Host: The Japan Society of Mechanical Engineers
Name : [in Japanese]
Date : November 23, 2018 - November 25, 2018
We investigated the impact of observation position for data assimilation using sensitivity analysis. The impact of observation position was evaluated by an observability index proposed by Kang et al. (2009). We conducted an identical twin experiment to evaluate the assimilated results using the WRF forecasting model. Three-dimensional variational data assimilation (3D-VAR) method was employed to assimilate observations of wind, whose locations were selected based on the observability index. The empirical observability Gramian matrix composed from time series of model outputs was used to obtain a map of observability index in the WRF domain. The results showed the correlation between the improvement of accuracy and the map of the observability index in the case where one observation was considered.
