ALBERT

Description: The direct radiative effect (DRE) of aerosols above clouds has been found to be significant over the south-east Atlantic Ocean during the African biomass burning season due to elevated smoke layers absorbing radiation above the cloud deck. So far, global climate models have been unsuccessful in reproducing the high DRE values measured by various satellite instruments. Meanwhile, the radiative effects by aerosols have been identified as the largest source of uncertainty in global climate models. In this paper, three independent satellite datasets of DRE during the biomass burning season in 2006 are compared to constrain the south-east Atlantic radiation budget. The DRE of aerosols above clouds is derived from the spectrometer SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY), the polarimeter Polarization and Directionality of the Earth's Reflectances (POLDER), and collocated measurements by the spectrometer Ozone Monitoring Instrument (OMI) and the imager Moderate Resolution Imaging Spectroradiometer (MODIS). All three datasets confirm the high DRE values during the biomass season, underlining the relevance of local aerosol effects. Differences between the instruments can be attributed mainly to sampling issues. When these are accounted for, the remaining differences can be explained by a higher cloud optical thickness (COT) derived from POLDER compared to the other instruments and a neglect of aerosol optical thickness (AOT) at shortwave infrared (SWIR) wavelengths in the method used for SCIAMACHY and OMI–MODIS. The higher COT from POLDER by itself can explain the difference found in DRE between POLDER and the other instruments. The AOT underestimation is mainly evident at high values of the aerosol DRE and accounts for about a third of the difference between POLDER and OMI–MODIS DRE. The datasets from POLDER and OMI–MODIS effectively provide lower and upper bounds for the aerosol DRE over clouds over the south-east Atlantic, which can be used to challenge global circulation models (GCMs). Comparisons of model and satellite datasets should also account for sampling issues. The complementary DRE retrievals from OMI–MODIS and POLDER may benefit from upcoming satellite missions that combine spectrometer and polarimeter measurements.

Description: Solar-induced fluorescence (SIF) data from satellites are increasingly used as a proxy for photosynthetic activity by vegetation and as a constraint on gross primary production. Here we report on improvements in the algorithm to retrieve mid-morning (09:30 LT) SIF estimates on the global scale from the GOME-2 sensor on the MetOp-A satellite (GOME-2A) for the period 2007–2019. Our new SIFTER (Sun-Induced Fluorescence of Terrestrial Ecosystems Retrieval) v2 algorithm improves over a previous version by using a narrower spectral window that avoids strong oxygen absorption and being less sensitive to water vapour absorption, by constructing stable reference spectra from a 6-year period (2007–2012) of atmospheric spectra over the Sahara and by applying a latitude-dependent zero-level adjustment that accounts for biases in the data product. We generated stable, good-quality SIF retrievals between January 2007 and June 2013, when GOME-2A degradation in the near infrared was still limited. After the narrowing of the GOME-2A swath in July 2013, we characterised the throughput degradation of the level-1 data in order to derive reflectance corrections and apply these for the SIF retrievals between July 2013 and December 2018. SIFTER v2 data compare well with the independent NASA v2.8 data product. Especially in the evergreen tropics, SIFTER v2 no longer shows the underestimates against other satellite products that were seen in SIFTER v1. The new data product includes uncertainty estimates for individual observations and is best used for mostly clear-sky scenes and when spectral residuals remain below a certain spectral autocorrelation threshold. Our results support the use of SIFTER v2 data being used as an independent constraint on photosynthetic activity on regional to global scales.

Description: 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 polluted NO2 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 and NO2 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.

