An OSSE for a Local Ensemble Transform Kalman Filter - Based Now-casting System of Biwa Lake, Japan
Abstract:
Having informations in real time about the three-dimensional circulation of the lake will facilitate the mitigation of the extreme events. To obtain such informations, we are developing a now-casting system for the tracking of Biwa lakes’s flow, the first in a limnological environment in Japan. We based our system on the coastal ocean simulator SUNTANS, and we added the LETKF scheme to assimilate available and future data streams. The system generates the ensemble of state vectors using six bred vectors and one unperturbed state vector.
We will present the assessment of performances of the now-casting during an extreme event. To analyse the performances, we first performed a fine-scale simulation of the typhoon Man-Yi (September 2013) on Biwa Lake’s circulation. We chose this specific event due to the strong wind and biomaterial discharge associated with it. The consistency analysis of the simulation was performed based on in-situ temperature data at six depth levels for the vertical consistency, space borne SST for the horizontal consistency. We also used near-infrared satellite data to analyse the propagation of biomaterial after the typhoon.
Because the original simulation was consistent with observations, artificial data streams from the simulation are assimilated into the now-casting system. We show the results of the hindcast of the typhoon ManYi using the now-casting system. We also talk about the presence of instabilities during and after the typhoon that are highlighted by the bred vectors, used in the now-casting system.