Variables that describe atmospheric conditions and constituents are important for environmental applications and method development. These variables include atmospheric water vapour, mineral dust, particulate-matter clouds, and pollen.
Atmospheric water vapour is one of the most effective greenhouse gases in the atmosphere. It shows high spatial and temporal variability depending on meteorological conditions and land use at the underlying Earth’s surface. Information on the regional distribution of atmospheric water vapour may, for example, improve atmospheric correction algorithms and facilitate the analysis of SAR data since radar signal transit time depends on atmospheric conditions.
Atmospheric constituents such as mineral dust and particulate-matter clouds originating from sand storm or biomass-burning areas also show highly variable temporal and spatial distribution. Knowing the mineral composition of such transported dust is essential to understanding climate forcing, the mineralogy of dust sources, aerosol optical properties, and mineral deposition to the ground. Furthermore, it may make it possible to differentiate spectral signals from the ground and those from mineral dust, allowing the separation of atmospheric influences from the ground signal.
Accordingly, scientific tasks related to atmospheric applications include:
- Developing and improving algorithms to retrieve columnar water vapour based on hyperspectral data
- Developing and improving algorithms to characterise mineral dust, particulate-matter clouds, and pollen based on hyperspectral data, and
- Developing and improving algorithms to separate the spectral signal of mineral dust from the ground signal.