LAFI consists of a network of ten closely intertwined projects addressing the six LAFI research objectives.
In order to achieve these research objectives, information on L-A interactions is required in unprecedented detail to be able to capture the whole complexity of the L-A system with all its processes and feedbacks. Thus, observation and modeling data are needed which go beyond the purposes of standard approaches. Such data need to comprise simultaneous measurements of key variable profiles and transport processes across all components of the L-A system as well as simulations of the meso-scale atmospheric conditions and its interactions with the local surface conditions from diurnal to seasonal time scales. However, this kind of data can only be produced by means of an inclusive combination of three-dimensional observations and high-resolution modeling. In the ten LAFI projects, this is realized by an unparalleled synergy of lidar systems, fiber-optic distributed temperature sensors (FODS), water stable isotope measurements and satellite remote sensing data in combination with a state-of-the-art modeling chain from the meso-gamma scale (~2 km) down to the micro-gamma scale (~ 2 m).
Collaboration across the LAFI projects will be fostered by three Cross Cutting Working Groups on Deep Learning, Sensor Synergy and Upscaling, as well as the LAFI Multi-model Experiment.
On the basis of this worldwide unique combination of L-A measurements (in-situ and remote sensing) and simulations at different resolutions, for the first time, a detailed and at the same time all-encompassing analysis of the L-A system with its individual key processes and spatial and temporal feedbacks is possible over the entire vegetation period.
Fig. 1: Composition of the dedicated research teams adressing the six Objectives (Os) and their contributions to the three Cross-Cutting Working Groups (CCWGs)
