Tropospheric Delay in the Neapolitan and Vesuvius Areas (Italy) by Means of a Dense GPS Array: A Contribution for Weather Forecasting and Climate Monitoring
Author(s)
Language
English
Obiettivo Specifico
7A. Geofisica per il monitoraggio ambientale
Status
Published
JCR Journal
JCR Journal
Peer review journal
Yes
Journal
Issue/vol(year)
/12 (2021)
Publisher
MDPI
Pages (printed)
1225
Date Issued
September 18, 2021
Alternative Location
Abstract
Studying the spatiotemporal distribution and motion of water vapour (WV), the most variable greenhouse gas in the troposphere, is pivotal, not only for meteorology and climatology, but for geodesy, too. In fact, WV variability degrades, in an unpredictable way, almost all geodetic observation based on the propagation of electromagnetic signal through the atmosphere. We use data collected on a dense GPS network, designed for the purposes of monitoring the active Neapolitan (Italy) volcanoes, to retrieve the tropospheric delay parameters and precipitable water vapour (PWV).
This study has two main targets: (a) the analysis of long datasets (11 years) to extract trends of climatological meaning for the region; (b) studying the main features of the time evolution of the PWV during heavy raining events to gain knowledge on the preparatory stages of highly impacting thunderstorms. For the latter target, both differential and precise point positioning (PPP) techniques are used, and the results are compared and critically discussed. An increasing trend, amounting to about 2 mm/decades, has been recognized in the PWV time series, which is in agreement with the results achieved in previous studies for the Mediterranean area. A clear topographic effect is detected for the Vesuvius volcano sector of the network and a linear relationship between PWV and altitude is quantitatively assessed. This signature must be taken into account in any modelling for the atmospheric correction of geodetic and remote-sensing data (e.g., InSAR). Characteristic temporal evolutions were recognized in the PWV in the targeted thunderstorms (which occurred in 2019 and
2020), i.e., a sharp increase a few hours before the main rain event, followed by a rapid decrease when the thunderstorm vanished. Accounting for such a peculiar trend in the PWV could be useful for setting up possible early warning systems for those areas prone to flash flooding, thus potentially providing a tool for disaster risk reduction.
This study has two main targets: (a) the analysis of long datasets (11 years) to extract trends of climatological meaning for the region; (b) studying the main features of the time evolution of the PWV during heavy raining events to gain knowledge on the preparatory stages of highly impacting thunderstorms. For the latter target, both differential and precise point positioning (PPP) techniques are used, and the results are compared and critically discussed. An increasing trend, amounting to about 2 mm/decades, has been recognized in the PWV time series, which is in agreement with the results achieved in previous studies for the Mediterranean area. A clear topographic effect is detected for the Vesuvius volcano sector of the network and a linear relationship between PWV and altitude is quantitatively assessed. This signature must be taken into account in any modelling for the atmospheric correction of geodetic and remote-sensing data (e.g., InSAR). Characteristic temporal evolutions were recognized in the PWV in the targeted thunderstorms (which occurred in 2019 and
2020), i.e., a sharp increase a few hours before the main rain event, followed by a rapid decrease when the thunderstorm vanished. Accounting for such a peculiar trend in the PWV could be useful for setting up possible early warning systems for those areas prone to flash flooding, thus potentially providing a tool for disaster risk reduction.
Sponsors
TRYAT (TRack Your ATmosphere) project (2017-1-DE02-KA202-004229) Co-funded by
ERASMUS + Programme of the European Union.
ERASMUS + Programme of the European Union.
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2. Jin, S.; Van Dam, T.;Widowinski, S. Observing and understanding the Earth system variations from space geodesy. J. Geodyn. 2013, 72, 1–10.
3. Guerova, G.; Jones, J.; Douša, J.; Dick, G.; de Haan, S.; Pottiaux, E.; Bock, O.; Pacione, R.; Elgered, G.; Vedel, H.; et al. Review of the state of the art and future prospects of the ground-based GNSS meteorology in Europe. Atmos. Meas. Tech. 2016, 9, 5385–5406.
4. Tapley, B.D.; Watkins, M.M.; Flechtner, F.; Reigber, C.; Bettadpur, S.; Rodell, M.; Sasgen, I.; Famiglietti, J.S.; Landerer, F.W.; Chambers, D.P.; et al. Contributions of GRACE to understanding climate change. Nat. Clim. Chang. 2019, 9, 358–369.
5. Famiglietti, J.S. The global groundwater crisis. Nat. Clim. Chang. 2014, 4, 945–948.
6. Bevis, M.; Businger, S.; Herring, T.A.; Rocken, C.; Anthes, R.A.;Ware, R.H. GPS Meteorology: Remote sensing of atmospheric water vapor using the global positioning system. J. Geophys. Res. Atmos. 1992, 97, 15787–15801.
