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

2017 ◽  
Author(s):  
Julien Chimot ◽  
J. Pepijn Veefkind ◽  
Tim Vlemmix ◽  
Pieternel F. Levelt
Keyword(s):  
Air Quality ◽  
Weighted Average ◽  
Saharan Dust ◽  
Cloud Formation ◽  
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 aerosol radiation effect 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 east 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, and of a Saharan dust outbreak over sea from OMI visible measurements. Complementary detailed analyses show that the assumed aerosol properties in the modeling 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 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 Validation, comparison, and integration of GOCI, AHI, MODIS, MISR, and VIIRS aerosol optical depth over East Asia during the 2016 KORUS-AQ campaign

2019 ◽  
Vol 12 (8) ◽  
pp. 4619-4641 ◽  
Author(s):  
Myungje Choi ◽  
Hyunkwang Lim ◽  
Jhoon Kim ◽  
Seoyoung Lee ◽  
Thomas F. Eck ◽  
...  
Keyword(s):  
Air Quality ◽  
East Asia ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Temporal Resolution ◽  
High Accuracy ◽  
The Yellow Sea ◽  
High Temporal Resolution ◽  
Earth Orbit ◽  
Satellite Sensors

Abstract. Recently launched multichannel geostationary Earth orbit (GEO) satellite sensors, such as the Geostationary Ocean Color Imager (GOCI) and the Advanced Himawari Imager (AHI), provide aerosol products over East Asia with high accuracy, which enables the monitoring of rapid diurnal variations and the transboundary transport of aerosols. Most aerosol studies to date have used low Earth orbit (LEO) satellite sensors, such as the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Multi-angle Imaging Spectroradiometer (MISR), with a maximum of one or two overpass daylight times per day from midlatitudes to low latitudes. Thus, the demand for new GEO observations with high temporal resolution and improved accuracy has been significant. In this study the latest versions of aerosol optical depth (AOD) products from three LEO sensors – MODIS (Dark Target, Deep Blue, and MAIAC), MISR, and the Visible/Infrared Imager Radiometer Suite (VIIRS), along with two GEO sensors (GOCI and AHI), are validated, compared, and integrated for a period during the Korea–United States Air Quality Study (KORUS-AQ) field campaign from 1 May to 12 June 2016 over East Asia. The AOD products analyzed here generally have high accuracy with high R (0.84–0.93) and low RMSE (0.12–0.17), but their error characteristics differ according to the use of several different surface-reflectance estimation methods. High-accuracy near-real-time GOCI and AHI measurements facilitate the detection of rapid AOD changes, such as smoke aerosol transport from Russia to Japan on 18–21 May 2016, heavy pollution transport from China to the Korean Peninsula on 25 May 2016, and local emission transport from the Seoul Metropolitan Area to the Yellow Sea in South Korea on 5 June 2016. These high-temporal-resolution GEO measurements result in more representative daily AOD values and make a greater contribution to a combined daily AOD product assembled by median value selection with a 0.5∘×0.5∘ grid resolution. The combined AOD is spatially continuous and has a greater number of pixels with high accuracy (fraction within expected error range of 0.61) than individual products. This study characterizes aerosol measurements from LEO and GEO satellites currently in operation over East Asia, and the results presented here can be used to evaluate satellite measurement bias and air quality models.

scholarly journals First validation of GOME-2/MetOp absorbing aerosol height using EARLINET lidar observations

2021 ◽  
Vol 21 (4) ◽  
pp. 3193-3213
Author(s):  
Konstantinos Michailidis ◽  
Maria-Elissavet Koukouli ◽  
Nikolaos Siomos ◽  
Dimitris Balis ◽  
Olaf Tuinder ◽  
...  
Keyword(s):  
Saharan Dust ◽  
Aerosol Layer ◽  
Pixel Size ◽  
Geometrical Features ◽  
Depth Analysis ◽  
Satellite Sensors ◽  
The Mean ◽  
The Difference ◽  
Ground Based Lidar ◽  
Lidar Observations

