scholarly journals The Role of Cloud Contamination, Aerosol Layer Height and Aerosol Model in the Assessment of the OMI near-UV Retrievals over the Ocean

2016 ◽  
Author(s):  
Santiago Gassó ◽  
Omar Torres
Keyword(s):  
Particle Shape ◽  
Spherical Shape ◽  
Detailed Examination ◽  
Index Of Refraction ◽  
Retrieval Algorithm ◽  
Aerosol Layer ◽  
Ozone Monitoring Instrument ◽  
Aerosol Model ◽  
Modis Aod ◽  
Absorbing Aerosols

Abstract. Retrievals of aerosol optical depth (AOD) at 388 nm over the ocean from the Ozone Monitoring Instrument (OMI) two-channel near UV algorithm (OMAERUV) have been compared with independent AOD measurements. The analysis was carried out over the open ocean (OMI and MODIS AOD comparisons) and over coastal and island sites (AERONET and OMI). Also, a research version of the retrieval algorithm (using MODIS and CALIPSO information as constraints) was utilized to evaluate the sensitivity of the retrieval to different assumed aerosol properties. Overall, the comparison resulted in differences (OMI minus independent measurements) within the expected levels of uncertainty for the OMI AOD retrievals. Using examples from case studies with outliers, the reasons that lead to the observed differences are examined with specific purpose to determine if they are related to instrument (i.e., pixel size, calibration) limitations or algorithm assumptions (such as aerosol shape, aerosol height). The analysis confirms that OMAERUV does an adequate job at rejecting cloudy scenes within the instrument capabilities. There is a residual cloud contamination in OMI pixels with quality flag 0 (the best conditions for aerosol retrieval according to the algorithm) resulting in a bias towards high AODs in OMAERUV. This bias is more pronounced at low concentrations of absorbing aerosols (AOD 388 nm ~< 0.5). For higher aerosol loadings, the bias remains within OMI’s AOD uncertainties. In pixels where OMAERUV assigned a dust aerosol model, a fraction of them (< 20 %) had retrieved AODs significantly lower than AERONET and MODIS AODs. In a case study, a detailed examination of the aerosol height from CALIOP and AODs from MODIS along with sensitivity tests was carried out by varying the different assumed parameters in the retrieval (imaginary index of refraction, size distribution, aerosol height, particle shape). It was found that spherical shape assumption for dust in the current retrieval is the main cause of the underestimate. Also, it is shown with an example how an incorrect assumption of the aerosol height can lead to an underestimate but this is not as large as the effect of particle shape. These findings will be incorporated in a future version of the retrieval algorithm.

scholarly journals The role of cloud contamination, aerosol layer height and aerosol model in the assessment of the OMI near-UV retrievals over the ocean

2016 ◽  
Vol 9 (7) ◽  
pp. 3031-3052 ◽  
Author(s):  
Santiago Gassó ◽  
Omar Torres
Keyword(s):  
Particle Shape ◽  
Spherical Shape ◽  
Detailed Examination ◽  
Index Of Refraction ◽  
Retrieval Algorithm ◽  
Orthogonal Polarization ◽  
Aerosol Layer ◽  
Ozone Monitoring Instrument ◽  
Aerosol Model ◽  
Modis Aod

Abstract. Retrievals of aerosol optical depth (AOD) at 388 nm over the ocean from the Ozone Monitoring Instrument (OMI) two-channel near-UV algorithm (OMAERUV) have been compared with independent AOD measurements. The analysis was carried out over the open ocean (OMI and MODerate-resolution Imaging Spectrometer (MODIS) AOD comparisons) and over coastal and island sites (OMI and AERONET, the AErosol RObotic NETwork). Additionally, a research version of the retrieval algorithm (using MODIS and CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) information as constraints) was utilized to evaluate the sensitivity of the retrieval to different assumed aerosol properties. Overall, the comparison resulted in differences (OMI minus independent measurements) within the expected levels of uncertainty for the OMI AOD retrievals (0.1 for AOD < 0.3, 30 % for AOD > 0.3). Using examples from case studies with outliers, the reasons that led to the observed differences were examined with specific purpose to determine whether they are related to instrument limitations (i.e., pixel size, calibration) or algorithm assumptions (such as aerosol shape, aerosol height). The analysis confirms that OMAERUV does an adequate job at rejecting cloudy scenes within the instrument's capabilities. There is a residual cloud contamination in OMI pixels with quality flag 0 (the best conditions for aerosol retrieval according to the algorithm), resulting in a bias towards high AODs in OMAERUV. This bias is more pronounced at low concentrations of absorbing aerosols (AOD 388 nm  ∼  < 0.5). For higher aerosol loadings, the bias remains within OMI's AOD uncertainties. In pixels where OMAERUV assigned a dust aerosol model, a fraction of them (< 20 %) had retrieved AODs significantly lower than AERONET and MODIS AODs. In a case study, a detailed examination of the aerosol height from CALIOP and the AODs from MODIS, along with sensitivity tests, was carried out by varying the different assumed parameters in the retrieval (imaginary index of refraction, size distribution, aerosol height, particle shape). It was found that the spherical shape assumption for dust in the current retrieval is the main cause of the underestimate. In addition, it is demonstrated in an example how an incorrect assumption of the aerosol height can lead to an underestimate. Nevertheless, this is not as significant as the effect of particle shape. These findings will be incorporated in a future version of the retrieval algorithm.

