Articles | Volume 11, issue 2
https://doi.org/10.5194/ascmo-11-133-2025
https://doi.org/10.5194/ascmo-11-133-2025
05 Sep 2025
 | 05 Sep 2025

A new data-standardization procedure for comprehensive outlier detection in correlated meteorological sensor data

Natalie D. Benschop, Temesgen Zewotir, Rajen N. Naidoo, and Delia North

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Short summary
Meteorological data recorded at high frequency by automatic sensors are often marred by multiple forms of error. Existing validation techniques, in isolation, are sub-optimal for such error-prone data. We propose a new data-standardization procedure for the validation of strongly correlated series which commonly arise in meteorology. We show the procedure to be more comprehensive in the simultaneous detection of solitary spikes, shifts in series means, and irregular diurnal patterns.
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