Impact of 3D cloud structures on tropospheric NO2 column measurements from UV-VIS sounders

2020 ◽  
Author(s):  
Huan Yu ◽  
Arve Kylling ◽  
Claudia Emde ◽  
Bernhard Mayer ◽  
Kerstin Stebel ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Mitigation Strategies ◽  
Trace Gas ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Vertical Column ◽  
Ice Clouds ◽  
Cloud Data ◽  
One Step ◽  
The Impact

<p>Operational retrievals of tropospheric trace gases from space-borne spectrometers are made using 1D radiative transfer models. To minimize cloud effects generally only partially cloudy pixels are analysed using simplified cloud contamination treatments based on radiometric cloud fraction estimates and photon path length corrections based on oxygen collision pair (O<sub>2</sub>-O<sub>2</sub>) or O<sub>2</sub>A-absorption band measurements. In reality, however, the impact of clouds can be much more complex, involving scattering of clouds in neighbouring pixels and cloud shadow effects. Therefore, to go one step further, other correction methods may be envisaged that use sub-pixel cloud information from co-located imagers. Such methods require an understanding of the impact of clouds on the real 3D radiative transfer. We quantify this impact using the MYSTIC 3D radiative transfer model. The generation of realistic 3D input cloud fields, needed by MYSTIC (or any other 3D radiative transfer model), is non-trivial. We use cloud data generated by the ICOsahedral Non-hydrostatic (ICON) atmosphere model for a region including Germany, the Netherlands and parts of other surrounding countries. The model simulates realistic liquid and ice clouds with a horizontal spatial resolution of 156 m and it has been validated against ground-based and satellite-based observational data.</p><p>As a trace gas example, we study NO<sub>2</sub>, a key tropospheric trace gas measured by the atmospheric Sentinels. The MYSTIC 3D model simulates visible spectra, which are ingested in standard DOAS retrieval algorithms to retrieve the NO<sub>2</sub> column amount. Spectra are simulated for a number of realistic cloud scenarios, snow free surface albedos, and solar and satellite geometries typical of low-earth and geostationary orbits. The retrieved NO<sub>2</sub> vertical column densities (VCD) are compared with the true values to identify conditions where 3D cloud effects lead to significant biases on the NO<sub>2</sub> VCDs. A variety of possible mitigation strategies for such pixels are then explored.</p>

Impact of 3D cloud structures on tropospheric NO2 column measurements from UV-VIS sounders

2021 ◽  
Author(s):  
Huan Yu ◽  
Arve Kylling ◽  
Claudia Emde ◽  
Bernhard Mayer ◽  
Michel Van Roozendael ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Synthetic Data ◽  
Sensitivity Study ◽  
Trace Gas ◽  
Radiative Transfer Model ◽  
Retrieval Algorithm ◽  
Transfer Model ◽  
Boundary Layer Clouds ◽  
Cloud Parameters ◽  
The Impact

<p>Operational retrievals of tropospheric trace gases from space-borne spectrometers are made using 1D radiative transfer models. To minimize cloud effects generally only partially cloudy pixels are analysed using simplified cloud contamination treatments based on radiometric cloud fraction estimates and photon path length corrections based on oxygen collision pair (O2-O2) or O2A-absorption band measurements. In reality, however, the impact of clouds can be much more complex, involving unresolved sub-pixel clouds, scattering of clouds in neighbouring pixels, and cloud shadow effects, such that 3D radiation scattering from unresolved boundary layer clouds may give significant biases in the trace gas retrievals. In order to quantify this impact, we use the MYSTIC 3D radiative transfer model to generate synthetic data. The realistic 3D cloud fields, needed for MYSTIC input, are generated by the ICOsahedral Non-hydrostatic (ICON) atmosphere model for a region including Germany, the Netherlands and parts of other surrounding countries. The retrieval algorithm is applied to the synthetic data and comparison to the known input trace gas concentrations yields the retrieval error due to 3D cloud effects. <br>In this study, we study NO2, which is a key tropospheric trace gas measured by TROPOMI and the future atmospheric Sentinels (S4 and S5). The work starts with a sensitivity study for the simulations with a simple 2D box cloud. The influence of cloud parameters (e.g., cloud top height, cloud optical thickness), observation geometry, and spatial resolution are studied, and the most significant dependences of retrieval biases are identified and investigated. Several approaches to correct the NO2 retrieval in the cloud shadow are explored and ultimately applied to both synthetic data with realistic 3D clouds and real observations.</p>

scholarly journals Impact of meteorological clouds on satellite detection and retrieval of volcanic ash during the Eyjafjallajökull 2010 and Grímsvötn 2011 eruptions: a modelling study

