile retrieval accuracy. It is found that the parameter with the largest impact is surface albedo, particularly for SCIAMACHY observations in the Southern Hemisphere where the error in stratospheric aerosol extinction can be up to 50% if the surface albedo is not well known. The effect of errors in the assumed ozone and neutral density profiles on the aerosol profile retrievals is with generally less than 6% relatively small. The aerosol extinction profiles retrieved from SCIAMACHY are compared with co-located SAGE II solar occultation measurements of stratospheric aerosol extinction during the period 2003–2005. The mean aerosol extinction profiles averaged over all co-locations agree to within 20% between 15 and 35 km altitude. However, larger differences are observed at specific latitudes.

scholarly journals A first comparison of TROPOMI aerosol layer height (ALH) to CALIOP data

2020 ◽  
Vol 13 (6) ◽  
pp. 3043-3059 ◽  
Author(s):  
Swadhin Nanda ◽  
Martin de Graaf ◽  
J. Pepijn Veefkind ◽  
Maarten Sneep ◽  
Mark ter Linden ◽  
...  
Keyword(s):  
Optimal Estimation ◽  
Satellite Observation ◽  
Radiative Transfer Model ◽  
Orthogonal Polarization ◽  
Ultraviolet Region ◽  
Transfer Model ◽  
Aerosol Layer ◽  
Layer Height ◽  
Significant Difference ◽  
Level 2

Abstract. The TROPOspheric Monitoring Instrument (TROPOMI) level-2 aerosol layer height (ALH) product has now been released to the general public. This product is retrieved using TROPOMI's measurements of the oxygen A-band, radiative transfer model (RTM) calculations augmented by neural networks and an iterative optimal estimation technique. The TROPOMI ALH product will deliver ALH estimates over cloud-free scenes over the ocean and land that contain aerosols above a certain threshold of the measured UV aerosol index (UVAI) in the ultraviolet region. This paper provides background for the ALH product and explores its quality by comparing ALH estimates to similar quantities derived from spaceborne lidars observing the same scene. The spaceborne lidar chosen for this study is the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP) on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) mission, which flies in formation with NASA's A-train constellation since 2006 and is a proven source of data for studying ALHs. The influence of the surface and clouds is discussed, and the aspects of the TROPOMI ALH algorithm that will require future development efforts are highlighted. A case-by-case analysis of the data from the four selected cases (mostly around the Saharan region with approximately 800 co-located TROPOMI pixels and CALIOP profiles in June and December 2018) shows that ALHs retrieved from TROPOMI using the operational Sentinel-5 Precursor Level-2 ALH algorithm is lower than CALIOP aerosol extinction heights by approximately 0.5 km. Looking at data beyond these cases, it is clear that there is a significant difference when it comes to retrievals over land, where these differences can easily go over 1 km on average.

scholarly journals Evaluation of the operational Aerosol Layer Height retrieval algorithm for Sentinel-5 Precursor: application to O<sub>2</sub> A band observations from GOME-2A

2015 ◽  
Vol 8 (11) ◽  
pp. 4947-4977 ◽  
Author(s):  
A. F. J. Sanders ◽  
J. F. de Haan ◽  
M. Sneep ◽  
A. Apituley ◽  
P. Stammes ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Surface Albedo ◽  
Single Layer ◽  
Retrieval Algorithm ◽  
Aerosol Layer ◽  
Surface Boundary ◽  
Layer Height ◽  
Aerosol Model ◽  
Sensitivity Experiments ◽  
Lidar Measurements

Abstract. An algorithm setup for the operational Aerosol Layer Height product for TROPOMI on the Sentinel-5 Precursor mission is described and discussed, applied to GOME-2A data, and evaluated with lidar measurements. The algorithm makes a spectral fit of reflectance at the O2 A band in the near-infrared and the fit window runs from 758 to 770 nm. The aerosol profile is parameterised by a scattering layer with constant aerosol volume extinction coefficient and aerosol single scattering albedo and with a fixed pressure thickness. The algorithm's target parameter is the height of this layer. In this paper, we apply the algorithm to observations from GOME-2A in a number of systematic and extensive case studies, and we compare retrieved aerosol layer heights with lidar measurements. Aerosol scenes cover various aerosol types, both elevated and boundary layer aerosols, and land and sea surfaces. The aerosol optical thicknesses for these scenes are relatively moderate. Retrieval experiments with GOME-2A spectra are used to investigate various sensitivities, in which particular attention is given to the role of the surface albedo. From retrieval simulations with the single-layer model, we learn that the surface albedo should be a fit parameter when retrieving aerosol layer height from the O2 A band. Current uncertainties in surface albedo climatologies cause biases and non-convergences when the surface albedo is fixed in the retrieval. Biases disappear and convergence improves when the surface albedo is fitted, while precision of retrieved aerosol layer pressure is still largely within requirement levels. Moreover, we show that fitting the surface albedo helps to ameliorate biases in retrieved aerosol layer height when the assumed aerosol model is inaccurate. Subsequent retrievals with GOME-2A spectra confirm that convergence is better when the surface albedo is retrieved simultaneously with aerosol parameters. However, retrieved aerosol layer pressures are systematically low (i.e., layer high in the atmosphere) to the extent that retrieved values no longer realistically represent actual extinction profiles. When the surface albedo is fixed in retrievals with GOME-2A spectra, convergence deteriorates as expected, but retrieved aerosol layer pressures become much higher (i.e., layer lower in atmosphere). The comparison with lidar measurements indicates that retrieved aerosol layer heights are indeed representative of the underlying profile in that case. Finally, subsequent retrieval simulations with two-layer aerosol profiles show that a model error in the assumed profile (two layers in the simulation but only one in the retrieval) is partly absorbed by the surface albedo when this parameter is fitted. This is expected in view of the correlations between errors in fit parameters and the effect is relatively small for elevated layers (less than 100 hPa). If one of the scattering layers is near the surface (boundary layer aerosols), the effect becomes surprisingly large, in such a way that the retrieved height of the single layer is above the two-layer profile. Furthermore, we find that the retrieval solution, once retrieval converges, hardly depends on the starting values for the fit. Sensitivity experiments with GOME-2A spectra also show that aerosol layer height is indeed relatively robust against inaccuracies in the assumed aerosol model, even when the surface albedo is not fitted. We show spectral fit residuals, which can be used for further investigations. Fit residuals may be partly explained by spectroscopic uncertainties, which is suggested by an experiment showing the improvement of convergence when the absorption cross section is scaled in agreement with Butz et al. (2013) and Crisp et al. (2012), and a temperature offset to the a priori ECMWF temperature profile is fitted. Retrieved temperature offsets are always negative and quite large (ranging between −4 and −8 K), which is not expected if temperature offsets absorb remaining inaccuracies in meteorological data. Other sensitivity experiments investigate fitting of stray light and fluorescence emissions. We find negative radiance offsets and negative fluorescence emissions, also for non-vegetated areas, but from the results it is not clear whether fitting these parameters improves the retrieval. Based on the present results, the operational baseline for the Aerosol Layer Height product currently will not fit the surface albedo. The product will be particularly suited for elevated, optically thick aerosol layers. In addition to its scientific value in climate research, anticipated applications of the product for TROPOMI are providing aerosol height information for aviation safety and improving interpretation of the Absorbing Aerosol Index.

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