Targeting Optimal Use of GPS Humidity Measurements in Meteorology
Knowledge of the atmospheric distribution of water vapour is of key importance in weather prediction and climate research. It is tightly coupled to processes like energy transfer, precipitation, and is an important greenhouse gas. However, currently there is lack of knowledge about the actual humidity field, both due to a shortage of observations and a sub optimal handling of humidity in the data assimilation systems, which are used to make estimates of the actual atmospheric field. Such fields are used to start numerical weather prediction models and for climate monitoring. Global Positioning System (GPS) signals are particularly sensitive to water vapour. The main purpose of this project is to develop and refine methods enabling the use of GPS data from existing European GPS stations in numerical weather prediction models, and to assess the impact of such data upon the skill of weather forecasts.
The GENERAL OBJECTIVES for the project are to improve the use of GPS data for numerical weather prediction and climate monitoring. This shall be done by innovation of new techniques and methodologies enabling proper correction of error sources identified in previous work, as well as by initiating use of the more detailed information available in the form of the individual delays between each receiver and the GPS satellites visible to it, rather than the single average type delay used by current methods. In the project we will:
- Carry out research to optimise the assimilation of ground-based GPS in numerical weather prediction models. This research will include a proper modelling of the GPS measurement errors and application of more advanced assimilation techniques. Each step/component in the optimisation of the assimilation techniques will be verified by impact studies.
- Develop methods for use of GPS slant delays in numerical weather prediction. Use of slants will enhance the amount of information available from each ground station.
- Running a research mode data collection, by co-ordinated pre-processing and distribution of ground-based GPS measurements from Europe through a few European processing centres in support of the proposed data assimilation research efforts. The data processing centres will provide pre-processed data from subsets of the total European network, and each subset of the data should have comparable error characteristics. These error characteristics will be documented through comparisons of data from stations included in several of the network subsets (network overlap).
- Investigate the benefit of using ground-based GPS-data in numerical weather prediction using the improved assimilation software through extended parallel data assimilation and forecast experiments, with and without ground-based GPS measurements, covering all four seasons.
After the project, the resulting methodologies can be utilised by European weather forecast agencies at large, and the results help pave the road for a future co-ordinated, operational European GPS moisture observation system. The exploitation of this new source of Earth Observation data is expected to benefit in particular the prediction of precipitation. In the longer run it will benefit also climate monitoring. When the Galileo satellites are launched the amount of observations of this type will increase and some of the error sources can be more easily controlled.