Observing the seasonal cycle of pCO2 from autonomous pH measurements in the South Atlantic sector of the Southern Ocean

• Main Author: Rawatlal,Mishka
• Other Authors: Altieri, Katye E, Monteiro, P M S
• Format: Master Thesis
• Language: English
• Published: Faculty of Science 2020
• Subjects: Oceanography; Antarctic; Indian; Southern Ocean; Antarc*
• Online Access: http://hdl.handle.net/11427/36916; https://open.uct.ac.za/bitstream/11427/36916/1/thesis_sci_2020_rawatlalmishka.pdf

Global climate predictions hinge on our understanding of the global carbon cycle, and in particular, the role of the Southern Ocean (SO). Sea surface measurements across the SO are sparse and subject to temporal, spatial and seasonal biases. These biases arise from the inaccessibility of the SO due to the high-risk weather conditions and ice coverage experienced during the winter. This study looks at the feasibility of autonomous measuring platforms in the SO for the purpose of reducing the uncertainty bias observed in the SO, constraining the global carbon budget and observing the seasonal cycle of carbonate chemistry in seawater. The high resolution Wave Glider (WG) dataset located in the sub-Antarctic zone (SAZ) of the SO, during the spring-summer bloom period of 2013/2014, resolves the seasonal cycle of TA from pCO2 and pH (WGTA) and the empirical expression for TA (Lee et al., 2006) using salinity and temperature and measurements of pH. The discrepancy between WGTA and the calculated TA gives rise to a summer bias in the seasonal cycle of TA attributed to the uptake of nitrate during the bloom period, and the entrainment of nitrate in the pre-bloom period. The effect of this bias on estimating pCO2 indicates that the amplitude of the pCO2 seasonal cycle may be overestimated by as much as 3.6% during the pre-bloom period. An assessment of the Lee et al., (2006) TA expression (LeeTA) in the SO regime against shipboard observations showed a significant regional different in TA between the Atlantic Ocean and Indian Ocean sectors of the SO at the onset of winter, where LeeTA overestimates TA observations in the Atlantic Ocean sector. This further emphasises the seasonal bias of the TA algorithm which provides an averaged TA across the SO as a whole. Hence, it is proposed that a regional formulation be developed for the prediction of TA in each ocean sector of the SO. To further assess the performance of empirical expressions for TA, the Carter et al., (2014) LIAR expression, utilized by the Southern Ocean Carbon ...