- 1National Research Council of Italy—Institute of Atmospheric Sciences and Climate (CNR-ISAC), via del Fosso del Cavaliere 100, 00133 Rome, Italy (rc.torcasio@isac.cnr.it)
- 2Geomatics Research & Development srl (GReD), via Cavour 2, 22074 Lomazzo, Italy
- 3University of Rome “La Sapienza” - Faculty of Civil and Industrial Engineering, via Eudossiana, 18 - 00184 Rome - Italy
A reliable Numerical Weather Prediction (NWP) is useful to guide responsive actions for mitigating the impact of severe weather. The accuracy of the forecast given by NWP models depends also on the knowledge of the initial conditions, which can be improved by data assimilation.
In the last three decades, there has been a significant advancement of GNSS technology, which has broadened its range of applications, especially within the realm of the meteorology. GNSS-ZTD has proven to be an important source of water vapor data, which can be used to improve the weather forecast, in general, including intense precipitation events (Torcasio et al., 2023).
However, a relevant part of the information related to water vapor distribution remains still unexploited. In fact, routinely zenith tropospheric delays (ZTDs) are estimated off-line generally on an hourly basis at each GNSS site only, introducing the hypothesis of azimuthal isotropy of the troposphere.
The objective of the NEW-ARGENT (Improvement of NumErical Weather prediction through data Assimilation of Real-time GNSS-Estimated Non-isotropic Troposphere) project, funded by the Ministry of University and Research, is to assimilate the GNSS delay along slant path, to recover the local directional anisotropy. A possible way to recover, at least, part of the directional information given by GNSS observations, is through the assimilation of the gradients in the East and North directions (Zus et al., 2023). While for GNSS-ZTD data assimilation the WRFDA offers a specific tool, gradients assimilation has been recently added in a version of the WRFDA distributed by the link https://doi.org/10.5281/zenodo.10276429 and presented in the paper (Thundathil et al., 2024).
In this work we show the impact of GNSS gradient data assimilation in the WRF model for the month of September 2022 when several convective and intense storms occurred over Italy. Specifically, we compared the precipitation forecast at the short-range in four different experiments set-up: CTRL (control), without GNSS data assimilation, GNSS-ZTD, with the assimilation of GNSS zenith delay, GNSS-GRA, in which the gradients are assimilated, and GNSS-ZTD-GRA, in which both the gradients and the zenith total delay are assimilated. Simulations, lasting 12 each, are performed in a Very Short-term Forecast (VSF) approach. The first six hours are for spin-up and data assimilation (one analysis per hour), while the last six hours are considered as forecast phase.
Results show that the assimilation of the gradients, both alone and with the GNSS-ZTD, is beneficial for the improvement of precipitation forecast of convective events over Italy.
References
Thundathil, R. et al., 2024, https://doi.org/10.5194/gmd-17-3599-2024
Torcasio, R. C. et al., 2023, https://doi.org/10.5194/nhess-23-3319-2023
Zus, F. et al., 2023, https://doi.org/10.3390/rs15215114
Acknowledgments
This work has been realized in the project PRIN-PNRR NEW-ARGENT (Improvement of NumErical Weather prediction through data Assimilation of Real-time GNSS-Estimated Non-isotropic Troposphere) funded by the Ministry of University and Research contract number: P20228LMA2.
How to cite: Torcasio, R. C., Transerici, C., Realini, E., Crespi, M., and Federico, S.: Preliminary results of the assimilation of GNSS delays along slant paths, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11151, https://doi.org/10.5194/egusphere-egu25-11151, 2025.
