The quality of weather forecasts, seasonal simulations, and climate projections depends critically on the adequate representation of land-atmosphere (L-A) feedbacks. These feedbacks are the result of a highly complex network of processes and variables related to the exchange of momentum, energy, and mass. Significant challenges persist in understanding processes and feedbacks, which this initiative will address. 

The Land-Atmosphere Feedback Initiative (LAFI) is an interdisciplinary consortium of researchers from atmospheric, agricultural, and soil sciences as well as from bio-geo-physics, hydrology, and neuroinformatics proposing a novel combination of advanced research methods. The overarching goal of LAFI is to understand and quantify L-A feedbacks via unique synergistic observations and model simulations from the micro-gamma (» 2 m) to the meso-gamma (» 2 km) scales across diurnal to seasonal time scales.  

LAFI consists of a network of closely intertwined projects addressing six research challenges formulated as objectives and hypotheses on 1) alternative similarity theories, 2) the impact of land-surface heterogeneity, 3) partitioning evapotranspiration, 4) understanding entrainment, 5) synergistic characterization of L-A feedback, and 6) droughts or heatwaves potentially investigated by ad-hoc field observations. Collaboration across the research 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.  

Fueled by the tightly interwoven collaborative research, the LAFI research unit will gain crucial new insights into L-A feedbacks and processes for the characterization of coupling strengths over agricultural regions in central Europe.