Abstract
Since many years, the GNSS has been regarded by the meteorological community as one of the systems for atmospheric water vapour remote sensing. Time series of wet delays, estimated as by-products of accurate positioning, have been assimilated into numerical weather prediction models. However, a dedicated use the system for water vapour monitoring is still under investigation. Ad hoc dense networks have been designed and implemented to collect data at a high spatial resolution, baseline lengths lower than 10 km, with the aim of describing the high spatial and temporal variability of tropospheric water vapour. Within this framework, the paper reports a study on how the positioning strategy affects the estimated coordinates and tropospheric parameters. The study was conducted on the data collected by an experimental network of geodetic receivers, used as single or dual frequency ones. More specifically, investigations were made on the use of L1-only or iono-free combinations in differential positioning of receivers 100 to 10 km apart, finding that L1-only data provide more accurate results. Therefore, comparisons between local coordinates and ZWD obtained from relative and absolute positioning were performed to provide the statistics of the differences; the agreement between the results for short baselines is always better than 1 cm standard deviation. In order to assess the differences in the results that can be obtained from the two strategies when applied to the same observation set, a further comparison was carried out in terms of baseline components and ZWD increments. It results that, even for dense networks, the differential approach produces accurate results without losing information compared to the absolute one.
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Abbreviations
- APS:
-
atmospheric phase screen
- CODE:
-
Center for Orbit Determination in Europe
- DD:
-
double difference
- GIM:
-
global ionosphere maps
- GNSS:
-
Global Navigation Satellite Systems
- InSAR:
-
Interferometric Synthetic Aperture Radar
- IWV:
-
integrated water vapour
- NWP:
-
numerical weather prediction models
- PCV:
-
phase center variation
- PN:
-
permanent network
- PPP:
-
precise point positioning
- PWV:
-
precipitable water vapour
- WVR:
-
water vapour radiometer
- ZTD:
-
zenith total delay
- ZWD:
-
zenith wet delay
References
Baby BH, Golé P, Lavergnat J (1988) A model for the tropospheric excess path length of radio waves from surface meteorological measurements. Radio Sci 23(6):1023–1038
Bennitt GV, Jupp A (2012) Operational assimilation of GPS zenith total delay observations into the Met office numerical weather prediction models. Mon Wea Rev 140(8):2706–2719
Bevis M, Businger S, Herring TA, Rocken C, Anthes RA, Ware RH (1992) GPS Meteorology: remote sensing of atmospheric water vapor using the Global Positioning System. J Geophys Res: Atmos 97(D14):15787–15801
BRIGAID - H2020 project - Precipitable Water Vapour Monitoring (2016) http://brigaid.eu/meet-our-innovations-precipitable-water-vapour-monitoring. Accessed 16 May 2017
Dach R, Lutz S, Walser P, Fridez P (2015) BERNESE GNSS Software version 5.2. University of Bern, Bern Open Publishing
EDWIGE - Eurostars-2 project (2016) https://www.eurostars-eureka.eu/project/id/10235. Accessed 16 May 2017
Elliott WP, Gaffen DJ (1991) On the utility of radiosonde humidity archives for climate studies. Bull Amer Meteor Soc 72:1507–1520
Gelb A (1974) Applied optimal estimation. MIT Press, Cambridge
Herring TA, Davis JL, Shapiro II (1990) Geodesy by radio interferometry: the application of Kalman filtering to the analysis of very long baseline interferometry data. J Geophys Res 95(B8):12561–12581
Herring TA (1992) Modeling atmospheric delays in the analysis of space geodetic data. J Geophys Res 74:4487–4499
Hofmann-Wellenhof B, Lichtenegger H, Collins J (2001) Global positioning system theory and practice. Springer-Verlag, Wien
Ishikawa Y (2010) The Use of Ground Based GPS Data for Meso-scale Analysis. Suuchi Yohouka Houkoku Bessatsu (Additional Vol Report Numer Prediction Div) 56:54–60. (In Japanese)
Kleijer F (2004) Troposphere modeling and filtering for precise GPS leveling. Dissertation, TU Delft
Kouba J, Héroux P (2001) Precise Point Positioning using IGS orbit and clock products. GPS Solutions 5(2):2–28
MacMillan DS (1995) Atmospheric gradients from very long base interferometry observations. Geophys Res Lett 22:1041–1044
METAWAVE - ESA Contract No. ESTEC-21207/07/NL/HE (2007) “Metawave - Mitigation of Electromagnetic Transmission errors induced by Atmospheric Water Vapour Effects” 2007–2009
MORFEO - Contratto ASI prot. n. 6003 del 31/07/2006 (2007) “MOnitoraggio Rischio da Frane con dati EO”, http://www.morfeoproject.it http://www.morfeoproject.it
Niell AE, Coster AJ, Solheim FS, Mendes VB, Toor PC, Langley RB, Upham CA (2001) Comparison of measurements of atmospheric wet delay by radiosonde, water vapor radiometer, GPS, and VLBI. J Atmos Ocean Tech 18(6):830–850
