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

2017 ◽  
Vol 10 (3) ◽  
pp. 783-809 ◽  
Author(s):  
Julien Chimot ◽  
J. Pepijn Veefkind ◽  
Tim Vlemmix ◽  
Johan F. de Haan ◽  
Vassilis Amiridis ◽  
...  
Keyword(s):  
Neural Network ◽  
Air Quality ◽  
Optical Thickness ◽  
Exploratory Study ◽  
Surface Albedo ◽  
Spectral Band ◽  
Single Scattering ◽  
Aerosol Layer ◽  
Layer Height

Abstract. This paper presents an exploratory study on the aerosol layer height (ALH) retrieval 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 to 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, our long-term motivation is to evaluate the possibility of retrieving ALH for potential future improvements of trace gas retrievals (e.g. NO2, HCHO, SO2) from UV–visible air quality satellite measurements over scenes including high aerosol concentrations. This study presents a first step of this long-term objective and evaluates, from a statistic point of view, an ensemble of OMI ALH retrievals over a long time period of 3 years covering a large industrialized continental region. This 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 MODIS Aqua τ(550 nm) as a prior information, absolute seasonal differences between the LIdar climatology of vertical Aerosol Structure for space-based lidar simulation (LIVAS) and average OMI ALH, over scenes with MODIS τ(550 nm) ≥ 1. 0, are in the range of 260–800 m (assuming single scattering albedo ω0 = 0. 95) and 180–310 m (assuming ω0 = 0. 9). OMI ALH retrievals depend on the assumed aerosol single scattering albedo (sensitivity up to 660 m) and the chosen surface albedo (variation less than 200 m between OMLER and MODIS black-sky albedo). Scenes with τ ≤ 0. 5 are expected to show too large biases due to the little impact 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. Following the previous work over ocean of Park et al.(2016), our study shows the first encouraging aerosol layer height retrieval results over land from satellite observations of the 477 nm O2 − O2 absorption spectral band.

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 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 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 Spatial distribution analysis of the OMI aerosol layer height: a pixel-by-pixel comparison to CALIOP observations

2018 ◽  
Vol 11 (4) ◽  
pp. 2257-2277 ◽  
Author(s):  
Julien Chimot ◽  
J. Pepijn Veefkind ◽  
Tim Vlemmix ◽  
Pieternel F. Levelt
Keyword(s):  
Air Quality ◽  
Eastern China ◽  
Weighted Average ◽  
Saharan Dust ◽  
Trace Gas ◽  
High Temporal Resolution ◽  
Aerosol Layer ◽  
Distribution Analysis ◽  
Layer Height ◽  
Satellite Sensors

Abstract. A global picture of atmospheric aerosol vertical distribution with a high temporal resolution is of key importance not only for climate, cloud formation, and air quality research studies but also for correcting scattered radiation induced by aerosols in absorbing trace gas retrievals from passive satellite sensors. Aerosol layer height (ALH) was retrieved from the OMI 477 nm O2−O2 band and its spatial pattern evaluated over selected cloud-free scenes. Such retrievals benefit from a synergy with MODIS data to provide complementary information on aerosols and cloudy pixels. We used a neural network approach previously trained and developed. Comparison with CALIOP aerosol level 2 products over urban and industrial pollution in eastern China shows consistent spatial patterns with an uncertainty in the range of 462–648 m. In addition, we show the possibility to determine the height of thick aerosol layers released by intensive biomass burning events in South America and Russia from OMI visible measurements. A Saharan dust outbreak over sea is finally discussed. Complementary detailed analyses show that the assumed aerosol properties in the forward modelling are the key factors affecting the accuracy of the results, together with potential cloud residuals in the observation pixels. Furthermore, we demonstrate that the physical meaning of the retrieved ALH scalar corresponds to the weighted average of the vertical aerosol extinction profile. These encouraging findings strongly suggest the potential of the OMI ALH product, and in more general the use of the 477 nm O2−O2 band from present and future similar satellite sensors, for climate studies as well as for future aerosol correction in air quality trace gas retrievals.

