Tropospheric NO2 and stratospheric NO2 vertical column densities are important TROPOspheric Monitoring Instrument (TROPOMI) data products.
In order to validate the
TROPOMI NO2 products, KNMI ...Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) instruments have measured NO2 on ship cruises over the Atlantic
and the Pacific oceans. The MAX-DOAS instruments have participated in five cruises on board RV Sonne (in 2017 and 2019)
and RV Maria S. Merian (in 2018). The MAX-DOAS measurements were acquired over 7 months and spanned
about 90∘ in latitude and 300∘ in longitude.
During the cruises aerosol measurements from Microtops sun photometers were also taken.
The MAX-DOAS measured stratospheric NO2 columns between
1.5×1015 and 3.5×1015 molec cm−2
and tropospheric NO2 up to 0.6×1015 molec cm−2.
The MAX-DOAS stratospheric NO2 vertical column densities have been compared with
TROPOMI stratospheric NO2 vertical column densities
and the stratospheric NO2 vertical column densities
simulated by the global chemistry Transport Model, version 5, Massively Parallel model (TM5-MP). Good correlation is found between the MAX-DOAS and TROPOMI and
TM5 stratospheric NO2 vertical column densities, with a correlation coefficient of 0.93 or larger. The TROPOMI and TM5
stratospheric NO2 vertical column densities are about 0.4×1015 molec cm−2 (19 %) higher than
the MAX-DOAS measurements.
The TROPOMI tropospheric NO2 also has good agreement with the MAX-DOAS measurements. The
tropospheric NO2 vertical column density is as low as 0.5×1015 molec cm−2 over remote oceans.
Tropospheric NO.sub.2 and stratospheric NO.sub.2 vertical column densities are important TROPOspheric Monitoring Instrument (TROPOMI) data products. In order to validate the TROPOMI NO.sub.2 ...products, KNMI Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) instruments have measured NO.sub.2 on ship cruises over the Atlantic and the Pacific oceans. The MAX-DOAS instruments have participated in five cruises on board RV Sonne (in 2017 and 2019) and RV Maria S. Merian (in 2018). The MAX-DOAS measurements were acquired over 7 months and spanned about 90.sup." in latitude and 300.sup." in longitude. During the cruises aerosol measurements from Microtops sun photometers were also taken. The MAX-DOAS measured stratospheric NO.sub.2 columns between 1.5x10.sup.15 and 3.5x10.sup.15 molec cm.sup.-2 and tropospheric NO.sub.2 up to 0.6x10.sup.15 molec cm.sup.-2 . The MAX-DOAS stratospheric NO.sub.2 vertical column densities have been compared with TROPOMI stratospheric NO.sub.2 vertical column densities and the stratospheric NO.sub.2 vertical column densities simulated by the global chemistry Transport Model, version 5, Massively Parallel model (TM5-MP). Good correlation is found between the MAX-DOAS and TROPOMI and TM5 stratospheric NO.sub.2 vertical column densities, with a correlation coefficient of 0.93 or larger. The TROPOMI and TM5 stratospheric NO.sub.2 vertical column densities are about 0.4x10.sup.15 molec cm.sup.-2 (19 %) higher than the MAX-DOAS measurements. The TROPOMI tropospheric NO.sub.2 also has good agreement with the MAX-DOAS measurements. The tropospheric NO.sub.2 vertical column density is as low as 0.5x10.sup.15 molec cm.sup.-2 over remote oceans.
A shortwave radiative closure analysis for cloudy skies is presented for the Cabauw Baseline Surface Radiation Network (BSRN) site (51.97°N, 4.93°E). The cloudy cases are carefully selected to be ...overcast, single‐layer, homogeneous, nonprecipitating water clouds. We selected in total 639 cases on 9 days between May 2008 and May 2009 and on 30 January 2007. The Doubling‐Adding KNMI (DAK) code is used to simulate global irradiances. The cloud optical thickness is derived from the cloud liquid water path from microwave radiometer (MWR) measurements and the MODIS L2 cloud effective radius product. The scattering phase matrix of the cloud particles is calculated using a Mie code with the two‐parameter Gamma size distribution. The MWR integrated water vapor column and an aerosol climatology are also used in the simulations. The cloudy cases cover a large range of liquid water path (30–400 g/m2), water vapor column (0.7–3.1 cm), and solar zenith angle (41°–75°). The mean difference between simulated global irradiances and BSRN measurements is 6 W/m2 (5%), with a standard deviation of 14 W/m2 (13%). This difference is within the uncertainties of the model input parameters and measurement errors. The correlation coefficient between the measured and simulated global irradiances is 0.95. The good closure results demonstrate the high quality of the MODIS effective radius data and MWR liquid water path data and the accuracy of the DAK model for the selected water cloud cases. Furthermore, the effects of clouds, aerosols, water vapor, and surface albedo on the global irradiance have been analyzed carefully. The sensitivity study shows that in order to achieve the closure with an uncertainty of a few W/m2, more frequent effective radius data, simultaneous aerosol and cloud measurements, and surface albedo measurements are essential.
