To resolve the complexity of Arctic greening trends and quantify vegetation feedbacks using satellite observations, ground-based measurements and Earth system models.

The continued warming has led to Arctic greening. However, it is still controversy about the greening trend and its feedback. We will investigate the spatiotemporal patterns in the trend and drivers of panarctic greening in recent decades using a physically-based vegetation index and predict its future trend and feedback using Earth system models. The specific aims are: (1) to investigate the Arctic growing season variations and their relationships to temperature, precipitation, and seasonal snow cover over circumpolar arctic region (>60°N); (2) to investigate the changes of seasonal maximum vegetation growth, annual total growth, and their relationships to temperature and precipitation in preceding seasons; and (3) to study the spring growth rate and acclimation of Arctic vegetation to warming and to investigate the controls of other climatic factors on spring growth; (4) to predict biogeophysical feedbacks to the climate system using process-based Earth system models and satellite-derived seasonal changes of land surface albedo, soil moisture, and evapotranspiration. The project involves intensive remote sensing data processing, biophysical indicator development, statistical analysis, and process-based ecosystem modeling. The project aspires to contribute to knowledge concerning arctic ecosystem responses to
climatic warming, their relationship to environmental drivers and impacts of vegetation feedbacks.