Data assimilation (DA) aims to optimally combine model forecasts and observations that are
both partial and noisy. Multi‐model DA generalizes the variational or Bayesian formulation …

Evaluating impacts of observations on the skill of numerical weather prediction (NWP) is
important. The Ensemble Forecast Sensitivity to Observation (EFSO) provides an efficient …

Recent studies have shown that the assimilation of all-sky infrared (IR) observations can be
beneficial for tropical cyclone analyses and predictions. The assimilation of tail Doppler …

Strongly coupled data assimilation (SCDA), where observations of one component of a
coupled model are allowed to directly impact the analysis of other components, sometimes …

The initial field has a crucial influence on numerical weather prediction (NWP). Data
assimilation (DA) is a reliable method to obtain the initial field of the forecast model. At the …

Prediction of spatiotemporal chaotic systems is important in various fields, such as numerical
weather prediction (NWP). While data assimilation methods have been applied in NWP …

Proactive quality control (PQC) is a fully flow-dependent QC for observations based on the
ensemble forecast sensitivity to observations technique (EFSO). It aims at reducing the …

Proactive quality control (PQC) is a fully flow dependent QC based on ensemble forecast
sensitivity to observations (EFSO). Past studies showed in several independent cases that …

To improve the forecast accuracy of numerical weather prediction, it is essential to obtain
better initial conditions by combining simulations and available observations via data …

Data assimilation is a crucial component in the Earth science field, enabling the integration
of observation data with numerical models. In the context of numerical weather prediction …