Hiebl et al. (2025) Correcting Breaks in Temperature and Humidity Observations: Implications for Climate Variability Analysis in Austria

⚠️ 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: 2025-12-15
• Authors: Johann Hiebl, Anna Rohrböck, Klaus Haslinger
• DOI: 10.1002/joc.70214

Research Groups

Not explicitly mentioned in the provided abstract.

Short Summary

This study quantifies and corrects a significant discontinuity in daily mean air temperature and relative humidity estimations across Austrian climate stations, caused by a 2-hour shift in evening observation timing in 1971. By employing station-specific multi-linear regressions, the method successfully eliminates spurious cooling and drying biases, substantially improving the accuracy of climate data and trend analyses.

Objective

• To comprehensively quantify and correct a discontinuity in daily mean air temperature and relative humidity estimations across all climate stations in Austria, which resulted from a 2-hour shift in the timing of evening observations in 1971.

Study Configuration

• Spatial Scale: 134 long-term climate stations across Austria.
• Temporal Scale: Hourly observations used to derive daily means over a period spanning from 1961 to 2022, with the discontinuity occurring in 1971.

Methodology and Data

• Models used: Station-specific multi-linear regressions, progressively refined and stratified by calendar month, station, and diurnal temperature range class. Two separate regressions were used to account for differing evening observation times before and after 1971.
• Data sources: Hourly and sub-daily observational time series from individual climate stations.

Main Results

• The 1971 observation shift caused an average spurious cooling of -0.15 K and drying of -2.1% in daily mean time series across all stations.
• The developed correction method reduced the typical error in predicting true daily means by almost half compared to common averaging formulae.
• Root Mean Square Error (RMSE) was reduced by up to 52% for temperature and up to 57% for humidity, depending on the averaging formulae used.
• Without correction, temperature and humidity trends for the period 1961–2022 were underestimated on average by -0.13 K and -1.5%, respectively.
• Break-corrected series largely eliminated systematic misestimation of climate indices and demonstrably improved temporal consistency in spatial climate monitoring.

Contributions

• First comprehensive quantification and correction of the specific discontinuity in Austrian climate station data caused by the 1971 observation time shift.
• Introduction of a novel, fully stand-alone, station-specific multi-linear regression method for break correction that requires only the station's own sub-daily time series.
• Significant improvement in the accuracy of daily mean temperature and humidity estimations, leading to more reliable climate trend assessments and spatial climate monitoring.
• The method's simplicity and autonomy make it easily applicable to similar issues in other regions, contributing to broader error reduction in climate data applications.

Funding

Not explicitly mentioned in the provided abstract.

Citation

@article{Hiebl2025Correcting,
  author = {Hiebl, Johann and Rohrböck, Anna and Haslinger, Klaus},
  title = {Correcting Breaks in Temperature and Humidity Observations: Implications for Climate Variability Analysis in Austria},
  journal = {International Journal of Climatology},
  year = {2025},
  doi = {10.1002/joc.70214},
  url = {https://doi.org/10.1002/joc.70214}
}