Notarpietro R, Cucca M, Gabella M, Venuti G, Perona G (2011) Tomographic reconstruction of wet and total refractivity fields from GNSS receiver networks. Adv Space Res 47:898–912
Onn F (2006) Modeling water vapor using GPS with application to mitigating inSAR atmospheric distorsions. Dissertation, Stanford University
Pierdicca N, Rocca F, Rommen B, Basili P, Bonafoni S, Cimini D, Ciotti P, Consalvi F, Ferretti R, Foster W, Marzano FS, Mattioli V, Mazzoni A, Montopoli M, Notarpietro R, Padmanabhan S, Perissin D, Pichelli E, Reising S, Sahoo S, Venuti G (2009) Atmospheric water vapour effects on spaceborne interferometric SAR imaging: comparison with ground based measurements and meteorological model simulations at different scales. In: 2009 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2009. IEEE, pp V-320-V-323
Pierdicca N, Rocca F, Basili P, Bonafoni S, Carlesimo G, Cimini D, Ciotti P, Ferretti R, Marzano FS, Mattioli V, Montopoli M, Notarpietro R, Perissin D, Pichelli E, Rommen B, Venuti G (2011) Synergic use of EO, NWP and ground based measurements for the mitigation of vapour artefacts in SAR interferometry. In: 2011 IEEE International Geoscience and remote sensing symposium (IGARSS). IEEE, pp 2566–2569
Perissin D, Rocca F, Pierdicca N, Cimini D, Pichelli E, Venuti G, Rommen B (2011) Mitigation of atmospheric delay in inSAR: The ESA Metawave project. In: 2011 IEEE international Geoscience and remote sensing symposium (IGARSS). IEEE, pp 2558–2561
Princea SD, Goetza SJ, Dubayaha RO, Czajkowskia KP, Thawleya M (1998) Inference of surface and air temperature, atmospheric precipitable water and vapour pressure deficit using advanced very high-resolution radiometer satellite observations: comparison with field observations. J Hydrol 212-213:230–249
Resch GM (1984) Water vapor radiometry in geodetic applications. In: Brunner FK (ed) Geodetic refraction. Springer, Berlin-Heidelberg
Sato K, Realini E, Tsuda T, Oigawa M, Iwaki Y, Shoji Y, Seko H (2013) A high-resolution, precipitable water vapor monitoring system using a dense network of GNSS receivers. J Disaster Res 8(1):37–47
Seeber G (2003) Satellite geodesy. Walter de Gruyter, Berlin
Shoji Y, Nakamura H, Iwabuchi T, Aonashi K, Seko H, Mishima K, Ohtani R (2004a) Tsukuba GPS dense net campaign observation: improvement in GPS analysis of slant path delay by stacking one-way postfit phase residuals. J Meteor Soc Japan 82(1B):301–314
Shoji Y, Yamauchi H, Mashiko W, Sato E (2014b) Estimation of Local-scale Precipitable Water Vapor Distribution Around Each GNSS Station using Slant Path Delay. SOLA 10:29–33
Saito K, Shoji Y, Origuchi S, Duc L (2017) GPS PWV Assimilation with the JMA Nonhydrostatic 4DVAR and Cloud Resolving Ensemble Forecast for the 2008 August Tokyo Metropolitan Area Local Heavy Rainfalls. Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications (Vol III), pp 383–404
Teunissen P J G, Kleusberg A (eds) (1998) GPS For geodesy. Springer, Berlin-Heidelberg
Tikhonov AN (1966) Regularization of incorrectly posed problems. Sov Math Dokl 1963 4:1624–1627
Tregoning P, Boers R, O’Brien D, Hendy M (1998) Accuracy of absolute precipitable water vapor estimates from GPS observations. J Geophys Res: Atmos 103(D22):28701–28710
Visconti MG (2009) L’esperimento MisT: stima dei ritardi troposferici da una rete GNSS locale. PhD dissertation, Politecnico di Milano
Acknowledgements
The authors acknowledge Dr. Grazia Visconti and Prof. Ludovico Biagi who collected and firstly analysed the data and Leica Geosystem Italy for providing the GNSS stations for the MisT experiment. We thank Dr. Daniele Sampietro for his suggestions in the results analysis and the anonymous referees for their important comments on the manuscript that allowed us to improve it significantly.
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AF, ER and GV designed the study, developed the methodology, collected the data, performed the analysis, and wrote the manuscript.
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AF, PhD in mathematics, PhD in Geodesy and Geomatics at Politecnico di Milano, is currently working as research fellow for the Italian National Research Council, CNR - IEIIT. ER, PhD in Geodesy and Geomatics, is working for Geomatics Research & Development srl (GReD), spin-off of Politecnico di Milano. GV is Associate Professor in Geospatial data analysis and responsible for the Geomatics and Earth observation laboratory (GEOlab) at Politecnico di Milano .
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Fermi, A., Realini, E. & Venuti, G. The impact of relative and absolute GNSS positioning strategies on estimated coordinates and ZWD in the framework of meteorological applications. Appl Geomat 11, 25–38 (2019). https://doi.org/10.1007/s12518-018-0234-2
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DOI: https://doi.org/10.1007/s12518-018-0234-2