1506 / 2024-09-27 20:21:32

Statistical analysis of thermal and non-thermal components of oceanic pCO2 time series at fixed position

Turbulence,Carbon dioxide,High-frequency,Time series

The ocean plays a critical role in regulating Earth's climate by acting as a major sink for atmospheric CO₂, absorbing approximately 25 % of anthropogenic CO₂ emissions annually (Friedlingstein et al., 2023). However, at smaller spatial and temporal scales, the dynamics of ocean-atmosphere CO₂ fluxes become more intricate. These fluxes are not always directed towards the ocean, as they depend on the partial pressure of CO₂ (pCO₂) difference, which is primarily influenced by fluctuations in oceanic pCO₂ (Robache et al., 2024). This complexity is particularly evident in coastal regions, where spatio-temporal variability is high. In such regions, both thermal and non-thermal fluctuations of oceanic pCO₂ play a significant role in driving these high-frequency dynamics. In this context, we used high-resolution data (30-minute intervals) from the ASTAN buoy, located in Brittany (France), which included measurements of sea surface temperature, salinity, fluorescence, oxygen saturation, and oceanic pCO₂ (Gac et al., 2020). We further separated the thermal and non-thermal components of pCO2 using the methodology outlined by Takahashi et al. (1993, 2009). These datasets were analyzed using turbulence framework methods: Fourier spectral analysis to assess scaling properties, triple correlation function for reversibility analysis, and the Liang-Kleeman information flow index for causality analysis. Our results revealed that all data series exhibited scaling properties close to 5/3, as predicted by Kolmogorov-Obukhov in 1941 for homogeneous and isotropic turbulence. Notably, even the non-thermal component of pCO₂ followed this pattern. Reversibility analysis suggested that biological processes appear to be reversible, whereas physical processes are not. Finally, we explored the causality between these time series, uncovering non-linear behavior, with varying values observed across different timescales.



References :

Friedlingstein, P. et al. (2023). Global carbon budget 2023. Earth System Science Data, 15(12), 5301-5369, https://doi.org/10.5194/essd-15-5301-2023.

Gac, J.-P. et al. (2020). Cardinal Buoys: An Opportunity for the Study of Air-Sea CO₂ Fluxes in Coastal Ecosystems, Frontiers in Marine Science, 7, https://doi.org/10.3389/fmars.2020.00712.

Robache, K et al. (2024). Scaling and intermittent properties of oceanic and atmospheric pCO₂ time series and their difference, Nonlin. Processes Geophys. Discuss. [preprint], https://doi.org/10.5194/npg-2024-7, in review.

Takahashi, T. et al. (1993). Seasonal Variation of CO₂ and Nutrients in the High-Latitude Surface Oceans: A Comparative Study, Global Biogeochemical Cycles, 7, 843–878, https://doi.org/10.1029/93GB02263.

Takahashi, T. et al. (2009). Climatological Mean and Decadal Change in Surface Ocean pCO₂, and Net Sea–Air CO₂ Flux over the Global Oceans, Deep Sea Research Part II, 56, 554–577, https://doi.org/10.1016/j.dsr2.2008.12.009.