• China’s temperature changes exhibit phased, seasonal, and regional imbalances. • Hot-season temperature decreased faster in cooling phases around −0.3 ∼ -0.6 K/decade. • Cold-season temperature increased faster in warming phases around 0.15 ∼ 0.4 K/decade. • Northern China experienced higher warming rate in hot seasons around 1.1 K/decade. Global climate change manifests heterogeneously across regions, yet reliably characterizing these patterns is contingent upon the datasets employed. As a climatically diverse and populous nation, China serves as a critical testbed for evaluating the consistency of temperature products. This study systematically compares six reanalysis datasets (JRA-55, MERRA-2, NCEP/NCAR, NCEP/DOE, CRA/Land, ERA5-Land) with in-situ observations to assess air temperature (Ta) and land surface temperature (LST) changes across China from 1948 to 2022. While all datasets confirm a mid-20th century cooling to late-century warming transition, the magnitudes show notable dataset-dependent variations. For example, the maximum pre-1980 s cooling rates range from −3.1 to −1.8 K/decade. Seasonal contrast is consistently identified: historical cooling was strongest in hot seasons, while recent warming is most rapid in cold seasons—a pattern aligned with aerosol forcing and snow-albedo feedbacks, though its intensity varies across products. A key finding is the significant inter-dataset discrepancy in regional trends, which directly impacts climate vulnerability interpretation. Estimated hot-season warming in northern China varies from 0.8 to 1.2 K/decade across datasets, compared to more modest rates in southern regions. These differences are attributable to variations in spatial resolution, assimilation schemes, and temperature variable definitions (e.g., ground vs. skin temperature). Crucially, systematic differences emerge between in-situ and reanalysis products: in-situ observations capture a larger regional temperature range (approximately 30 K) compared to reanalysis datasets (approximately 19 K), and exhibit faster cooling and warming rates—approximately 0.5 K/decade higher than the reanalysis average during recent decades—highlighting the tendency of gridded products to underestimate both spatial heterogeneity and the pace of change. Our analysis underscores that conclusions on regional temperature changes are contingent upon dataset choice. The substantial spread among state-of-the-art products highlights a critical uncertainty for impact assessments, underscoring the necessity of multi-dataset ensembles to robustly constrain trends and inform climate adaptation strategies over China.
Yao Shen (2026) studied this question.