Quantifying the E ects of Noise on Biogeochemical Models

The need to understand the eeects of anthropogenic perturbations on the ocean carbon cycle has sparked a new interest in biogeochemical models in recent years. These models are now being coupled with physical ocean circulation models. For this coupling to generate realistic uxes of nutrients and carbon, the biogeochemical equations need to exhibit realistic dynamics. As a rst step in the development of a class of stochastic biogeochemical models, we propose an approach to quantify the eeects of diierent types of noise on biogeochemical system dynamics. The biogeochemical model we use in our investigation is a model of plankton dynamics and nitrogen cycling. It is a compartmental model (NPZ) consisting of a compartment for Nitrogen (N), Phytoplankton (P), and Zooplankton (Z). The ows or intercompartmental exchanges are modeled as a nonlinear system of three rst order diierential equations. The types of noise of interest are both independent and correlated. Here we present a preliminary study of the eeects of noise on the state variables of the system and parameter errors. Because the noise is an integral part of the system's dynamics, a nonlinear time series approach is used to quantify the dynamics and predictability of the system. This involves tting nonlinear models, estimating dynamical systems quantities of interest such as global and local Lyapunov exponents along with measures of uncertainty for these estimates.