AOS Research Staff Profile
Brendan Carter
Postdoctoral Research Associate
Address: 307 Sayre Hall
Phone: (609) 258-0979
Email: brcarter at princeton.edu
Publications Vita
Research Field
My research is focused on the questions:
"How does carbon cycle through the oceans?"
"How might we better constrain and decrease the uncertainties on our knowledge of the marine carbon cycle?"
To date, I have primarily approached these questions from the starting point of hydrographic data. My thesis work began with the development of a semi-autonomous system for shipboard measurements of seawater pH, a key parameter for any investigation of the marine carbon cycle. The system is designed to make these measurements more accessible while maintaining the high precision that has become their hallmark. It has now been deployed on several (4 and counting) hydrographic cruises associated with the CLIVAR program, and may also prove an important tool for calibrating pH sensors currently under development for moorings and floats. Additionally, I’ve used the datasets generated by these hydrographic cruises in inverse models designed to examine biogeochemical cycling in the mode and intermediate waters of the Southern Ocean. My aim with this effort has been to assess the biasing effects of mixing on several commonly-used inverse methods, and to develop a method for extracting long timescale trends from dataset comparisons that are dominated by the effects of short timescale (<1 year) phenomena.
I am currently working to combine the inverse and forward modeling approaches. The forward modeling method suffers from uncertainty in the assumptions inherent to the model. The inverse method typically suffers from a lack of measurement constraints to fully resolve the time-history of a parcel of measured water. I intend to incorporate the high-uncertainty estimates of processes obtained with forward models into inverse models that would otherwise be under-constrained. I am beginning this effort by reexamining calcium carbonate cycling using alkalinity distributions and ocean mixing parameterizations from ocean circulation models.