2014 ◽  
Vol 7 (11) ◽  
pp. 11303-11343 ◽  
Author(s):  
A. Kylling ◽  
N. Kristiansen ◽  
A. Stohl ◽  
R. Buras-Schnell ◽  
C. Emde ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Liquid Water ◽  
Volcanic Ash ◽  
Detection Efficiency ◽  
Radiative Transfer Model ◽  
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 effect of ice and liquid water clouds on detection and retrieval of volcanic ash is quantified by simulating synthetic equivalents to satellite infrared images with a 3-D radiative transfer model. The simulations were made both with and without realistic water and ice clouds taken from European Centre for Medium-Range Weather Forecast (ECMWF) analysis data. The volcanic ash cloud fields were taken from simulations by the Lagrangian particle dispersion model FLEXPART. The radiative transfer calculations were made for the geometry and channels of the Spinning Enhanced Visible and Infrared Imager (SEVIRI), for the full duration of the Eyjafjallajökull 2010 and Grímsvötn 2011 eruptions. The synthetic SEVIRI images were then used as input to standard reverse absorption ash detection and retrieval methods. Meteorological 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. The detection efficiency (detected ash pixels relative to Flexpart ash pixels with ash loading > 0.2 g m−2) was on average only 14.6% (22.1%) for the cloudy (cloudless) simulation for the Eyjafjallajökull 2010 eruption, and 3.6% (10.0%) for the Grímsvötn 2011 eruption. If only Flexpart ash pixels with ash loading > 1.0 g m−2 are considered the detection efficiency increase to 54.7% (74.7) for the Eyjafjallajökull 2010 eruption and to 4.8% (15.1%) for the Grímsvötn 2011 eruption. For coincident pixels, i.e., pixels where ash was both present in the Flexpart simulation and detected by the algorithm, the presence of meteorological 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 (SD of ±30 and ±20% for Eyjafjallajökull and Grímsvötn respectively) and even larger ones within scenes. If all pixels are included the total mass from all scenes is severely underestimated. For the Eyjafjallajökull 2010 eruption the cloudless (cloudy) mass is underestimateed by 52% (66%) compared to the Flexpart mass, while for the Grímsvötn 2011 eruption the Flexpart mass is underestimated by 82% (91%) for the cloudless (cloudy) simulation. 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, satellite ash measurements should be combined with ash dispersion modelling.

The impact of the OSIRIS grating efficiency on radiance and trace-gas retrievals

2002 ◽  
Vol 80 (4) ◽  
pp. 469-481 ◽  
Author(s):  
C A McLinden ◽  
J C McConnell ◽  
K Strong ◽  
I C McDade ◽  
R L Gattinger ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Diffraction Grating ◽  
Infrared Imaging ◽  
Imaging System ◽  
Trace Gas ◽  
Radiative Transfer Model ◽  
Optical Absorption Spectroscopy ◽  
Transfer Model ◽  
Efficiency Coefficient ◽  
The Impact

The optical spectrograph and infrared imaging system (OSIRIS), launched in 2001, is a UV–visible diffraction-grating instrument designed to measure light scattered from the Earth's limb. Laboratory measurements of the OSIRIS diffraction-grating efficiency reveal a sensitivity to polarization including an anomalous structure of width 20–30 nm introduced into light polarized in a direction perpendicular to the grooves of the grating. A vector radiative-transfer model was used to generate synthetic OSIRIS spectra in an effort to examine the effect of this on radiances and trace-gas retrievals. Radiances that included grating effects were found to deviate by nearly 10% from those that did not and also contained the anomalous structure. Performing differential optical absorption spectroscopy (DOAS) on these spectra revealed errors in ozone apparent column densities of up to 80 DU. The size of the error was controlled mainly by the difference in polarization between the two DOAS spectra. Two possible correction methods were investigated. The first was to remove the grating effects by applying a correction factor to the raw radiances calculated using the vector radiative-transfer model. The second was to include the efficiency coefficient spectra in the DOAS fit. PACS Nos.: 42.68Mj, 98.55Qf

scholarly journals Three-dimensional radiative transfer effects on airborne, satellite and ground-based trace gas remote sensing

2020 ◽  
Author(s):  
Marc Schwaerzel ◽  
Claudia Emde ◽  
Dominik Brunner ◽  
Randulph Morales ◽  
Thomas Wagner ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Radiative Transfer ◽  
High Spatial Resolution ◽  
Three Dimensional ◽  
Trace Gas ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Vertical Column ◽  
Different Types ◽  
3D Effects

