Published by Copernicus Publications on behalf of the European Geosciences Union. 8698 J. Quaas et al.: Aerosol indirect effects -general circulation model intercomparisonbetween τ a and f cld . The short-wave total aerosol radiative forcing as simulated by the GCMs is strongly influenced by the simulated anthropogenic fraction of τ a , and parameterisation assumptions such as a lower bound on N d . Nevertheless, the strengths of the statistical relationships are good predictors for the aerosol forcings in the models. An estimate of the total short-wave aerosol forcing inferred from the combination of these predictors for the modelled forcings with the satellite-derived statistical relationships yields a global annual mean value of −1.5±0.5 Wm −2 . In an alternative approach, the radiative flux perturbation due to anthropogenic aerosols can be broken down into a component over the cloud-free portion of the globe (approximately the aerosol direct effect) and a component over the cloudy portion of the globe (approximately the aerosol indirect effect). An estimate obtained by scaling these simulated clearand cloudy-sky forcings with estimates of anthropogenic τ a and satellite-retrieved N d -τ a regression slopes, respectively, yields a global, annual-mean aerosol direct effect estimate of −0.4±0.2 Wm −2 and a cloudy-sky (aerosol indirect effect) estimate of −0.7±0.5 Wm −2 , with a total estimate of −1.2±0.4 Wm −2 .
Producing a global and comprehensive description of atmospheric aerosols requires integration of ground-based, airborne, satellite and model datasets. Due to its complexity, aerosol monitoring requires the use of several data records with complementary information
[1] The Sea-viewing Wide Field-of-view Sensor (SeaWiFS) provides a well-calibrated 13-year (1997-2010) record of top-of-atmosphere radiance, suitable for use in retrieval of atmospheric aerosol optical depth (AOD). This paper presents and validates a SeaWiFS Ocean Aerosol Retrieval (SOAR) algorithm, which retrieves the AOD at 550 nm and the partition of aerosol particle volume between fine and coarse modes. The algorithm has been applied over water to the whole SeaWiFS record. The data set includes quality flags to identify those retrievals suitable for quantitative use. SOAR has been validated against Aerosol Robotic Network (AERONET) and Maritime Aerosol Network (MAN) data and found to compare well (correlation 0.86 at 550 nm and 0.88 at 870 nm for AERONET, and 0.87 at 550 nm and 0.85 at 870 nm for MAN, using recommended quality control settings). These comparisons are used to identify the typical level of uncertainty on the AOD, estimated as 0.03 + 15% at 550 nm and 0.03 + 10% at 870 nm. The data set also includes the Ångström exponent, although as expected this is noisy for low aerosol loadings (correlation 0.50; 0.78 for points where the AOD at 550 nm is 0.3 or more). Retrieved AOD is compared with colocated observations from other satellite sensors; regional and seasonal patterns are found to be common between all data sets, and differences generally linked to factors such as cloud screening and retrieval assumptions.
Abstract. New cloud property datasets based on measurements from the passive imaging satellite sensors AVHRR, MODIS, ATSR2, AATSR and MERIS are presented. Two retrieval systems were developed that include components for cloud detection and cloud typing followed by cloud property retrievals based on the optimal estimation (OE) technique. The OE-based retrievals are applied to simultaneously retrieve cloud-top pressure, cloud particle effective radius and cloud optical thickness using measurements at visible, near-infrared and thermal infrared wavelengths, which ensures spectral consistency. The retrieved cloud properties are further processed to derive cloud-top height, cloud-top temperature, cloud liquid water path, cloud ice water path and spectral cloud albedo. The Cloud_cci products are pixel-based retrievals, daily composites of those on a global equal-angle latitude-longitude grid, and monthly cloud properties such as averages, standard deviations and histograms, also on a global grid. All products include rigorous propagation of the retrieval and sampling uncertainties. Grouping the orbital properties of the sensor families, six datasets have been defined, which are named AVHRR-AM, AVHRR-PM, MODIS-Terra, MODIS-Aqua, ATSR2-AATSR and MERIS+AATSR, each comprising a specific subset of all available sensors. The individual characteristics of the datasets are presented together with a summary of the retrieval systems and measurement records on which the dataset generation were based. Example validation results are given, based on comparisons to well-established reference observations, which demonstrate the good quality of the data. In particular the ensured spectral consistency and the rigorous Published by Copernicus Publications. M. Stengel et al.: Cloud_cci datasetsuncertainty propagation through all processing levels can be considered as new features of the Cloud_cci datasets compared to existing datasets. In addition, the consistency among the individual datasets allows for a potential combination of them as well as facilitates studies on the impact of temporal sampling and spatial resolution on cloud climatologies.
Abstract.A model of the sea surface bidirectional reflectance distribution function (BRDF) is presented for the visible and near-IR channels (over the spectral range 550 nm to 1.6 µm) of the dual-viewing Along-Track Scanning Radiometers (ATSRs). The intended application is as part of the Oxford-RAL Aerosols and Clouds (ORAC) retrieval scheme. The model accounts for contributions to the observed reflectance from whitecaps, sun-glint and underlight. Uncertainties in the parametrisations used in the BRDF model are propagated through into the forward model and retrieved state. The new BRDF model offers improved coverage over previous methods, as retrievals are possible into the sunglint region, through the ATSR dual-viewing system. The new model has been applied in the ORAC aerosol retrieval algorithm to process Advanced ATSR (AATSR) data from September 2004 over the south-eastern Pacific. The assumed error budget is shown to be generally appropriate, meaning the retrieved states are consistent with the measurements and a priori assumptions. The resulting field of aerosol optical depth (AOD) is compared with colocated MODIS-Terra observations, AERONET observations at Tahiti, and cruises over the oceanic region. MODIS and AATSR show similar spatial distributions of AOD, although MODIS reports values which are larger and more variable. It is suggested that assumptions in the MODIS aerosol retrieval algorithm may lead to a positive bias in MODIS AOD of order 0.01 at 550 nm over ocean regions where the wind speed is high.
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