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GNSS Tropospheric Products

Final conference of the project HUSKROUA/1101/252. GNSS Tropospheric Products. Stepan Savchuk, project expert, Dr. Tech. Sci., professor of the Department of Geodesy and Astronomy, National University "Lviv Polytechnic" (Lviv, Ukraine). December 17-19, 2015.

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GNSS Tropospheric Products

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  1. Final conference of the project HUSKROUA/1101/252 GNSS Tropospheric Products Stepan Savchuk, project expert, Dr. Tech. Sci., professor of the Department of Geodesy and Astronomy, National University "Lviv Polytechnic" (Lviv, Ukraine) December 17-19, 2015

  2. РОЗВ’ЯЗУВАННЯ ЗАДАЧ МЕТЕОРОЛОГІЇ ІЗ ЗАСТОСУВАННЯМ ГЛОБАЛЬНИХ СУПУТНИКОВИХ НАВІГАЦІЙНИХ СИСТЕМ (GNSS) Степан Савчук Національний університет “Львівська політехніка Київ, 25 березня 2011

  3. Зміст • Теоретичні основи GNSS метеорології Затримка GNSS сигналів в тропосфері та іоносфері Реалізації дистанційного зондування атмосфери на основі GNSS вимірювань • Загальні відомості про мережі активних референцних станцій в Україні MetApps Lec 12

  4. Pseudo range (code observation) the measure of the transit time from satellite to receiver using correlation between received and replicated signal (the time is coded in signal) absolute positioning with accuracy of a few meters. Carrier phase (phase observation) the measure of the phase difference btw. received and replicated carrier frequency mm level of relative positioning GNSS observables

  5. Non-linear code observation equations

  6. GNSS model - error sources vs. parameters satellites: ephemeris, clocks, differential code/phase biases, ... receivers: clocks, phase center offsets and variations differential code/phase biases, … environment: TROPOSPHERE, IONOSPHERE, multipath, Earth’s dynamics and crust deformations, … processing: cycle-slips (initial phases ambiguties) model deficiencies, …

  7. GNSS model - error sources vs. parameters we introduce: receiver and satellite positions (satellite clocks) and precise models (PCVs, loading effects, mapping functions ...), we eliminate: ionospheric effect (receiver and satellite clock error), we estimate: troposphere, ambiguities (receiver clocks)

  8. Review of GNSS meteorology Remote sensing of the atmosphere with the microwave signal of the Global Navigation Satellite Systems (GNSS) has become a well-established field of research with its major application in meteorology. The primary use of the microwave signals is obviously the positioning of receiving antennas on the Earth. The following compilation summarizes the today’s GNSS meteorology products that are of interest to the meteorological community and outlines their application.

  9. But the waves passing the atmosphere are affected by the concentration of free electrons in the ionosphere and by the air density in the lower stratosphere and the troposphere. Review of GNSS meteorology

  10. There are two major contributions of the atmosphere: • Neutral atmospheric delay composed of hydrostatic component (N2, O2, CO2, trace gases and part of the water vapor contribution) and water vapor component. • Ionospheric delay component due to free electrons. This component is frequency dependent and can be estimated from dual frequency measurements (L1 and L2 frequencies). • These atmospheric influences can be retrieved to a certain degree in the processing of the GNSS data with sophisticated software. • We will focus on the troposphere and discuss the possible parameters to be retrieved from the GNSS data. Review of GNSS meteorology

  11. Concept of ground-based GNSS meteorology

  12. GNSS tropospheric products Tropospheric delay effects in GNSS model is composed from: a) signal delay (major) + delay due to signal trajectory bending (minor) b) hydrostatic delay (major) + wet delay (minor) Standard parameters: ZTD – zenith total path delay ZHD/ZWD – zenith hydrostatic/wet path delay (ZTD = ZHD + ZWD) STD – slant total path delay SHD/SWD – slant hydrostatic/wet path delay (STD = SHD + SWD) GN– North-South horizontal tropospheric gradients GE– East-West horizontal tropospheric gradients

  13. Troposphere estimation strategies • Network mode Double-differenced observations  baseline(s)  network ‘Traditional approach’ Availability: re-processing/post-processing, near real-time ……………………………………………………. GAMIT/GLOBK Software, Bernese Software real-time ……………………………………………………… Trimble Atmosphere App • Precise Point Positioning Raw observations (undifferenced)  autonomous solution! Availability: • real-time • ……………………………………………………… • Alberding GNSS Status Software

  14. Zenith total delay - ZTD The basic tropospheric parameter in present GNSS software is the Zenith Total Delay (ZTD) that describes the signal delay in zenith direction above the receiver. It results from the mapping of the delays to each individual satellite into the zenith direction with appropriate mapping functions. The zenith delay is the combination of all these mapped delays into one parameter. It is therefore an average over all elevation angles and azimuths of the satellites in view and as such a spatial average over a certain part of the atmosphere.

