The potential of the ensemble Kalman filter for NWP—a comparison with 4D‐Var

TLDR

The study reviews the ensemble Kalman filter’s assimilation characteristics and implementation ease, compares it to 4D‑Var, and highlights hybrid methods as attractive for limited‑area mesoscale NWP. The authors review EnKF’s expected assimilation characteristics and ease of implementation, compare it to 4D‑Var, and discuss hybrid methods for limited‑area mesoscale NWP. EnKF is attractive for new medium‑range ensemble NWP systems but is less suitable for systems with wide‑scale uncertainty and may not use high‑resolution satellite data as effectively as 4D‑Var. © 2003 Crown copyright, Royal Meteorological Society.

Abstract

Abstract The ensemble Kalman filter (EnKF) is reviewed for its expected assimilation characteristics and ease of implementation, and compared to the currently more popular four‐dimensional variational assimilation (4D‐Var). The EnKF is attractive when building a new medium‐range ensemble numerical weather prediction (NWP) system. However it is less suitable for NWP systems with uncertainty in a wide range of scales; it may not use high‐resolution satellite data as effectively as 4D‐Var. For limited‐area mesoscale NWP systems a hybrid method is attractive. © Crown copyright, 2003. Royal Meteorological Society