par Popp, Thomas;Griesfeller, Jan;Heckel, Andreas;Kinne, Stefan;Klüser, Lars;Kosmale, Miriam;Kolmonen, Pekka;Lelli, Luca;Litvinov, Pavel;Mei, Linlu;North, Peter;De Leeuw, Gerrit;Pinnock, Simon;Povey, Adam;Roberts, Charles W M;Schulz, Michael;Sogacheva, Larisa;Stebel, Kerstin;Zweers, Deborah Stein;Thomas, GarethM G.M.;Tilstra, Lieuwe Gijsbert;Vandenbussche, Sophie ;Bingen, Christine Y. ;Veefkind, Pepijn J.;Vountas, Marco;Xue, Yong;Brühl, Christoph;Capelle, Virginie;Chédin, Alain;Clarisse, Lieven ;Dubovik, Oleg;Grainger, Roy Gordon
Référence Remote Sensing, 8, 5, 421
Publication Publié, 2016
Référence Remote Sensing, 8, 5, 421
Publication Publié, 2016
Article révisé par les pairs
Résumé : | Producing a global and comprehensive description of atmospheric aerosols requires integration of ground-based, airborne, satellite and model datasets. Due to its complexity, aerosol monitoring requires the use of several data records with complementary information content. This paper describes the lessons learned while developing and qualifying algorithms to generate aerosol Climate Data Records (CDR) within the European Space Agency (ESA) Aerosol_cci project. An iterative algorithm development and evaluation cycle involving core users is applied. It begins with the application-specific refinement of user requirements, leading to algorithm development, dataset processing and independent validation followed by user evaluation. This cycle is demonstrated for a CDR of total Aerosol Optical Depth (AOD) from two subsequent dual-view radiometers. Specific aspects of its applicability to other aerosol algorithms are illustrated with four complementary aerosol datasets. An important element in the development of aerosol CDRs is the inclusion of several algorithms evaluating the same data to benefit from various solutions to the ill-determined retrieval problem. The iterative approach has produced a 17-year AOD CDR, a 10-year stratospheric extinction profile CDR and a 35-year Absorbing Aerosol Index record. Further evolution cycles have been initiated for complementary datasets to provide insight into aerosol properties (i.e., dust aerosol, aerosol absorption). |