Earth Observation Data Group

Abstract:

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. 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 inspection of monthly mean AOD maps and quantitatively by comparing daily gridded satellite data against daily averaged AERONET sun photometer observations for the different versions of each algorithm globally (land and coastal) and for three regions with different aerosol regimes. The analysis allowed for an assessment of sensitivities of all algorithms, which helped define the best algorithm versions 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. It is noted that all these observations are mostly consistent for all five analyses (global land, global coastal, three regional), which can be understood well, since the set of aerosol components defined in Sect. 3.1 was explicitly designed to cover different global aerosol regimes (with low and high absorption fine mode, sea salt and dust). © Author(s) 2013.

Abstract:

Airborne volcanic ash poses a significant danger to aircraft, but is difficult to quantify accurately using satellite data, while sulphur dioxide is much easier to detect accurately, but is much less of a direct hazard to aviation. This paper investigates the reliability of using SO2 as a proxy for the location of volcanic ash, using an SO2 retrieval from the Infrared Atmospheric Sounding Interferometer (IASI) and ash detections from IASI and the Advanced Along Track Scanning Radiometer (AATSR). Using a numerical “missed ash fraction” applied to the eruptions of Eyjafjallajökull in 2010 and Puyehue‐Cordón Caulle in 2011 reveals that the SO2 flag typically misses ∼30% of the detectable ash. Furthermore, the missed ash fraction is found to be highly variable, both between the two eruptions and over the course of each eruption, with values of over 80% found on some days. The detection threshold of the AATSR ash flag is also investigated using radiative transfer calculations, allowing the threshold of the IASI flag to be inferred, and these are related to the ash contamination levels.

Abstract:

Meteorological covariation may drive relationships between aerosol and cloud-related properties. It is important to account for the meteorological contribution to observed cloud–aerosol relationships in order to improve understanding of aerosol–cloud–climate interactions. A new method of investigating the contribution of meteorological covariation to observed cloud–aerosol relationships is introduced. Other studies have investigated the contribution of local meteorology to cloud–aerosol relationships. In this paper, a complimentary large-scale view is presented. Extratropical cyclones have been previously shown to affect satellite-retrieved aerosol optical depth (τ), due to en- hanced emission of sea salt and sea surface brightness artefacts in regions of higher wind speed. Extratropical cyclones have also been shown to affect cloud-related properties such as cloud fraction (fc) and cloud top temperature (Ttop). Therefore, it seems plausible to hypothesise that extratropical cyclones may drive relationships between cloud-related properties and τ. In this paper, a description of extratropical cyclones, based on the relative vorticity of the storm and position in the storm domain, is used to analyse MODerate resolution Imaging Spectroradiometer (MODIS) retrieved τ, fc and Ttop data. This storm-centric description is capable of explaining fc–τrelationships, although the relationships explained represent only a small component of the relationships observed in the MODIS data. This storm-centric approach produces no statistically robust explanation for Ttop–τ relationships, suggesting that large-scale synoptic conditions in the mid-latitudes do not drive Ttop–τ relationships. The primary causes for observed cloud–aerosol relationships are likely to be other factors such as retrieval errors, local meteorology or aerosol–cloud interactions.