Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12779/6258
Title: Assimilation of MODIS Chlorophyll-a Data Into a Coupled Hydrodynamic-Biological Model of Taihu Lake
Authors: Qi, Lin
Ma, Ronghua
Hu, Weiping
Loiselle, Steven Arthur 
Issue Date: 2013
Project: None 
Journal: IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
Abstract: 
MODIS chlorophyll-a concentration (Chla) data were assimilated into a coupled hydrodynamic-biological model using an Optimal Interpolation method. Simulations were conducted using MODIS data covering Taihu Lake in May 2009, when algal blooms typically begin to occur. The results of the assimilation approach showed improvements in the estimation of Chla distributions in spatial coherency and temporal continuity. Bias of assimilation (model run after assimilation) was 5.1%, with a RMSE of 49.7%. In comparison, the free run (model run without assimilation) had a bias of -34.9% and RMSE of 176.5%. In situ data used for comparison showed reduced RMSE and the Bias for assimilation. Two sensitivity experiments were used to determine the suitable correlation length scale with respect to observation data accuracy. The result showed that 500m is the optimum scale to construct the background error covariance matrix. The sensitivity experiment of observational data accuracy also showed that more accurate observation data allowed for better assimilation results.
Description: 
65467
URI: http://hdl.handle.net/20.500.12779/6258
ISSN: 1939-1404
DOI: 10.1109/JSTARS.2013.2280815
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