Prediction of ocean colour: Monte Carlo simulation applied to a virtual ecosystem based on the Lagrangian Ensemble method
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...
| Published in: | International Journal of Remote Sensing |
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| Main Authors: | , |
| Other Authors: | |
| Format: | Article in Journal/Newspaper |
| Language: | English |
| Published: |
Taylor & Francis
2004
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| Subjects: | |
| Online Access: | https://doi.org/10.1080/0143116031000139809 http://ir.lib.ncku.edu.tw/handle/987654321/96022 |
| Summary: | 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. |
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