Characterizing Low-Frequency DAS Responses to Subsea Temperature Variability

Monitoring subsea temperature variations is essential for capturing dynamic physical processes, including mesoscale eddies, wind-driven upwelling and downwelling, internal wave propagation, and turbulent mixing. These phenomena strongly influence nutrient distribution and biological productivity within marine ecosystems. However, traditional in situ measurements often fail to resolve fine-scale thermal fluctuations due to limited sampling density. To address this limitation, Distributed Acoustic Sensing (DAS) offers a transformative solution by leveraging existing fiber-optic infrastructure to enable continuous, high-resolution monitoring of the subsea environment. Nevertheless, low-frequency (LF) DAS signals are influenced by multiple factors, including mechanical cable vibrations and deformation, thermo-optic effects, and optical noise, which complicate their interpretation.

Here, we evaluate the potential and limitations of DAS for long-range temperature measurements by characterizing the LF-DAS response to subsea temperature variations and optimizing these signals across timescales from days to seasons. The results show that DAS strain and temperature are highly coherent (>0.5) at frequencies below 10 cycles per day. After denoising, DAS strain variations correlate well with temperature changes ranging from 0.4 to 10 K, although discrepancies between channels emerge at ultra-low frequencies. These signals are likely influenced by optical noise and amplified during rapid temperature changes, but can be mitigated through spatial averaging. With preliminary processing, DAS can resolve temperature fluctuations below 0.1 K, achieving meter-scale spatial resolution and minute-scale temporal resolution. These results demonstrate that DAS provides a powerful approach for observing subsea temperature variability, offering new insights into ocean dynamics through unprecedented spatiotemporal resolution.