Analysis and Comparison of GPS Precipitable Water Estimates between Two Nearby Stations on Tahiti Island

Since Bevis first proposed Global Positioning System (GPS) meteorology in 1992, the precipitable water (PW) estimates retrieved from Global Navigation Satellite System (GNSS) networks with high accuracy have been widely used in many meteorological applications. The proper estimation of GNSS PW can be affected by the GNSS processing strategy as well as the local geographical properties of GNSS sites. To better understand the impact of these factors, we compare PW estimates from two nearby permanent GPS stations (THTI and FAA1) in the tropical Tahiti Island, a basalt shield volcano located in the South Pacific, with a mean slope of 8% and a diameter of 30 km. The altitude difference between the two stations is 86.14 m, and their horizontal distance difference is 2.56 km. In this paper, Bernese GNSS Software Version 5.2 with precise point positioning (PPP) and Vienna mapping function 1 (VMF1) was applied to estimate the zenith tropospheric delay (ZTD), which was compared with the International GNSS Service (IGS) Final products. The meteorological parameters sourced from the European Center for Medium-Range Weather Forecasts (ECMWF) and the local weighted mean temperature (Tm) model were used to estimate the GPS PW for three years (May 2016 to April 2019). The results show that the differences of PW between two nearby GPS stations is nearly a constant with value 1.73 mm. In our case, this difference is mainly driven by insolation differences, the difference in altitude and the wind being only second factors.

[1]  Marie-Noëlle Bouin,et al.  Comparison of ground‐based GPS precipitable water vapour to independent observations and NWP model reanalyses over Africa , 2007 .

[2]  K. Trenberth,et al.  Earth's annual global mean energy budget , 1997 .

[3]  Peter Steigenberger,et al.  Generation of a consistent absolute phase-center correction model for GPS receiver and satellite antennas , 2007 .

[4]  Yibin Yao,et al.  A globally applicable, season-specific model for estimating the weighted mean temperature of the atmosphere , 2012, Journal of Geodesy.

[5]  J. Barriot,et al.  Initiation and recession of the fluvial knickpoints of the Island of Tahiti (French Polynesia) , 2013 .

[6]  Galina Dick,et al.  GNSS water vapour tomography – Expected improvements by combining GPS, GLONASS and Galileo observations , 2011 .

[7]  Peter Steigenberger,et al.  Comparison of GMF/GPT with VMF1/ECMWF and implications for atmospheric loading , 2009 .

[8]  Dorota A. Grejner-Brzezinska,et al.  GPS-PWV estimation and validation with radiosonde data and numerical weather prediction model in Antarctica , 2012, GPS Solutions.

[9]  Peng Jiang,et al.  Retrieving Precipitable Water Vapor Data Using GPS Zenith Delays and Global Reanalysis Data in China , 2016, Remote. Sens..

[10]  L. Noto,et al.  Wind speed and temperature trends impacts on reference evapotranspiration in Southern Italy , 2014, Theoretical and Applied Climatology.

[11]  Nicolas Jeannin,et al.  Distribution of Tropospheric Water Vapor in Clear and Cloudy Conditions from Microwave Radiometric Profiling , 2009 .

[12]  Frank Kleijer,et al.  Troposphere Modeling and Filtering for Precise GPS Leveling , 2004 .

[13]  I. Shapiro,et al.  Geodesy by radio interferometry: Effects of atmospheric modeling errors on estimates of baseline length , 1985 .

[14]  G. Ruffini,et al.  Tropospheric Tomography using GPS Estimated Slant Delays , 2008 .

[15]  Jing-Shan Hong,et al.  Determining the precipitable water vapor thresholds under different rainfall strengths in Taiwan , 2017 .

[16]  Henrik Vedel,et al.  Accuracy and Variability of GPS Tropospheric Delay Measurements of Water Vapor in the Western Mediterranean , 2003 .

[17]  H. Schuh,et al.  Troposphere mapping functions for GPS and very long baseline interferometry from European Centre for Medium‐Range Weather Forecasts operational analysis data , 2006 .

[18]  Joao P. S. Catalao,et al.  On the inclusion of GPS precipitable water vapour in the nowcasting of rainfall , 2015 .

[19]  T. Herring,et al.  GPS Meteorology: Remote Sensing of Atmospheric Water Vapor Using the Global Positioning System , 1992 .

[20]  Junyu Liu,et al.  A New Method for Refining the GNSS-Derived Precipitable Water Vapor Map , 2019, Sensors.

[21]  Yulong Ge,et al.  Assessment of BeiDou-3 and Multi-GNSS Precise Point Positioning Performance , 2019, Sensors.

[22]  Yibin Yao,et al.  Establishing a method of short-term rainfall forecasting based on GNSS-derived PWV and its application , 2017, Scientific Reports.

[23]  Yashar Falamarzi,et al.  Estimating evapotranspiration from temperature and wind speed data using artificial and wavelet neural networks (WNNs) , 2014 .

[24]  Junhong Wang,et al.  Global estimates of water‐vapor‐weighted mean temperature of the atmosphere for GPS applications , 2005 .

