Day‐to‐Day Temperature Variability in Meteorological Observations and Reanalysis Data Over China

Abstract Temperature variability on the synoptic scale is most directly related to human perception, and requires more attention from scientists and researchers. This study quantifies the day‐to‐day temperature variability (DTD) as the absolute value of the difference between the air temperatures from two consecutive days, and analyzes the spatiotemporal variations using meteorological station observations and four reanalysis data sets. Across China, the annual cycle of DTD ranges from 1.4 to 2.5°C with distinct seasonality: spring and winter exhibit a larger DTD magnitude than summer. There are large heterogeneities among different river basin regions, with the highest annual mean DTD observed in the Songliao River Basin (2.18°C) and the lowest in the Southwest River Basin (1.08°C). For the reanalysis data sets, the DTD values from JRA55 are closest to the observations, with a largest correlation of 0.98 in Southwest River Basin and smallest RMSE of 0.01°C in Yangtze River Basin. The DTD trends from JRA55 and ERA5 are comparable to those from the observational data. Further analysis of the top 1, 5 and 10 day‐to‐day temperature variabilities (DTDmax1, DTDmax5, DTDmax10) reveals that these large DTD values are characterized by rapid cooling, with DTDmax1 exhibiting a fluctuation range of 3.29°C–14.59°C. Additionally, DTDmax1 occurs mainly in spring and winter, with the occurrence date becoming earlier (−8.8 days/10y, p < 0.05) over the study area between 1980 and 2022. These results enhance our understanding of temperature changes at the synoptic scale, providing better services for warning and mitigating disasters.

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Publication Details

Journal
Earth and Space Science
Published
2025-11-01
DOI
https://doi.org/10.1029/2025ea004573
Citations
1
Primary Topic
Urban Heat Island Mitigation
Type
article
Field-Weighted Citation Impact
0.80

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article

Day‐to‐Day Temperature Variability in Meteorological Observations and Reanalysis Data Over China

Xuejie Wang, Yuna Mao, Kaicun Wang, Guocan Wu
1 citations
Earth and Space Science
Urban Heat Island Mitigation
0.80
article

Day‐to‐Day Temperature Variability in Meteorological Observations and Reanalysis Data Over China

Xuejie Wang, Yuna Mao, Kaicun Wang, Guocan Wu
article en
1 citations

Abstract

Abstract Temperature variability on the synoptic scale is most directly related to human perception, and requires more attention from scientists and researchers. This study quantifies the day‐to‐day temperature variability (DTD) as the absolute value of the difference between the air temperatures from two consecutive days, and analyzes the spatiotemporal variations using meteorological station observations and four reanalysis data sets. Across China, the annual cycle of DTD ranges from 1.4 to 2.5°C with distinct seasonality: spring and winter exhibit a larger DTD magnitude than summer. There are large heterogeneities among different river basin regions, with the highest annual mean DTD observed in the Songliao River Basin (2.18°C) and the lowest in the Southwest River Basin (1.08°C). For the reanalysis data sets, the DTD values from JRA55 are closest to the observations, with a largest correlation of 0.98 in Southwest River Basin and smallest RMSE of 0.01°C in Yangtze River Basin. The DTD trends from JRA55 and ERA5 are comparable to those from the observational data. Further analysis of the top 1, 5 and 10 day‐to‐day temperature variabilities (DTDmax1, DTDmax5, DTDmax10) reveals that these large DTD values are characterized by rapid cooling, with DTDmax1 exhibiting a fluctuation range of 3.29°C–14.59°C. Additionally, DTDmax1 occurs mainly in spring and winter, with the occurrence date becoming earlier (−8.8 days/10y, p < 0.05) over the study area between 1980 and 2022. These results enhance our understanding of temperature changes at the synoptic scale, providing better services for warning and mitigating disasters.

Earth and Space ScienceVol. 12(11)
Peking University (CN), Beijing Normal University (CN)
National Natural Science Foundation of China, National Key Research and Development Program of China
Openalex Percentile: Top 23%
Urban Heat Island Mitigation
0.80
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