  15. Zenith total delay - ZTD A priori atmospheric values for SULP Station (Lviv) Geodetic height(m) = 375.347 Met source UFL VMF1G JB Dry Zen UFL Wet Zen GP25 Dry Map VMF1 Wet Map VMF1 Yr Doy Hr Mn Sec PRN Azimuth Elevation Total Zen, m Total Slant, m 2015 297 0 0 0. 13 174.5314 47.2675 2.2879 3.1115 2015 297 0 0 0. 15 239.0167 58.9054 2.2879 2.6706 2015 297 0 0 0. 18 296.0942 15.3539 2.2879 8.5091 2015 297 0 0 0. 20 236.0749 5.1499 2.2879 22.7051 Total Slant = Slant total delay (STD)

  16. Comparison of zenith total delays from GNSS and radiosonde measurements

  17. Zenith total delays from GAMIT Software ……………………….. more than 150 stations Ukraine

  18. Comparison of zenith total delays from different GNSS processing algorithms

  19. Zenith total delay - ZTD The ZTD is traditionally either separated into a dry and wet part, called the Zenith Dry Delay (ZDD) and the Zenith Wet Delay (ZWD), or into a hydrostatic and non-hydrostatic (also termed: wet) part. The hydrostatic and dry part are much larger in amplitude but less varying in time. They are of the order of 2.30 m at sea level. The non-hydrostatic or wet part is more variable but smaller in amplitude, typically 0.0–0.40 m.

  20. Zenith Dry Delay (ZDD) and Zenith Wet Delay (ZWD) A priori atmospheric values for SULP Station (Lviv) Geodetic height(m) = 375.347 Met source UFL VMF1G JB Dry Zen UFL Wet Zen GP25 Dry Map VMF1 Wet Map VMF1 Yr Doy Hr Mn Sec PRN Azimuth Elevation Total Zen,m Dry Zen,m Wet Zen,m 2015 297 0 0 0. 13 174.5314 47.2675 2.2879 2.2306 0.0573 2015 297 0 0 0. 15 239.0167 58.9054 2.2879 2.2306 0.0573 2015 297 0 0 0. 18 296.0942 15.3539 2.2879 2.2306 0.0573 2015 297 0 0 0. 20 236.0749 5.1499 2.2879 2.2306 0.0573 The hydrostatic delay can be inferred from surface pressure without any correction for the water vapor included therein. The dry delay additionally needs measurements of ground water vapor pressure.

  21. Effect of the Neutral Atmosphere on GPS Measurements Depending on the research groups, the one or the other formulation is used. Note that GNSS software packages model the dry or hydrostatic delay with the corresponding mapping function as a priori given delays, whereas the wet or non-hydrostatic part is estimated.

  22. Integrated Water Vapor (IWV) and Precipitable Water Vapor (PWV) Integrated Water Vapor (IWV) [kg/m2] and Precipitable Water Vapor (PWV) [mm] are two equivalent terms and denote a parameter describing the column integrated water vapor in the atmosphere. They are not considered a GPS observable as such, but can be derived from ZTD, ground pressure and mean atmospheric temperature. Mean atmospheric temperature can be approximately inferred from surface temperature or determined from NWP models. Compared to water vapor radiometer measurements as reference method, show that GPS can recover PWV with an Root Mean Square (RMS) uncertainty of 1.0–1.5 mm.

  23. Comparison of Integrated Water Vaporfrom different GNSS processing algorithms

  24. GNSS-meteorology in Europe

  25. Conclusions The ZTD from GNSS processing is a broadly accepted descriptor of the integrated atmospheric state. Its assimilation into NWP models as ZTD has become a very common application of GNSS meteorology. As such, it is treated like any other measurement of the atmosphere. It is bias-corrected and gets some uncertainty assigned in the form of a standard deviation. The quantification of the standard deviation of GNSS ZTDs requires accurate reference measurements. The radiosonde is usually considered to be the reference of choice.

  26. Conclusions The systematic part of the GNSS ZTD uncertainty amounts to a few millimeters of station-specific mean offset and 1–2 mm annual fluctuation. The mean offset and the annual systematic fluctuation are likely to contain radiosonde contributions of millimeter magnitude. The random measurement uncertainties of GNSS ZTDs are determined to be 2.5 mm–3.5 mm in winter and 3.5–5.0 mm in summer.

  27. Suggestions Establishmentof a realtimemonitoringandwarningsystemintheregionHungary, Slovakia, Romania and Ukrainebymeansofexploitationofsatellitetechnologies tomaintain, extend, upgradeSpace emergency system upgrading for Multi-GNSS (Galileo) jointing E-GVAP utilizingSpace emergency systemdatainmeteorology

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