ALBERT

Description: The detection of multilayer cloud situations is important for satellite retrieval algorithms and for many climate-related applications. In this paper, the authors describe an algorithm based on the exploitation of the Polarization and Directionality of the Earth’s Reflectance (POLDER) observations to identify monolayered and multilayered cloudy situations along with a confidence index. The authors’ reference comes from the synergy of the active instruments of the A-Train satellite constellation. The algorithm is based upon a decision tree that uses a metric from information theory and a series of tests on POLDER level-2 products. The authors obtain a multilayer flag as the final result of a tree classification, which takes discrete values between 0 and 100. Values closest to 0 (100) indicate a higher confidence in the monolayer (multilayer) character. This indicator can be used as it is or with a threshold level that minimizes the risk of misclassification, as a binary index to distinguish between monolayer and multilayer clouds. For almost fully covered and optically thick enough cloud scenes, the risk of misclassification ranges from 29% to 34% over the period 2006–10, and the average confidences in the estimated monolayer and multilayer characters of the cloud scenes are 74.0% and 58.2%, respectively. With the binary distinction, POLDER provides a climatology of the mono–multilayer cloud character that exhibits some interesting features. Comparisons with the performance of the Moderate Resolution Imaging Spectroradiometer (MODIS) multilayer flag are given.

Description: The global spatial and diurnal distribution of cloud properties is a key issue for understanding the hydrological cycle, and critical for advancing efforts to improve numerical weather models and general circulation models. Satellite data provides the best way of gaining insight into global cloud properties. In particular, the determination of cloud thermodynamic phase is a critical first step in the process of inferring cloud optical and microphysical properties from satellite measurements. It is important that cloud phase be derived together with an estimate of the confidence of this determination, so that this information can be included with subsequent retrievals (optical thickness, effective particle radius, and ice/liquid water content). In this study, we combine three different and well documented approaches for inferring cloud phase into a single algorithm. The algorithm is applied to data obtained by the MODIS (MODerate resolution Imaging Spectroradiometer) and POLDER3 (Polarization and Directionality of the Earth Reflectance) instruments. It is shown that this synergistic algorithm can be used routinely to derive cloud phase along with an index that helps to discriminate ambiguous phase from confident phase cases. The resulting product provides a semi-continuous index ranging from confident liquid to confident ice instead of the usual discrete classification of liquid phase, ice phase, mixed phase (potential combination of ice and liquid particles), or simply unknown phase clouds. The index value provides simultaneously information on the phase and the associated confidence. This approach is expected to be useful for cloud assimilation and modeling efforts while providing more insight into the global cloud properties derived from satellite data.

Description: Cloud optical thickness (COT) is one of the most important parameter for the characterization of cloud in the Earth radiative budget. Its retrieval strongly depends on instrument characteristics and on many cloud and environment factors. Using coincident observations from POLDER/PARASOL and MODIS/AQUA in the A-Train constellation, geographical distributions and seasonal changes of COT are presented, in good agreement with general cloud climatology characteristics. Retrieval uncertainties mainly associated to sensor spatial resolution, cloud inhomogeneity and microphysical assumptions are discussed. Comparisons of COT derived from POLDER and MODIS illustrate that as the primary factor, the sensor spatial resolution impacts COT retrievals and statistics through both cloud detection and sub-pixel cloud inhomogeneity sensitivity. The uncertainties associated to cloud microphysics assumptions, namely cloud phase, particle size and shape, also impact significantly COT retrievals. For clouds with unambiguous cloud phase, strong correlations exist between the two COTs, with MODIS values comparable to POLDER ones for liquid clouds and MODIS values larger than POLDER ones for ice clouds. The large differences observed in ice phase cases are due to the use of different microphysical models in the two retrieval schemes. In cases when the two sensors disagree on cloud phase decision, COT retrieved assuming liquid phase is systematically larger. The angular biases related to specific observation geometries are also quantified and discussed in particular based on POLDER observations. Those exhibit a clear increase of COT with decreasing sun elevation and a decrease of COT in forward scattering directions due to sub-pixel inhomogeneities and shadowing effects, this especially for lower sun. It also demonstrates unrealistic COT variations in the cloudbow and backward directions due to inappropriate cloud optical properties representation and an important increase of COT in the sun-glint directions in case of broken cloud.