7. Rius, A.; Ruffini, G.; Romeo, A. Analysis of ionospheric electron density distribution from GPS/MET occultation. IEEE Trans. Geosci. Rem. Sens. 1998, 36, 383–394.
8. Zhang, K.; Fu, E.; Silcock, D.; Wang, Y.; Kuleshov, Y. An investigation of atmospheric temperature profiles in the Australian region using collocated GPS radio occultation and radiosonde data. Atmos. Meas. 2011, 4, 2087–2092.
9. Gaffen, D.J.; Elliott,W.P.; Robock, A. Relationships between tropospheric water vapor and surface temperature as observed by radiosondes. Geophys. Res. Lett. 1992, 19, 1839–1842.
10. IPCC. Climate Change 2013: The Physical Science Basis. In Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change; Stocker, T.F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S.K., Boschung, J., Nauels, A., Xia, Y., Bex, V., Midgley, P.M., Eds.; Cambridge University Press: Cambridge, UK; New York, NY, USA; p. 1535.
11. Seneviratne, S.I.; Nicholls, N.; Easterling, D.; Goodess, C.M.; Kanae, S.; Kossin, J.; Luo, Y.; Marengo, J.; McInnes, K.; Rahimi, M. Changes in Climate Extremes and Their Impacts on the Natural Physical Environment.; Cambridge University Press: Cambridge, UK, 2012; pp. 109–230.
12. Champollion, C.; Masson, F.; Van Baelen, J.; Walpersdorf, A.; Chéry, J.; Doerflinger, E. GPS monitoring of the tropospheric water vapor distribution and variation during the 9 September 2002 torrential precipitation episode in the Cévennes (southern France). J. Geophys. Res. 2004, 109, D24102.
13. Riccardi, U.; Tammaro, U.; Capuano, P. Evaluation of the atmospheric precipitable water at local scale during extreme weather using groundbased CGPS measurements. In Proceedings of the 2013 IEEEWorkshop on Environmental, Energy and Structural Monitoring Systems, Trento, Italy, 11–12 September 2013; pp. 37–40.
14. Tammaro, U.; Riccardi, U.; Masson, F.; Capuano, P.; Boy, J.P. Atmospheric PrecipitableWater in Somma-Vesuvius Area during Extreme Weather Events from Ground-Based GPS Measurements. In International Symposium on Earth and Environmental Sciences for Future Generations; International Association of Geodesy Symposia; Freymueller, J.T., Sánchez, L., Eds.; Springer: Cham, Swizterland, 2016; Volume 147.
15. Ejigu, Y.G.; Teferle, F.N.; Klos, A.; Bogusz, J.; Hunegnaw, A. Tracking Hurricanes Using GPS Atmospheric Precipitable Water Vapor Field. In International Association of Geodesy Symposia; Springer: Berlin/Heidelberg, Germany, 2020.
16. Palumbo, A.; Mazzarella, A. The heat-island over Naples. Weather 1981, 36, 28–29.
17. Palumbo, A.; Mazzarella, A. Local recent changes in extreme air temperatures. Clim. Chang. 1984, 6, 303–309.
18. Fortelli, A.; Scafetta, N.; Mazzarella, A. Local Warming in the Historical Center of Naples. Int. J. Heat Technol. 2016, 34, S569–S572.
19. Scafetta, N.; Di Cristo, R.; Mazzarella, A.; Viola, R. L’Osservatorio Meteorologico di San Marcellino Napoli Centro. Rend. Acc. Sc. Fis. Mat. Napoli 2019, LXXXVI, 201–250. Available online: http://www.societanazionalescienzeletterearti.it/index.php?pg=218 (accessed on 15 September 2021).
20. Tranfaglia, G.; Braca, G. Analisi Idrologica e Meteorologica dell’Evento Alluvionale del 25–26 Ottobre 1954: Confronto con le Serie Storiche e Valutazione del Periodo di Ritorno di Eventi Analoghi. In Il Nubifragio dell’Ottobre 1954 a Vietri sul Mare. Costa di Amalfi, Salerno; Esposito, E., Porfido, S., Violante, C., Eds.; 2004; pp. 295–348. Available online: https://www.researchgate.net/publication/285503827_Analisi_idrologica_e_meteorologica_dell\T1\textquoterightevento_alluvionale_del_25-26_ottobre_19
54_confronto_con_le_serie_storiche_evalutazione_del_periodo_di_ritorno_di_eventi_analoghi (accessed on 15 September 2021).
