A computationally efficient Kalman smoother for the evaluation of the \(\text{CH}_4\) budget in Europe (Q1303245)

Two new data assimilation methods of the Kalman filtering approach applied to the evaluation of \(\text{CH}_4\) budget in the atmosphere of Europe using simulated and real concentration data are reported. The heavy computation burden and huge storage requirement of the conventional Kalman filter for large-scale systems are removed by using special efficient computational algorithms for approximating optimal Kalman filtering. A smoother algorithm is developed to identify the emission input uncertainty.