Satellite derived Climate Data Records in the ESA Aerosol_cci project

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), PARASOL and OMI (EOS-Aura) (both part of NASA’s A-Train). Whereas OMI and GOMOS were used to derive absorbing aerosol index and stratospheric extinction profiles, respectively, Aerosol Optical Depth (AOD) and Ångström coefficient were retrieved from the other sensors. The cooperation between the project partners, including both retrieval teams and independent validation teams, has resulted in a strong improvement of most algorithms. In particular the AATSR retrieved AOD is qualitatively similar to that from MODIS, usually taken as the standard, MISR and SeaWiFS. This conclusion has been reached by several different ways of validation of the L2 and L3 products. 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. Quantitatively, the limited AATSR swath width of 512km results in a smaller amount of data. Nevertheless, the assimilation of AATSR-retrieved AOD, together with MODIS data, contributes to improving ECMWF / MACC climate model results. In addition to the multi-spectral AOD, and thus the Ångström Exponent, also a per-pixel uncertainty is provided and validated. By the end of Aerosol_cci Phase 1 the ATSR algorithms have been applied to both ATSR-2 and AATSR resulting in an AOD time series of 17 years dating back to 1995. In phase 2 this work is continued with a focus on the further improvement of the ATSR algorithms as well as those for the other instruments and algorithms, mentioned above, which in phase 1 were considered less mature. The first efforts are on the further characterization of the uncertainties and on better understanding of the cloud screening in the various algorithms. Other efforts will focus on surface treatment and possible improvement of aerosol models used in the retrieval. A yearly re-processing of the full 17-year global ATSR-2/AATSR data set is planned to evaluate the effect of different changes and to monitor further improvement. As a new additional focus in phase 2 it is envisaged to produce a full-mission dataset of dust AOD from IASI with four different algorithms, which are based on different retrieval techniques. A major task within the project is the first inter-comparison of those IASI dust retrieval algorithms on the basis of a large set of observations. For this purpose one year of IASI observations (2013) over the major dust belt of the Northern hemisphere, including the Northern Atlantic Ocean, the Sahara desert, the Arabian Peninsula as well as the Central Asian desert regions, is consistently processed with all four algorithms and similar retrieval output (visible and infrared AOD, AOD uncertainty, retrieval quality, cloud flags) is generated in order to facilitate the comparison of results. The retrieval inter-comparison, called Round Robin exercise, consists of an analysis of the different sensitivities of the four algorithms to dust and environmental conditions. The retrieval methods are based on different retrieval strategies such as look-up tables, optimal estimation and singular value decomposition. The sensitivity analysis will reveal the major uncertainties of infrared dust remote sensing from space as well as specific strengths and weaknesses of the different retrieval approaches under varying environmental conditions and can be used to select the best-suited approach for specific conditions. The Round Robin exercise includes the evaluation of retrieval results from the four different algorithms with external data. AERONET sun photometers are used for evaluation as well as observations from the German SALTRACE campaign over the tropical Atlantic Ocean in summer 2013. Evaluation of subsets, for example subdivided by atmospheric moisture or surface characteristics, will thus allow for an improved understanding of the feasibility of hyperspectral infrared dust remote sensing with different approaches under varying conditions. The presentation will summarize the concept and status of the Aerosol_cci project in both phases and discuss in particular the achievements regarding the 17 year ATSR time series and the 1 year IASI round robin exercise