scholarly journals Minimizing aerosol effects on the OMI tropospheric NO<sub>2</sub> retrieval – An improved use of the 477 nm O<sub>2</sub> − O<sub>2</sub> band and an estimation of the aerosol correction uncertainty

2019 ◽  
Vol 12 (1) ◽  
pp. 491-516 ◽  
Author(s):  
Julien Chimot ◽  
J. Pepijn Veefkind ◽  
Johan F. de Haan ◽  
Piet Stammes ◽  
Pieternel F. Levelt
Keyword(s):  
Air Quality ◽  
Eastern China ◽  
Spectral Band ◽  
Aerosol Layer ◽  
Atmospheric Conditions ◽  
Ozone Monitoring Instrument ◽  
Vertical Column ◽  
Aerosol Model ◽  
Tropospheric No2 ◽  
Aerosol Parameters

Abstract. Global mapping of satellite tropospheric NO2 vertical column density (VCD), a key gas in air quality monitoring, requires accurate retrievals over complex urban and industrialized areas and under any atmospheric conditions. The high abundance of aerosol particles in regions dominated by anthropogenic fossil fuel combustion, e.g. megacities, and/or biomass-burning episodes, affects the space-borne spectral measurement. Minimizing the tropospheric NO2 VCD biases caused by aerosol scattering and absorption effects is one of the main retrieval challenges from air quality satellite instruments. In this study, the reference Ozone Monitoring Instrument (OMI) DOMINO-v2 product was reprocessed over cloud-free scenes, by applying new aerosol correction parameters retrieved from the 477 nm O2−O2 band, over eastern China and South America for 2 years (2006–2007). These new parameters are based on two different and separate algorithms developed during the last 2 years in view of an improved use of the OMI 477 nm O2−O2 band: the updated OMCLDO2 algorithm, which derives improved effective cloud parameters, the aerosol neural network (NN), which retrieves explicit aerosol parameters by assuming a more physical aerosol model. The OMI aerosol NN is a step ahead of OMCLDO2 because it primarily estimates an explicit aerosol layer height (ALH), and secondly an aerosol optical thickness τ for cloud-free observations. Overall, it was found that all the considered aerosol correction parameters reduce the biases identified in DOMINO-v2 over scenes in China with high aerosol abundance dominated by fine scattering and weakly absorbing particles, e.g. from [-20%:-40%] to [0 %:20 %] in summertime. The use of the retrieved OMI aerosol parameters leads in general to a more explicit aerosol correction and higher tropospheric NO2 VCD values, in the range of [0 %:40 %], than from the implicit correction with the updated OMCLDO2. This number overall represents an estimation of the aerosol correction strategy uncertainty nowadays for tropospheric NO2 VCD retrieval from space-borne visible measurements. The explicit aerosol correction theoretically includes a more realistic consideration of aerosol multiple scattering and absorption effects, especially over scenes dominated by strongly absorbing particles, where the correction based on OMCLDO2 seems to remain insufficient. However, the use of ALH and τ from the OMI NN aerosol algorithm is not a straightforward operation and future studies are required to identify the optimal methodology. For that purpose, several elements are recommended in this paper. Overall, we demonstrate the possibility of applying a more explicit aerosol correction by considering aerosol parameters directly derived from the 477 nm O2−O2 spectral band, measured by the same satellite instrument. Such an approach can, in theory, easily be transposed to the new-generation of space-borne instruments (e.g. TROPOMI on board Sentinel-5 Precursor), enabling a fast reprocessing of tropospheric NO2 data over cloud-free scenes (cloudy pixels need to be filtered out), as well as for other trace gas retrievals (e.g. SO2, HCHO).

