Estimating the state of the atmosphere from observations is essential for monitoring climate and also for the initialization of weather, sub-seasonal and seasonal weather forecasts. A popular way of making such estimates is using a method called the Ensemble Kalman Filter.
A known weakness of the Ensemble Kalman filter approach is that its ability to provide state estimates that closely match densely distributed observations is very limited.
This paper describes a computationally inexpensive innovative variation on the technique that greatly ameliorates this difficulty.
- Huang, B., X. Wang, and C.H. Bishop, 2019: The High-Rank Ensemble Transform Kalman Filter.Mon. Wea. Rev.,147, 3025–3043, https://doi.org/10.1175/MWR-D-18-0210.1