Conceptual analysis on synergetic retrievals of self-consistent aerosol property climate data records

The influence of aerosols on climate is determined not only by their global distribution but also by their composition. However, so far, a large fraction of the development efforts for satellite-based aerosol retrievals has focused on inverting from different single instruments the total column aerosol optical depth (AOD), as measure of the total abundance of atmospheric aerosols. As the information content of single instruments is smaller than necessary to retrieve a comprehensive quantification of all parameters of atmospheric aerosol, there is a need for using auxiliary information to fill this gap (e.g., pre-defined optical aerosol properties, “climatological” vertical profiles, …). Retrievals capable of inverting further aerosol parameters from one instrument (e.g., Fine Mode or Dust AOD) also depend on some auxiliary assumptions (but to a lesser degree) and on the sensitivity of the available instrument channels to the various aerosol properties. This leads to inconsistencies even between AOD results from different sensors and certainly for additional parameters inverted from them. Synergetic retrievals exploiting several sensors together increase the information content and therefore hold the potential to reduce the dependence on assumed properties and thus improve consistency. Building on lessons from 2 decades of ESA Aerosol_cci developments linked with the international AEROCOM/AEROSAT community and early simplistic synergetic retrievals (SYNAER with AATSR and SCIAMACHY), this paper presents a conceptual framework for advancing synergetic aerosol retrieval methodologies as a logical next step towards long aerosol Climate Data records. Key elements include versatile multi-sensor algorithms and the use of “climatologies” of still needed auxiliary properties (as pre-defined or a priori knowledge and covariances) from recent most powerful polarimeter and lidar retrievals. On the basis of, user requirements for required parameters and “climatological” requirements for historic satellite sensor records (length, consistency), the necessary research is defined: information content analysis to find optimal sensor/channel combinations, methods to use the “climatological” auxiliary data, cross-calibrations in overlapping periods between weaker and stronger algorithms, using one early polarimeter as transfer standard. Altogether, this conceptual analysis establishes a roadmap for synergetic aerosol retrieval developments, paving the way for more robust and comprehensive, i.e., self-consistent climate data records.