For the determination of aerosol optical thickness (AOT) Bremen AErosol Retrieval (BAER) has been developed. Method and main features on the aerosol retrieval are described together with validation ...and results. The retrieval separates the spectral aerosol reflectance from surface and Rayleigh path reflectance for the shortwave range of the measured spectrum of top-of-atmosphere reflectance for wavelength less than 0.670 μm. The advantage of MERIS (Medium Resolution Imaging Spectrometer on the Environmental Satellite – ENVISAT – of the European Space Agency – ESA) and SeaWiFS (Sea viewing Wide Field Sensor on OrbView-2 spacecraft) observations is the availability of several spectral channels in the blue and visible range enabling the spectral determination of AOT in 7 (or 6) channels (0.412–0.670 μm) and additionally channels in the NIR, which can be used to characterize the surface properties. A dynamical spectral surface reflectance model for different surface types is used to obtain the spectral surface reflectance for this separation. The normalized differential vegetation index (NDVI), taken from the satellite observations, is the model input. Further surface bi-directional reflectance distribution function (BRDF) is considered by the Raman-Pinty-Verstraete (RPV) model. Spectral AOT is obtained from aerosol reflectance using look-up-tables, obtained from radiative transfer calculations with given aerosol phase functions and single scattering albedos either from aerosol models, given by model package "optical properties of aerosol components" (OPAC) or from experimental campaigns. Validations of the obtained AOT retrieval results with data of Aerosol Robotic Network (AERONET) over Europe gave a preference for experimental phase functions derived from almucantar measurements. Finally long-term observations of SeaWiFS have been investigated for 11 year trends in AOT. Western European regions have negative trends with decreasing AOT with time. For the investigated Asian region increasing AOT have been found.
We present a global and regional multi-annual (June 1996–May 2003) analysis of cloud properties (spherical cloud albedo – CA, cloud optical thickness – COT and cloud top height – CTH) of optically ...thick (COT > 5) clouds, derived using measurements from the GOME instrument on board the ESA ERS-2 space platform. We focus on cloud top height, which is obtained from top-of-atmosphere backscattered solar light measurements in the O2 A-band using the Semi-Analytical CloUd Retrieval Algorithm SACURA. The physical framework relies on the asymptotic equations of radiative transfer. The dataset has been validated against independent ground- and satellite-based retrievals and is aimed to support trace-gases retrievals as well as to create a robust long-term climatology together with SCIAMACHY and GOME-2 ensuing retrievals. We observed the El Niño-Southern Oscillation anomaly in the 1997–1998 record through CTH values over the Pacific Ocean. The global average CTH as derived from GOME is 5.6 ± 3.2 km, for a corresponding average COT of 19.1 ± 13.9.
One significant limitation to the accuracy of the remote sensing of trace gas constituents in the atmosphere, using UV-visible spectroscopy and scattered sunlight, has often been a reliable knowledge ...of the so-called Ring effect. In this study it is demonstrated that the filling-in of Fraunhofer and gas absorption features, resulting from Rotational Raman scattering (RRS), explains to high accuracy the Ring effect. A radiative transfer model has been adapted to include RRS and carefully validated by comparison with Ring effect data by other models and from ground-based and satellite data. The analysis of the principle components of the simulated Ring spectra enabled the Fraunhofer and gas absorption filling-in to be separated. This yields a simple, and therefore computational fast, parameterization of the Ring effect suitable for trace gas retrievals. This approach was tested for the retrieval of NO
2 which is considered to be a worst case with respect to absorption feature filling-in for a trace gas retrieved from scattered light. Analysis of the errors in the vertical column of NO
2 derived using differential optical absorption spectroscopy (DOAS) technique indicate that they are dependent on the amount of NO
2 present in the atmosphere when regarding the experimental Ring spectra. This implies that calculated Ring spectra may be superior for DOAS retrievals, compared to the experimentally determined Ring spectra.
Two decades of measurements of spectral reflectance of solar radiation at
the top of the atmosphere and a complementary record of cloud properties
from satellite passive remote sensing have been ...analyzed for their
pan-Arctic, regional, and seasonal changes. The pan-Arctic loss of
brightness, which is explained by the retreat of sea ice during the current
warming period, is not compensated by a corresponding increase in cloud
cover. A systematic change in the thermodynamic phase of clouds has taken
place, shifting towards the liquid phase at the expense of the ice phase.
Without significantly changing the total cloud optical thickness or the
mass of condensed water in the atmosphere, liquid water content has
increased, resulting in positive trends in liquid cloud optical thickness
and albedo. This leads to a cooling trend by clouds being superimposed on
top of the pan-Arctic amplified warming, induced by the anthropogenic
release of greenhouse gases, the ice–albedo feedback, and related effects.
Except over the permanent and parts of the marginal sea ice zone around the
Arctic Circle, the rate of surface cooling by clouds has increased, both in
spring (−32 % in total radiative forcing for the whole Arctic) and in
summer (−14 %). The magnitude of this effect depends on both the
underlying surface type and changes in the regional Arctic climate.
