scholarly journals Determination of aerosol properties from satellite observations of the Ring effect

2010 ◽  
Vol 3 (4) ◽  
pp. 3535-3599 ◽  
Author(s):  
T. Wagner ◽  
S. Beirle ◽  
T. Deutschmann ◽  
M. P. de Vries
Keyword(s):  
Radiative Transfer ◽  
Optical Depth ◽  
Satellite Observations ◽  
Transfer Model ◽  
Layer Height ◽  
Polarisation Sensitivity ◽  
The Impact ◽  
Aerosol Properties ◽  
Ring Effect

Abstract. In this study we explore the potential of satellite observations of the Ring effect (at various wavelengths) for the retrieval of atmospheric aerosol properties. Compared to clouds, aerosols have a rather weak influence on the Ring effect, thus the requirements on the accuracy of the measurements and the radiative transfer simulations are high. In this study, we show that for moderate and high aerosol optical depth (AOD), Ring effect observations are sensitive enough to yield information not only on the AOD, but also on the absorbing properties of aerosols and the aerosol layer height. The latter two quantities are especially important for the determination of the radiative effects of aerosols. Our investigations are based on observations by the satellite instrument SCIAMACHY on ENVISAT (2004–2008) and on model simulations using the Monte-Carlo radiative transfer model McArtim. In addition to the Ring effect we investigate the impact of aerosols on the absorptions of the oxygen molecule (O2) and dimer (O4) as well as the radiance. In general good consistency between measured and simulated quantities is found. In some cases also systematic differences occurred, which are probably mainly related to the strong polarisation sensitivity of the SCIAMACHY instrument. Our study indicates that Ring effect observations have important advantages for aerosol retrievals: in contrast to O2 and O4 absorptions they are only weakly affected by the surface albedo; they can be analysed with high accuracy in various wavelength ranges; and depending on the wavelength range, they show different sensitivities on aerosol properties like single scattering albedo, optical depth or layer height. The results of this study are of particular interest for future satellite instruments with reduced polarisation sensitivity and smaller ground pixels, capable of measuring the Ring effect with higher accuracy.

scholarly journals A sensitivity analysis of Ring effect to aerosol properties and comparison to satellite observations

2010 ◽  
Vol 3 (6) ◽  
pp. 1723-1751 ◽  
Author(s):  
T. Wagner ◽  
S. Beirle ◽  
T. Deutschmann ◽  
M. Penning de Vries
Keyword(s):  
Radiative Transfer ◽  
Optical Depth ◽  
Satellite Observations ◽  
Transfer Model ◽  
Aerosol Layer ◽  
Layer Height ◽  
Polarisation Sensitivity ◽  
The Impact ◽  
Aerosol Properties ◽  
Ring Effect

Abstract. In this study we explore the sensitivity of satellite observations of the Ring effect (at various wavelengths) to atmospheric aerosol properties. Compared to clouds, aerosols have a rather weak influence on the Ring effect, thus the requirements on the accuracy of the measurements and the radiative transfer simulations are high. In this study, we show that for moderate and high aerosol optical depth (AOD), Ring effect observations are sensitive enough to yield information not only on the AOD, but also on the absorbing properties of aerosols and the aerosol layer height. The latter two quantities are especially important for the determination of the radiative effects of aerosols. Our investigations are based on observations by the satellite instrument SCIAMACHY on ENVISAT (2004–2008) and on model simulations using the Monte-Carlo radiative transfer model McArtim. In addition to the Ring effect we investigate the impact of aerosols on the absorptions of the oxygen molecule (O2) and dimer (O4) as well as the radiance. In general good consistency between measured and simulated quantities is found. In some cases also systematic differences occurred, which are probably mainly related to the strong polarisation sensitivity of the SCIAMACHY instrument. Our study indicates that Ring effect observations have important advantages for aerosol retrievals: they can be analysed with high accuracy in various wavelength ranges; and depending on the wavelength range, they show different sensitivities on aerosol properties like single scattering albedo, optical depth or layer height. The results of this study are of particular interest for future aerosol inversion algorithms for satellite instruments with reduced polarisation sensitivity and smaller ground pixels, capable of measuring the Ring effect with higher accuracy.

scholarly journals Performance of the Line-By-Line Radiative Transfer Model (LBLRTM) for temperature, water vapor, and trace gas retrievals: recent updates evaluated with IASI case studies

2013 ◽  
Vol 13 (14) ◽  
pp. 6687-6711 ◽  
Author(s):  
M. J. Alvarado ◽  
V. H. Payne ◽  
E. J. Mlawer ◽  
G. Uymin ◽  
M. W. Shephard ◽  
...  
Keyword(s):  
Water Vapor ◽  
Radiative Transfer ◽  
Fixed Ratio ◽  
Satellite Observations ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Temperature Profiles ◽  
A Posteriori ◽  
The Impact ◽  
Temperature Water