Key Points
Cloudy shortwave radiative closure is achieved
DAK model is validated for cloudy cases
Sensitivity of cloudy closure to aerosols, water vapor, and surface albedo
DISAMAR (determining instrument specifications
and analysing methods for atmospheric retrieval) is a computer model developed to simulate retrievals of properties of atmospheric trace gases, ...aerosols, clouds, and the ground surface from passive remote sensing observations in a wavelength range from
270 to 2400 nm. It is being used for the TROPOMI/Sentinel-5P and Sentinel-4/5 missions to derive
Level-1b product specifications. DISAMAR uses the doubling–adding method and the layer-based orders of scattering method for radiative transfer calculations. It can perform retrievals using three different approaches: optimal estimation (OE), differential optical absorption spectroscopy (DOAS), and the combination of DOAS and OE, called DISMAS (differential and smooth absorption separated). The derivatives, which are needed in the OE and DISMAS retrievals, are derived in a semi-analytical way from the adding formulae. DISAMAR uses plane-parallel homogeneous atmospheric layers with a pseudo-spherical correction for large solar zenith angles. DISAMAR has various novel features and diverse retrieval possibilities, such as retrieving aerosol layer heights and ozone vertical profiles. This paper provides an overview of the DISAMAR model version 4.1.5 without treating all the details. We focus on the principle of the layer-based orders of scattering method, the calculation of the semi-analytical derivatives, and the DISMAS retrieval method, and it is to our knowledge the first time that these methods are described. We demonstrate some applications of DISMAS and the derivatives.
How big is an OMI pixel? de Graaf, Martin; Sihler, Holger; Tilstra, Lieuwe G ...
Atmospheric measurement techniques,
08/2016, Letnik:
9, Številka:
8
Journal Article
Recenzirano
Odprti dostop
The Ozone Monitoring Instrument (OMI) is a push-broom imaging spectrometer, observing solar radiation backscattered by the Earth's atmosphere and surface. The incoming radiation is detected using a ...static imaging CCD (charge-coupled device) detector array with no moving parts, as opposed to most of the previous satellite spectrometers, which used a moving mirror to scan the Earth in the across-track direction. The field of view (FoV) of detector pixels is the solid angle from which radiation is observed, averaged over the integration time of a measurement. The OMI FoV is not quadrangular, which is common for scanning instruments, but rather super-Gaussian shaped and overlapping with the FoV of neighbouring pixels. This has consequences for pixel-area-dependent applications, like cloud fraction products, and visualisation.The shapes and sizes of OMI FoVs were determined pre-flight by theoretical and experimental tests but never verified after launch. In this paper the OMI FoV is characterised using collocated MODerate resolution Imaging Spectroradiometer (MODIS) reflectance measurements. MODIS measurements have a much higher spatial resolution than OMI measurements and spectrally overlap at 469 nm. The OMI FoV was verified by finding the highest correlation between MODIS and OMI reflectances in cloud-free scenes, assuming a 2-D super-Gaussian function with varying size and shape to represent the OMI FoV. Our results show that the OMPIXCOR product 75FoV corner coordinates are accurate as the full width at half maximum (FWHM) of a super-Gaussian FoV model when this function is assumed. The softness of the function edges, modelled by the super-Gaussian exponents, is different in both directions and is view angle dependent.The optimal overlap function between OMI and MODIS reflectances is scene dependent and highly dependent on time differences between overpasses, especially with clouds in the scene. For partially clouded scenes, the optimal overlap function was represented by super-Gaussian exponents around 1 or smaller, which indicates that this function is unsuitable to represent the overlap sensitivity function in these cases. This was especially true for scenes before 2008, when the time differences between Aqua and Aura overpasses was about 15 min, instead of 8 min after 2008. During the time between overpasses, clouds change the scene reflectance, reducing the correlation and influencing the shape of the optimal overlap function.
