Prediction of ocean colour: Monte Carlo simulation applied to a virtual ecosystem based on the Lagrangian Ensemble method

Cheng Chien Liu, J. D. Woods

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

The annual variation of ocean-colour signals in the North Atlantic Ocean is successfully simulated by combining the plankton ecosystem model and the optical model. The first model uses the Lagrangian Ensemble method of Woods and Barkmann to simulate the upper-ocean ecosystem, including the vertical profile of chlorophyll concentration. The second model employs the Monte Carlo technique to compute the optical environment for that virtual ecosystem with 31 wavebands in the visible spectrum (400–700 nm). Ocean-colour signals are determined from the spectrum of the relatively few photons that are scattered back up through the sea surface. This information is then substituted into various satellite ocean-colour algorithms to calculate the satellite-derived surface chlorophyll concentration. Results show that substantial differences exist among the predictions from different ocean-colour algorithms. In addition, the average chlorophyll concentration of the upper few layers is not equal to the satellite-derived surface chlorophyll concentration. Our research encourages the adoption of the Monte Carlo optical model to simulate the satellite ocean-colour signals for the purpose of evaluating the plankton ecosystem model.

Original languageEnglish
Pages (from-to)921-936
Number of pages16
JournalInternational Journal of Remote Sensing
Volume25
Issue number5
DOIs
Publication statusPublished - 2004 Mar

All Science Journal Classification (ASJC) codes

  • Earth and Planetary Sciences(all)

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