scholarly journals Improvements to the OMI near UV aerosol algorithm using A-train CALIOP and AIRS observations

2013 ◽  
Vol 6 (3) ◽  
pp. 5621-5652 ◽  
Author(s):  
O. Torres ◽  
C. Ahn ◽  
Z. Chen
Keyword(s):  
Retrieval Algorithm ◽  
Orthogonal Polarization ◽  
Aerosol Layer ◽  
Carbonaceous Aerosols ◽  
Ozone Monitoring Instrument ◽  
Atmospheric Infrared Sounder ◽  
Layer Height ◽  
Aerosol Retrieval ◽  
Polarization Sensor ◽  
Aerosol Properties

Abstract. The height of desert dust and carbonaceous aerosols layers and, to a lesser extent, the difficulty in determining the predominant size mode of these absorbing aerosol types, are sources of uncertainty in the retrieval of aerosol properties from near UV satellite observations. The availability of independent, near-simultaneous measurements of aerosol layer height, and aerosol-type related parameters derived from observations by other A-train sensors, makes possible the use of this information as input to the OMI (Ozone Monitoring Instrument) near UV aerosol retrieval algorithm (OMAERUV). A monthly climatology of aerosol layer height derived from observations by the CALIOP (Cloud–Aerosol Lidar with Orthogonal Polarization) sensor, and real-time AIRS (Atmospheric Infrared Sounder) CO observations are used in an upgraded version of the OMAERUV algorithm. AIRS CO measurements are used as a reliable tracer of carbonaceous aerosols, which allows the identification of smoke layers in regions and seasons when the dust-smoke differentiation is difficult in the near-UV. The use of CO measurements also enables the identification of elevated levels of boundary layer pollution undetectable by near UV observations alone. In this paper we discuss the combined use of OMI, CALIOP and AIRS observations for the characterization of aerosol properties, and show an improvement in OMI aerosol retrieval capabilities.

scholarly journals Multi-Satellite Retrieval of SSA using OMI-MODIS algorithm

2018 ◽  
Author(s):  
Kruthika Eswaran ◽  
Sreedharan Krishnakumari Satheesh ◽  
Jayaraman Srinivasan
Keyword(s):  
Radiative Forcing ◽  
Single Scattering ◽  
Retrieval Algorithm ◽  
Ozone Monitoring Instrument ◽  
Aerosol Composition ◽  
Aerosol Radiative Forcing ◽  
Aerosol Absorption ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Absorbing Aerosols ◽  
Aerosol Type

Abstract. Single scattering albedo (SSA) represents a unique identification of aerosol type and aerosol radiative forcing. However, SSA retrievals are highly uncertain due cloud contamination and aerosol composition. Recent improvement in the SSA retrieval algorithm has combined the superior cloud masking technique of Moderate Resolution Imaging Spectroradiometer (MODIS) and the better sensitivity of Ozone Monitoring Instrument (OMI) to aerosol absorption. The combined OMI-MODIS algorithm has been validated over a small spatial and temporal scale only. The present study validates the algorithm over global oceans for the period 2008–2012. The geographical heterogeneity in the aerosol type and concentration over the Atlantic Ocean, the Arabian Sea and the Bay of Bengal was useful to delineate the effect of aerosol type on the retrieval algorithm. We also noted that OMI overestimates SSA when absorbing aerosols were present closer to the surface. We attribute this overestimation to data discontinuity in the aerosol height climatology derived from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite. OMI uses pre-defined aerosol heights over regions where CALIPSO climatology is not present leading to overestimation of SSA. The importance of aerosol height was also studied using the Santa Barbara DISORT radiative transfer (SBDART) model. The results from the joint retrieval were validated with ground-based measurements and it was seen that OMI-MODIS SSA retrievals were better constrained than OMI only retrieval.

scholarly journals Improvements to the OMI near-UV aerosol algorithm using A-train CALIOP and AIRS observations

2013 ◽  
Vol 6 (11) ◽  
pp. 3257-3270 ◽  
Author(s):  
O. Torres ◽  
C. Ahn ◽  
Z. Chen
Keyword(s):  
Retrieval Algorithm ◽  
Orthogonal Polarization ◽  
Aerosol Layer ◽  
Carbonaceous Aerosols ◽  
Ozone Monitoring Instrument ◽  
Atmospheric Infrared Sounder ◽  
Layer Height ◽  
Aerosol Retrieval ◽  
Polarization Sensor ◽  
Aerosol Properties

