Quantifying climate change across standardized reference periods is essential for tracking the pace and spatial structure of ongoing shifts in Earth’s climate system. However, robust and comprehensive global comparisons between consecutive climatological normals remain absent. Using high-resolution ERA5-Land reanalysis data (∼9 km), we compared the 1961–1990 and 1991–2020 normals to document changes in temperature, precipitation, and Köppen–Geiger climate classification across the global land surface. Mean land surface temperatures increased by 0.731 °C between periods, with amplified warming at mid- and high latitudes, a pattern consistent with polar amplification. Global mean precipitation decreased by 8.8 mm between the two 30-year normals; range −1,343 to +3,887 mm, implicating the intensification of the hydrological cycle and drying in subtropical regions. These hydroclimatic shifts drove Köppen–Geiger reclassification across 18.5 × 106 km2, or 12.4% of the global continental land area, a rate substantially exceeding prior estimates based on coarser data. Most net transitions predominantly occurred towards warmer and drier regimes. The spatial autocorrelation of both temperature and precipitation anomalies (Moran’s I = 0.76 and 0.7, respectively) is consistent with spatially coherent patterns of change, confirmed by a complementary Fourier surrogate test, rather than purely localized noise. These results demonstrate that measurable, geographically structured climate transformation has already occurred within a single interannual interval, with direct implications for the stability of ecosystems, agricultural systems, and water resources. The magnitude and spatial coherence of observed changes underscore the urgency of updating planning baselines and adapting vulnerability assessments to the new climatic normal. High-resolution ERA5-Land analysis reveals widespread warming, drying, and Köppen–Geiger reclassifications across 12.4% of global continental landmass
Quantifying projected changes in local hydroclimate characteristics as a function of degree of global warming (DGW) is difficult due to the coarse resolution of global climate models and internal variability necessitating large ensembles to isolate climate change signals. Alternatively, thermodynamic global warming...
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As greenhouse gas concentrations continue to rise and the world enters uncharted climate conditions, climate projections at the regional scale are becoming more and more crucial for planning adequate adaptation and mitigation strategies. In particular, in mountainous regions, high spatial resolution of climate inform...
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