Real-time national GPS networks for atmospheric sensing

Abstract

Real-time national global positioning system (GPS) networks are being established in a number of countries for atmospheric sensing. The authors, in collaboration with participating universities, are developing one of these networks in the United States. The proposed network, named "SuomiNet" to honor meteorological satellite pioneer Verner Suomi, is funded by the US National Science Foundation to exploit the recently shown ability of ground-based GPS receivers to make thousands of accurate upper and lower atmospheric measurements per day. Phase delays induced in GPS signals by the ionosphere and neutral atmosphere can be measured with high precision simultaneously along a dozen or so GPS ray paths in the ÿeld of view. These delays can be converted into integrated water-vapor (if surface pressure data or estimates are available) and total electron content (TEC), along each GPS ray path. The resulting continuous, accurate, all-weather, real-time GPS moisture data will help advance university research in mesoscale modeling and data assimilation, severe weather, precipitation, cloud dynamics, regional climate and hydrology. Similarly, continuous, accurate, all-weather, real-time TEC data have applications in modeling and prediction of severe terrestrial and space weather, detection and forecasting of low-latitude ionospheric scintillation activity and geomagnetic storm e ects at ionospheric mid-latitudes, and detection of ionospheric e ects induced by a variety of geophysical events. SuomiNet data also have potential applications in coastal meteorology, providing ground truth for satellite radiometry, correction of synthetic aperture radar data for crustal deformation and topography studies, and detection of scintillation associated with atmospheric turbulence in the lower troposphere. In this paper we describe SuomiNet, its applications, and the larger opportunity to coordinate national real-time GPS networks to maximize their scientiÿc and operational impact.

Evaluation of AERONET precipitable water vapor versus microwave radiometry, GPS, and radiosondes at ARM sites

“…Global measurements of W can be assessed from satellite observations [e.g., Smith, 1991] generally at low temporal resolution [Tobin et al, 2006]. To address such limitation a wide range of ground-based measurements of W are currently done through intense observational programs, including Sun photometry [e.g., Alexandrov et al, 2009], radiosondes [e.g., Durre et al, 2006], Raman lidar systems [e.g., Whiteman et al, 2010Whiteman et al, , 2012, Fourier transform spectrometers [e.g., Leblanc et al, 2011], microwave radiometers [e.g., Cadeddu et al, 2013], and Global Positioning System (GPS) receivers [e.g., Elgered et al, 1997;Ware et al, 2001].…”

“…We also extend the comparisons to GPS retrievals provided by the SOUMINET activity [http://www.suominet.ucar.edu/intro.html] at ARM sites. SOUMINET is funded by the U.S. National Science Foundation and managed by the University Corporation for Atmospheric Research [ Ware et al , ]. Table summarizes the measurement concepts and estimates the uncertainties of each of the instruments used here.…”

Sensitivity of zenith total delay accuracy to GPS orbit errors and implications for near‐real‐time GPS meteorology

“…The retrieval of ZTD parameters in near real‐time over this network has been implemented operationally in the framework of the MAGIC project [ Haase et al , 1999, 2001]. Several processing centers are now testing the operational delivery of GPS‐derived ZTD to meteorological agencies in the framework of the COST‐716 action [ Brockmann et al , 2001] or of other national initiatives [e.g., Dousa , 2001; Gendt et al , 2001; Ware et al , 2001].…”

Data gathering and communication for wireless sensor networks using ant colony optimization

“…The development makes it possible that the GPS equipment sensors are ready and suitable for sensor network application. [31,32] Other approaches which can be more practical for sensor networks have also been studied by many researchers recently. These algorithms are designed to look for the relative location of the sensor nodes.…”