Improvements of synergetic aerosol retrieval for ENVISAT

Abstract

The synergetic aerosol retrieval method SYNAER (Holzer-Popp et al., 2002a) has been extended to the use of ENVISAT measurements. It exploits the complementary information of a radiometer and a spectrometer onboard one satellite platform to extract aerosol optical depth (AOD) and speciation (as a choice from a representative set of pre-defined mixtures of watersoluble, soot, mineral dust, and sea salt components). SYNAER consists of two retrieval steps. In the first step the radiometer is used for accurate cloud screening, and subsequently to quantify the aerosol optical depth (AOD) at 550 nm and spectral surface brightness through a dark field technique for different pre-defined aerosol mixtures. In the second step the spectrometer is applied to choose the most plausible aerosol mixture through a least square fit of the measured spectrum with simulated spectra using the mixture-dependent values of AOD and surface brightness retrieved in the first step. This method was developed and a first case study evaluation against few (15) multi-spectral ground-based AERONET sun photometer observations was conducted with a sensor pair (ATSR-2 and GOME) onboard ERS-2. Due to instrumental limitations the coverage of SYNAER/ERS-2 is very sparse. Therefore, SYNAER was transferred to similar sensors AATSR and SCIAMACHY onboard ENVISAT. While transferring to the new sensor pair significant improvements in the methodology were made based on a thorough evaluation of the methodology: (1) an update of the aerosol model, (2) improved cloud detection in the tropics and sub tropics, and (3) an enhanced dark field albedo characterization. This paper describes these improvements in detail and assesses their combined impact on the results. After a brief assessment of atmospheric noise impact on comparisons of pixel and station measurements a validation against ground-based measurements establishes error bars for the SYNAER/ENVISAT method version 2.0. A theoretical analysis of the information content with regard to aerosol composition (second retrieval step) is presented to quantify the potential and limitations of this new capability provided by the SYNAER method. Building on this analysis, first seasonal and monthly composition results calculated by applying SYNAER version 2.0 to AATSR and SCIAMACHY are shown to demonstrate the potential of the approach. An inter-comparison to earlier results of SYNAER version 1.0 is made for both the validation and the example datasets.