21. Principe, C.; Rosi, M.; Santacroce, R.; Sbrana, A. Explanatory Notes to the Geological Map. In Somma-Vesuvius, Quaderni de “La Ricerca Scientifica”, CNR, 114 (Progetto Finalizzato Geodinamica, Monografie Finali, 8); Santacroce, R., Ed.; Consiglio Nazionale della Ricerca: Naples, Italy, 1987; pp. 11–52. ISSN 0556-9664.
22. Thayer, G.D. An improved equation for the radio refractive index of air. Radio Sci. 1974, 9, 803–807.
23. Saastamoinen, J. Atmospheric correction for the troposphere and stratosphere in radio ranging satellites. The use of artificial satellites for geodesy. Geophys. Monogr. Ser. 1972, 15, 247–251.
24. Davis, J.L.; Herring, T.A.; Shapiro, I.I.; Rogers, A.; Elgered, G. Geodesy by radio interferometry: Effects of atmospheric modeling errors on estimates of baseline length. Radio Sci. 1985, 20, 1593–1607.
25. Boehm, J.; Schuh, H. Vienna mapping functions in VLBI analyses. Geophys. Res. Lett. 2004, 31, L01603.
26. Boehm, J.B.; Werl, S.H. Troposphere mapping functions for GPS and very long baseline interferometry from European Centre for Medium-Range Weather Forecasts operational analysis data. J. Geophys. Res. 2006, 111, B02406.
27. Lagler, K.; Schindelegger, M.; Böhm, J.; Krásná, H.; Nilsson, T. GPT2: Empirical slant delay model for radio space geodetic techniques. Geophys. Res. Lett. 2013, 40, 1069–1073.
28. Askne, J.; Nordius, H. Estimation of tropospheric delay for microwaves from surface weather data. Radio Sci. 1987, 22, 379–386.
29. Bevis, M.; Businger, S.; Chiswell, S.; Herring, T.A.; Anthes, R.A.; Rocken, C.; Ware, R.H. GPS Meteorology: Mapping Zenith Wet Delays onto Precipitable Water. J. Appl. Meteorol. 1994, 33, 379–386.
30. Rizos, C.; Janssen, V.; Roberts, C.; Grinter, T. GNSS: Precise Point Positioning PPP versus DGNSS. Geomat. World 2012, 20, 18–20.
31. Teunissen, P.J.G.; Khodabandeh, A. Review and principles of PPP-RTK methods. J. Geod. 2015, 89, 217–240.
32. Banville, S. CSRS-PPP Version 3: Tutorial. Last update: 25 August 2020; p. 11. Available online: https://webapp.geod.nrcan.gc.
ca/geod/tools-outils/sample_doc_filesV3/NRCan%20CSRS-PPP-v3_Tutorial%20EN.pdf (accessed on 15 September 2021).
33. Herring, T.A.; King, R.W.; Floyd, M.A.; McClusky, R.W. Gamit-Globk. Reference Manuals. Release 10.71. 2018, p. 168. Available online: http://geoweb.mit.edu/gg/docs.php (accessed on 15 September 2021).
34. Blewitt, G.; Hammond, W.C.; Kreemer, C. Harnessing the GPS Data Explosion for Interdisciplinary Science. Eos 2018, 99, 99.
35. Lyard, F.; Lefevre, F.; Letellier, T.; Francis, O. Modelling the global ocean tides: Modern insights from FES2004. Ocean Dyn. 2006, 56, 5–6.
36. Altamimi, Z.; Rebischung, P.; Métivier, L.; Collilieux, X. ITRF2014: A new release of the International Terrestrial Reference Frame modeling nonlinear station motions. J. Geophys. Res. Solid Earth 2016, 121, 6109–6613.
37. Duan, J.; Bevis, M.; Fang, P.; Bock, Y.; Chiswell, S.R.; Businger, S.; Rocken, C.; Solheim, F.S.; Van Hove, T.; Ware, R.; et al. GPS meteorology: Direct estimation of the absolute value of precipitable water. J. Appl. Meteorol. 1996, 35, 830–838.
38. Ortiz de Galisteo, J.P.; Bennouna, Y.; Toledano, C.; Cachorro, V.; Romero, P.; Andres, M.I.; Torres, B. Analysis of the annual cycle of the precipitable water vapour over Spain from 10-year homogenized series of GPS data. Q. J. R. Meteorol. Soc. 2014, 140, 397–406.
39. Amendola, S.; Maimone, F.; Pelino, V.; Pasini, A. New records of monthly temperature extremes as a signal of climate change in Italy. Int. J. Climatol. 2019, 39, 2491–2503.
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