A review of new aerosol climate data records from the ESA CCI Aerosol project

Kurzfassung

Within the ESA Climate Change Initiative (CCI) project Aerosol_cci (Phase 1: 2010 –2014; Phase 2: 2014-2017) intensive work has been conducted to improve algorithms for the retrieval of aerosol information from European sensors ATSR-2 (ERS-2), AATSR (3 algorithms), MERIS (3 algorithms), synergetic AATSR/SCIAMACHY, GOMOS (all on ENVISAT), IASI (on METOP), PARASOL and OMI (EOS-Aura) (both part of NASA’s A-Train). Whereas OMI and GOMOS are used to derive absorbing aerosol index and stratospheric extinction profiles, respectively, Aerosol Optical Depth (AOD), Fine-mode AOD and Ångström coefficient are retrieved from the other sensors, while the infrared IASI retrievals deliver mineral dust AOD. In addition also a per-pixel uncertainty is provided and validated. The algorithms are then used to produce full-mission time series covering 10 (stratospheric extinction), 17 (AOD) and 35(AAI) years. Using AERONET sun photometer data as the common ground-truth both ‘traditional’ statistical techniques and a ‘scoring’ technique based on spatial and temporal correlations were applied for thorough L2 and L3 product validation. The iterative cooperation between the project partners, including retrieval teams, independent validation teams and core users has resulted in a strong improvement of most algorithms. Several user case studies (data assimilation, trend analysis, radiative forcing, stratospheric climate-chemistry interaction, aerosol cloud interaction) are analyzing the potential usefulness and limitations of these datasets. Several retrieval inter-comparisons, so-called Round Robin exercise, have been conducted to assess the sensitivities of different algorithms for the same sensor (AATSR, IASI) or variable (absorption, layer height) and to reveal the major uncertainties, specific strengths and weaknesses of the different retrieval approaches under varying environmental conditions. The presentation will summarize and discuss the status of the Aerosol_cci efforts to produce consistent aerosol time series and characterize and document appropriately to users their potential benefits and limitations. An outlook overview of future potential developments will be deduced from the current status.