The ESA aerosol_cci project: Intensive retrieval algorithm characterization

Kurzfassung

The ESA’s Climate Change Initiative project aerosol_cci started mid-2010. As part of this project, consistent prototype algorithms are prepared for the production of long-term aerosol datasets from European Earth Observation sensors. The overall concept of the project rests on four pillars: - understand the differences between various algorithms and products - cooperation between major European aerosol EO teams and consultation with external experts - start with ENVISAT sensors (no miss-time) and extend to other European sensors - work with AEROCOM model user community The project builds on 9 existing algorithms to produce multi-spectral aerosol optical depth as well as information on aerosol type probability other derived parameters: - 3 for ATSR (ORAC by RAL / Oxford university, ADV by FMI and the algorithm of Swansea university) - 2 for MERIS (BAER by Bremen university and the ESA standard handled by HYGEOS) - 1 for POLDER over ocean (LOA) - 1 for spectrometer absorbing aerosol index with averaging kernel information (KNMI) - 1 for synergetic retrieval (SYNAER by DLR ) - 1 for GOMOS stratospheric extinction profile retrieval (BIRA) In the first phase of aerosol-cci an in-depth analysis and comparison of the algorithms and their results for a selected dataset (September 2008) is conducted to understand the strengths and weaknesses of each algorithm. This analysis covers the major assumptions and modules which are needed in aerosol retrieval algorithms due to the ill-posed nature of the underlying inversion problem: - optical aerosol properties, where a harmonized choice of four common aerosol components with suitable mixing in each algorithm is used - cloud masking, where a common AATSR APOLLO cloud mask is used for all morning sensors - surface reflectance / bi-directionality treatment, where sensor-specific harmonization of estimation approaches is explored - auxiliary datasets with an attempt to agree on common use of e.g. ECMWF analysis wind speed to specify ocean white caps in the retrieval, land cover, ocean colour Later in the project, differences between the algorithms will be explored within a round robin exercise. Product uncertainties and pixel-level errors will be characterized through inter-comparison and validation of 4 months of global data (1 month per season) produced by each algorithm against other satellite (MODIS, MISR) and ground-based reference datasets (AERONET). Finally, based on the round robin analysis and a critical review of GCOS requirements for satellite aerosol products the best modules or combinations of modules will be identified for each sensor and prototype algorithms will be integrated by consolidating the pre-cursor algorithms. Annual global datasets including their uncertainties will then be produced and validated. The presentation will summarize results of the ongoing phase 1 inter-comparison and evaluation work within the Aerosol_cci project.