Assimilation of the GPS-derived integrated water vapour (IWV) in the MeteoSwiss numerical weather prediction model—a first experiment

摘要

A high resolution (7 km) limited area model called aLpine model (aLMo) is used for operational numerical weather prediction (NWP) at MeteoSwiss. A continuous data assimilation scheme based on the nudging technique produces the initial conditions for the forecast. Since November 2001 all standard meteorological observations have been routinely assimilated. The goal of this study is to evaluate the benefit of introducing GPS-derived integrated water vapour (IWV) in this scheme. In this first observing system experiment, data provided for COST action 716 "Exploitation of ground based GPS for climate and numerical weather prediction application" are used. A two week period in mid September 2001 was selected, characterized by an advective weather regime and intense precipitation events. On average observations from 80 European GPS sites are assimilated by the model. Results presented here are based on the aLMo assimilation cycle only, the impact on the forecast has not been evaluated. This experiment shows a tendency for GPS data to increase the model IWV amounts in the day-time, and shows a substantial impact of GPS in the southern part of the model domain. The negative bias of the model IWV daily cycle is mainly corrected by assimilating GPS data. An improvement of the daily precipitation cycle over Switzerland for the grid points below 800 m is also observed in the GPS run. The bias precipitation score confirms the better model performance when the GPS data are assimilated. This experiment has also revealed a weakness in the way the IWV is assimilated. In presence of highly inhomogeneous humidity fields an isotropic influence of the IWV increments can be detrimental. The first GPS assimilation results are considered encouraging but need to be consolidated. New assimilation experiments will be performed to investigate the GPS data impact for different weather regimes.