The retrieval of geophysical parameters is increasingly dependent on synergistic use of satellite instruments. More sophisticated parameters can be retrieved and the accuracy of retrievals can be ...increased when more information is combined. In this paper, a synergistic application of Ozone Monitoring Instrument (OMI), on the Aura platform, and Moderate Resolution Imaging Spectroradiometer (MODIS), on the Aqua platform, Level 1B reflectances is described, enabling the retrieval of the aerosol direct radiative effect (DRE) over clouds using the differential aerosol absorption (DAA) technique. This technique was first developed for reflectances from the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) on the Environmental Satellite (Envisat), which had the unique capability of measuring contiguous radiances from the ultraviolet (UV) at 240 to 1750 nm in the shortwave-infrared (SWIR), at a moderate spectral resolution of 0.2 to 1.5 nm. However, the spatial resolution and global coverage of SCIAMACHY was limited, and Envisat stopped delivering data in 2012. In order to continue the DRE data retrieval, reflectances from OMI and MODIS, flying in formation, were combined from the UV to the SWIR. This resulted in reflectances at a limited but sufficient spectral resolution, available at the OMI pixel grid, which have a much higher spatial resolution and coverage than SCIAMACHY. The combined reflectance spectra allow the retrieval of cloud microphysical parameters in the SWIR, and the subsequent retrieval of aerosol DRE over cloud scenes using the DAA technique. For liquid cloud scenes in the south-east Atlantic region with cloud fraction (CF) 0.3, the area-averaged instantaneous aerosol DRE over clouds in June to August 2006 was 25 Wm.sup.-2 with a standard deviation of 30 Wm.sup.-2 . The maximum area-averaged instantaneous DRE from OMI-MODIS in August 2006 was 75.6±13 Wm.sup.-2 . The new aerosol DRE over-cloud dataset from OMI-MODIS is compared to the SCIAMACHY dataset for the period 2006 to 2009, showing a very high correlation. The OMI-MODIS DRE dataset over the Atlantic Ocean is highly correlated to above-cloud AOT measurements from OMI and MODIS. It is related to AOT measurements over Ascension Island in 2016, showing the transport of smoke all the way from its source region in Africa over the Atlantic to Ascension and beyond.
Cloud shadows are observed by the TROPOMI satellite instrument as a result of its high spatial resolution compared to its predecessor instruments. These shadows contaminate TROPOMI's air quality ...measurements, because shadows are generally not taken into account in the models that are used for aerosol and trace gas retrievals. If the shadows are to be removed from the data, or if shadows are to be studied, an automatic detection of the shadow pixels is needed. We present the Detection AlgoRithm for CLOud Shadows (DARCLOS) for TROPOMI, which is the first cloud shadow detection algorithm for a spaceborne spectrometer. DARCLOS raises potential cloud shadow flags (PCSFs), actual cloud shadow flags (ACSFs), and spectral cloud shadow flags (SCSFs). The PCSFs indicate the TROPOMI ground pixels that are potentially affected by cloud shadows based on a geometric consideration with safety margins. The ACSFs are a refinement of the PCSFs using spectral reflectance information of the PCSF pixels and identify the TROPOMI ground pixels that are confidently affected by cloud shadows. Because we find indications of the wavelength dependence of cloud shadow extents in the UV, the SCSF is a wavelength-dependent alternative for the ACSF at the wavelengths of TROPOMI's air quality retrievals. We validate the PCSF and ACSF with true-colour images made by the VIIRS instrument on board Suomi NPP orbiting in close proximity to TROPOMI on board Sentinel-5P. We find that the cloud evolution during the overpass time difference between TROPOMI and VIIRS complicates this validation strategy, implicating that an alternative cloud shadow detection approach using co-located VIIRS observations could be problematic. We conclude that the PCSF can be used to exclude cloud shadow contamination from TROPOMI data, while the ACSF and SCSF can be used to select pixels for the scientific analysis of cloud shadow effects.
Global mapping of satellite tropospheric NO2 vertical column
density (VCD), a key gas in air quality monitoring, requires accurate
retrievals over complex urban and industrialized areas and under any
...atmospheric conditions. The high abundance of aerosol particles in regions
dominated by anthropogenic fossil fuel combustion, e.g. megacities, and/or
biomass-burning episodes, affects the space-borne spectral measurement.
