Research

Oceanography
Team Members: Phillip Moore, Amanda Bland, Diaminatou Goudiaby
Team Mentor: Dr. Jinchun Yuan
[Team Website]
A Multiple Linear Regression of pCO₂ Against Sea Surface Temperature, Salinity and Chlorophyll a at Station ALOHA and its Potential for Estimate pCO₂ From Satellite Data

ABSTRACT

The Ocean is one of the major reservoirs of carbon and can be a major sink of anthropogenic carbon dioxide. Together with pH, alkalinity, and total dissolved inorganic carbon (DIC), partial pressure of carbon dioxide (pCO₂) is one of the four essential parameters for determining aquatic CO₂ systems. These four CO₂ parameters are interrelated through chemical equilibrium and the determination of any two is sufficient for calculating the other two parameters. Ship-based oceanographic research cruise, that is expensive to operate and inefficient to provide global coverage, has long been th2e main source of data for characterizing oceanic CO₂ system. Recently Lohrenz and Cai (2006) conducted a field study of pCO₂, temperature, salinity, and chlorophyll a in surface waters of the Northern Gulf of Mexico and developed a correlation method for estimating carbon dioxide distribution from the Moderate Resolution Imaging Spectrophotometer (MODIS) remote sensing data. Although it showed great potential, the correlation is based on field data with a small temperature variation and typical salinity, and it is not clear if it can be applied elsewhere. Here, we propose to extend the applicability of the method by conducting a data analysis study of field observations conducted at station ALOHA (A Long-Term Oligarchic Habitat Assessments)
Our primary goal of the research project was to develop a multiple linear correlation between pCO₂ and a combination of temperature, salinity, dissolved organic carbon, particular carbon, and chlorophyll a. Specifically, we: (1) Obtained field data of alkalinity, DIC, temperature, salinity, and Chlorophyll a determined at station ALOHA in the last two decades; (2) Calculated pCO₂ from alkalinity and DIC; (3) Applied the correlation method to test the applicability of the method in the central North Pacific Ocean; (4) Applied the correlation method and predict the distributions of partial-pressure and air-sea fluxes of carbon dioxide in the central Pacific Ocean from MODIS data.

Comiing Soon.......More Work!!!!!