Abstract. The height of desert dust and carbonaceous aerosols layers and, to a lesser extent, the difficulty in determining the predominant size mode of these absorbing aerosol types, are sources of uncertainty in the retrieval of aerosol properties from near-UV satellite observations. The availability of independent, near-simultaneous measurements of aerosol layer height, and aerosol-type related parameters derived from observations by other A-train sensors, makes possible the use of this information as input to the OMI (ozone monitoring instrument) near-UV aerosol retrieval algorithm (OMAERUV). A monthly climatology of aerosol layer height derived from observations by the CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) sensor, and real-time AIRS (Atmospheric Infrared Sounder) carbon monoxide (CO) observations are used in an upgraded version of the OMAERUV algorithm. AIRS CO measurements are used as an adequate tracer of carbonaceous aerosols, which allows the identification of smoke layers in regions and seasons when the dust-smoke differentiation is difficult in the near-UV. The use of CO measurements also enables the identification of high levels of boundary layer pollution undetectable by near-UV observations alone. In this paper we discuss the combined use of OMI, CALIOP and AIRS observations for the characterization of aerosol properties, and show an improvement in OMI aerosol retrieval capabilities.

scholarly journals Model Selection in Atmospheric Remote Sensing with an Application to Aerosol Retrieval from DSCOVR/EPIC, Part 1: Theory

2020 ◽  
Vol 12 (22) ◽  
pp. 3724
Author(s):  
Sruthy Sasi ◽  
Vijay Natraj ◽  
Víctor Molina García ◽  
Dmitry S. Efremenko ◽  
Diego Loyola ◽  
...  
Keyword(s):  
Model Selection ◽  
Optical Thickness ◽  
Marginal Likelihood ◽  
Likelihood Estimation ◽  
Retrieval Algorithm ◽  
Aerosol Layer ◽  
Aerosol Model ◽  
Microphysical Properties ◽  
Cloud Properties ◽  
Atmospheric Remote Sensing

The retrieval of aerosol and cloud properties such as their optical thickness and/or layer/top height requires the selection of a model that describes their microphysical properties. We demonstrate that, if there is not enough information for an appropriate microphysical model selection, the solution’s accuracy can be improved if the model uncertainty is taken into account and appropriately quantified. For this purpose, we design a retrieval algorithm accounting for the uncertainty in model selection. The algorithm is based on (i) the computation of each model solution using the iteratively regularized Gauss–Newton method, (ii) the linearization of the forward model around the solution, and (iii) the maximum marginal likelihood estimation and the generalized cross-validation to estimate the optimal model. The algorithm is applied to the retrieval of aerosol optical thickness and aerosol layer height from synthetic measurements corresponding to the Earth Polychromatic Imaging Camera (EPIC) instrument onboard the Deep Space Climate Observatory (DSCOVR) satellite. Our numerical simulations show that the heuristic approach based on the thesolution minimizing the residual, which is frequently used in literature, is completely unrealistic when both the aerosol model and surface albedo are unknown.

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.

scholarly journals Evaluating the assumptions of surface reflectance and aerosol type selection within the MODIS aerosol retrieval over land: the problem of dust type selection

2010 ◽  
Vol 3 (4) ◽  
pp. 3425-3453 ◽  
Author(s):  
T. Mielonen ◽  
R. C. Levy ◽  
V. Aaltonen ◽  
M. Komppula ◽  
G. de Leeuw ◽  
...  
Keyword(s):  
Model Selection ◽  
Vegetation Index ◽  
Retrieval Algorithm ◽  
Physical Relationship ◽  
Selection Scheme ◽  
Aerosol Model ◽  
Type Selection ◽  
Comparison Results ◽  
Filter Radiometer ◽  
Modis Aod

