Climate sensitivity and the rate of ocean acidification: future impacts, and implications for experimental design: Towards a Broader Perspective on Ocean Acidification Research Part 2 A special issue of the ICES Journal of Marine Science

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Abstract

The global mean surface temperature and partial pressure of carbon dioxide (CO2) are increasing both in the atmosphere and ocean. Oceanic CO2 uptake causes a decline in pH called ocean acidification (OA), which also alters other biologically important carbonate system variables such as carbonate mineral saturation states. Here, we discuss how a “temperature buffering” effect chemically links the rates of warming and OA at a more fundamental level than is often appreciated, meaning that seawater warming could mitigate some of the adverse biological impacts of OA. In a global mean sense, the rate of warming relative to the CO2 increase can be quantified by the climate sensitivity (CS), the exact value of which is uncertain. It may initially appear that a greater CS would therefore reduce the negative influence of OA. However, the dependence of the rate of CO2 increase on the CS could enhance, nullify or even reverse the temperature buffering effect, depending upon the future trajectory of anthropogenic CO2 emissions. Regional deviations from the global mean seawater temperature and CO2 uptake trends could modulate local responses to OA. For example, mitigation of OA impacts through temperature buffering could be particularly effective in the Arctic Ocean, where the surface seawater warming rate is greater than the global mean, and the aqueous CO2 concentration might increase more slowly than elsewhere. Some carbonate system variables are more strongly affected than others, highlighting the need to develop a mechanistic understanding of precisely which variables are important to each biogeochemical process. Temperature buffering of the marine carbonate system should be taken into account when designing experiments to determine marine species and ecosystem responses to warming and OA, in order that their results accurately reflect future conditions, and therefore can generate realistic predictions when applied to Earth system models.

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