Recent progress in machine learning (ML) inspires the idea of improving (or learning) earth
system models directly from the observations. Earth sciences already use data assimilation …

This article reviews developments towards assimilating cloud‐and precipitation‐affected
satellite radiances at operational forecasting centres. Satellite data assimilation is moving …

An order of magnitude reduction in the cost of four‐dimensional variational assimilation (4D‐
Var) is required before operational implementation is possible. Preconditioning is …

An ensemble Kalman filter may be considered for the 4D assimilation of atmospheric data. In
this paper, an efficient implementation of the analysis step of the filter is proposed. It employs …

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 …

To assimilate atmospheric and surface radiance measurements from satellites in a
numerical weather prediction model, a fast radiative transfer model is required to compute …

In the first of this set of three papers, the formulation of the European Centre for Medium‐
Range Weather Forecasts (ECMWF) implementation of 3D‐Var is described. In the second …

With improved assimilation techniques, it is now possible to directly assimilate cloud-cleared
radiances, rather than temperature and moisture retrievals, in objective analyses. The direct …

Ten years ago, humidity observations were thought to give little benefit to global weather
forecasts. Nowadays, at the European Centre for Medium‐range Weather Forecasts …

Recent verification statistics show a considerable improvement in the accuracy of forecasts
from three global numerical weather prediction systems. The improvement amounts to about …