International Funding Bodies

European cooperation in the field of Scientific and Technical Research (COST) Action Grant

Advanced Global Navigation Satellite Systems tropospheric products for monitoring severe weather events and climate

This project explores ground-based Global Navigation Satellite System (GNSS) tropospheric products and their role in forecasting severe weather events and climate monitoring.

The project will address new and improved capabilities from new developments in the GNSS and meteorological communities. For the first time, the synergy of the three GNSS systems (the American GPS, Russian GLONASS and European Galileo) will be used to develop new, advanced tropospheric products. This will exploit the full potential of multi-GNSS water vapour estimates on a wide range of temporal and spatial scales, from real-time monitoring and forecasting of severe weather, to climate research.

The primary objectives of this research are:

to develop new GNSS tropospheric products and assess their benefits in operational NWP and now-casting, with a special focus on forecasting of severe weather
to coordinate the analysis of case studies to target known problems with modelling and forecasting of severe weather
to strengthen and extend the dialogue between GNSS tropospheric product providers and end-users from the meteorological and climate communities, stimulate transfer of knowledge and data exchange
to stimulate the exploitation of NWP data as an input to GNSS processing schemes, and assess the benefits for real-time GNSS positioning, navigation, and timing services
to generate recommendations on optimal GNSS reprocessing algorithms for climate applications and standardise the method of conversion between propagation delay and atmospheric water vapour with respect to climate standards
to coordinate the collection, archiving and exchange of raw GNSS data from various regional networks in Europe
to establish a database of reprocessed GNSS tropospheric products at global and regional scales and assess their quality by inter-comparison with in-situ and remote sensing techniques
to collaborate with the climate and meteorological communities, to assess and improve reanalyses and climate models (e.g. by assimilation of reprocessed GNSS tropospheric products) and investigate climate signals (trends and variability).

Another main focus of the project is to strengthen and intensify this inter-disciplinary collaboration and to encourage cross-border cooperation.

Partners

This research is a large scale project involving research institutions from the following countries; Austria, Belgium, Bulgaria, Switzerland, Czech Republic, Germany, Denmark, Estonia, Greece, Spain, France, Hungary, Italy, Luxembourg, Latvia, Netherlands, Norway, Poland, Portugal, Sweden, Slovakia, Turkey, United Kingdom, Australia, Canada, Hong Kong, Tunisia and the United States.

Hong Kong Research Grants Council

3D Water vapour tomographic modelling

This project develops a 3D water vapour tomographic modelling technique to improve weather forecasting in Hong Kong and mainland China.

Extreme weather events have caused significant casualties and property damage worldwide in recent times (Goklany, 2009). Floods, as a typical extreme weather phenomenon in China, claimed more than 700 lives in 2010 alone, resulting in US $21 billion loss and damage (Bloomberg, 2010). These statistics highlight the dire need for a reliable and precise weather forecasting system for extreme weather events.

Water vapour is highly variable in space and time and significantly influences many weather and climate processes and the accuracy of current prediction and forecasting models. It plays an important role in cloud formation, redistribution of water and the control of temperature in the troposphere. In order to better monitor and predict extreme weather events, it is essential to analyse water vapour information (including quantity & uncertainty in the horizontal distribution, vertical profile, and in the time domain) through comprehensive and precise observation and modelling methods. Such analyses will provide crucial data to weather forecasting and climate modelling systems.

This project aims to develop an innovative, continuous, three-dimensional (3D) water vapour tomographic modelling technique using a multiple sensor system based on both ground- and space- based observation techniques. It is expected that the 3D water vapour distribution data extracted in this study of the Hong Kong and mainland China regions will be able to be input into Numerical Weather Prediction (NWP) algorithms to improve forecasting accuracy.

This research will contribute to the improvement of NWP capabilities for Hong Kong and mainland China (particularly for extreme weather prediction). The outcomes of this research will have a significant impact reducing the number of casualties and level property loss incurred during extreme weather events. The outcomes of this research are fundamental for climate change monitoring, hydrological cycle research, planning and prediction of agriculture production, water resource management and environment related decision-making processes.

Partners

This is a joint research venture between the RMIT University SPACE Research Centre and the Hong Kong Polytechnic University’s Department of Land Surveying and Geo-Informatics.

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