The team of researchers from UPWr, TU Wien, U Wrocław, and U Sofia, made a breakthrough in bringing the GNSS tomography closer to the end-user. The GNSS tomography is a technology to picture 3D distribution of water vapour using the GNSS signal. Until now it was a matter of research in both remote sensing and meteorology. However, recent works by Trzcina et al., (2020) and Łoś et al., (2020), from SpaceOS UPWr, for the first time, show that it is a vital solution to both forecasting and nowcasting.
In the recent paper by Trzcina et al., (2020) researchers show that the developed tomography specific assimilation operator can achieve a reduction of water vapour uncertainty by 0.5% (Fig. 1) which leads to 0.1 mm enhancements in rain bias forecast. These small numbers are actually converted to large benefits to end-users changing the intensive rain into a drizzle or clean road into a black ice-covered trap in 18h forecast.
Another dimension to the use of tomography brings a new paper by Łoś et al., (2020) where authors demonstrated that the 3D troposphere model, and point GNSS observations could be used with machine learning algorithms to get a short time storms forecast (Fig. 2). This study demonstrated that the GNSS data alone can predict the location of the discharges in the next 2h with 87% accuracy.
We are working with our business partners to make these solutions available to the public soon!
Łoś, M.; Smolak, K.; Guerova, G.; Rohm, W. (2020). GNSS-Based Machine Learning Storm Nowcasting. Remote Sens. 12, 2536, https://doi.org/10.3390/rs12162536
Trzcina, E., Hanna, N., Kryza, M., & Rohm, W. (2020). TOMOREF operator for assimilation of GNSS tomography wet refractivity fields in WRF DA system. Journal of Geophysical Research: Atmospheres, 125, https://doi.org/10.1029/2020JD032451