Abstract. The aim of this study is to investigate the potential of the Global Ozone Monitoring Experiment-2 (GOME-2) instruments, aboard the Meteorological Operational (MetOp)-A, MetOp-B and MetOp-C satellite programme platforms, to deliver accurate geometrical features of lofted aerosol layers. For this purpose, we use archived ground-based lidar data from stations available from the European Aerosol Research Lidar Network (EARLINET) database. The data are post-processed using the wavelet covariance transform (WCT) method in order to extract geometrical features such as the planetary boundary layer (PBL) height and the cloud boundaries. To obtain a significant number of collocated and coincident GOME-2 – EARLINET cases for the period between January 2007 and September 2019, 13 lidar stations, distributed over different European latitudes, contributed to this validation. For the 172 carefully screened collocations, the mean bias was found to be −0.18 ± 1.68 km, with a near-Gaussian distribution. On a station basis, and with a couple of exceptions where very few collocations were found, their mean biases fall in the ± 1 km range with an associated standard deviation between 0.5 and 1.5 km. Considering the differences, mainly due to the temporal collocation and the difference, between the satellite pixel size and the point view of the ground-based observations, these results can be quite promising and demonstrate that stable and extended aerosol layers as captured by the satellite sensors are verified by the ground-based data. We further present an in-depth analysis of a strong and long-lasting Saharan dust intrusion over the Iberian Peninsula. We show that, for this well-developed and spatially well-spread aerosol layer, most GOME-2 retrievals fall within 1 km of the exact temporally collocated lidar observation for the entire range of 0 to 150 km radii. This finding further testifies for the capabilities of the MetOp-borne instruments to sense the atmospheric aerosol layer heights.

scholarly journals Volcanic SO<sub>2</sub> effective layer height retrieval for the Ozone Monitoring Instrument (OMI) using a machine-learning approach

2021 ◽  
Vol 14 (5) ◽  
pp. 3673-3691
Author(s):  
Nikita M. Fedkin ◽  
Can Li ◽  
Nickolay A. Krotkov ◽  
Pascal Hedelt ◽  
Diego G. Loyola ◽  
...  
Keyword(s):  
Volcanic Eruptions ◽  
Volcanic Plume ◽  
Aerosol Layer ◽  
Ozone Monitoring Instrument ◽  
Layer Height ◽  
Monitoring Instrument ◽  
Satellite Sensors ◽  
Ozone Monitoring ◽  
Computationally Intensive ◽  
Learning Machine

Abstract. Information about the height and loading of sulfur dioxide (SO2) plumes from volcanic eruptions is crucial for aviation safety and for assessing the effect of sulfate aerosols on climate. While SO2 layer height has been successfully retrieved from backscattered Earthshine ultraviolet (UV) radiances measured by the Ozone Monitoring Instrument (OMI), previously demonstrated techniques are computationally intensive and not suitable for near-real-time applications. In this study, we introduce a new OMI algorithm for fast retrievals of effective volcanic SO2 layer height. We apply the Full-Physics Inverse Learning Machine (FP_ILM) algorithm to OMI radiances in the spectral range of 310–330 nm. This approach consists of a training phase that utilizes extensive radiative transfer calculations to generate a large dataset of synthetic radiance spectra for geophysical parameters representing the OMI measurement conditions. The principal components of the spectra from this dataset in addition to a few geophysical parameters are used to train a neural network to solve the inverse problem and predict the SO2 layer height. This is followed by applying the trained inverse model to real OMI measurements to retrieve the effective SO2 plume heights. The algorithm has been tested on several major eruptions during the OMI data record. The results for the 2008 Kasatochi, 2014 Kelud, 2015 Calbuco, and 2019 Raikoke eruption cases are presented here and compared with volcanic plume heights estimated with other satellite sensors. For the most part, OMI-retrieved effective SO2 heights agree well with the lidar measurements of aerosol layer height from Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) and thermal infrared retrievals of SO2 heights from the infrared atmospheric sounding interferometer (IASI). The errors in OMI-retrieved SO2 heights are estimated to be 1–1.5 km for plumes with relatively large SO2 signals (>40 DU). The algorithm is very fast and retrieves plume height in less than 10 min for an entire OMI orbit.

scholarly journals Comparison of dust layer heights from active and passive satellite sensors

2017 ◽  
Author(s):  
Arve Kylling ◽  
Sophie Vandenbussche ◽  
Virginie Capelle ◽  
Juan Cuesta ◽  
Lars Klüser ◽  
...  
Keyword(s):  
Geometric Mean ◽  
European Space Agency ◽  
General Tendency ◽  
Aerosol Layer ◽  
Dust Layer ◽  
Layer Height ◽  
Space Agency ◽  
Satellite Sensors ◽  
Geometrical Mean ◽  
The Impact

Abstract. Aerosol layer height is an essential parameter to understand 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 by four different algorithms (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 to be 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 to geometric mean height there is a shift by −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 1.4 km. When looking at different conditions (day, night, land, ocean) there are is more detail in variabilities (e.g. all algorithms overestimate more at night than at day).

scholarly journals The 2018 fire season in North America as seen by TROPOMI: aerosol layer height intercomparisons and evaluation of model-derived plume heights

2020 ◽  
Vol 13 (3) ◽  
pp. 1427-1445 ◽  
Author(s):  
Debora Griffin ◽  
Christopher Sioris ◽  
Jack Chen ◽  
Nolan Dickson ◽  
Andrew Kovachik ◽  
...  
Keyword(s):  
Air Quality ◽  
North America ◽  
Measurement Techniques ◽  
Fire Season ◽  
Orthogonal Polarization ◽  
Potential Game ◽  
Aerosol Layer ◽  
Plume Height ◽  
Layer Height ◽  
Fire Emissions

