Periodic time-dependent parameters improving forecasting abilities of biological ocean models

Abstract

Using two emulator-based procedures, we estimate time-dependent values for two key plankton parameters in a three-dimensional biogeochemical (BGC) ocean model. The estimation is based on a 4 year time series of daily surface satellite chlorophyll observations. The estimated parameters display an annual periodicity that can be explained by the succession of plankton groups in the study region. Model simulations using these parameters show improved fit to observations and better forecasting abilities compared to simulations with constant optimal parameters; the newly introduced sequential parameter estimation procedure creates the strongest improvement. The inclusion of time-dependent parameters represents a simple way to improve the predictive skill of BGC models and their representation of plankton dynamics.

Publication
in Geophysical Research Letters