<abstract xmlns="http://www.w3.org/1999/xhtml"><p>This paper investigates information potential contained in tropospheric delay product for selected International GNSS Service (IGS) stations in climatologic research. Long time series of daily averaged Integrated Precipitable Water (IPW) can serve as climate indicator. The seasonal model of IPW change has been adjusted to the multi-year series (by the least square method). Author applied two modes: sinusoidal and composite (two or more oscillations). Even simple sinusoidal seasonal model (of daily IPW values series) clearly represents diversity of world climates. Residuals in periods from 10 up to 17 years are searched for some long-term IPW trend – self-evident climate change indicator. Results are ambiguous: for some stations or periods IPW trends are quite clear, the following years (or the other station) not visible. Method of fitting linear trend to IPW series does not influence considerably the value of linear trend. The results are mostly influenced by series length, completeness and data (e.g. meteorological) quality. The longer and more homogenous IPW series, the better chance to estimate the magnitude of climatologic IPW changes.</p></abstract>

This paper investigates information potential contained in tropospheric delay product for selected International GNSS Service (IGS) stations in climatologic research. Long time series of daily averaged Integrated Precipitable Water (IPW) can serve as climate indicator. The seasonal model of IPW change has been adjusted to the multi-year series (by the least square method). Author applied two modes: sinusoidal and composite (two or more oscillations). Even simple sinusoidal seasonal model (of daily IPW values series) clearly represents diversity of world climates. Residuals in periods from 10 up to 17 years are searched for some long-term IPW trend – self-evident climate change indicator. Results are ambiguous: for some stations or periods IPW trends are quite clear, the following years (or the other station) not visible. Method of fitting linear trend to IPW series does not influence considerably the value of linear trend. The results are mostly influenced by series length, completeness and data (e.g. meteorological) quality. The longer and more homogenous IPW series, the better chance to estimate the magnitude of climatologic IPW changes.

Long Series of GNSS Integrated Precipitable Water as a Climate Change Indicator

Department of Geodesy and Geodetic Astronomy, Faculty of Geodesy and Cartography, Warsaw University of Technology Warsaw, Poland

Reports on Geodesy and Geoinformatics

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"Long Series of GNSS Integrated Precipitable Water as a Climate Change Indicator"}

This paper investigates information potential contained in tropospheric delay product for selected International GNSS Service (IGS) stations in climatologic...

Long Series of GNSS Integrated Precipitable Water as a Climate Change Indicator

Published Online: Feb 12, 2016

Page range: 1 - 18

DOI: https://doi.org/10.2478/rgg-2015-0008

Keywords
water vapour, GPS, IPW, IWV, tropospheric delay, climate change, climatological time series

© 2015 Michał Kruczyk, published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Long Series of GNSS Integrated Precipitable Water as a Climate Change Indicator

Published Online: Feb 12, 2016

Page range: 1 - 18

DOI: https://doi.org/10.2478/rgg-2015-0008

Keywordswater vapour, GPS, IPW, IWV, tropospheric delay, climate change, climatological time series

© 2015 Michał Kruczyk, published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Keywords
water vapour, GPS, IPW, IWV, tropospheric delay, climate change, climatological time series