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Title: Spatio-temporal variability in surface ocean pCO₂ inferred from observations
Author: Jones, Steve
ISNI:       0000 0004 2735 8184
Awarding Body: University of East Anglia
Current Institution: University of East Anglia
Date of Award: 2012
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The variability of surface ocean pCO₂ is examined on multiple spatial and temporal scales. Temporal autocorrelation analysis is used to examine pCO₂ variability over multiple years. Spatial autocorrelation analysis describes pCO₂ variability over multiple spatial scales. Spatial autocorrelation lengths range between <50 km in coastal regions and other areas of physical turbulence up to 3,000 km along major currents. Analysis of the drivers of pCO₂ shows that ocean currents are the primary driver of spatial variability. Autocorrelation lengths of air-sea CO2 fluxes are approximately half as long as for pCO₂ due to the effects of highly variable wind speeds. The influence of modes of climate variability on ocean pCO₂ and related air-sea CO₂ fluxes is examined through correlations of climate indices with interannual pCO₂ anomalies separated from the long-term trend and mean seasonal cycle. Changes in the El Niño Southern Oscillation alter pCO₂ levels by -6.6 ± 1.0 μatm per index unit (μatm iu⁻¹) in the Equatorial Pacific, leading to changes in air-sea flux of up to 0.40 ± 0.06 Pg C yr⁻¹. The Pacific Decadal Oscillation shows statistically significant correlations with pCO₂ across the Equatorial Pacific, North Pacific and North Atlantic. No statistically significant correlations are found with the North Atlantic Oscillation in the North Atlantic. An important product of the analysis performed in this thesis is a spatially and temporally complete interpolated data set of surface ocean pCO₂ data over an extended period. This data product is the first of its kind, both in terms of its coverage and the fact that it does not rely on the derivation of empirical relationships between pCO₂ and other biogeochemical variables. The technique works as well as or better than previous regional interpolations, with 90% of values likely to be within 30μatm of the actual pCO₂ value.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available