Understanding vegetation response to climate variability from space: recent advances towards the SPECTRA Mission

The monitoring of the carbon stock in terrestrial environments, as well as the improved understanding of the surface-atmosphere interactions controlling the exchange of matter, energy and momentum, is of immediate interest for an improved assessment of the various components of the global carbon cycle. Studies of the Earth System processes at the global scale rely on models that require an advanced understanding and proper characterization of processes at smaller scales. The prime objective of the Surface Processes and Ecosystem Changes Through Response Analysis (SPECTRA) Mission is to determine the amount, assess the conditions and understand the response of terrestrial vegetation to climate variability and its role in the coupled cycles of energy, water and carbon. The amount and state of vegetation will be determined by the combination of observed vegetation properties and data assimilation. Many vegetation properties are related to features of reflectance spectra in the region 400 nm - 2500 nm. Detailed observations of spectral reflectance reveal subtle features related to biochemical components of leaves such as chlorophyll and water. The architecture of vegetation canopies determines complex changes of observed reflectance spectra with view and illumination angle. Quantitative analysis of reflectance spectra requires, therefore, an accurate characterization of the anisotropy of reflected radiance. This can be achieved with nearly - simultaneous observations at different view angles. Exchange of energy between the biosphere and the atmosphere is an important mechanism determining the response of vegetation to climate variability. This requires measurements of the component temperature of foliage and soil. The latter are closely related to the angular variation in thermal infrared emittance. Scientific preparations for SPECTRA are pursued along two avenues: a) the nature of the expected data and candidate algorithms are evaluated by generating and using synthetic hyper - spectral multi - angular\radiometric data; algorithms are evaluated with actual hyper -spectral data collected with a variety of airborne systems and concurrent ground measurements;