Revealing spatial and temporal connections of climate variables and vegetation vigour in the circumpolar tundra and boreal region

The effects of the rapid warming in the Arctic region on the sparse tundra vegetation are complex. While some plant functional types like shrubby vegetation thrive under the changing climate and increase in abundance, others like lichen deteriorate. These responses are however not uniform throughout the circumpolar Arctic and depend on various environmental, biotic and climatic factors. Snow cover and snow depth are crucial variables influencing the Arctic vegetation by regulating the plant phenology, growing season length and the soil moisture availability during the growing period. In turn, the vegetation cover type also influences the snow characteristics by capturing more snow in dense and tall vegetation. Furthermore, the active layer thickness of the permafrost layer is affected by the interaction of snow and vegetation. The dynamic interaction between snow and vegetation is also reflected in changes to land surface albedo, providing valuable insights into the Arctic's radiative energy budget. This complex feedback system underscores the intricate relationships between snow, vegetation, and permafrost in the Arctic environment.

Remote sensing can capture the spatial and temporal changes of these important variables throughout the vast and remote Artic region, encompassing both tundra and boreal biomes. The presented study links the datasets of MODIS NDVI (MOD13A1 & MYD13A1) to a suite of ERA5 climate variables such as precipitation, temperature, evaporation and snow depth. The analysis is stratified by considering different auxiliary information encompassing topography, soil characteristics and permafrost, as well as ecoregions. At the EGU26, the methodology and results of the time series analysis will be presented, revealing different snow and vegetation interactions for selected sites in the Arctic tundra.