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This article discusses the difficulties inherent in weather prediction that persist despite advances in weather prediction technology. Specifically, the focus is on the problems that global warming creates for weather forecasting for services such as Météo France. The differences between the time scale which Meteorology and Climatology concern themselves with is examined.

This article discusses three thousand individuals who work for the organization Météo France on a daily, volunteer basis during the year 2008. It discusses their motivations, which include better understanding the territory they live in, as well as the recognition they receive, even if they are not responsible for any weather prediction.

A depth-averaged, numerical storm-surge model has been developed and configured to provide a stand-alone system to forecast tropical cyclone storm-surges. The primary data requirement for modeling storm surges is accurate surface wind and atmospheric pressure fields, in particular in the vicinity of maximum winds. These fields are inferred from an analytical-empirical cyclone model, which requires only cyclone position, intensity, and size. The model has been adapted to run on a personal computer in a few minutes. The storm-surge model was tested in hindcast mode on tropical cyclones which gave significant surges over the French overseas territories during the period 1975-1990. The system has been operated since the 1990s in the French Antilles, New Caledonia, the French Polynesia, and La Reunion. The model can be used in two different ways. In real-time mode as a tropical cyclone is approaching an island or in climatological mode: a cyclone climatology is used to prepare a database of precomputed surges. [ABSTRACT FROM AUTHOR]

The French operational radar network is being upgraded and expanded from 2002 to 2006 by Meteo-France in partnership with the French Ministry of the Environment. A detailed examination of the quality of the raw polarimetric variables is reported here. The analysis procedures determine the precision of the measurements and quantify errors resulting from miscalibration, near-radome interference, and noise effects. Correction methods to remove biases resulting from effective noise powers in the horizontal and vertical channels, radar miscalibration, and the system offset in differential propagation phase measurements are presented and evaluated. Filtering methods were also required in order to remove azimuthal dependencies discovered with fields of differential reflectivity and differential propagation phase. The developed data quality analysis procedures may be useful to the agencies that are in the process of upgrading their radar networks with dual-polarization capabilities. [ABSTRACT FROM AUTHOR]