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This section presents a twin experiment aimed for getting more understanding about the data assimilation under an idealized situation. In reality, model noise as well as the true state of a system is unknown. One needs to make certain assumptions in order to apply a data assimilation technique. A twin experiment allows us to study the effect of various assumptions on the behaviour of a data assimilation system. The goal of this first twin experiment is to check if the data assimilation can improve the estimate of all model state variables for the Yeongsan EFDC model in an ideal case where all error statistics are known.
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The study period is the whole year 2015. The simulations are splitted into shorter simulations of 3 days; each simulation started from the previous run. The first run with T0=01-01-2015 00:00 (GMT+9) starts from T-10 days (21-12-2014 00:00 GMT+9).
In this experiment, an EnKF with 8 ensemble members is used, running on a machine with CPU 3.20 GHz and RAM 32 GB. The simulation took about 59 hours to finish (about 0.5 hour per 3 day interval).
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