Caves are unique natural laboratories for studying climate change and its ecological impacts. However, analyzing air temperature in these environments is challenging due to stable microclimatic conditions and high humidity. Collecting reliable data requires dedicated devices and protocols. We developed a standardized quality control procedure-Cave Air Temperature Quality Control (CAT-QC)-to assess the reliability of temperature data collected inside caves. The protocol consists of four main steps: (i) assessing data completeness; (ii) identifying physically implausible values; (iii) detecting statistical outliers using three progressively sensitive methods; and (iv) conducting a final manual check. We tested CAT-QC on a dataset from 19 caves in the Piedmont region (Northwest Italy), recorded with iButton devices. The protocol effectively identified gaps, absurd values, and abrupt temperature changes, many of which were due to human interference or sensor issues. Data flagged through CAT-QC can be further reviewed to address biases and rerun through the process if needed. Designed for broad applicability, CAT-QC is dynamic and can be tailored to local series characteristics, making it suitable for diverse subterranean environments. This tool provides a robust framework for ensuring data quality and comparability in cave climate studies, supporting research and conservation efforts in the context of climate change.
Ensuring reliable cave temperature data for climate change research
Cimenti, Alice;Cresi, Lorenzo;Isaia, Marco;Piano, Elena;Piquet, Anna;Nicolosi, Giuseppe;Mammola, Stefano;Acquaotta, Fiorella
2026-01-01
Abstract
Caves are unique natural laboratories for studying climate change and its ecological impacts. However, analyzing air temperature in these environments is challenging due to stable microclimatic conditions and high humidity. Collecting reliable data requires dedicated devices and protocols. We developed a standardized quality control procedure-Cave Air Temperature Quality Control (CAT-QC)-to assess the reliability of temperature data collected inside caves. The protocol consists of four main steps: (i) assessing data completeness; (ii) identifying physically implausible values; (iii) detecting statistical outliers using three progressively sensitive methods; and (iv) conducting a final manual check. We tested CAT-QC on a dataset from 19 caves in the Piedmont region (Northwest Italy), recorded with iButton devices. The protocol effectively identified gaps, absurd values, and abrupt temperature changes, many of which were due to human interference or sensor issues. Data flagged through CAT-QC can be further reviewed to address biases and rerun through the process if needed. Designed for broad applicability, CAT-QC is dynamic and can be tailored to local series characteristics, making it suitable for diverse subterranean environments. This tool provides a robust framework for ensuring data quality and comparability in cave climate studies, supporting research and conservation efforts in the context of climate change.| File | Dimensione | Formato | |
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