There is increasing evidence that the Earth's climate has undergone unprecedented change, at least in recent history, with mankind driving much of the observed change through increase in greenhouse gases. The capability of anthropogenic actions to severely interfere with the climate system were clearly shown in the early 1980s with the discovery of the Antarctic ozone hole caused by human-made chlorofluorocarbons and other ozone-depleting substances. The understanding of the role of mankind emissions and of natural variability is vital to predict the future behaviour of climate. A major scientific gap in furthering our understanding of the Earth System is nowadays the lack of a model that couples all its aspects (interaction of climate with clouds, chemistry, aerosols and dynamics and, in turn, interaction of these processes with the ocean, ice and land surfaces). Observations need to contribute to filling these gaps, bringing new scientific bases for modeling relevant processes. In this contest, satellite missions, with their global and multi-year coverage, give the possibility to study the distribution, variability and long-term trends of the physical and chemical quantities of the atmosphere.

This project investigates the atmosphere through remote sensing techniques applying tomographic methods to current observations to improve the description of the atmosphere and gather the expertise needed for future higher resolution missions. Particularly in regions dominated by dynamics and transport, such as the UTLS (Upper Troposphere/Lower Stratosphere), the natural variability is strong and covers a very large spectrum of scales. Current satellite products characterized by low spatial resolution or retrieved without accounting the inhomogeneity of the atmosphere suffer from limitations in correctly describing these regions. Looking forward to a new generation of satellites having much higher spatial resolution and innovative methods to account for atmospheric inhomogeneity, this project aims to develop and use tomographic retrieval methods that correctly model horizontal atmospheric gradients along the line of sight of limb sounders.

The necessity of a more realistic description of inhomogeneous atmospheric fields has been addressed in a study performed on Envisat MIPAS observations. It is reported that non-physical day-night differences are present in 1-D retrievals from MIPAS spectra, mostly at locations where horizontal temperature gradients are strong in the atmosphere. These differences almost disappear using a tomographic approach.

It has also been investigated the three MIPAS observation modes that sound the UTLS region using the ‘Information Load (IL)’ quantifier, evaluating the nominal (NOM), UTLS-1 and UTLS-2 observation modes performance in terms of strength, spatial coverage and uniformity of the IL distribution. This approach, possible only using a 2-D representation of the atmospheric fields, showed that the two UTLS observation modes are competitive with the third one, that was designed for the whole stratosphere, up to altitudes that far exceed the UTLS.

All available MIPAS observations have been analyzed, on a common 2-D retrieval grid, with the GMTR code in order to obtain fields of pressure, temperature, H₂O, O₃, HNO₃, CH₄, N₂O, NO₂. The temporal extension of the obtained database allows studies of long-term trends.

A similar approach is also applied to an UV-VIS instrument by developing a tomographic code for the limb observations of Envisat SCIAMACHY. In this case the spectra need to be simulated with a Radiative Transfer Model (RTM) that takes into account single and multiple scattering processes. The DOAS technique was used, which consists in obtaining at each tangent height (TH), the Slant Column Density (SCD) of the considered species, through a spectral fitting. The trace gas SCDs are converted into number density by a tomographic approach that consists in one inversion applying 2-D box Airmass Factors (computed using the RTM) to the SCDs of all scanning sequences and THs simultaneously.

The next steps of the study foresee the update of the MIPAS Level 2 database by analyzing the new coming Level1b files and the comparison of the datasets with a Chemical Transport Model. Since an homogeneous database (having almost the same systematic errors) is highly desirable in order to allow long-term studies it is planned to degrade the resolution of all the spectra of the first period of MIPAS mission (Full Resolution). Subsequently, it is foreseen to retrieve the atmospheric fields from the degraded spectra using the auxiliary data of the second period of the mission (Optimized Resolution). Through the IL analysis, it is also planned to investigate the characteristics of an advanced imaging spectrometer (sounding the atmosphere with a very fine scan-pattern) that allows innovative studies (e.g. the structure of the UTLS with high level of detail). The outcome of this study may give a support in the definition of requirements for future Earth Explorers Missions.