Abstract. Air mass factors (AMF) are used in passive trace gas remote sensing for converting slant column densities (SCD) to vertical column densities (VCD). AMFs are traditionally computed with 1D radiative transfer models assuming horizontally homogeneous conditions. However, when observations are made with high spatial resolution in a heterogeneous atmosphere or above a heterogeneous surface, 3D effects may not be negligible. To study the importance of 3D effects on AMFs for different types of trace gas remote sensing, we implemented 1D-layer and 3D-box AMFs into the Monte Carlo radiative transfer model (RTM) MYSTIC. The 3D-box AMF implementation is fully consistent with 1D-layer AMFs under horizontally homogeneous conditions and agrees very well (

scholarly journals Impact of 3D Cloud Structures on the Atmospheric Trace Gas Products from UV-VIS Sounders – Part II: impact on NO<sub>2</sub> retrieval and mitigation strategies

2021 ◽  
Author(s):  
Huan Yu ◽  
Claudia Emde ◽  
Arve Kylling ◽  
Ben Veihelmann ◽  
Bernhard Mayer ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Surface Albedo ◽  
Three Dimensional ◽  
Sensitivity Study ◽  
Mitigation Strategies ◽  
Trace Gas ◽  
Transfer Model ◽  
Cloud Models ◽  
Significant Bias ◽  
The Impact

Abstract. Operational retrievals of tropospheric trace gases from space-borne spectrometers are based on one-dimensional radiative transfer models. To minimize cloud effects, trace gas retrievals generally implement Lambertian cloud models based on radiometric cloud fraction estimates and photon path length corrections. The latter relies on measurements of the oxygen collision pair (O2-O2) absorption at 477 nm or on the oxygen A-band around 760 nm. In reality however, the impact of clouds is much more complex, involving unresolved sub-pixel clouds, scattering of clouds in neighboring pixels and cloud shadow effects, such that unresolved three-dimensional effects due to clouds may introduce significant biases in trace gas retrievals. In order to quantify this impact, we study NO2 as a trace gas example, and apply standard retrieval methods including approximate cloud corrections to synthetic data generated by the state-of-the-art three-dimensional Monte Carlo radiative transfer model MYSTIC. A sensitivity study is performed for simulations including a box-cloud, and the dependency on various parameters is investigated. The most significant bias is found for cloud shadow effects under polluted conditions. Biases depend strongly on cloud shadow fraction, NO2 profile, cloud optical thickness, solar zenith angle, and surface albedo. Several approaches to correct NO2 retrievals under cloud shadow conditions are explored. We find that air mass factors calculated using fitted surface albedo or corrected using the O2-O2 slant column density can partly mitigate cloud shadow effects. However, these approaches are limited to cloud-free pixels affected by surrounding clouds. A parameterization approach is presented based on relationships derived from the sensitivity study. This allows identifying measurements for which the standard NO2 retrieval produces a significant bias, and therefore provides a way to improve the current data flagging approach.

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.

scholarly journals Performance of the line-by-line radiative transfer model (LBLRTM) for temperature and species retrievals: IASI case studies from JAIVEx

2009 ◽  
Vol 9 (19) ◽  
pp. 7397-7417 ◽  
Author(s):  
M. W. Shephard ◽  
S. A. Clough ◽  
V. H. Payne ◽  
W. L. Smith ◽  
S. Kireev ◽  
...  
Keyword(s):  
Water Vapor ◽  
Radiative Transfer ◽  
Trace Gas ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Line Intensities ◽  
Remote Sounding ◽  
Instrument Noise ◽  
Large Peak ◽  
Line Coupling

Abstract. Presented here are comparisons between the Infrared Atmospheric Sounding instrument (IASI) and the "Line-By-Line Radiative Transfer Model" (LBLRTM). Spectral residuals from radiance closure studies during the IASI JAIVEx validation campaign provide insight into a number of spectroscopy issues relevant to remote sounding of temperature, water vapor and trace gases from IASI. In order to perform quality IASI trace gas retrievals, the temperature and water vapor fields must be retrieved as accurately as possible. In general, the residuals in the CO2 ν2 region are of the order of the IASI instrument noise. However, outstanding issues with the CO2 spectral regions remain. There is a large residual ~−1.7 K in the 667 cm−1 Q-branch, and residuals in the CO2 ν2 and N2O/CO2 ν3 spectral regions that sample the troposphere are inconsistent, with the N2O/CO2 ν3 region being too negative (warmer) by ~0.7 K. Residuals on this lower wavenumber side of the CO2 ν3 band will be improved by line parameter updates, while future efforts to reduce the residuals reaching ~−0.5 K on the higher wavenumber side of the CO2 ν3 band will focus on addressing limitations in the modeling of the CO2 line shape (line coupling and duration of collision) effects. Brightness temperature residuals from the radiance closure studies in the ν2 water vapor band have standard deviations of ~0.2–0.3 K with some large peak residuals reaching ±0.5–1.0 K. These are larger than the instrument noise indicating that systematic errors still remain. New H2O line intensities and positions have a significant impact on the retrieved water vapor, particularly in the upper troposphere where the water vapor retrievals are 10% drier when using line intensities compared with HITRAN 2004. In addition to O3, CH4, and CO, of the IASI instrument combined with an accurate forward model allows for the detection of minor species with weak atmospheric signatures in the nadir radiances, such as HNO3 and OCS.

