Design and implementation of an experimental data assimilation system for chlorophyll-a in Lake Taihu based on the ensemble Kalman filter

doi:10.7523/j.issn.2095-6134.2013.05.009

Abstract

Abstract:

We develop a novel data assimilation approach for the prediction of algal blooms in Lake Taihu. Our approach is based on a 2D ecological model which combines a physical model, 250 m MODIS inversion chlorophyll-a data, and an ensemble Kalman filter (EnKF) analysis scheme. Our results indicate that the data assimilation approach is reliable for predicting algal blooms in these complex waters.

Key words: data assimilation, EnKF, Chlorophyll-a, algal bloom forecast

CLC Number:

X328

WANG Ze-Ren, MA Rong-Hua, DUAN Hong-Tao, ZHANG Yu-Chao, QI Lin. Design and implementation of an experimental data assimilation system for chlorophyll-a in Lake Taihu based on the ensemble Kalman filter[J]. , 2013, 30(5): 628-636.

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