Permafrost is a key indicator of global climate change and hence considered an Essential Climate Variable (ECV). Current studies show a warming trend of permafrost globally, which induces widespread permafrost thaw, leading to near-surface permafrost loss at local to regional scales and impacting ecosystems, hydrological systems, greenhouse gas emissions, and infrastructure stability. Especially the understanding of abrupt, rapid permafrost thaw dynamics, unfolding within merely a couple of days to years and impacting the landscape irreversibly, such as thermokarst formation, lake drainage, and retrogressive thaw slumps, are of high relevance as their projected greenhouse gas emissions, including methane and carbon dioxide, are substantial. Permafrost is defined as the thermal state of the subsurface but is greatly influenced by changes in the surface state, which is tightly connected to the atmosphere, biosphere, geosphere, and cryosphere by topography, water, snow and vegetation. Hence, examining changes in the surface state will help to identify regions that are particular vulnerable to permafrost thaw. Our primary aim is to investigate changes in the surface state by assessing positive and negative feedbacks to the surface state that potentially influence permafrost and thus derive an index for permafrost vulnerability to thaw. Earth observation (EO) based datasets provide great opportunity to analyse relevant variables impacting the surface state and obtain trends and changes from long-term consistent datasets. Relevant variables for assessment are land surface temperature, land cover, snow cover, fire, albedo, soil moisture, and information on the freeze/thaw state, which are all ECVs as well, and are available globally following ESA CCI and GCOS product developments. Furthermore, two modelled permafrost_cci products are available for comparison: ground temperature and active layer thickness. However, so far, a combined assessment of these products to better understand, quantify, and project permafrost changes and trajectories is still missing. Therefore, the objective of this ongoing project is to develop a permafrost vulnerability framework which focuses on the surface state, including the above listed ECVs. By conducting spatiotemporal variability analyses of the individual ECVs, correlation assessments among them, and decadal trend analysis, a better understanding of their positive and/or negative feedbacks will be established. Combining the feedback results of the ECVs in a vulnerability assessment will help identifying prevailing trends in the surface state and evaluating consequences for the thermal state of the permafrost. Preliminary results show that the individual ECVs show differing trends in the spatiotemporal variability analysis, indicating positive and negative feedbacks. The results will be incorporated in a circumpolar Arctic permafrost vulnerability assessment, integrating the coupled feedbacks and determining their combined effect on the thermal state of the permafrost. The resulting new permafrost vulnerability index will give a more comprehensive and spatially detail-rich understanding of circumpolar permafrost vulnerabilities and their magnitude. It will indicate areas that are particularly vulnerable to experience thaw and hence highlight areas of particular importance for close monitoring. The circumpolar Arctic permafrost vulnerability index dataset will be a great foundation for a wide range of permafrost-thaw focus studies, such as hydrological change, infrastructure stability, ecosystem change or greenhouse gas emissions, as well as useful for qualitatively assessing the permafrost-climate feedback.