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Abstract AimClimate change regulates autumn leaf senescence date (LSD), exhibiting a strong phenological control of plant carbon uptake. Unlike the delaying effect of daily mean temperature (T_mean) on LSD, the impact of warming asymmetry in daytime and nighttime, as evidenced by variations of the diurnal temperature range (DTR), remains elusive. The objectives of this study were to investigate physiological and ecological impacts of DTR on LSD using long‐termin situobservations and to predict the future trends of LSD under warming. LocationEurope. Time period1950–2015. Major taxa studiedPlant phenology. MethodsWe used partial correlation analysis, multiple linear regression and ridge regression to explore the impacts of DTR on LSD. To quantify the importance of potential drivers of LSD, we trained random forest models and applied the SHapley Additive exPlanations method to isolate the marginal contributions of each predictor on LSD. For LSD modelling and projection, we first evaluated two temperature‐driven LSD models [i.e., cooling‐degree‐day (CDD, without DTR effect) and day–night‐temperature CDD (DN_CDD, with DTR effect)], then applied them to predict future LSDs. ResultsWe found that observational increases inT_meanand DTR had contrasting effects on LSD. IncreasedT_meandelayed the LSD, whereas larger DTR overall had an advancing effect. Considering the DTR effect, theT_meansensitivity of LSD was 14% lower than presently estimated (2.4 vs. 2.8 days °C⁻¹). Warming asymmetry‐related drought stress and plant functional traits (i.e., plant isohydricity and water‐use efficiency) potentially explained the advancing effect of DTR on LSD. We found that current projections of future LSD are overestimated because the DTR effect is discounted, suggesting the need for an adequate understanding of how plant phenology responds to warming asymmetry. Main conclusionsOur findings highlight the importance of DTR in controlling LSD variations with an advancing‐dominant effect and call for the improvement of phenology modelling incorporating the DTR effect. Given that DTR showed a globally narrowing trend over the last several decades, more efforts are needed to understand the potential ecological impacts of warming asymmetry and vegetation response to climate change. 

Abstract Science, engineering, and society increasingly require integrative thinking about emerging problems in complex systems, a notion referred to as convergence science. Due to the concurrent pressures of two main stressors—rapid climate change and industrialization, Arctic research demands such a paradigm of scientific inquiry. This perspective represents a synthesis of a vision for its application in Arctic system studies, developed by a group of disciplinary experts consisting of social and earth system scientists, ecologists, and engineers. Our objective is to demonstrate how convergence research questions can be developed via a holistic view of system interactions that are then parsed into material links and concrete inquiries of disciplinary and interdisciplinary nature. We illustrate the application of the convergence science paradigm to several forms of Arctic stressors using the Yamal Peninsula of the Russian Arctic as a representative natural laboratory with a biogeographic gradient from the forest‐tundra ecotone to the high Arctic. 

Abstract Satellite observations have shown widespread greening during the last few decades over the northern permafrost region, but the impact of vegetation greening on permafrost thermal dynamics remains poorly understood, hindering the understanding of permafrost‐vegetation‐climate feedbacks. Summer surface offset (SSO), defined as the difference between surface soil temperature and near‐surface air temperature in summer (June‐August), is often predicted as a function of surface thermal characteristics for permafrost modeling. Here we examined the impact of leaf area index (LAI), detected by satellite as a proxy to permafrost vegetation dynamics, on SSO variations from 2003 to 2021 across the northern permafrost region. We observed latitude‐ and biome‐dependent patterns of SSO changes, with a pronounced increase in Siberian shrublands and a decrease in Tibetan grasslands. Based on partial correlation and sensitivity analyses, we found a strong LAI signal (∼30% of climatic signal) on SSO with varying elevation‐ and canopy height‐dependent patterns. Positive correlations or sensitivities, that is, increases in LAI lead to higher SSO, were distributed in relatively cold and wet areas. Biophysical effects of permafrost greening on surface albedo, evapotranspiration, and soil moisture (SM) could link the connection between LAI and SSO. Increased LAI substantially reduced surface albedo and enhanced evapotranspiration, influenced energy redistribution, and further controlled interannual variability of SSO. We also found contrasting effects of LAI on surface SM, consequently leading to divergent impacts on SSO. The results offer a fresh perspective on how greening affects the thermal balance and dynamics of permafrost, which is enlightening for improved permafrost projections. 

Abstract Ground heat flux (G₀) is a key component of the land‐surface energy balance of high‐latitude regions. Despite its crucial role in controlling permafrost degradation due to global warming,G₀is sparsely measured and not well represented in the outputs of global scale model simulation. In this study, an analytical heat transfer model is tested to reconstructG₀across seasons using soil temperature series from field measurements, Global Climate Model, and climate reanalysis outputs. The probability density functions of ground heat flux and of model parameters are inferred using availableG₀data (measured or modeled) for snow‐free period as a reference. When observedG₀is not available, a numerical model is applied using estimates of surface heat flux (dependent on parameters) as the top boundary condition. These estimates (and thus the corresponding parameters) are verified by comparing the distributions of simulated and measured soil temperature at several depths. Aided by state‐of‐the‐art uncertainty quantification methods, the developedG₀reconstruction approach provides novel means for assessing the probabilistic structure of the ground heat flux for regional permafrost change studies.