Description: The FRESCO (Fast Retrieval Scheme for Clouds from the Oxygen A band) algorithm is a simple, fast and robust algorithm used to retrieve cloud information in operational satellite data processing. It has been applied to GOME-1 (Global Ozone Monitoring Experiment), SCIAMACHY (Scanning Imaging Absorption Spectrometer for Atmospheric Chartography), GOME-2 and more recently to TROPOMI (Tropospheric Monitoring Instrument). FRESCO retrieves effective cloud fraction and cloud pressure from measurements in the oxygen A band around 761 nm. In this paper, we propose a new version of the algorithm, called FRESCO-B, which is based on measurements in the oxygen B band around 687 nm. Such a method is interesting for vegetated surfaces where the surface albedo is much lower in the B band than in the A band, which limits the ground contribution to the top-of-atmosphere reflectances. In this study we first perform retrieval simulations. These show that the retrieved cloud pressures from FRESCO-B and FRESCO differ only between −10 and +10 hPa, except for high, thin clouds over vegetation where the difference is larger (about +15 to +30 hPa), with FRESCO-B yielding higher pressure. Next, inter-comparison between FRESCO-B and FRESCO retrievals over 1 month of GOME-2B data reveals that the effective cloud fractions retrieved in the O2 A and B bands are very similar (mean difference of 0.003), while the cloud pressures show a mean difference of 11.5 hPa, with FRESCO-B retrieving higher pressures than FRESCO. This agrees with the simulations and is partly due to deeper photon penetrations of the O2 B band in clouds compared to the O2 A-band photons and partly due to the surface albedo bias in FRESCO. Finally, validation with ground-based measurements shows that the FRESCO-B cloud pressure represents an altitude within the cloud boundaries for clouds that are not too far from the Lambertian reflector model, which occurs in about 50 % of the cases.

Description: 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−2 with a standard deviation of 30 Wm−2. The maximum area-averaged instantaneous DRE from OMI–MODIS in August 2006 was 75.6±13 Wm−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.

Description: The Direct Radiative Effect (DRE) of aerosols above clouds has been found to be significant over the south-east Atlantic Ocean during the African biomass burning season due to elevated smoke layers absorbing radiation above the cloud deck. So far, global climate models have been unsuccessful in reproducing the high DRE values measured by various satellite instruments. Meanwhile, the radiative effects by aerosols have been identified as the largest source of uncertainty in global climate models. In this paper, three independent satellite datasets of DRE during the biomass burning season in 2006 are compared to constrain the south-east Atlantic radiation budget. The DRE of aerosols above clouds is derived from the spectrometer SCIAMACHY, the polarimeter POLDER, and from collocated measurements by the spectrometer OMI and imager MODIS. All three confirm the high DRE values during the biomass season, underlining the relevance of local aerosol effects. Differences between the instruments can be attributed mainly to sampling issues. When these are accounted for, the remaining differences can be completely explained by the higher cloud optical thickness derived from POLDER compared to the other instruments. Additionally, a neglect of AOT at SWIR wavelengths in the method used for SCIAMACHY and OMI/MODIS accounts for 26 % of the difference between POLDER and OMI/MODIS DRE.

Description: An improved tropospheric nitrogen dioxide (NO2) retrieval algorithm from the Global Ozone Monitoring Experiment-2 (GOME-2) instrument based on air mass factor (AMF) calculations performed with more realistic model parameters is presented. The viewing angle-dependency of surface albedo is taken into account by improving the GOME-2 Lambertian-equivalent reflectivity (LER) climatology with a directionally dependent LER (DLER) dataset over land and an ocean surface albedo parametrization over water. A priori NO2 profiles with higher spatial and temporal resolutions are obtained from the IFS(CB05BASCOE) chemistry transport model based on recent emission inventories. A more realistic cloud treatment is provided by a Cloud-As-Layers (CAL) approach, which treats the clouds as uniform layers of water droplets, instead of the current Clouds-as-Reflecting-Boundaries (CRB) model, which assumes the clouds as Lambertian reflectors. Improvements in the AMF calculation affect the tropospheric NO2 columns on average within ±15 % in winter and ±5 % in summer over largely polluted regions. In addition, the impact of aerosols on our tropospheric NO2 retrieval is investigated by comparing the concurrent retrievals based on ground-based aerosol measurements (explicit aerosol correction) and aerosol-induced cloud parameters (implicit aerosol correction). Compared to the implicit aerosol correction through the CRB cloud parameters, the use of CAL reduces the AMF errors by more than 10 %. Finally, to evaluate the improved GOME-2 tropospheric NO2 columns, a validation is performed using ground-based Multi-AXis Differential Optical Absorption Spectroscopy (MAXDOAS) measurements at the BIRA-IASB Xianghe station. The improved tropospheric NO2 dataset shows good agreement with coincident ground-based measurements with a correlation coefficient of 0.94 and a relative difference of −9.9 % on average.

