Investigation of the 16-year and 18-year ZTD Time Series Derived from GPS Data Processing

• Autorzy: Bałdysz Z. , Nykiel G. , Figurski M. , Szafranek K. , Kroszczyński K.

Identyfikatory

DOI

10.1515/acgeo-2015-0033

• Języki publikacji: EN

Abstrakty

EN

The GPS system can play an important role in activities related to the monitoring of climate. Long time series, coherent strategy, and very high quality of tropospheric parameter Zenith Tropospheric Delay (ZTD) estimated on the basis of GPS data analysis allows to investigate its usefulness for climate research as a direct GPS product. This paper presents results of analysis of 16-year time series derived from EUREF Permanent Network (EPN) reprocessing performed by the Military University of Technology. For 58 stations Lomb-Scargle periodograms were performed in order to obtain information about the oscillations in ZTD time series. Seasonal components and linear trend were estimated using Least Square Estimation (LSE) and Mann-Kendall trend test was used to confirm the presence of a linear trend designated by LSE method. In order to verify the impact of the length of time series on trend value, comparison between 16 and 18 years were performed.

Słowa kluczowe

EN

GPS; ZTD; Zenith Tropospheric Delay; time series; troposphere

PL

GPS; ZTD; opóźnienie w troposferze; szereg czasowy; troposfera

• Wydawca: Instytut Geofizyki PAN ; Springer
• Czasopismo: Acta Geophysica
• Rocznik: 2015
• Tom: Vol. 63, no. 4
• Strony: 1103--1125
• Opis fizyczny: Bibliogr. 34 poz., rys., tab., wykr.

Twórcy

autor

Bałdysz Z.

• Military University of Technology, Faculty of Civil Engineering and Geodesy, Warszawa, Poland

autor

Nykiel G.

• Military University of Technology, Faculty of Civil Engineering and Geodesy, Warszawa, Poland

autor

Figurski M.

• Military University of Technology, Faculty of Civil Engineering and Geodesy, Warszawa, Poland

autor

Szafranek K.

• Military University of Technology, Faculty of Civil Engineering and Geodesy, Warszawa, Poland

autor

Kroszczyński K.

• Military University of Technology, Faculty of Civil Engineering and Geodesy, Warszawa, Poland

