Gelaro, R., R. Buizza, TN Palmer, and E. Klinker, 1998: Sensitivity analysis of forecast errors
and the construction of optimal perturbations using singular vectors. J. Atmos. Sci., 55, 1012 …

The essential guide to state-of-the art mobile positioning and tracking techniques—fully
updated for new and emerging trends in the field Mobile Positioning and Tracking, Second …

Conventional optimal interpolation (OI) analysis systems solve the standard statistical
analysis equations approximately, by invoking a local approximation and a data selection …

Four‐dimensional variational data assimilation (4DVAR) is a powerful tool for data
assimilation in meteorology and oceanography. However, a major hurdle in use of 4DVAR …

The demand for minute-scale forecasts of wind power is continuously increasing with the
growing penetration of renewable energy into the power grid, as grid operators need to …

The known properties of equivalence between four‐dimensional variational (4D‐Var) data
assimilation and the Kalman filter as well as the fixed‐interval Kalman smoother point to …

A Simple Data Assimilation System for Complex Snow Distributions (SnowAssim) in:
Journal of Hydrometeorology Volume 9 Issue 5 (2008) Jump to Content Jump to Main …

The ultimate purpose of environmental studies is the forecast of its natural evolution. A
prerequisite before a prediction is to retrieve at best the state of the environment. Data …

A new method to quantify the nonlinearity of data assimilation problems is proposed. The
method includes the effects of system errors, measurement errors, observational network …

This article examines the relationship between two apparently unrelated methods for
estimating error statistics or uncertainties of relevance to data assimilation (DA). The first …