Description: The FRESCO (Fast Retrieval Scheme for Clouds from the Oxygen A-band) algorithm is a simple, fast and robust algorithm used to retrieve cloud information in operational satellite data processing. It has been applied to GOME-1, SCIAMACHY, GOME-2 and more recently to TROPOMI. FRESCO retrieves effective cloud fraction and cloud pressure from measurements in the oxygen A-band around 761 nm. In this paper, we propose a new version of the algorithm, called FRESCO-B, which is based on measurements in the oxygen B-band around 687 nm. Such a method is interesting for vegetated surfaces where the surface albedo is much lower in the B-band than in the A-band, which limits the ground contribution to the top-of-atmosphere reflectances. In this study we first perform retrieval simulations. These show that the retrieved cloud pressures from FRESCO-B and FRESCO differ only between −10 hPa and +10 hPa, except for high thin clouds over vegetation where the difference is larger, about +15 to +30 hPa, with FRESCO-B yielding higher pressures. Next, inter-comparison between FRESCO-B and FRESCO retrievals over one month of GOME-2B data reveals that the effective cloud fractions retrieved in the O2 A and B bands are very similar (mean difference of 0.003) while the cloud pressures show a mean difference of 11.5 hPa, with FRESCO-B retrieving higher pressures than FRESCO. This agrees with the simulations and is partly due to deeper photons penetrations of O2 B-band in clouds as compared to the O2 A-band photons, and partly due to the surface albedo bias in FRESCO. Finally, validation with ground-based measurements shows that the FRESCO-B cloud pressure represents an altitude within the cloud boundaries for clouds that are not too far from the Lambertian reflector model, which occurs in about 50 % of the cases.

Description: 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 % over rugged terrain, 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-art RTMs LIDORT and SCIATRAN, we find that simulated TOA reflectance generally agrees to within 1 %. By replacing the assumption of isotropic surface reflection in the cloud retrievals over vegetated scenes with scattering kernels and corresponding BRDF parameters from a daily, high-resolution database derived from 16 years' worth of MODIS measurements, the East-West bias in the retrieved cloud fractions largely vanishes. We conclude that across-track biases in cloud fractions can be explained by cloud algorithms not adequately accounting for the effects of surface reflectance anisotropy. The implications for NO2 air mass factor (AMF) calculations are substantial. Under moderately polluted NO2 and backscatter 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 backscatter geometries (and decrease by up to 35 % for forward scattering geometries), 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 emphasize that surface reflectance anisotropy needs to be taken into account in a coherent manner for more realistic and accurate retrievals of clouds and NO2 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.

Description: 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 OMI/Aura and MODIS/Aqua 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 SCIAMACHY/Envisat, which had the unique capability of measuring contiguous radiances from the ultraviolet (UV) at 240 nm to 1750 nm in the shortwave-infrared (SWIR), at a moderate spectral resolution of 0.2–1.5 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. The new aerosol DRE over clouds dataset from OMI/MODIS is compared to the SCIAMACHY dataset for the period 2006–2009, showing a very high correlation. The average aerosol DRE over clouds in August 2006 was 31.5 Wm−2 with a standard deviation of 16 Wm−2. The maximum daily averaged DRE from OMI/MODIS in August 2006 was 75.6 ± 13 Wm−2. Over the Atlantic Ocean, the OMI/MODIS DRE dataset 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.