Bibliografia

• [1] Bengtsson, L., S. Hagemann, and K.I. Hodges (2004), Can climate trends be calculated from reanalysis data? J. Geophys. Res. 109, D11, D1111, DOI: 10.1029/2004JD004536.
• [2] Bevis, M., S. Businger, T.A. Herring, C. Rocken, R.A. Anthes, and R.H. Ware (1992), GPS meteorology: Remote sensing of atmospheric water vapor using the global positioning system, J. Geophys. Res. 97, D14, 15787-15801, DOI: 10.1029/92JD01517.
• [3] Bock, O., M.-N. Bouin, A. Walpersdorf, J.-P. Lafore, S. Janicot, F. Guichard, and A. Agusti-Panareda (2007), Comparison of ground-based GPS precipitable water vapour to independent observations and numerical weather prediction model reanalyses over Africa, Q. J. Roy. Meteor. Soc. 133, 629, 2011-2027, DOI: 10.1002/qj.185.
• [4] Bock, O., P. Willis, J. Wang, and C. Mears (2014), A high-quality, homogenized, global, long-term (1993-2008) DORIS precipitable water data set for climate monitoring and model verification, J. Geophys. Res. - Atmos. 119, 12, 7209-7230, DOI: 10.1002/2013JD021124.
• [5] Bruyninx, C. (2004), The EUREF Permanent Network: a multi-disciplinary network serving surveyors as well as scientists, GeoInformatics 7, 5, 32-35.
• [6] Byun, S.H., and Y.E. Bar-Server (2009), A new type of troposphere zenith path delay product of the international GNSS service, J. Geodesy 83, 3-4, 367-373, DOI: 10.1007/s00190-008-0288-8.
• [7] COST (2012), Memorandum of understanding for the implementation of a European Concerted Research Action, COST Action ES1206, Advanced Global Navigation Satellite Systems tropospheric products for monitoring severe weather events and climate (GNSS4SWEC), European Cooperation in Science and Technology.
• [8] Dach, R., U. Hugentobler, P. Fridez, and M. Meindl (eds.) (2007), Bernese GPS software version 5.0, User manual, Astronomical Institute, University of Bern, Bern, Switzerland.
• [9] Figurski, M., P. Kamiński, and A. Kenyeres (2009), Preliminary results of the complete EPN reprocessing computed by the MUT EPN Local Analysis Centre, Bull. Geod. Geomatics 1, 163-174.
• [10] Goosens, C., and A. Berger (1986), Annual and seasonal climatic variations over the northern hemisphere and Europe during the last century, Ann. Geophys. 4, 4, 385-400.
• [11] Guerova, G. (2013), Ground-based GNSS meteorology, Gfg2 Summer School, 2 July 2013, Potsdam, Germany.
• [12] Hagemann, S., L. Bengtsson, and G. Gendt (2003), On the determination of atmospheric water vapor from GPS measurements, J. Geophys. Res. 108, D21, 4678, DOI: 10.1029/2002JD003235.
• [13] Held, I.M., and B.J. Soden (2006), Robust responses of the hydrological cycle to global warming, J. Climate 19, 21, 5686-5699, DOI: 10.1175/JCLI3990.1.
• [14] Herring, T.A. (1992), Modeling atmospheric delays in the analysis of space geodetic data. In: J.C. de Munck, and T.A.T. Spoelstra (eds.), Proc. Symp. Refraction of Transatmospheric Signals in Geodesy, 19-22 May 1992, Hague, The Netherlands, 157-164.
• [15] Hocke, K. (1998), Phase estimation with Lomb-Scargle periodogram method, Ann.Geophys. 16, 3, 356-358.
• [16] Jin, S., J.-U. Park, J.-H. Cho, and P.-H. Park (2007), Seasonal variability of GPSderived zenith tropospheric delay (1994-2006) and climate implications, J. Geophys. Res. 112, D9, D09110, DOI: 10.1029/2006JD007772.
• [17] Karmeshu, N. (2012), Trend detection in annual temperature and precipitation using Mann Kendall test - A case study to assess climate change on select states in the Northeastern United States, M.Sc. Thesis, University of Pennsylvania, Philadelphia, USA.
• [18] Kendall, M.G., and A. Stuart (1970), The Advanced Theory of Statistics. Vol. 2: Interference and Relationship, 3rd ed., Hafner, New York.
• [19] Lomb, N.R. (1976), Least-squares frequency analysis of unequally spaced data, Astrophys. Space Sci. 39, 2, 447-462, DOI: 10.1007/BF006483.
• [20] Mann, H.B. (1945), Nonparametric tests against trend, Econometrica 13, 3, 245-259, DOI: 10.2307/1907187.
• [21] Marini, J.W. (1972), Correction of satellite tracking data for an arbitrary tropospheric profile, Radio Sci. 7, 2, 223-231, DOI: 10.1029/RS007i002p00223.
• [22] Mavromatis, T., and D. Stathis (2011), Response of the water balance in Greece to temperature and precipitation trends, Theor. Appl. Climatol. 104, 1-2, 13-24, DOI: 10.1007/s00704-010-0320-9.
• [23] Niell, A.E. (1996), Global mapping functions for the atmospheric delay at radio wavelengths, J. Geophys. Res. 101, B2, 3227-3246, DOI: 10.1029/ 95JB03048.
• [24] Nilsson, T., and G. Elgered (2008), Long-term trends in the atmospheric water vapor content estimated from ground-based GPS data, J. Geophys. Res. 113, D19, D19101, DOI: 10.1029/2008JD010110.
• [25] Ning, T. (2012), GPS meteorology: with focus on climate application, Ph.D. Thesis, Department of Earth and Space Sciences, Chalmers University of Technology, Göteborg, Sweden.
• [26] Pacione, R., B. Pace, and G. Bianco (2014), An homogeneously reprocessed Zenith Total Delay long-term time series over Europe. In: EGU General Assembly, 27 April - 2 May 2014, Vienna, Austria, id. 2945.
• [27] Press, W.H., S.A. Teukolsky, W.T. Vetterling, and B.P. Flannery (1992), Numerical recipes in Fortran, 2nd ed., Cambridge University Press, Cambridge.
• [28] Ross, R.J., and W.P. Elliott (2001), Radiosonde-based northern hemisphere tropospheric water vapor trends, J. Climate 14, 7, 1602-1612, DOI: 10.1175/ 1520-0442(2001)014<1602:RBNHTW>2.0.CO;2.
• [29] Schüler, T. (2001), On ground-based GPS tropospheric delay estimation, Ph.D. Thesis, Universität der Bundeswehr, München, Germany, 364 pp.
• [30] Söhne, W., M. Figurski, and K. Szafranek (2010), Homogeneous Zenith Total Delay parameter estimation from European permanent GNSS sites, Bull. Geod. Geomatics 69, 1, 11-22.
• [31] Steigenberger, P., M. Rothacher, R. Dietrich, M. Fritsche, A. Rülke, and S. Vey (2006), Reprocessing of a global GPS network, J. Geophys. Res. 111, B5, B05402, DOI: 10.1029/2005JB003747.
• [32] van Malderen, R., H. Brenot, E. Pottiaux, S. Beirle, C. Hermans, M. de Mazière, T. Wagner, H. de Backer, and C. Bruyninx (2014), A multi-site intercomparison of integrated water vapour observations for climate change analysis, Atmos. Meas. Tech. 7, 8, 2487-2512, DOI: 10.5194/amt-7-2487-2014.
• [33] Wang, J., and L. Zhang (2009), Climate applications of a global, 2-hourly atmospheric precipitable water dataset derived from IGS tropospheric products, J. Geodesy 83, 3-4, 209-217, DOI: 10.1007/s00190-008-0238-5.
• [34] Yong, W., Y. Binyun, W. Debao, and L. Yanping (2008), Zenith Tropospheric Delay from GPS monitoring climate change of Chinese Mainland. In: Int. Workshop on Education Technology and Training and on Geoscience and Remote Sensing, 21-22 December 2008, Shanghai, China, Vol. 1, 365-368, DOI: 10.1109/ETTandGRS.2008.43.