Abstract. Modern data assimilation algorithms depend on accurate infrared spectroscopy in order to make use of the information related to temperature, water vapor (H2O), and other trace gases provided by satellite observations. Reducing the uncertainties in our knowledge of spectroscopic line parameters and continuum absorption is thus important to improve the application of satellite data to weather forecasting. Here we present the results of a rigorous validation of spectroscopic updates to an advanced radiative transfer model, the Line-By-Line Radiative Transfer Model (LBLRTM), against a global dataset of 120 near-nadir, over-ocean, nighttime spectra from the Infrared Atmospheric Sounding Interferometer (IASI). We compare calculations from the latest version of LBLRTM (v12.1) to those from a previous version (v9.4+) to determine the impact of spectroscopic updates to the model on spectral residuals as well as retrieved temperature and H2O profiles. We show that the spectroscopy in the CO2 ν2 and ν3 bands is significantly improved in LBLRTM v12.1 relative to v9.4+, and that these spectroscopic updates lead to mean changes of ~0.5 K in the retrieved vertical temperature profiles between the surface and 10 hPa, with the sign of the change and the variability among cases depending on altitude. We also find that temperature retrievals using each of these two CO2 bands are remarkably consistent in LBLRTM v12.1, potentially allowing these bands to be used to retrieve atmospheric temperature simultaneously. The updated H2O spectroscopy in LBLRTM v12.1 substantially improves the a posteriori residuals in the P-branch of the H2O ν2 band, while the improvements in the R-branch are more modest. The H2O amounts retrieved with LBLRTM v12.1 are on average 14% lower between 100 and 200 hPa, 42% higher near 562 hPa, and 31% higher near the surface compared to the amounts retrieved with v9.4+ due to a combination of the different retrieved temperature profiles and the updated H2O spectroscopy. We also find that the use of a fixed ratio of HDO to H2O in LBLRTM may be responsible for a significant fraction of the remaining bias in the P-branch relative to the R-branch of the H2O ν2 band. There were no changes to O3 spectroscopy between the two model versions, and so both versions give positive a posteriori residuals of ~ 0.3 K in the R-branch of the O3 ν3 band. While the updates to the H2O self-continuum employed by LBLRTM v12.1 have clearly improved the match with observations near the CO2 ν3 band head, we find that these updates have significantly degraded the match with observations in the fundamental band of CO. Finally, significant systematic a posteriori residuals remain in the ν4 band of CH4, but the magnitude of the positive bias in the retrieved mixing ratios is reduced in LBLRTM v12.1, suggesting that the updated spectroscopy could improve retrievals of CH4 from satellite observations.

scholarly journals Performance of the line-by-line radiative transfer model (LBLRTM) for temperature, water vapor, and trace gas retrievals: recent updates evaluated with IASI case studies

2013 ◽  
Vol 13 (1) ◽  
pp. 79-144 ◽  
Author(s):  
M. J. Alvarado ◽  
V. H. Payne ◽  
E. J. Mlawer ◽  
G. Uymin ◽  
M. W. Shephard ◽  
...  
Keyword(s):  
Water Vapor ◽  
Radiative Transfer ◽  
Weather Forecasting ◽  
Fixed Ratio ◽  
Satellite Observations ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Temperature Profiles ◽  
The Impact ◽  
Temperature Water

