The use of GNSS observations from reference stations for the derivation of Integrated Water Vapour and assimilated into Numerical Weather Prediction Models has been demonstrated and is in use for weather prediction. With the emergence of multi-constellation and multi-frequency GNSS the possibilities of weather prediction with GNSS are increasing dramatically.
Furthermore, with the emergence of powerful handheld GNSS receivers, with multi-frequency capability and access to both code and carrier-phase observables, the possibility of GNSS weather monitoring with collaborative crowdsourcing is emerging as a very promising field.
This activity, therefore, is needed in order to assess the use of GNSS carrier-phase and multi-sensor localisation in smartphones and similar devices for monitoring extreme weather and supporting weather forecasting. Furthermore, the development and testing of a complete end-to-end demonstrator of this innovative concept is hereby proposed to prove the concept.
Some of the innovation aspects proposed are the following:

• use of low-quality sensors (namely fitted in handheld devices) but in a very large number, allowing a very large sample of observations and spatial resolution accuracy;
• maximising the exploitation of GNSS data for weather forecasting, in particular the use of code and carrier-phase observables (future chipsets will provide these new observables for multi-constellation, driven by the Android version providing those), and preferably dual-frequency (new feature for handheld receivers), in particular for the derivation of integrated water vapour (IWV) measurements for assimilation in weather prediction models (this requires a high-precision processing approach). The use of this observable has not yet been exploited because they were not available until very recently.

The tasks to be performed will include:

• a thorough assessment of all existing GNSS technologies and GNSS data processing in support of this proposed weather monitoring (e.g. determining water vapour content);
• understanding of the potential of other weather-sensitive sensors built in to mobile phones (existing or that could be integrated);
• assessing the exploitation of mobile weather sensitive geo-location and collaborative crowdsourcing for weather monitoring and forecasting;
• an end-to-end representative demonstrator.