scholarly journals Impact of 3D Cloud Structures on the Atmospheric Trace Gas Products from UV-VIS Sounders – Part I: Synthetic dataset for validation of trace gas retrieval algorithms

2021 ◽  
Author(s):  
Claudia Emde ◽  
Huan Yu ◽  
Arve Kylling ◽  
Michel van Roozendael ◽  
Kerstin Stebel ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
3D Structure ◽  
Three Dimensional ◽  
Synthetic Data ◽  
Synthetic Dataset ◽  
Trace Gas ◽  
Transfer Model ◽  
Retrieval Error ◽  
Retrieval Algorithms ◽  
The Impact

Abstract. Retrievals of trace gas concentrations from satellite observations are mostly performed for clear regions or regions with low cloud coverage. However, even fully clear pixels can be affected by clouds in the vicinity, either by shadowing or by scattering of radiation from clouds in the clear region. Quantifying the error of retrieved trace gas concentrations due to cloud scattering is a difficult task. One possibility is to generate synthetic data by three-dimensional (3D) radiative transfer simulations using realistic 3D atmospheric input data, including 3D cloud structures. Retrieval algorithms may be applied on the synthetic data and comparison to the known input trace gas concentrations yields the retrieval error due to cloud scattering. In this paper we present a comprehensive synthetic dataset which has been generated using the Monte Carlo radiative transfer model MYSTIC. The dataset includes simulated spectra in two spectral ranges (400–500 nm and the O2A-band from 755–775 nm). Moreover it includes layer air mass factors (layer-AMF) calculated at 460 nm. All simulations are performed for a fixed background atmosphere for various sun positions, viewing directions and surface albedos. Two cloud setups are considered: The first includes simple box-clouds with various geometrical and optical thicknesses. This can be used to systematically investigate the sensitivity of the retrieval error on solar zenith angle, surface albedo and cloud parameters. Corresponding 1D simulations are also provided. The second includes realistic three-dimensional clouds from an ICON large eddy simulation (LES) for a region covering Germany and parts of surrounding countries. The scene includes cloud types typical for central Europe such as shallow cumulus, convective cloud cells, cirrus, and stratocumulus. This large dataset can be used to quantify the trace gas concentration retrieval error statistically. Along with the dataset the impact of horizontal photon transport on reflectance spectra and layer-AMFs is analyzed for the box-cloud scenarios. Moreover, the impact of 3D cloud scattering on the NO2 vertical column density (VCD) retrieval is presented for a specific LES case. We find that the retrieval error is largest in cloud shadow regions, where the NO2 VCD is underestimated by more than 20 %. The dataset is available for the scientific community to assess the behavior of trace gas retrieval algorithms and cloud correction schemes in cloud conditions with 3D structure.

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 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.

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

&lt;p&gt;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&lt;sub&gt;2&lt;/sub&gt;-O&lt;sub&gt;2&lt;/sub&gt;) or O&lt;sub&gt;2&lt;/sub&gt;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.&lt;/p&gt;&lt;p&gt;As a trace gas example, we study NO&lt;sub&gt;2&lt;/sub&gt;, 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&lt;sub&gt;2&lt;/sub&gt; 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&lt;sub&gt;2&lt;/sub&gt; vertical column densities (VCD) are compared with the true values to identify conditions where 3D cloud effects lead to significant biases on the NO&lt;sub&gt;2&lt;/sub&gt; VCDs. A variety of possible mitigation strategies for such pixels are then explored.&lt;/p&gt;

scholarly journals Three-dimensional effects in polarization signatures as observed from precipitating clouds by low frequency ground-based microwave radiometers

2006 ◽  
Vol 6 (3) ◽  
pp. 5427-5456
Author(s):  
A. Battaglia ◽  
C. Simmer ◽  
H. Czekala
Keyword(s):  
Radiative Transfer ◽  
Monte Carlo Model ◽  
Three Dimensional ◽  
Low Frequency ◽  
Radiative Transfer Model ◽  
Observation Angle ◽  
Transfer Model ◽  
One Dimensional ◽  
Dimensional Effects ◽  
The Impact