Abstract. Modern data assimilation algorithms depend on accurate infrared spectroscopy in order to make use of the information related to temperature, water vapor (H2O), and other trace gases provided by satellite observations. Reducing the uncertainties in our knowledge of spectroscopic line parameters and continuum absorption is thus critical to improving the application of satellite data to weather forecasting. Here we present the results of a rigorous validation of spectroscopic updates to an advanced radiative transfer model, the Line-By-Line Radiative Transfer Model (LBLRTM), against a global dataset of 120 near-nadir, over-ocean, nighttime spectra from the Infrared Atmospheric Sounding Instrument (IASI). We compare calculations from the latest version of LBLRTM (v12.1) to those from a previous version (v9.4+) to determine the impact of spectroscopic updates to the model on spectral residuals as well as retrieved temperature and H2O profiles. We show that the spectroscopy in the CO2 ν2 and ν3 bands is significantly improved in LBLRTM v12.1 relative to v9.4+, and that these spectroscopic updates lead to changes of ~0.5 K in the retrieved vertical temperature profiles below 10 hPa, with the sign of the change and the variability among cases depending on altitude. We also find that temperature retrievals using each of these two CO2 bands are remarkably consistent in LBLRTM v12.1, potentially allowing these bands to be used to retrieve atmospheric temperature simultaneously. The updated H2O spectroscopy in LBLRTM v12.1 substantially improves the residuals in the P-branch of the H2O ν2 band, while the improvements in the R-branch are more modest. The H2O amounts retrieved with LBLRTM v12.1 are on average 14% lower between 100 and 200 hPa, 42% higher near 562 hPa, and 31% higher near the surface compared to the amounts retrieved with v9.4+ due to a combination of the different retrieved temperature profiles and the updated H2O spectroscopy. We also find that the use of a fixed ratio of HDO to H2O in LBLRTM may be responsible for a significant fraction of the remaining bias in the P-branch of the H2O ν2 band. There were no changes to O3 spectroscopy between the two model versions, and so both versions gives positive residuals of ~0.3 K in the R-branch of the O3 ν3 band. While the updates to the H2O self continuum employed by LBLRTM v12.1 have clearly improved the match with observations near the CO2 ν3 bandhead, we find that these updates have significantly degraded the match with observations in the fundamental band of CO. Finally, significant systematic residuals remain in the ν4 band of CH4, but the magnitude of the positive bias in the retrieved mixing ratios is reduced in LBLRTM v12.1, suggesting that the updated spectroscopy could improve retrievals of CH4 from satellite observations.

scholarly journals The role of aerosol layer height in quantifying aerosol absorption from ultraviolet satellite observations

2019 ◽  
Vol 12 (12) ◽  
pp. 6319-6340
Author(s):  
Jiyunting Sun ◽  
Pepijn Veefkind ◽  
Swadhin Nanda ◽  
Peter van Velthoven ◽  
Pieternel Levelt
Keyword(s):  
Radiative Transfer ◽  
Kernel Functions ◽  
Satellite Observations ◽  
Support Vector ◽  
Transfer Model ◽  
Aerosol Layer ◽  
Layer Height ◽  
Aerosol Absorption ◽  
Near Ultraviolet

Abstract. The purpose of this study is to demonstrate the role of aerosol layer height (ALH) in quantifying the single scattering albedo (SSA) from ultraviolet satellite observations for biomass burning aerosols. In the first experiment, we retrieve SSA by minimizing the near-ultraviolet (near-UV) absorbing aerosol index (UVAI) difference between observed values and those simulated by a radiative transfer model. With the recently released S-5P TROPOMI ALH product constraining forward simulations, a significant gap in the retrieved SSA (0.25) is found between radiative transfer simulations with spectral flat aerosols and those with strong spectrally dependent aerosols, implying that inappropriate assumptions regarding aerosol absorption spectral dependence may cause severe misinterpretations of the aerosol absorption. In the second part of this paper, we propose an alternative method to retrieve SSA based on a long-term record of co-located satellite and ground-based measurements using the support vector regression (SVR) approach. This empirical method is free from the uncertainties due to the imperfection of a priori assumptions on aerosol microphysics seen in the first experiment. We present the potential capabilities of SVR using several fire events that have occurred in recent years. For all cases, the difference between SVR-retrieved SSA and AERONET are generally within ±0.05, and over half of the samples are within ±0.03. The results are encouraging, although in the current phase the model tends to overestimate the SSA for relatively absorbing cases and fails to predict SSA for some extreme situations. The spatial contrast in SSA retrieved by radiative transfer simulations is significantly higher than that retrieved by SVR, and the latter better agrees with SSA from MERRA-2 reanalysis. In the future, more sophisticated feature selection procedures and kernel functions should be taken into consideration to improve the SVR model accuracy. Moreover, the high-resolution TROPOMI UVAI and co-located ALH products will guide us to more reliable training data sets and more powerful algorithms to quantify aerosol absorption from UVAI records.

scholarly journals A model sensitivity study of the impact of clouds on satellite detection and retrieval of volcanic ash

2015 ◽  
Vol 8 (5) ◽  
pp. 1935-1949 ◽  
Author(s):  
A. Kylling ◽  
N. Kristiansen ◽  
A. Stohl ◽  
R. Buras-Schnell ◽  
C. Emde ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Liquid Water ◽  
Volcanic Ash ◽  
Spectral Band ◽  
Sensitivity Study ◽  
Transfer Model ◽  
Mass Loading ◽  
Ice Clouds ◽  
Medium Range Weather Forecast ◽  
The Impact

