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).

The article presents new high-quality continuous stratospheric aerosol observations spanning 1994–2015 at the French Observatoire de Haute-Provence (OHP, 44° N, 6° E) obtained by two independent, regularly maintained lidar systems operating within the Network for Detection of Atmospheric Composition Change (NDACC). Lidar series are compared with global-coverage observations by Stratospheric Aerosol and Gas Experiment (SAGE II), Global Ozone Monitoring by Occultation of Stars (GOMOS), Optical Spectrograph and InfraRed Imaging System (OSIRIS), Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), and Ozone Mapping Profiling Suite (OMPS) satellite instruments, altogether covering the time span of OHP lidar measurements. Local OHP and zonal-mean satellite series of stratospheric aerosol optical depth are in excellent agreement, allowing for accurate characterization of stratospheric aerosol evolution and variability at northern midlatitudes during the last 2 decades. The combination of local and global observations is used for a careful separation between volcanically perturbed and quiescent periods. While the volcanic signatures dominate the stratospheric aerosol record, the background aerosol abundance is found to be modulated remotely by the poleward transport of convectively cleansed air from the deep tropics and aerosol-laden air from the Asian monsoon region. The annual cycle of background aerosol at midlatitudes, featuring a minimum during late spring and a maximum during late summer, correlates with that of water vapor from the Aura Microwave Limb Sounder (MLS). Observations covering two volcanically quiescent periods over the last 2 decades provide an indication of a growth in the nonvolcanic component of stratospheric aerosol. A statistically significant factor of 2 increase in nonvolcanic aerosol since 1998, seasonally restricted to late summer and fall, is associated with the influence of the Asian monsoon and growing pollution therein.

We describe a new spectral imaging instrument using a ${\mathrm{TeO}}_2$ acousto-optical tunable filter (AOTF) operating in the visible domain (450–900 nm). It allows for fast ($\sim 1$ second), monochromatic (FWHM ranges from 0.6 nm at 450 nm to 3.5 nm at 800 nm) picture acquisition with good spatial resolution. This instrument was designed as a breadboard of the visible channel of a new satellite-borne atmospheric limb spectral imager, named the Atmospheric Limb Tracker for the Investigation of the Upcoming Stratosphere (ALTIUS), that is currently being developed. We tested its remote sensing capabilities by observing the dense, turbulent plume exhausted by a waste incinerator stack at two wavelengths sensitive to ${\mathrm{NO}}_2$. An average value of $6.0\pm 0.4\times 10^{17}\text{molecules}{\mathrm{cm}}^{-2}$ has been obtained for the ${\mathrm{NO}}_2$ slant column density within the plume, close to the stack outlet. Although this result was obtained with a rather low accuracy, it demonstrates the potential of spectral imaging by using AOTFs in remote sensing.

The GOMOS instrument on Envisat has successfully demonstrated that a UV–Vis–NIR spaceborne stellar occultation instrument is capable of delivering quality data on the gaseous and particulate composition of Earth's atmosphere. Still, some problems related to data inversion remained to be examined. In the past, it was found that the aerosol extinction profile retrievals in the upper troposphere and stratosphere are of good quality at a reference wavelength of 500 nm but suffer from anomalous, retrieval-related perturbations at other wavelengths. Identification of algorithmic problems and subsequent improvement was therefore necessary. This work has been carried out; the resulting AerGOM Level 2 retrieval algorithm together with the first data version AerGOMv1.0 forms the subject of this paper. The AerGOM algorithm differs from the standard GOMOS IPF processor in a number of important ways: more accurate physical laws have been implemented, all retrieval-related covariances are taken into account, and the aerosol extinction spectral model is strongly improved. Retrieval examples demonstrate that the previously observed profile perturbations have disappeared, and the obtained extinction spectra look in general more consistent. We present a detailed validation study in a companion paper; here, to give a first idea of the data quality, a worst-case comparison at 386 nm shows SAGE II–AerGOM correlation coefficients that are up to 1 order of magnitude larger than the ones obtained with the GOMOS IPFv6.01 data set.