Results of a new methodology for retrievals of surface particulate matter concentration (PM10) from satellite reflectance measurements over Germany are presented in this paper. The retrieval derives ...effective radii from Ångström-α exponents and benefits from the fitting of a smooth spectral slope from seven MERIS spectrometer channels. Comparisons with ground measurements from the air quality surveillance show standard deviations of 33.9% with −18.9% bias over Hamburg. Over rural sites a standard deviation of 17.9% (bias 12.9%) is reached. We discuss critically limitations and potential applications of the retrieval. Additionally, we talk about the aspects at comparing of retrieved particulate matter with ground station measurements.
A cloud identification algorithm used for cloud masking, which is based on the spatial variability of reflectances at the top of the atmosphere in visible wavelengths, has been developed for the ...retrieval of aerosol properties by MODIS. It is shown that the spatial pattern of cloud reflectance, as observed from space, is very different from that of aerosols. Clouds show a high spatial variability in the scale of a hundred metres to a few kilometres, whereas aerosols in general are homogeneous. The concept of spatial variability of reflectances at the top of the atmosphere is mainly applicable over the ocean, where the surface background is sufficiently homogeneous for the separation between aerosols and clouds. Aerosol retrievals require a sufficiently accurate cloud identification to be able to mask these ground scenes. However, a conservative mask will exclude strong aerosol episodes and a less conservative mask could introduce cloud contamination that biases the retrieved aerosol optical properties (e.g. aerosol optical depth and effective radii). A detailed study on the effect of cloud contamination on aerosol retrievals has been performed and parameters are established determining the threshold value for the MODIS aerosol cloud mask (3×3-STD) over the ocean. The 3×3-STD algorithm discussed in this paper is the operational cloud mask used for MODIS aerosol retrievals over the ocean. A prolonged pollution haze event occurred in the northeast part of China during the period 16–21 December 2016. To assess the impact of such events, the amounts and distribution of aerosol particles, formed in such events, need to be quantified. The newly launched Ocean Land Colour Instrument (OLCI) onboard Sentinel-3 is the successor of the MEdium Resolution Imaging Spectrometer (MERIS). It provides measurements of the radiance and reflectance at the top of the atmosphere, which can be used to retrieve the aerosol optical thickness (AOT) from synoptic to global scales. In this study, the recently developed AOT retrieval algorithm eXtensible Bremen AErosol Retrieval (XBAER) has been applied to data from the OLCI instrument for the first time to illustrate the feasibility of applying XBAER to the data from this new instrument. The first global retrieval results show similar patterns of aerosol optical thickness, AOT, to those from MODIS and MISR aerosol products. The AOT retrieved from OLCI is validated by comparison with AERONET observations and a correlation coefficient of 0.819 and bias (root mean square) of 0.115 is obtained. The haze episode is well captured by the OLCI-derived AOT product. XBAER is shown to retrieve AOT well from the observations of MERIS and OLCI.
The central Arctic cryosphere is influenced by the Arctic amplification (AA) and is warming faster than the lower latitudes. AA affects the formation, loss, and transport of aerosols. Efforts to ...assess the underlying processes determining aerosol variability are currently limited due to the lack of ground-based and space-borne aerosol observations with high spatial coverage in this region. This study addresses the observational gap by making use of total aerosol optical depth (AOD) datasets retrieved by the AEROSNOW algorithm over the vast cryospheric region of the central Arctic during Arctic spring and summer. GEOS-Chem (GC) simulations combined with AEROSNOW-retrieved data are used to investigate the processes controlling aerosol loading and distribution at different temporal and spatial scales. For the first time, an integrated study of AOD over the Arctic cryosphere during sunlight conditions was possible with the AEROSNOW retrieval and GC simulations. The results show that the spatial patterns observed by AEROSNOW differ from those simulated by GC. During spring, which is characterized by long-range transport of anthropogenic aerosols in the Arctic, GC underestimates the AOD in the vicinity of Alaska in comparison with AEROSNOW retrieval. At the same time, it overestimates the AOD along the Bering Strait, northern Europe, and the Siberian central Arctic sea-ice regions, with differences of -12.3 % and 21.7 %, respectively. By contrast, GC consistently underestimates AOD compared with AEROSNOW in summer, when transport from lower latitudes is insignificant and local natural processes are the dominant source of aerosol, especially north of 70° N. This underestimation is particularly pronounced over the central Arctic sea-ice region, where it is -10.6 %. Conversely, GC tends to overestimate AOD along the Siberian and Greenland marginal sea-ice zones by 19.5 % but underestimates AOD along the Canadian Archipelago by -9.3 %. The differences in summer AOD between AEROSNOW data products and GC-simulated AOD highlight the need to integrate improved knowledge of the summer aerosol process into existing models in order to constrain its effects on cloud condensation nuclei, on ice nucleating particles, and on the radiation budget over the central Arctic sea ice during the developing AA period.
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