Description: Cloud optical thickness (COT) is one of the most important parameter for the characterization of cloud in the Earth radiative budget. Its retrieval strongly depends on instrument characteristics and on many cloud and environment factors. Using coincident observations from POLDER/PARASOL and MODIS/AQUA in the A-train constellation, geographical distributions and seasonal changes of COT are presented, in good agreement with general cloud climatology characteristics. Retrieval uncertainties mainly associated to sensor spatial resolution, cloud inhomogeneity and microphysical assumptions are also discussed. Comparisons of COT derived from POLDER and MODIS illustrate that as the primary factor, the sensor spatial resolution impacts COT retrievals and statistics through both cloud detection and sub-pixel cloud inhomogeneity sensitivity. The uncertainties associated to cloud microphysics assumptions, namely cloud phase, particle size and shape, also impact significantly COT retrievals. For clouds with unambiguous cloud phase, strong correlations exist between the two COTs, with MODIS values comparable to POLDER ones for liquid clouds and MODIS values larger than POLDER ones for ice clouds. The large differences observed in ice phase cases are due to the use of different microphysical models in the two retrieval schemes. In cases when the two sensors disagree on cloud phase decision, COT retrieved assuming liquid phase are systematically larger. The angular biases related to specific observation geometries are also quantified and discussed in particular based on POLDER observations. Those exhibit a clear increase of COT with decreasing sun elevation and a decrease of COT in forward scattering directions due to sub-pixel inhomogeneities and shadowing effects, this especially for lower sun. It also demonstrates unrealistic COT variations in the rainbow and backward directions due to inappropriate cloud optical properties representation and an important increase of COT in the sun-glint directions in case of broken cloud.

Description: Sulfur-rich degassing, which is mostly composed of sulfur dioxide (SO2), plays a major role in the overall impact of volcanism on the atmosphere and climate. The accurate assessment of this impact is currently hampered by the poor knowledge of volcanic SO2 emissions. Here, using an inversion procedure, we show how assimilating snapshots of the volcanic SO2 load derived from the Infrared Atmospheric Sounding Interferometer (IASI) allows for reconstructing both the flux and altitude of the SO2 emissions with an hourly resolution. For this purpose, the regional chemistry-transport model CHIMERE is used to describe the dispersion of SO2 when released in the atmosphere. As proof of concept, we study the 10 April 2011 eruption of the Etna volcano (Italy), which represents one of the few volcanoes instrumented on the ground for the continuous monitoring of SO2 degassing. We find that the SO2 flux time-series retrieved from satellite imagery using the inverse scheme is in agreement with ground observations during ash-poor phases of the eruption. However, large discrepancies are observed during the ash-rich paroxysmal phase as a result of enhanced plume opacity affecting ground-based ultraviolet (UV) spectroscopic retrievals. As a consequence, the SO2 emission rate derived from the ground is underestimated by almost one order of magnitude. Altitudes of the SO2 emissions predicted by the inverse scheme are validated against a RGB MODIS image capturing the near-source atmospheric pathways followed by Etna plumes, in combination with forward trajectories from the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model. At large distance from the source, modeled SO2 altitudes are confronted with independent information on the volcanic cloud height. We find that the altitude predicted by the inverse scheme is in agreement with snapshots of the SO2 height retrieved from recent algorithms exploiting the high spectral resolution of IASI. The validity of the modeled SO2 altitude is further confirmed by the detection of a layer of particles at the same altitude by the spaceborne CALIOP LiDAR. Analysis of CALIOP color and depolarization ratios suggests that these particles consist of sulfate aerosols formed from precursory volcanic SO2. The reconstruction of emission altitude, through inversion procedures which assimilate volcanic SO2 column amounts, requires specific meteorological conditions, especially sufficient wind shear so that gas parcels emitted at different altitudes follow distinct trajectories. We consequently explore the possibility and limits of assimilating in inverse schemes infrared (IR) imagery of the volcanic SO2 cloud altitude which will render the inversion procedure independent of the wind shear prerequisite.

