In this paper we describe and summarize the main achievements of the European Aerosol Cloud Climate and Air Quality Interactions project (EUCAARI). EUCAARI started on 1 January 2007 and ended on 31 December 2010 leaving a rich legacy including: (a) a comprehensive database with a year of observations of the physical, chemical and optical properties of aerosol particles over Europe, (b) the first comprehensive aerosol measurements in four developing countries, (c) a database of airborne measurements of aerosols and clouds over Europe during May 2008, (d) comprehensive modeling tools to study aerosol processes fron nano to global scale and their effects on climate and air quality. In addition a new Pan-European aerosol emissions inventory was developed and evaluated, a new cluster spectrometer was built and tested in the field and several new aerosol parameterizations and computations modules for chemical transport and global climate models were developed and evaluated. This work enabled EUCAARI to improve our understanding of aerosol radiative forcing and air quality-climate interactions. The EUCAARI results can be utilized in European and global environmental policy to assess the aerosol impacts and the corresponding abatement strategies
One major source of uncertainty in the cloud-mediated aerosol forcing arises from the magnitude of the cloud liquid water path (LWP) adjustment to aerosol-cloud interactions, which is poorly constrained by observations. Many of the recent satellite-based studies have observed a decreasing LWP as a function of cloud droplet number concentration (CDNC) as the dominating behavior. Estimating the LWP response to the CDNC changes is a complex task since various confounding factors need to be isolated. However, an important aspect has not been sufficiently considered: the propagation of natural spatial variability and errors in satellite retrievals of cloud optical depth and cloud effective radius to estimates of CDNC and LWP. Here we use satellite and simulated measurements to demonstrate that, because of this propagation, even a positive LWP adjustment is likely to be misinterpreted as negative. This biasing effect therefore leads to an underestimate of the aerosol-cloud-climate cooling and must be properly considered in future studies.
Abstract. The uncertainty associated with satellite-retrieved aerosol properties is needed when these data are used to constrain chemical transport or climate models by using data assimilation. Global uncertainty as provided by comparison with independent ground-based observations is usually not adequate for that purpose. Rather the per-pixel uncertainty is needed. In this work we describe how these are determined in the AATSR dual and single view aerosol retrieval algorithms (ADV and ASV) which are used to retrieve aerosol optical properties from reflectance measured at the top of the atmosphere. AATSR is the Aerosol Along-Track Scanning Radiometer which flies on the European Space Agency Environmental Satellite ENVISAT. In addition, issues related to multi-year retrievals are described and discussed. The aerosol optical depth (AOD) retrieved for the year 2008 is validated versus ground-based AERONET sun photometer measurements with good agreement (r = 0.85). The comparison of the AOD uncertainties with those provided by AERONET shows that they behave well in a statistical sense. Other considerations regarding global multi-year aerosol retrievals are presented and discussed.
Within the ESA Climate Change Initiative (CCI) project Aerosol_cci (2010–2013) algorithms for the production of long-term total column aerosol optical depth (AOD) datasets from European Earth Observation sensors are developed. Starting with eight existing pre-cursor algorithms three analysis steps are conducted to improve and qualify the algorithms: (1) a series of experiments applied to one month of global data to understand several major sensitivities to assumptions needed due to the ill-posed nature of the underlying inversion problem, (2) a round robin exercise of "best" versions of each of these algorithms (defined using the step 1 outcome) applied to four months of global data to identify mature algorithms, and (3) a comprehensive validation exercise applied to one complete year of global data produced by the algorithms selected as mature based on the round robin exercise. The algorithms tested included four using AATSR, three using MERIS and one using PARASOL.
This paper summarizes the first step. Three experiments were conducted to assess the potential impact of major assumptions in the various aerosol retrieval algorithms. In the first experiment a common set of four aerosol components was used to provide all algorithms with the same assumptions. The second experiment introduced an aerosol property climatology, derived from a combination of model and sun photometer observations, as a priori information in the retrievals on the occurrence of the common aerosol components and their mixing ratios. The third experiment assessed the impact of using a common nadir cloud mask for AATSR and MERIS algorithms in order to characterize the sensitivity to remaining cloud contamination in the retrievals against the baseline dataset versions. The impact of the algorithm changes was assessed for one month (September 2008) of data qualitatively by visible analysis of monthly mean AOD maps and quantitatively by comparing global daily gridded satellite data against daily average AERONET sun photometer observations for the different versions of each algorithm.
The analysis allowed an assessment of sensitivities of all algorithms which helped define the best algorithm version for the subsequent round robin exercise; all algorithms (except for MERIS) showed some, in parts significant, improvement. In particular, using common aerosol components and partly also a priori aerosol type climatology is beneficial. On the other hand the use of an AATSR-based common cloud mask meant a clear improvement (though with significant reduction of coverage) for the MERIS standard product, but not for the algorithms using AATSR
Abstract. A satellite-based approach to derive the aerosol direct short wave (SW) radiative effect (ADRE) was studied in an environment with highly variable aerosol conditions over Eastern China from March to October 2009. The method is based on using coincident SW Top of the Atmosphere (TOA) fluxes from the Clouds and the Earth's Radiant Energy System (CERES) and aerosol optical depths (AODs) from the Moderate Resolution Imaging Sectroradiometer (MODIS). The estimate for instantaneous clear sky ADRE is obtained by establishing linear regression between CERES fluxes and MODIS AODs. Even though the approach has been used in a number of studies, less focus has been paid to the method itself. In this study the main goals were first to study the method in more detail as well as it's applicability over Eastern China, and second to derive a satellite-based estimate of ADRE over the study area. Before the linear fitting, CERES fluxes were normalized to a fixed solar zenith angle, Earth–Sun distance and atmospheric water vapour content to reduce the noise in the flux observations that was not related to aerosols. The satellite based clear sky estimates for median instantaneous and diurnally averaged ADRE over the study area were −8.8 W m−2, and −5.1 W m−2, respectively. Over heavily industrialized areas the cooling at TOA was two to more than three times the median value, and associated with high AODs (>0.5). Especially during the summer months positive ADREs were observed locally over dark surfaces. This was most probably a method artifact related to systematic change of aerosol type, subvisual cloud contamination or both. The key question in the satellite-based approach is the accuracy of the estimated aerosol-free TOA flux (F0,TOA). Comparison with simulated F0,TOA showed that both the satellite method and the model produced qualitatively similar spatial patterns, but absolute values differed. In 58% of the cases the satellite based F0,TOA was within ±10 W m−2 of the modeled value. Over bright surfaces the satellite-based method tend to produce lower F0,TOA than the model.
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