Abstract. Volcanic ash is commonly observed by infrared detectors on board Earth-orbiting satellites. In the presence of ice and/or liquid-water clouds, the detected volcanic ash signature may be altered. In this paper the sensitivity of detection and retrieval of volcanic ash to the presence of ice and liquid-water clouds was quantified by simulating synthetic equivalents to satellite infrared images with a 3-D radiative transfer model. The sensitivity study was made for the two recent eruptions of Eyjafjallajökull (2010) and Grímsvötn (2011) using realistic water and ice clouds and volcanic ash clouds. The water and ice clouds were taken from European Centre for Medium-Range Weather Forecast (ECMWF) analysis data and the volcanic ash cloud fields from simulations by the Lagrangian particle dispersion model FLEXPART. The radiative transfer simulations were made both with and without ice and liquid-water clouds for the geometry and channels of the Spinning Enhanced Visible and Infrared Imager (SEVIRI). The synthetic SEVIRI images were used as input to standard reverse absorption ash detection and retrieval methods. Ice and liquid-water clouds were on average found to reduce the number of detected ash-affected pixels by 6–12%. However, the effect was highly variable and for individual scenes up to 40% of pixels with mass loading >0.2 g m−2 could not be detected due to the presence of water and ice clouds. For coincident pixels, i.e. pixels where ash was both present in the FLEXPART (hereafter referred to as "Flexpart") simulation and detected by the algorithm, the presence of clouds overall increased the retrieved mean mass loading for the Eyjafjallajökull (2010) eruption by about 13%, while for the Grímsvötn (2011) eruption ash-mass loadings the effect was a 4% decrease of the retrieved ash-mass loading. However, larger differences were seen between scenes (standard deviations of ±30 and ±20% for Eyjafjallajökull and Grímsvötn, respectively) and even larger ones within scenes. The impact of ice and liquid-water clouds on the detection and retrieval of volcanic ash, implies that to fully appreciate the location and amount of ash, hyperspectral and spectral band measurements by satellite instruments should be combined with ash dispersion modelling.

Volcanic ash detection and retrievals using SLSTR. Test case: 2019 Raikoke  eruption

2021 ◽  
Author(s):  
Ilaria Petracca ◽  
Davide De Santis ◽  
Stefano Corradini ◽  
Lorenzo Guerrieri ◽  
Matteo Picchiani ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Volcanic Ash ◽  
Thermal Infrared ◽  
Integrated Approach ◽  
Effective Radius ◽  
Volcanic Plume ◽  
Transfer Model ◽  
Volcanic Cloud

<p>When an eruption event occurs it is necessary to accurately and rapidly determine the position and evolution during time of the volcanic cloud and its parameters (such as Aerosol Optical Depth-AOD, effective radius-Re and mass-Ma of the ash particles), in order to ensure the aviation security and the prompt management of the emergencies.</p><p>Here we present different procedures for volcanic ash cloud detection and retrieval using S3 SLSTR (Sentinel-3 Sea and Land Surface Temperature Radiometer) data collected the 22 June at 00:07 UTC by the Sentinel-3A platform during the Raikoke (Kuril Islands) 2019 eruption.</p><p>The volcanic ash detection is realized by applying an innovative machine learning based algorithm, which uses a MultiLayer Perceptron Neural Network (NN) to classify a SLSTR image in eight different surfaces/objects, distinguishing volcanic and weather clouds, and the underlying surfaces. The results obtained with the NN procedure have been compared with two consolidated approaches based on an RGB channels combination in the visible (VIS) spectral range and the Brightness Temperature Difference (BTD) procedure that exploits the thermal infrared (TIR) channels centred at 11 and 12 microns (S8 and S9 SLSTR channels respectively). The ash volcanic cloud is correctly identified by all the models and the results indicate a good agreement between the NN classification approach, the VIS-RGB and BTD procedures.</p><p>The ash retrieval parameters (AOD, Re and Ma) are obtained by applying three different algorithms, all exploiting the volcanic cloud “mask” obtained from the NN detection approach. The first method is the Look Up Table (LUT<sub>p</sub>) procedure, which uses a Radiative Transfer Model (RTM) to simulate the Top Of Atmosphere (TOA) radiances in the SLSTR thermal infrared channels (S8, S9), by varying the aerosol optical depth and the effective radius. The second algorithm is the Volcanic Plume Retrieval (VPR), based on a linearization of the radiative transfer equation capable to retrieve, from multispectral satellite images, the abovementioned parameters. The third approach is a NN model, which is built on a training set composed by the inputs-outputs pairs TOA radiances vs. ash parameters. The results of the three retrieval methods have been compared, considering as reference the LUT<sub>p</sub> procedure, since that it is the most consolidated approach. The comparison shown promising agreement between the different methods, leading to the development of an integrated approach for the monitoring of volcanic ash clouds using SLSTR.</p><p>The results presented in this work have been obtained in the sphere of the VISTA (Volcanic monItoring using SenTinel sensors by an integrated Approach) project, funded by ESA and developed within the EO Science for Society framework [https://eo4society.esa.int/projects/vista/].</p>

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