Homogenization of Air Temperature in Xinxiang, China, Using RHtestsV4 and Implications for Regional Climate Change Assessment

Inhomogeneities in climate observations can bias assessments of regional and local climate change. Taking Xinxiang, a major grain-producing region in Henan Province, China, as the study area, this study compiled temperature observations from eight national basic meteorological stations for 1951–2024. The RHtestsV4 software package was employed, using the penalized maximal t test (PMT) and a mean-adjustment scheme for series homogeneity testing and correction. Climate change characteristics in Xinxiang were analyzed at annual, seasonal, and monthly time scales and across stations to describe spatial patterns. The results indicate that the temperature series in this region exhibit marked inhomogeneity, with minimum temperature (Tmin) being the most sensitive to inhomogeneous factors; station relocation is the primary cause (accounting for over 50%). Over the past ~60 years, the regional mean warming rate increased from 0.278 °C/decade before correction to 0.370 °C/decade after correction. At the seasonal scale, spring showed the strongest warming (0.433 °C/decade), and at the monthly scale, March had the highest warming rate (0.68 °C/decade). Homogenization reduces non-climatic noise such as station relocation, improves the representation of regional temperature contrasts, highlights the stronger warming response in rapidly urbanizing areas in the east, and better represents the spatial pattern and temporal evolution of temperature.