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Abstract. The Arctic poses many challenges for Earth system and snow physics models, which are commonly unable to simulate crucial Arctic snowpack processes,such as vapour gradients and rain-on-snow-induced ice layers. These limitations raise concerns about the current understanding of Arctic warming and its impact on biodiversity, livelihoods, permafrost, and the global carbon budget. Recognizing that models are shaped by human choices, 18 Arctic researchers were interviewed to delve into the decision-making process behind model construction. Although data availability, issues of scale, internal model consistency, and historical and numerical model legacies were cited as obstacles to developing an Arctic snowpack model, no opinion was unanimous. Divergences were not merely scientific disagreements about the Arctic snowpack but reflected the broader research context. Inadequate and insufficient resources, partly driven by short-term priorities dominating research landscapes, impeded progress. Nevertheless, modellers were found to be both adaptable to shifting strategic research priorities – an adaptability demonstrated by the fact that interdisciplinary collaborations were the key motivation for model development – and anchored in the past. This anchoring and non-epistemic values led to diverging opinions about whether existing models were “good enough” and whether investing time and effort to build a new model was a useful strategy when addressing pressing research challenges. Moving forward, we recommend that both stakeholders and modellers be involved in future snow model intercomparison projects in order to drive developments that address snow model limitations currently impeding progress in various disciplines. We also argue for more transparency about the contextual factors that shape research decisions. Otherwise, the reality of our scientific process will remain hidden, limiting the changes necessary to our research practice. 

Accurate representation of permafrost carbon emissions is crucial for climate projections, yet current Earth system models inadequately represent permafrost carbon. Sustained funding opportunities are needed from government and private sectors for prioritized model development. 

Tundra vegetation productivity and composition are responding rapidly to climatic changes in the Arctic. These changes can, in turn, mitigate or amplify permafrost thaw. In this Review, we synthesize remotely sensed and field-observed vegetation change across the tundra biome, and outline how these shifts could influence permafrost thaw. Permafrost ice content appears to be an important control on local vegetation changes; woody vegetation generally increases in ice-poor uplands, whereas replacement of woody vegetation by (aquatic) graminoids following abrupt permafrost thaw is more frequent in ice-rich Arctic lowlands. These locally observed vegetation changes contribute to regional satellite-observed greening trends, although the interpretation of greening and browning is complicated. Increases in vegetation cover and height generally mitigate permafrost thaw in summer, yet, increase annual soil temperatures through snow-related winter soil warming effects. Strong vegetation–soil feedbacks currently alleviate the consequences of thaw-related disturbances. However, if the increasing scale and frequency of disturbances in a warming Arctic exceeds the capacity for vegetation and permafrost recovery, changes to Arctic ecosystems could be irreversible. To better disentangle vegetation– soil– permafrost interactions, ecological field studies remain crucial, but require better integration with geophysical assessments.