[25]  P. Ortega,et al.  Interactions between intraseasonal and diurnal variability of precipitation in the South Central Pacific: The case of a small high island, Tahiti, French Polynesia , 2018, International Journal of Climatology.

[26]  Guochang Xu,et al.  Metrology Assessment of the Accuracy of Precipitable Water Vapor Estimates from GPS Data Acquisition in Tropical Areas: The Tahiti Case , 2018, Remote. Sens..

[27]  G. Ruffini,et al.  4D tropospheric tomography using GPS slant wet delays , 2000 .

[28]  Shirong Ye,et al.  A new global grid model for the determination of atmospheric weighted mean temperature in GPS precipitable water vapor , 2019, Journal of Geodesy.

[29]  R. S. Lawrence,et al.  Theoretical and calculational aspects of the radio refractive index of water vapor , 1982 .

[30]  Honglin He,et al.  An Empirical Method of Estimating Soil Thermal Inertia , 2015 .

[31]  Hans van der Marel,et al.  Integrated atmospheric water vapor estimates from a regional GPS network , 2002 .

[32]  R. Dach,et al.  Bernese GNSS Software Version 5.2 , 2015 .

[33]  J. Zumberge,et al.  Precise point positioning for the efficient and robust analysis of GPS data from large networks , 1997 .

[34]  Fei Yang,et al.  A Method to Improve the Distribution of Observations in GNSS Water Vapor Tomography , 2018, Sensors.

[35]  J. Ceron,et al.  Climate change, Pacific climate drivers and observed precipitation variability in Tahiti, French Polynesia , 2015 .

[36]  J. Saastamoinen Contributions to the theory of atmospheric refraction , 1972 .

[37]  Steven Businger,et al.  GPS Meteorology: Mapping Zenith Wet Delays onto Precipitable Water , 1994 .

[38]  Will climate change shift the lower ecotone of tropical montane cloud forests upwards on islands? , 2018 .

[39]  Harald Schuh,et al.  Estimation and evaluation of real-time precipitable water vapor from GLONASS and GPS , 2016, GPS Solutions.

[40]  J. R. Carreker The relation of solar radiation to evapotranspiration from cotton , 1963 .

[41]  Christian Rocken,et al.  Validation of line‐of‐sight water vapor measurements with GPS , 2001 .

[42]  Richard B. Langley,et al.  An Evaluation of the Accuracy of Models for the Determination of the Weighted Mean Temperature of the Atmosphere , 2000 .

[43]  J. Barriot,et al.  The evolution of precipitable water and precipitation over the Island of Tahiti from hourly to seasonal periods , 2014 .

[44]  Jan M. Johansson,et al.  Three months of continuous monitoring of atmospheric water vapor with a network of Global Positioning System receivers , 1998 .

[45]  Yibin Yao,et al.  Global empirical model for mapping zenith wet delays onto precipitable water , 2013, Journal of Geodesy.

[46]  Xu Tang,et al.  Precipitable Water Vapour Retrieval from GPS Precise Point Positioning and NCEP CFSv2 Dataset during Typhoon Events , 2018, Sensors.

[47]  Rebecca J. Ross,et al.  Estimating mean weighted temperature of the atmosphere for Global Positioning System applications , 1997 .

[48]  Yuei-An Liou,et al.  Comparison of Precipitable Water Observations in the Near Tropics by GPS, Microwave Radiometer, and Radiosondes , 2001 .

[49]  J. Meyer Conservation des forêts naturelles et gestion des aires protégées en Polynésie française , 2007 .

[50]  K. Parameswaran,et al.  Empirical model for mean temperature for Indian zone and estimation of precipitable water vapor from ground based GPS measurements , 2007 .

[51]  V. Cachorro,et al.  Improvement in PWV estimation from GPS due to the absolute calibration of antenna phase center variations , 2010 .

[52]  Junhong Wang,et al.  A near-global, 2-hourly data set of atmospheric precipitable water from ground-based GPS measurements , 2007 .

[53]  Ludwig Combrinck,et al.  Modelling weighted mean temperature in the West African region: implications for GNSS meteorology , 2016 .

[54]  D. Streets,et al.  Dangerous human-made interference with climate: a GISS modelE study , 2006, physics/0610115.

[55]  Bryan Butler,et al.  Precipitable Water at the VLA | 1990 { 1998 , 1998 .

[56]  T. Hsiao,et al.  A soil surface psychrometer for measuring humidity and studying evaporation , 1984 .

[57]  Jean-Louis Dufresne,et al.  Role of Soil Thermal Inertia in Surface Temperature and Soil Moisture‐Temperature Feedback , 2017 .

[58]  Gerd Gendt,et al.  On the determination of atmospheric water vapor from GPS measurements , 2003 .

[59]  Qile Zhao,et al.  Assessment of precipitable water vapor derived from ground-based BeiDou observations with Precise Point Positioning approach , 2015 .

[60]  New trends for reference evapotranspiration and climatic water deficit , 2012 .

[61]  S. El-Gayar,et al.  EFFECT OF SOLAR RADIATION ON THE CROPS EVAPOTRANSPIRATION IN EGYPT , 2010 .