Seasonal Variation in Coastal Air-Sea CO2 Exchange from the Scripps Pier in San Diego, California

Melissa Ward, San Diego State University and Bodega Marine Laboratory, San Diego, CA, United States; UC Davis, CA and Walter C Oechel, San Diego State University, San Diego, CA, United States
Abstract:
The world’s oceans absorb approximately one-third of anthropogenic CO2 emissions and coastal waters could be responsible for 30% of this absorption. Consequently, there has been significant effort over the last few decades to understand the patterns and controls on air-sea exchange of CO2 (flux). CO2 fluxes can differ dramatically with changes in ambient meteorological and oceanographic conditions. As such, carbon exchange in coastal waters remains poorly understood due to their highly dynamic, heterogeneous nature. The analysis presented here measured CO2 fluxes over coastal waters from the Scripps Pier in San Diego, California continuously for 12 months using eddy covariance. These data show that the 2.5 km area of coastal sea represented by the eddy covariance tower act as a strong CO2 sink on an annual basis, but that this CO2 flux is highly temporally variable. Specifically, the summer and spring months act as strong sinks, while the winter months act as weak sinks to weak sources of CO2. This variation in CO2 exchange was explored by measuring a large number of physical and biological parameters for correlation comparisons. Among these parameters, wind speed and photosynthetically active radiation both demonstrated control over the CO2 flux to varying levels of significance over different temporal scales. While seasonal and monthly trends are apparent from the current data, further investigation is necessary to understand flux controls under shorter temporal periods (e.g., daily, hourly). Nonetheless, this study provides insight on the amount of carbon absorbed annually by productive coastal waters. Furthermore, understanding the regulatory mechanisms behind these fluxes can ultimately improve our global carbon models and future climate change projections.