Improving the operational forecasting system of the stratified flow in Osaka Bay using an ensemble Kalman filter–based steady state Kalman filter

Numerical models of a water system are always based on assumptions and simplifications that may result in errors in the model's predictions. Such errors can be reduced through the use of data assimilation and thus can significantly improve the success rate of the predictions and operational forecasts. The ensemble Kalman filter (EnKF) is a...

Data assimilation in atmospheric chemistry models using Kalman filtering

The problem of air pollution around urbanized area across Europe is strongly related to ozone. Ozone is a result of photo-chemical oxidation, and therefore an indication of the presence of pollutants. Overexposure to ozone is harmful to the health, and the concentrations are therefore measured on a regular basis to check exceedance of air...