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|Title:||Assimilation of MODIS Chlorophyll-a Data Into a Coupled Hydrodynamic-Biological Model of Taihu Lake||Authors:||Qi, Lin
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.
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