scholarly journals Comparison of PARASOL Observations with Polarized Reflectances Simulated Using Different Ice Habit Mixtures

2013 ◽  
Vol 52 (1) ◽  
pp. 186-196 ◽  
Author(s):  
Benjamin H. Cole ◽  
Ping Yang ◽  
Bryan A. Baum ◽  
Jerome Riedi ◽  
Laurent C.-Labonnote ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Ice Crystal ◽  
Ice Clouds ◽  
Atmospheric Sciences ◽  
Reflection Data ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Polarized Reflectance

AbstractInsufficient knowledge of the habit distribution and the degree of surface roughness of ice crystals within ice clouds is a source of uncertainty in the forward light scattering and radiative transfer simulations of ice clouds used in downstream applications. The Moderate Resolution Imaging Spectroradiometer (MODIS) collection-5 ice microphysical model presumes a mixture of various ice crystal shapes with smooth facets, except for the compact aggregate of columns for which a severely rough condition is assumed. When compared with Polarization and Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar (PARASOL) polarized reflection data, simulations of polarized reflectance using smooth particles show a poor fit to the measurements, whereas very rough-faceted particles provide an improved fit to the polarized reflectance. In this study a new microphysical model based on a mixture of nine different ice crystal habits with severely roughened facets is developed. Simulated polarized reflectance using the new ice habit distribution is calculated using a vector adding–doubling radiative transfer model, and the simulations closely agree with the polarized reflectance observed by PARASOL. The new general habit mixture is also tested using a spherical albedo differences analysis, and surface roughening is found to improve the consistency of multiangular observations. These results are consistent with previous studies that have used polarized reflection data. It is suggested that an ice model incorporating an ensemble of different habits with severely roughened surfaces would potentially be an adequate choice for global ice cloud retrievals.

Modelling understory light availability in a heterogeneous landscape using drone-derived structural parameters and a 3D radiative transfer model

2020 ◽  
Author(s):  
Dominic Fawcett ◽  
Jonathan Bennie ◽  
Karen Anderson
Keyword(s):  
Radiative Transfer ◽  
Vegetation Index ◽  
Structural Parameters ◽  
Point Clouds ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Area Index ◽  
Vegetation Height ◽  
Plant Area Index ◽  
The Impact

&lt;p&gt;The light environment within vegetated landscapes is a key driver of microclimate, creating varied habitats over small spatial extents and controls the distribution of understory plant species. Modelling spatial variations of light at these scales requires finely resolved (&lt; 1 m) information on topography and canopy properties. We demonstrate an approach to modelling spatial distributions and temporal progression of understory photosynthetically active radiation (PAR) utilising a three dimensional radiative transfer model (discrete anisotropic radiative transfer model: DART) where the scene is parameterised by drone-based data.&lt;/p&gt;&lt;p&gt;The study site, located in west Cornwall, UK, includes a small mixed woodland as well as isolated free-standing trees. Data were acquired from March to August 2019. Vegetation height and distribution were derived from point clouds generated from drone image data using structure-from-motion (SfM) photogrammetry. These data were supplemented by multi-temporal multispectral imagery (Parrot Sequoia camera) which were used to generate an empirical model by relating a vegetation index to plant area index derived from hemispherical photography taken over the same time period. Simulations of the 3D radiative budget were performed for the PAR wavelength interval (400 &amp;#8211; 700 nm) using DART.&lt;/p&gt;&lt;p&gt;Besides maps of instantaneous above and below canopy irradiance, we provide models of daily light integrals (DLI) which are assessed against field validation measurements with PAR quantum sensors. We find relatively good agreement for simulated PAR in the woodland. The impact of simplifying assumptions regarding leaf angular distributions and optical properties are discussed. Finally, further opportunities which fine-grained drone data can provide in a radiative transfer context are highlighted.&lt;/p&gt;

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