Quantifying the processes governing the seasonality of accelerated Arctic warming
摘要
Accelerated Arctic warming exhibits pronounced seasonality, with the strongest amplification during the cold seasons (autumn, winter, and spring) and the weakest warming in summer. Yet a unified physical explanation for this contrast remains unclear. Here we present a process-based, seasonally resolved quantification of recent Arctic warming by jointly diagnosing changes in near-surface air temperature, surface temperature, and atmospheric moisture within a unified framework. Two fundamentally distinct seasonal warming regimes emerge. In summer, near-surface air warming is weak and primarily governed by adiabatic heating. Surface warming is driven mainly by increased net shortwave radiation associated with sea ice–albedo feedback, with a secondary contribution from downward longwave radiation. Nearly 86% of the additionally absorbed energy is sequestered in subsurface processes (e.g., sea-ice melt and upper-ocean heat uptake), suppressing upward turbulent heat fluxes and limiting surface–atmosphere coupling. Summertime atmospheric moistening arises predominantly from enhanced poleward water vapor transport and acts primarily as a radiative amplifier of surface warming, without establishing a strong local thermodynamic feedback for atmospheric warming. In contrast, cold-season warming is controlled by a tightly coupled thermodynamic regime centered on moisture processes. Increased atmospheric water vapor enhances downward longwave radiation, warms the surface, strengthens upward turbulent heat fluxes, and drives lower-tropospheric diabatic heating. Subsurface heat release further reinforces this warming. Together, these processes establish a positive moisture–radiation–turbulence feedback that efficiently amplifies both surface and near-surface air temperatures. This seasonally differentiated framework provides a physically consistent explanation for the observed seasonality of accelerated Arctic warming and offers a process-oriented benchmark for climate model evaluation.