Improving Weather Forecast Skill through Reduced-Precision Data Assimilation

Forecast and analysis assessment through skill scores

Forecast Skill and Computational Cost of the Correlation Models in 3dvar Data Assimilation

have been conducted. Here I is the identity operator and v is the diffusion tensor, whose spatial variability is derived from the forecast field and m is the spline approximation order. Performance of these BEC representations are compared in the framework of numerical experiments with real 3dVar data assimilation into the Navy Coastal Ocean model (NCOM) in the Western TVopical Pacific. It is s...

Cloudy forecast for weather satellite data.

IN THE NEWS FOCUS STORY “WEATHER forecasts slowly clearing up” (9 November, p. 734), R. Kerr nicely summarizes how the growing improvement in prediction is coming from a focus on “more computer power, the assimilation of radar observations, and more physically realistic models.” He emphasizes that better assimilation of satellite data is a key element of improved forecasting. Unfortunately, the...

Data Assimilation in Reduced Modeling

This paper considers the problem of optimal recovery of an element u of a Hilbert space H from measurements of the form `j(u), j = 1, . . . ,m, where the `j are known linear functionals on H. Problems of this type are well studied [18] and usually are carried out under an assumption that u belongs to a prescribed model class, typically a known compact subset of H. Motivated by reduced modeling ...

Data assimilation of OMI NO2 observations for improving air quality forecast over Europe

This paper concerns the improvements of NO2 forecast due to satellite data assimilation. The Ozone Monitoring Instrument (OMI) aboard NASA Aura satellite provides observations of NO2 columns for air quality study. These satellite observations are assimilated, with the optimal-interpolation method, in an air quality model from Polyphemus, in order to improve NO2 forecasts in Europe. Good consist...