Abstract. Before the launch of the TROPOspheric Monitoring Instrument (TROPOMI), only two other satellite instruments were able to observe aerosol plume heights globally, the Multi-angle Imaging SpectroRadiometer (MISR) and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP). The TROPOMI aerosol layer height is a potential game changer, since it has daily global coverage, and the aerosol layer height retrieval is available in near real time. The aerosol layer height can be useful for aviation and air quality alerts, as well as for improving air quality forecasting related to wildfires. Here, TROPOMI's aerosol layer height product is evaluated with MISR and CALIOP observations for wildfire plumes in North America for the 2018 fire season (June to August). Further, observing system simulation experiments were performed to interpret the fundamental differences between the different products. The results show that MISR and TROPOMI are, in theory, very close for aerosol profiles with single plumes. For more complex profiles with multiple plumes, however, different plume heights are retrieved; the MISR plume height represents the top layer, and the plume height retrieved with TROPOMI tends to have an average altitude of several plume layers. The comparison between TROPOMI and MISR plume heights shows that, on average, the TROPOMI aerosol layer heights are lower, by approximately 600 m, compared to MISR, which is likely due to the different measurement techniques. From the comparison to CALIOP, our results show that the TROPOMI aerosol layer height is more accurate over dark surfaces, for thicker plumes, and plumes between approximately 1 and 4.5 km. MISR and TROPOMI are further used to evaluate the plume height of Environment and Climate Change Canada's operational forecasting system FireWork with fire plume injection height estimates from the Canadian Forest Fire Emissions Prediction System (CFFEPS). The modelled plume heights are similar compared to the satellite observations but tend to be slightly higher with average differences of 270–580 and 60–320 m compared to TROPOMI and MISR, respectively.

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

2018 ◽  
Vol 11 (5) ◽  
pp. 2911-2936 ◽  
Author(s):  
Arve Kylling ◽  
Sophie Vandenbussche ◽  
Virginie Capelle ◽  
Juan Cuesta ◽  
Lars Klüser ◽  
...  
Keyword(s):  
Geometric Mean ◽  
European Space Agency ◽  
General Tendency ◽  
Aerosol Layer ◽  
Dust Layer ◽  
Layer Height ◽  
Space Agency ◽  
Satellite Sensors ◽  
Geometrical Mean ◽  
The Impact

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).

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 The 2018 fire season in North America as seen by TROPOMI: aerosol layer height validation and evaluation of model-derived plume heights

2019 ◽  
Author(s):  
Debora Griffin ◽  
Christopher Sioris ◽  
Jack Chen ◽  
Nolan Dickson ◽  
Andrew Kovachik ◽  
...  
Keyword(s):  
Air Quality ◽  
North America ◽  
Measurement Techniques ◽  
Fire Season ◽  
Potential Game ◽  
Aerosol Layer ◽  
Fire Plume ◽  
Plume Height ◽  
Layer Height ◽  
Fire Emissions

Abstract. Before the launch of TROPOMI, only two other satellite instruments were able to observe aerosol plume heights globally, MISR and CALIOP. The TROPOMI aerosol layer height is a potential game changer, since it has daily global coverage and the aerosol layer height retrieval is available in near-real time. The aerosol layer height can be useful for aviation and air quality alerts, as well as for improving air quality forecasting related to wildfires. Here, TROPOMI's aerosol layer height product is evaluated with MISR and CALIOP observations for wildfire plumes in North America for the 2018 fire season (June to August). Further, observing system simulation experiments were performed to interpret the fundamental differences between the different products. The results show that MISR and TROPOMI are, in theory, very close for aerosol profiles with single plumes. For more complex profiles with multiple plumes, however, different plume heights are retrieved: the MISR plume height represents the top layer, and the plume height retrieved with TROPOMI tends to be an average altitude of several plume layers. The comparison between TROPOMI and MISR plume heights shows, that on average, the TROPOMI aerosol layer heights are lower, by approximately 600 m, compared to MISR which is likely due to the different measurement techniques. From the comparison to CALIOP, our results show that the TROPOMI aerosol layer height is more accurate for thicker plumes and plumes below approximately 4.5 km. MISR and TROPOMI are further used to evaluate the plume height of Environment and Climate Change Canada's operational forecasting system FireWork with fire plume injection height estimates from the Canadian Forest Fire Emissions Prediction System (CFFEPS). The modelled plume heights are similar compared to the satellite observations, but tend to be slightly higher with average differences of 270–580 m and 60–320 m compared to TROPOMI and MISR, respectively.

Sign in / Sign up

Export Citation Format

Share Document