Underestimation of surface <i>p</i>CO2 and air-sea CO2 fluxes due to freshwater stratification in an Arctic shelf sea, Hudson Bay
Bibliographic record
Abstract
The objective of this study is to quantify the impact of freshwater stratification on the vertical gradients of partial pressure of CO2 (pCO2) and estimates of air-sea CO2 exchange in Hudson Bay during peak sea-ice melt and river runoff. During the spring of 2018, we sampled water in Hudson Bay and Hudson Strait for dissolved inorganic carbon, total alkalinity, salinity, the oxygen stable isotope ratio in the water (δ18O), and other ancillary data. The coastal domain and regions close to the ice edge had significant vertical concentration gradients of pCO2 across the top meters of the ocean due to the presence of a stratified fresh layer at the surface. The pCO2 and salinity in the central (where sea-ice melt was significant) and the southeast (where river runoff and sea-ice melt were significant) side of the bay generally increased with depth, with average gradients of 4.5 μatm m–1 and 0.5 m–1, respectively. Ignoring these gradients causes a significant error in calculating air-sea CO2 fluxes, especially when using shipboard underway systems that measure pCO2 at several meters below the sea surface. We found that the oceanic CO2 sink in Hudson Bay is underestimated by approximately 50% if underway pCO2 system measurements are used without correction. However, we observed that these gradients do not persist for more than 5 weeks following ice melt. We have derived a linear correction for underway pCO2 measurements to account for freshwater stratification during periods of 1–5 weeks after ice breakup. Given the lack of measurements in stratified Arctic waters, our results provide a road map to better estimates of the important role of these regions in global carbon cycles.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".