Abstract. Consistent negative polarization differences (i.e. differences between the vertical and the horizontal brightness temperature) are observed when looking at precipitating systems by ground-based radiometers at slant angles. These signatures can be partially explained by one-dimensional radiative transfer computations that include oriented non-spherical raindrops. However some cases are characterized by polarization values that exceed differences expected from one-dimensional radiative transfer. A three-dimensional fully polarized Monte Carlo model has been used to evaluate the impact of the horizontal finiteness of rain shafts with different rain rates at 10, 19, and 30 GHz. The results show that because of the reduced slant optical thickness in finite clouds, the polarization signal can strongly differ from its one-dimensional counterpart. At the higher frequencies and when the radiometer is positioned underneath the cloud, significantly higher negative values for the polarization are found which are also consistent with some observations. When the observation point is located outside of the precipitating cloud, typical polarization patterns (with troughs and peaks) as a function of the observation angle are predicted. An approximate 1-D slant path radiative transfer model is considered as well and results are compared with the full 3-D simulations to investigate whether or not three-dimensional effects can be explained by geometry effects alone. The study has strong relevance for low-frequency passive microwave polarimetric studies.

scholarly journals Estimating bias in the OCO-2 retrieval algorithm caused by 3-D radiation scattering from unresolved boundary layer clouds

2015 ◽  
Vol 8 (4) ◽  
pp. 1641-1656 ◽  
Author(s):  
A. Merrelli ◽  
R. Bennartz ◽  
C. W. O'Dell ◽  
T. E. Taylor
Keyword(s):  
Radiative Transfer ◽  
Scattering Problem ◽  
Three Dimensional ◽  
Co2 Concentration ◽  
Bare Soil ◽  
Short Wave ◽  
Radiative Transfer Model ◽  
Retrieval Algorithm ◽  
Transfer Model ◽  
Retrieval Algorithms

Abstract. Due to the complexity of the multiple scattering problem for shortwave radiative transfer in Earth's atmosphere, operational physical retrieval algorithms commonly use a plane parallel radiative transfer model (RTM). This so-called one-dimensional (1-D) assumption allows practical retrieval algorithms to be implemented. In order to understand the impacts of this assumption for low altitude, unresolved clouds observed by OCO-2, the three-dimensional (3-D) radiative transfer model SHDOM is used to generate synthetic observations which are then processed by the operational retrieval algorithm based on a 1-D RTM. Simulations are performed over three realistic surface spectral albedos, corresponding to snow, vegetation, and bare soil. The results show that the existing cloud screening algorithm has difficulty identifying sub-field of view (FOV), unresolved clouds that fill less than half of the FOV. The unresolved clouds introduce a bias in the retrieved CO2 concentration, as quantified by the dry air mole fraction (XCO2). The biases are relatively small (less than 1 ppm) when the albedo at 2.1 μm is high, which is common over bare land surfaces. For cases with low 2.1 μm albedo, such as snow, the bias becomes much larger, up to 5 ppm. These results indicate that the XCO2 retrieval appears robust to 3-D scattering effects from unresolved low level clouds when the short wave infrared surface albedo is large, but for darker surfaces these clouds can introduce significant biases.

scholarly journals Inelastic scattering in ocean water and its impact on trace gas retrievals from satellite data

2003 ◽  
Vol 3 (5) ◽  
pp. 1365-1375 ◽  
Author(s):  
M. Vountas ◽  
A. Richter ◽  
F. Wittrock ◽  
J. P. Burrows
Keyword(s):  
Correction Term ◽  
Chlorophyll Concentration ◽  
Synthetic Data ◽  
Sensitivity Study ◽  
Trace Gas ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Data Sets ◽  
Strong Impact ◽  
The Impact

Abstract. Over clear ocean waters, photons scattered within the water body contribute significantly to the upwelling flux. In addition to elastic scattering, inelastic Vibrational Raman Scattering (VRS) by liquid water is also playing a role and can have a strong impact on the spectral distribution of the outgoing radiance. Under clear-sky conditions, VRS has an influence on trace gas retrievals from space-borne measurements of the backscattered radiance such as from e.g. GOME (Global Ozone Monitoring Experiment). The effect is particularly important for geo-locations with small solar zenith angles and over waters with low chlorophyll concentration. In this study, a simple ocean reflectance model (Sathyendranath and Platt, 1998) accounting for VRS has been incorporated into a radiative transfer model. The model has been validated by comparison with measurements from a swimming-pool experiment dedicated to detect the effect of scattering within water on the outgoing radiation and also with selected data sets from GOME. The comparisons show good agreement between experimental and model data and highlight the important role of VRS. To evaluate the impact of VRS on trace gas retrieval, a sensitivity study was performed on synthetic data. If VRS is neglected in the data analysis, errors of more than 30% are introduced for the slant column (SC) of BrO over clear ocean scenarios. Exemplarily DOAS retrievals of BrO from real GOME measurements including and excluding a VRS compensation led to comparable results as in the sensitivity study, but with somewhat smaller differences between the two analyses. The results of this work suggest, that DOAS retrievals of atmospheric trace species from measurements of nadir viewing space-borne instruments have to take VRS scattering into account over waters with low chlorophyll concentrations, and that a simple correction term is enough to reduce the errors to an acceptable level.