Abstract. Aerosol Optical Depth (AOD) and Ångström exponent (AE) values derived with the MODIS retrieval algorithm over land (Collection 5) were compared with ground based sun photometer measurements in Europe, Asia, Africa, North America and South America. In Finland (Jokioinen and Sodankylä) measurements were done with Precision Filter Radiometer (PFR), while in Estonia (Toravere), Italy (Ispra, Rome Tor Vergata), India (Kanpur), China (Xianghe), GSFC (USA), Mexico (Mexico City), Zambia (Mongu) and Brazil (Alta Floresta) Cimel (AERONET, level 2) measurements were used. Comparison results for AOD were generally good, although there seems to be room for improvement in the MODIS aerosol model selection, particularly how dust is taken into account. At all studied sites, the MODIS algorithm often selects the dust aerosol model even when dust does not seem to be present and the air masses are not coming from arid regions. This happens especially when AOD values are relatively small (<0.3). The selection of the dust model reduces the correlation between ground based and MODIS AOD measurements in dust-free situations. Moreover, the current aerosol model selection scheme produces unphysical AE values. Our study suggests that the aerosol model combining is sensitive to the ratio of 660 nm and 2130 nm surface reflectances (slope(660/2130)). Furthermore, the value of the slope in the algorithm is mainly dependent on the Normalized Difference Vegetation Index (NDVI). The current relationship of these two parameters in the algorithm is not supported by the surface albedo climatology derived from MODIS measurements. The use of a more physical relationship improves the AE retrieval at the studied sites. However, at some sites the AOD correspondence deteriorates when the new relationship is used.

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 (6) ◽  
pp. 6045-6118 ◽  
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 parameterized 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 are not realistically representing actual extinction profiles anymore. 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). In case one of the scattering layers is near the surface (boundary layer aerosols), the effect becomes surprisingly large such 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. (2012) 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.

scholarly journals Rethinking the correction for absorbing aerosols in the OMI- and TROPOMI-like surface UV algorithms

2021 ◽  
Vol 14 (7) ◽  
pp. 4947-4957
Author(s):  
Antti Arola ◽  
William Wandji Nyamsi ◽  
Antti Lipponen ◽  
Stelios Kazadzis ◽  
Nickolay A. Krotkov ◽  
...  
Keyword(s):  
Optical Depth ◽  
Uv Radiation ◽  
Correction Factor ◽  
Zenith Angle ◽  
Solar Zenith Angle ◽  
Retrieval Algorithm ◽  
Ozone Monitoring Instrument ◽  
Aerosol Absorption ◽  
Uv Irradiance ◽  
Absorbing Aerosols

Abstract. Satellite estimates of surface UV irradiance have been available since 1978 from the TOMS UV spectrometer and have continued with significantly improved ground resolution using the Ozone Monitoring Instrument (OMI 2004–current) and Sentinel 5 Precursor (S5P 2017–current). The surface UV retrieval algorithm remains essentially the same: it first estimates the clear-sky UV irradiance based on measured ozone and then accounts for the attenuation by clouds and aerosols, applying two consecutive correction factors. When estimating the total aerosol effect in surface UV irradiance, there are two major classes of aerosols to be considered: (1) aerosols that only scatter UV radiation and (2) aerosols that both scatter and absorb UV radiation. The former effect is implicitly included in the measured effective Lambertian-equivalent scene reflectivity (LER), so the scattering aerosol influence is estimated through cloud correction factor. Aerosols that absorb UV radiation attenuate the surface UV radiation more strongly than non-absorbing aerosols of the same extinction optical depth. Moreover, since these aerosols also attenuate the outgoing satellite-measured radiance, the cloud correction factor that treats these aerosols as purely scattering underestimates their aerosol optical depth (AOD), causing underestimation of LER and overestimation of surface UV irradiance. Therefore, for correction of aerosol absorption, additional information is needed, such as a model-based monthly climatology of aerosol absorption optical depth (AAOD). A correction for absorbing aerosols was proposed almost a decade ago and later implemented in the operational OMI and TROPOMI UV algorithms. In this study, however, we show that there is still room for improvement to better account for the solar zenith angle (SZA) dependence and nonlinearity in the absorbing aerosol attenuation, and as a result we propose an improved correction scheme. There are two main differences between the new proposed correction and the one that is currently operational in OMI and TROPOMI UV algorithms. First, the currently operational correction for absorbing aerosols is a function of AAOD only, while the new correction additionally takes the solar zenith angle dependence into account. Second, the second-order polynomial of the new correction takes the nonlinearity in the correction as a function of AAOD better into account, if compared to the currently operational one, and thus better describes the effect by absorbing aerosols over a larger range of AAOD. To illustrate the potential impact of the new correction in the global UV estimates, we applied the current and new proposed correction for global fields of AAOD from the aerosol climatology currently used in OMI UV algorithm, showing a typical differences of ±5 %. This new correction is easy to implement operationally using information of solar zenith angle and existing AAOD climatology.

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