UC Santa Barbara

The ocean contains reservoirs of carbon that influence atmospheric CO2, impact climate, fuel deep-sea metabolism, and sustain fisheries worldwide. Despite the ocean’s substantial role in the global carbon cycle, much remains to be known about the fundamental influences for carbon transport over climatically relevant scales. These details remain elusive because 1) available data is sparse, 2) the collection of new data is expensive, time consuming, and logistically difficult, and 3) the system itself is complex and highly variable. Overall, this dissertation confronts sources of uncertainty for data and models associated with differences in technology, incongruous spatiotemporal sampling schemes, and model complexity in order to extract as much as possible given what is currently available to use.

The chapter specific objectives are as follows:

(1) Examine how intrinsic and extrinsic sources of variability affect model calibration through a compilation of data sets spanning method, space and time,

(2) Assess mechanisms of the biological pump given available data products, and diagnose mechanistic parameter sensitivities as they relate to experimental/observational work,

(3) Test and recalibrate parameters to predict the flux of carbon from a rapidly growing technology (Underwater Vision Profiler data) from the surface to depth.

In Chapter 1 carbon export predictions from a mechanistic model are compared with observations of particulate organic carbon (POC) fluxes from several datasets compiled from the literature spanning different space, time, and depth scales as well as using different observational methodologies. Model parameters are optimized to provide the best match between model-predicted and observed POC fluxes, explicitly accounting for sources of error associated with each dataset. Model-predicted globally integrated values of POC flux at the base of the euphotic layer range from 3.8 to 5.5 Pg C yr-1, depending on the dataset used to optimize the model. Results from Chapter 2 reveal that modeled carbon export pathways also vary depending on the dataset used to optimize the model, and depending on the processes explicitly represented within a quite of nested models. Chapter 3 tests the relationship between the particle size distribution and flux in the global ocean using abundant observations of particle size spectra in tandem with high-resolution model outputs. Results motivate the need for improved parameterizations that link particle size to flux based on depth and/or surface ecosystem characteristics. Altogether these findings highlight the importance of collecting field data that average over the substantial natural temporal and spatial variability in carbon export fluxes, and of advancing satellite algorithms for ocean NPP, in order to improve predictions of biological carbon export.