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 effects in polarization signatures as observed from precipitating clouds by low frequency ground-based microwave radiometers

2006 ◽  
Vol 6 (12) ◽  
pp. 4383-4394 ◽  
Author(s):  
A. Battaglia ◽  
C. Simmer ◽  
H. Czekala
Keyword(s):  
Radiative Transfer ◽  
Monte Carlo Model ◽  
Three Dimensional ◽  
Low Frequency ◽  
Radiative Transfer Model ◽  
Observation Angle ◽  
Transfer Model ◽  
One Dimensional ◽  
Dimensional Effects ◽  
The Impact

Abstract. Consistent negative polarization differences (i.e. differences between the vertical and the horizontal brightness temperature) are observed when looking at precipitating systems by ground-based radiometers at slant angles. These signatures can be partially explained by one-dimensional radiative transfer computations that include oriented non-spherical raindrops. However some cases are characterized by polarization values that exceed differences expected from one-dimensional radiative transfer. A three-dimensional fully polarized Monte Carlo model has been used to evaluate the impact of the horizontal finiteness of rain shafts with different rain rates at 10, 19, and 30 GHz. The results show that because of the reduced slant optical thickness in finite clouds, the polarization signal can strongly differ from its one-dimensional counterpart. At the higher frequencies and when the radiometer is positioned underneath the cloud, significantly higher negative values for the polarization are found which are also consistent with some observations. When the observation point is located outside of the precipitating cloud, typical polarization patterns (with troughs and peaks) as a function of the observation angle are predicted. An approximate 1-D slant path radiative transfer model is considered as well and results are compared with the full 3-D simulations to investigate whether or not three-dimensional effects can be explained by geometry effects alone. The study has strong relevance for low-frequency passive microwave polarimetric studies.

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 Estimating bias in the OCO-2 retrieval algorithm caused by 3-D radiation scattering from unresolved boundary layer clouds

2014 ◽  
Vol 7 (11) ◽  
pp. 11547-11591
Author(s):  
A. Merrelli ◽  
R. Bennartz ◽  
C. W. O'Dell ◽  
T. E. Taylor
Keyword(s):  
Radiative Transfer ◽  
Scattering Problem ◽  
Three Dimensional ◽  
Co2 Concentration ◽  
Bare Soil ◽  
Short Wave ◽  
Radiative Transfer Model ◽  
Retrieval Algorithm ◽  
Transfer Model ◽  
Retrieval Algorithms

Abstract. Due to the complexity of the multiple scattering problem for shortwave radiative transfer in Earth's atmosphere, operational physical retrieval algorithms commonly use a plane parallel Radiative Transfer Model (RTM). This so-called One-Dimensional (1-D) assumption allows practical retrieval algorithms to be implemented. In order to understand the impacts of this assumption for low altitude, unresolved clouds observed by OCO-2, the Three-Dimensional (3-D) radiative transfer model SHDOM is used to generate synthetic observations which are then processed by the operational retrieval algorithm based on a 1-D RTM. Simulations are performed over three realistic surface spectral albedos, corresponding to snow, vegetation, and bare soil. The results show that the existing cloud screening algorithm has difficulty identifying sub-Field of View (FOV), unresolved clouds that fill less than half of the FOV. The unresolved clouds introduce a bias in the retrieved CO2 concentration, as quantified by the dry air mole fraction (XCO2). The biases are relatively small (less than 1 ppm) when the albedo at 2.1 μm is high, which is common over bare land surfaces. For cases with low 2.1 μm albedo, such as snow, the bias becomes much larger, up to 5 ppm. These results indicate that the XCO2 retrieval appears robust to 3-D scattering effects from unresolved low level clouds when the short wave infrared surface albedo is large, but for darker surfaces these clouds can introduce significant biases.

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