Improving carbon export estimates through the paired use of autonomous platforms and remote sensing algorithms near Ocean Station Papa

Jacqueline Long1, Andrea J Fassbender2, William Haskell1 and Margaret L Estapa3, (1)Monterey Bay Aquarium Research Institute, Moss Landing, CA, United States, (2)NOAA Pacific Marine Environmental Laboratory, Seattle, United States, (3)Skidmore College, Saratoga Springs, NY, United States
Satellites have the ability to collect near-global estimates of ocean net primary production (NPP) and export efficiency (e-ratio) on a daily basis; however, they are often limited to clear-sky conditions and observations from the first optical depth in the water column, missing a seasonally varying portion of the euphotic zone. Because satellite ocean color observations are near-surface estimates, they require assumptions to be made about the depth structures of phytoplankton biomass and growth rate in their derivation of NPP. High-resolution (≤5m) water column observations from biogeochemical profiling floats could thus be a useful tool for evaluating the fidelity of remote sensing approaches for NPP and e-ratio by applying algorithms that are commonly used with satellite observations to the float data. Building from prior work in the Subtropical North Atlantic [1], we apply NPP and e-ratio algorithms to observations from historical and active biogeochemical profiling floats in the Subarctic Northeast Pacific Ocean, near Ocean Station Papa (OSP). Nearly a decade of collocated, ~weekly NPP and e-ratio estimates from the floats and satellites are compared and patterns of discrepancy are evaluated. The algorithms are also used to calculate carbon export (equivalent to NPP e-ratio) from float data for comparison with independent carbon export and e-ratio estimates derived from chemical and bio-optical sensors on the floats. Results from this study expand the in situ observational record of NPP, e-ratio, and export throughout the region and provide context for the 2018 NASA EXPORTS cruise.