Status: this preprint is open for discussion and under review for Geoscientific Instrumentation, Methods and Data Systems (GI).
Tipping point analysis helps identify sensor phenomena in humidity data
Valerie N. Livina,Kate Willett,and Stephanie Bell
Abstract. Humidity variables are important for monitoring climate. Unlike, for instance, temperature, they require data transformation to derive water vapour variables from observations. Hygrometer technologies have changed over the years and, in some cases, have been prone to sensor drift due to aging, condensation or contamination in service, requiring replacement. Analysis of these variables may provide rich insight into both instrumental and climate dynamics. We apply tipping point analysis to dew point and relative humidity values from hygrometers at 55 observing stations in the UK. Our results demonstrate these techniques, which are usually used for studying geophysical phenomena, are also potentially useful for identifying historic instrumental changes that may be undocumented or lack metadata.
Received: 27 Mar 2025 – Discussion started: 21 May 2025
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A novel approach that uses tipping point analysis for identifying instrumental changes in sensor data that may not have full description of legacy hardware. The technique helps interpret changes of pattern in the data (autocorrelations) and distinguish them from climatic and environmental effects. This is particularly important for historic datasets, where instrumental changes may be undocumented or lack metadata.
A novel approach that uses tipping point analysis for identifying instrumental changes in sensor...
