All data assimilation systems are affected by biases, caused by problems with the data, by
approximations in the observation operators used to simulate the data, by limitations of the …

Treatment of Observation Error due to Unresolved Scales in Atmospheric Data Assimilation in:
Monthly Weather Review Volume 134 Issue 10 (2006) Jump to Content Jump to Main …

Statistical‐analysis methods are generally derived under the assumption that forecast errors
are strictly random and zero in the mean. If the short‐term forecast, used as the background …

In this paper, the optimal configurations of model resolution, observation resolution and
observation density are investigated in a simple one‐dimensional framework. In this context …

Variational and ensemble methods have been developed separately by various research
and development groups and each brings its own benefits to data assimilation. In the last …

This article reviews the characteristics of forecast error statistics in meteorological data
assimilation from the substantial literature on this subject. It is shown how forecast error …

Representation, representativity, representativeness error, forward interpolation error,
forward model error, observation‐operator error, aggregation error and sampling error are …

Recent data assimilation developments which have taken place at numerical weather‐
prediction centres are briefly discussed, from the perspectives of both the importance of data …

Observation bias correction schemes are important components of the data assimilation
(DA) systems used in operational numerical weather prediction (NWP). They are used at …

In this study, the localization of background‐error correlations in both the spectral and the
spatial domains is examined. While spatial localization has become a standard approach for …