Katata et al. (2025) Reconstruction of the Background Air Temperature Record in Japan (1916–2023): Implications for Climate Change and Urbanisation Bias in the 20th Century

⚠️ Warning: This summary was generated from the abstract only, as the full text was not available.

Identification

• Journal: International Journal of Climatology
• Year: 2025
• Date: 2025-10-06
• Authors: Genki Katata, Ryusei Nakayama, Fumiaki Fujibe, Shigeya Maeda
• DOI: 10.1002/joc.70141

Research Groups

Not explicitly mentioned in the abstract, but likely involving researchers associated with the Japan Meteorological Agency (JMA) or related academic institutions responsible for climate data analysis.

Short Summary

This study reconstructed long-term annual mean temperature trends in rural Japan (1916-2023) using newly digitized data, revealing a lower warming rate (+0.11 °C per decade) compared to JMA stations (+0.15 °C per decade) due to urbanization bias, and uncovering a significant climatic jump (decreasing trend) in the 1960s after bias removal.

Objective

• To reconstruct long-term trends of annual mean temperatures in rural Japan (1916-2023) to estimate global warming rates without urbanization bias.
• To identify and quantify the impact of urbanization bias on temperature trends in Japan.
• To investigate natural climate variations that might be masked by urbanization bias.

Study Configuration

• Spatial Scale: Rural Japan (stations with population density < 100 people km⁻²), including 15 monitoring stations of the JMA. Comparisons made with other regions of the Northern Hemisphere and sea surface temperatures around the Japan region.
• Temporal Scale: 1916–2023 (108 years). Specific data digitization for 1926–1940. Analysis of trends, particularly during the 1960s.

Methodology and Data

• Models used: Not explicitly mentioned as a specific climate model. The methodology involves reconstruction of annual mean temperature trends and statistical analysis to identify and subtract urbanization bias.
• Data sources: Digitized monthly maximum and minimum temperature data from rural weather stations in Japan (1916-2023). Monthly temperature data from 1926 to 1940 were newly digitized from printed materials of the Japan Meteorological Agency (JMA). Comparison data included temperature trends from other regions of the Northern Hemisphere and sea surface temperatures.

Main Results

• The linear rate of increase in the annual temperature averaged for 15 JMA monitoring stations was +0.15 °C per decade for the period 1916–2023.
• The linear rate of increase averaged for rural stations (population density < 100 people km⁻²) was lower at +0.11 °C per decade, indicating a significant urbanization bias in the JMA station data.
• After subtracting the urbanization biases, a significant decreasing trend (a climatic jump) was detected in the rural temperature record during the 1960s.
• Urbanization bias likely partially masked the importance of natural variations, such as the Pacific Decadal Oscillation (PDO) and solar variability, in the observed temperature trends.

Contributions

• Provided a long-term (1916-2023) and contiguous record of rural temperature trends in Japan, free from urbanization bias, utilizing newly digitized historical data.
• Quantified the impact of urbanization bias on temperature trends in Japan, demonstrating its role in overestimating the regional warming rate.
• Revealed a previously masked significant climatic jump (decreasing trend) in rural Japan during the 1960s, highlighting the influence of natural climate variability.
• Emphasized the critical need to account for urbanization bias when assessing regional and global warming trends and understanding the interplay with natural climate drivers.

Funding

Not mentioned in the abstract.

Citation

@article{Katata2025Reconstruction,
  author = {Katata, Genki and Nakayama, Ryusei and Fujibe, Fumiaki and Maeda, Shigeya},
  title = {Reconstruction of the Background Air Temperature Record in Japan (1916–2023): Implications for Climate Change and Urbanisation Bias in the 20th Century},
  journal = {International Journal of Climatology},
  year = {2025},
  doi = {10.1002/joc.70141},
  url = {https://doi.org/10.1002/joc.70141}
}