Description: Total and polarized radiances provided by the Polarization and Directionality of Earth Reflectances (POLDER) satellite sensor are used to retrieve the microphysical and optical properties of the volcanic plume observed during the Eyjafjallajökull volcano eruption in 2010, over cloud-free and cloudy ocean scenes. We selected two plume conditions, fresh aerosols near the sources (three cases) and a downwind volcanic plume observed over the North Sea 30 h after its injection into the atmosphere (aged aerosols). In the near-source conditions, the aerosol properties depend on the distance to the plume. Within the plume, aerosols are mainly non-spherical and in the coarse mode with an effective radius equal to 1.50 (± 0.15) μm and an Ångström Exponent (AE) close to 0.0. Far from the plume, in addition to the coarse mode, there are smaller particles retrieved in the accumulation mode suggesting a mixture of sulfate aerosols and volcanic dust, resulting in an AE around 0.8. The properties of the aerosols also depend on whether the plume is fresh or aged. For the downwind (aged) plume, if non-spherical coarse particles as well as some fine mode particles are still retrieved, the AE is smaller, around ~ 0.4. In addition, the real refractive index (RR) values are larger for the downwind plume (1.42 〈 RR 〈 1.58) than for the near-source plume (1.38 〈 RR 〈 1.48). The mean Single Scattering Albedo (SSA) retrieved at 0.865 μm was estimated at 0.97 over some parts of the downwind and near-source plumes; despite the low accuracy of our retrievals, the derived SSA values suggest that the ash particles are rather absorbing. To consider the particle shape, a combination of spheroid models is used. Although the employed model enabled accurate modeling of the POLDER signal in case of non-spherical ash, our approach failed to model the signal over the optically thickest parts of the near-source plume. The most probable reason for this is speculated to be the presence of ice crystals within the plume. For the Aerosol Above Clouds (AAC) scenes, polarized measurements allowed the retrieval of the Optical Thickness (OT) and the AE of optically thin volcanic ash. We found that all the cloud parameters retrieved by passive sensors were biased due to the presence of the elevated volcanic plumes. Finally, thermal infrared measurements were used to identify the type of multi-layer scene (i.e. cirrus clouds or volcanic dust above liquid clouds) and the retrieval method also provided the OT of thin cirrus layers above the clouds near Iceland.

Description: The albedo of clouds and the aerosol absorption are key parameters to evaluate the direct radiative effect of an aerosol layer above clouds. While most of the retrievals of above clouds aerosol characteristics rely on assumptions on the aerosol properties, this study offers a new method to evaluate aerosol and cloud optical properties simultaneously (i.e. aerosol and cloud optical thickness, aerosol single scattering albedo and angström exponent). It is based on multi-angle total and polarized radiances both provided by the A-train satellite instrument POLDER – Polarization and Directionality of Earth Reflectances. The sensitivities brought by each kind of measurements are used in a complementary way. Polarization mostly translates scattering processes and is thus used to estimate the scattering aerosol optical thickness and the aerosol size. On the other hand, total radiances, together with the scattering properties of aerosols, are used to evaluate the absorption optical thickness of aerosols and the cloud optical thickness. In addition, a procedure has been developed to process the shortwave direct radiative effect of aerosols above clouds based on exact modeling. Besides the three case studies (i.e. biomass burning aerosols from Africa and Siberia and Saharan dust), both algorithms have been applied on the South East Atlantic Ocean and results have been averaged through August 2006. The mean direct radiative effect is found to be 33.5 W m−2. Finally, the effect of the heterogeneity of clouds has been investigated and reveals that it affects mostly the retrieval of the cloud optical thickness and not much the aerosols properties. The homogenous cloud assumption used in both the properties retrieval and the DRE processing leads to a slight underestimation of the DRE.