Observing Temporally Varying Synoptic-Scale Total Alkalinity and Dissolved Inorganic Carbon in the Arctic Ocean

The long-term absorption by the oceans of atmospheric carbon dioxide is leading to the slow decline of ocean pH, a process termed ocean acidification (OA). The Arctic is a challenging region to gather enough data to examine the changes in carbonate chemistry over sufficient scales. However, algorithms that calculate carbonate chemistry parameters from more frequently measured parameters, such as temperature and salinity, can be used to fill in data gaps. Here, these published algorithms were evaluated against in situ measurements using different data input types (data from satellites or in situ re-analysis climatologies) across the Arctic Ocean. With the lowest uncertainties in the Atlantic influenced Seas (AiS), where re-analysis inputs achieved total alkalinity estimates with Root Mean Squared Deviation (RMSD) of 21 mu mol kg-1 and a bias of 2 mu mol kg-1 (n = 162) and dissolved inorganic carbon RMSD of 24 mu mol kg-1 and bias of -14 mu mol kg-1 (n = 262). AiS results using satellite observation inputs show similar bias but larger RMSD, although due to the shorter time span of available satellite observations, more contemporary in situ data would provide further assessment and improvement. Synoptic-scale observations of surface water carbonate conditions in the Arctic are now possible to monitor OA, but targeted in situ data collection is needed to enable the full exploitation of satellite observation-based approaches. The long-term absorption by the oceans of atmospheric carbon dioxide is leading to the slow decline of ocean pH, a process termed ocean acidification (OA). Sea surface salinity and temperature measurements from satellites or in situ re-analysis products can be used as input to empirical algorithms to calculate OA parameters. This paper provides a first analysis of published Arctic Ocean empirical algorithms to estimate surface water OA parameters using observation-based data sets. Results show promise in the Atlantic influenced Seas using both in situ re-analysis and satellite products, but satellite salinity is relatively recent, and a paucity of in situ data in the satellite salinity era precludes a robust assessment. To fully exploit satellite-based approaches, efforts need to focus on collecting in situ data while these satellites are overhead and operating in orbit. Observation-based data sets enable synoptic spatio-temporal assessments of Arctic Ocean carbonate system parametersRe-analysis and satellite products predict total alkalinity with accuracies of similar to 21 mu mol kg-1Targeted in situ data collection is needed to fully exploit satellite observations in the Arctic to enable carbonate system monitoring