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 Modelling Particulate Matter Using Multivariate and Multistep Recurrent Neural Networks

2021 ◽  
Vol 9 ◽  
Author(s):  
Tushar Saini ◽  
Pratik Chaturvedi ◽  
Varun Dutt
Keyword(s):  
Neural Network ◽  
Air Quality ◽  
Recurrent Neural Network ◽  
Network Models ◽  
Economic Losses ◽  
Ensemble Model ◽  
Neural Network Models ◽  
Ensemble Techniques ◽  
Bidirectional Lstm

Air quality is a major problem in the world, having severe health implications. Long-term exposure to poor air quality causes pulmonary and cardiovascular diseases. Several studies have also found that deteriorating air quality also causes substantial economic losses. Thus, techniques that can forecast air quality with higher accuracy may help reduce health and economic consequences. Prior research has utilized state-of-the-art artificial neural network and recurrent neural network models for forecasting air quality. However, a comprehensive investigation of different architectures of recurrent neural network, especially LSTMs and ensemble techniques, has been less explored. Also, there have been less explorations of long-term air quality forecasts via these methods exists. This research proposes the development and calibration of recurrent neural network models and their ensemble, which can forecast air quality in terms of PM2.5 concentration 6 hours ahead in time. For forecasting air quality, a vanilla-LSTM, a stack-LSTM, a bidirectional-LSTM, a CNN-LSTM, and an ensemble of individual LSTM models were trained on the UCI Machine Learning Beijing dataset. Data were split into two parts, where 80% of data were used for training the models, while the remaining 20% were used for validating the models. For comparative analysis, four regression losses were calculated, namely root mean squared error, mean absolute percentage error, mean absolute error and Pearson’s correlation coefficient. Results revealed that among all models, the ensemble model performed the best in predicting the PM2.5 concentrations. Furthermore, the ensemble model outperformed other models reported in literature by a long margin. Among the individual models, the bidirectional-LSTM performed the best. We highlight the implications of this research on long-term forecasting of air quality via recurrent and ensemble techniques.

scholarly journals Absorption of aerosols above clouds from POLDER/PARASOL measurements and estimation of their Direct Radiative Effect

2014 ◽  
Vol 14 (18) ◽  
pp. 25533-25579 ◽  
Author(s):  
F. Peers ◽  
F. Waquet ◽  
C. Cornet ◽  
P. Dubuisson ◽  
F. Ducos ◽  
...  
Keyword(s):  
Optical Thickness ◽  
Single Scattering ◽  
Saharan Dust ◽  
Aerosol Layer ◽  
Radiative Effect ◽  
East Atlantic ◽  
Aerosol Absorption ◽  
Cloud Optical Thickness ◽  
The Mean ◽  
Aerosol Properties

Abstract. The albedo of clouds and the aerosol absorption are key parameters to evaluate the direct radiative effect of an aerosol layer above clouds. While most of the retrievals of above clouds aerosol characteristics rely on assumptions on the aerosol properties, this study offers a new method to evaluate aerosol and cloud optical properties simultaneously (i.e. aerosol and cloud optical thickness, aerosol single scattering albedo and angström exponent). It is based on multi-angle total and polarized radiances both provided by the A-train satellite instrument POLDER – Polarization and Directionality of Earth Reflectances. The sensitivities brought by each kind of measurements are used in a complementary way. Polarization mostly translates scattering processes and is thus used to estimate the scattering aerosol optical thickness and the aerosol size. On the other hand, total radiances, together with the scattering properties of aerosols, are used to evaluate the absorption optical thickness of aerosols and the cloud optical thickness. In addition, a procedure has been developed to process the shortwave direct radiative effect of aerosols above clouds based on exact modeling. Besides the three case studies (i.e. biomass burning aerosols from Africa and Siberia and Saharan dust), both algorithms have been applied on the South East Atlantic Ocean and results have been averaged through August 2006. The mean direct radiative effect is found to be 33.5 W m−2. Finally, the effect of the heterogeneity of clouds has been investigated and reveals that it affects mostly the retrieval of the cloud optical thickness and not much the aerosols properties. The homogenous cloud assumption used in both the properties retrieval and the DRE processing leads to a slight underestimation of the DRE.

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