The Spring‐Summer Persistent Uniform Warming Regime in Northwest China: Characteristics and Dynamical Origins

Abstract Northwest China (NWC) is warming far faster than the global average and is highly vulnerable to climate change. Spring‐summer temperature anomalies in NWC critically affect ecosystems and socioeconomics, yet their cross‐seasonal coherence and mechanisms remain unclear. Using ERA5 data (1959–2025), Season‐reliant Empirical Orthogonal Function analysis identifies the Persistent Uniform Warming Regime (PUWR) as the dominant spring‐summer mode, featuring distinct interannual and interdecadal variability. Climate variability associated with PUWR exhibit phase asymmetry and timescale dependence: during its warm phase, PUWR increases extreme heat events and reduces interannual spring precipitation on the interannual timescale, but increases spring precipitation on the interdecadal timescale; conversely, its cold phase amplifies interdecadal extreme cold events. The PUWR warm phase is driven by persistent local high‐pressure anomalies, which induce adiabatic subsidence and diabatic heating in spring and warm advection in summer on the interannual timescale, while diabatic heating dominates in both seasons on the interdecadal timescale. These high‐pressure systems are embedded within atmospheric teleconnection wave trains emanating from midlatitude North Atlantic and North Pacific, driven by persistent sea surface temperature gradients. On the interannual timescale, two distinct wave trains propagate meridionally and zonally, respectively. On the interdecadal timescale, the wave trains are linked to the Atlantic Multidecadal Oscillation and Pacific Decadal Oscillation, exhibiting meridional propagation in spring and zonal propagation in summer. All observed wave trains are well reproduced in linear baroclinic model experiments with combined midlatitude vorticity forcing. This study systematically elucidates the multiscale characteristics and mechanisms of PUWR, advancing our understanding of temperature variability and supporting improved regional climate prediction in NWC.