<abstract xmlns="http://www.w3.org/1999/xhtml"><p>The total zenith tropospheric delay (ZTD) and its components, hydrostatic and wet parts are important parameters of the atmosphere and directly or indirectly reflect climate processes. This possibility can be more adaptive when meteorological data are combined to co-located meteorological sensors with GPS stations. In this paper eighteen months with one hour time interval ZTD estimates of a permanent GPS station are analyzed with the associated atmospheric parameters provided from a co-located meteorological sensor. The mathematical relationship through the multiple stepwise regression analysis reflects the plausible physical link of temperature and relative humidity values with ZTD’s. This regression equation is assessed by a second data set performed by a small GPS baseline few months later for the same study area. It was found that mainly due to the zenith wet delay variations and with the help of fundamental meteorological equations the behavior of water vapor pressure can be monitored and estimated. This is possible when an appropriate setup of GPS stations and a co-located meteorological sensor exist and if the GPS stations sound the same part of atmosphere. Therefore, the GPS tropospheric products are good indicators for a climate monitoring tool and can help address the physics of a climate model.</p></abstract>

The total zenith tropospheric delay (ZTD) and its components, hydrostatic and wet parts are important parameters of the atmosphere and directly or indirectly reflect climate processes. This possibility can be more adaptive when meteorological data are combined to co-located meteorological sensors with GPS stations. In this paper eighteen months with one hour time interval ZTD estimates of a permanent GPS station are analyzed with the associated atmospheric parameters provided from a co-located meteorological sensor. The mathematical relationship through the multiple stepwise regression analysis reflects the plausible physical link of temperature and relative humidity values with ZTD’s. This regression equation is assessed by a second data set performed by a small GPS baseline few months later for the same study area. It was found that mainly due to the zenith wet delay variations and with the help of fundamental meteorological equations the behavior of water vapor pressure can be monitored and estimated. This is possible when an appropriate setup of GPS stations and a co-located meteorological sensor exist and if the GPS stations sound the same part of atmosphere. Therefore, the GPS tropospheric products are good indicators for a climate monitoring tool and can help address the physics of a climate model.

Monitoring Climate Changes on Small Scale Networks Using Ground Based GPS and Meteorological Data

Aristotle University of Thessaloniki, Department of Geodesy and Surveying University box 432, 54124, Thessaloniki, Greece

Artificial Satellites

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

The total zenith tropospheric delay (ZTD) and its components, hydrostatic and wet parts are important parameters of the atmosphere and directly or indirectly...

Monitoring Climate Changes on Small Scale Networks Using Ground Based GPS and Meteorological Data

Publié en ligne: 05 sept. 2014

Pages: 125 - 135

Reçu: 21 févr. 2014

Accepté: 02 juin 2014

DOI: https://doi.org/10.2478/arsa-2014-0010

Mots clés
GPS data, Ground Meteorological data, Zenith Tropospheric Delay, Stepwise regression analysis, water vapor pressure, Climate variation

© Artificial Satellites

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

Monitoring Climate Changes on Small Scale Networks Using Ground Based GPS and Meteorological Data

Publié en ligne: 05 sept. 2014

Pages: 125 - 135

Reçu: 21 févr. 2014

Accepté: 02 juin 2014

DOI: https://doi.org/10.2478/arsa-2014-0010

Mots clésGPS data, Ground Meteorological data, Zenith Tropospheric Delay, Stepwise regression analysis, water vapor pressure, Climate variation

© Artificial Satellites

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

Mots clés
GPS data, Ground Meteorological data, Zenith Tropospheric Delay, Stepwise regression analysis, water vapor pressure, Climate variation