Minimizing the tropospheric NO2 VCD biases caused by aerosol
scattering and absorption effects is one of the main retrieval challenges
from air quality satellite instruments. In this study, the reference Ozone
Monitoring Instrument (OMI) DOMINO-v2 product was reprocessed over cloud-free
scenes, by applying new aerosol correction parameters retrieved from the
477 nm O2−O2 band, over eastern China and South America for 2 years
(2006–2007). These new parameters are based on two different and separate
algorithms developed during the last 2 years in view of an improved use of
the OMI 477 nm O2−O2 band:
the updated OMCLDO2 algorithm, which derives improved effective cloud
parameters, the aerosol neural network (NN), which retrieves explicit aerosol
parameters by assuming a more physical aerosol model.
The OMI aerosol NN is a step ahead of OMCLDO2 because it primarily estimates an
explicit aerosol layer height (ALH), and secondly an aerosol optical
thickness τ for cloud-free observations. Overall, it was found that all
the considered aerosol correction parameters reduce the biases identified in
DOMINO-v2 over scenes in China with high aerosol abundance dominated by fine
scattering and weakly absorbing particles, e.g. from
-20%:-40% to
0 %:20 % in summertime. The use of the retrieved OMI aerosol
parameters leads in general to a more explicit aerosol correction and higher
tropospheric NO2 VCD values, in the range of 0 %:40 %, than
from the implicit correction with the updated OMCLDO2. This number overall
represents an estimation of the aerosol correction strategy uncertainty
nowadays for tropospheric NO2 VCD retrieval from space-borne visible
measurements. The explicit aerosol correction theoretically includes a more
realistic consideration of aerosol multiple scattering and absorption
effects, especially over scenes dominated by strongly absorbing particles,
where the correction based on OMCLDO2 seems to remain insufficient. However,
the use of ALH and τ from the OMI NN aerosol algorithm is not a
straightforward operation and future studies are required to identify the
optimal methodology. For that purpose, several elements are recommended in
this paper. Overall, we demonstrate the possibility of applying a more explicit
aerosol correction by considering aerosol parameters directly derived from
the 477 nm O2−O2 spectral band, measured by the same satellite
instrument. Such an approach can, in theory, easily be transposed to the
new-generation of space-borne instruments (e.g. TROPOMI on board Sentinel-5
Precursor), enabling a fast reprocessing of tropospheric NO2 data
over cloud-free scenes (cloudy pixels need to be filtered out), as well as
for other trace gas retrievals (e.g. SO2, HCHO).
The angular distribution of the light reflected by the Earth's surface influences top-of-atmosphere (TOA) reflectance values. This surface reflectance anisotropy has implications for UV/Vis satellite ...retrievals of albedo, clouds, and trace gases such as nitrogen dioxide (NO2). These retrievals routinely assume the surface to reflect light isotropically. Here we show that cloud fractions retrieved from GOME-2A and OMI with the FRESCO and OMCLDO2 algorithms have an east–west bias of 10 % to 50 %, which are highest over vegetation and forested areas, and that this bias originates from the assumption of isotropic surface reflection. To interpret the across-track bias with the DAK radiative transfer model, we implement the bidirectional reflectance distribution function (BRDF) from the Ross–Li semi-empirical model. Testing our implementation against state-of-the-art RTMs LIDORT and SCIATRAN, we find that simulated TOA reflectance generally agrees to within 1 %. We replace the assumption of isotropic surface reflection in the equations used to retrieve cloud fractions over forested scenes with scattering kernels and corresponding BRDF parameters from a daily high-resolution database derived from 16 years' worth of MODIS measurements. By doing this, the east–west bias in the simulated cloud fractions largely vanishes. We conclude that across-track biases in cloud fractions can be explained by cloud algorithms that do not adequately account for the effects of surface reflectance anisotropy. The implications for NO2 air mass factor (AMF) calculations are substantial. Under moderately pollutedNO2 and backward-scattering conditions, clear-sky AMFs are up to 20 % higher and cloud radiance fractions up to 40 % lower if surface anisotropic reflection is accounted for. The combined effect of these changes is that NO2 total AMFs increase by up to 30 % for backward-scattering geometries (and decrease by up to 35 % for forward-scattering geometries), which is stronger than the effect of either contribution alone. In an unpolluted troposphere, surface BRDF effects on cloud fraction counteract (and largely cancel) the effect on the clear-sky AMF. Our results emphasise that surface reflectance anisotropy needs to be taken into account in a coherent manner for more realistic and accurate retrievals of clouds andNO2 from UV/Vis satellite sensors. These improvements will be beneficial for current sensors, in particular for the recently launched TROPOMI instrument with a high spatial resolution.
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