GNSS troposphere

Horizontal and vertical deformation of the Earth’s crust is due to a variety of different geophysical processes that take place on various spatiotemporal scales. The quality of the observations from spaced-based geodesy instruments such as Global Positioning System
(GPS) and differential interferometric synthetic aperture radar (DInSAR) data for monitoring these deformations are dependent on numerous error sources. Therefore, accurately identifying and eliminating the dominant sources of the error, such as troposphere error in
GPS signals, is fundamental to obtain high quality, sub-centimeter accuracy levels in positioning results.
In this work, I present the results of double-differenced processing of five years of GPS data, between 2008 and 2012, for sparsely distributed GPS stations in southeastern Ontario and western Québec. I employ Bernese GPS Software Version 5.0 (BSW5.0) and found two
optimal sub-networks which can provide high accuracy estimation of the position changes. I
demonstrate good agreement between the resulted coordinate time series and the estimates of the crustal motions obtained from a global solution. In addition, I analyzed the GPS position time series by using a complex noise model, a combination of white and power-law noises.
The estimated spectral index of the noise model demonstrates that the flicker noise is the dominant noise in most GPS stations in our study area. The interpretation of the observed velocities suggests that they provide an accurate constraint on glacial isostatic adjustment
(GIA) prediction models.
Based on a deeper analysis of these same GPS stations, I propose a model that accurately estimates the seasonal amplitude of zenith tropospheric delay (ZTD) error in the GPS data on local and regional spatial scales. I process the data for the period 2008 through 2012 from eight GPS stations in eastern Ontario and western Québec using precise point positioning (PPP) online analysis available from Natural Resource Canada (NRCan) (https://webapp.geod.nrcan.gc.ca/geod/tools-outils/ppp.php). The model is an elevation-dependent model and is a function of the decay parameter of refractivity with altitude and the seasonal amplitude of refractivity computed from atmospheric data (pressure, temperature,
and water vapor pressure) at a given reference station. I demonstrate that it can accurately estimate the seasonal amplitude of ZTD signals for the GPS stations at any altitude relative to that reference station. Based on the comparison of the observed seasonal amplitudes of the
differenced ZTD at each station and the estimates from the proposed model, it can provide an accurate estimation for the stations under normal atmospheric conditions. The differenced ZTD is defined as the differences of ZTD derived from PPP at each station and ZTD at the
reference station. Moreover, I successfully compute a five-year precipitable water vapor (PWV) at each GPS site, based on the ZTD derived from meteorological data and GPS processing. The results provide an accurate platform to monitor long-term climate changes
and inform future weather predictions.
In an extension of this research, I analyze DInSAR data between 2014 and 2017 with high temporal and spatial resolution, from Kilauea volcano in Hawaii in order to derive the spatial and temporal pattern of the seasonal amplitude of ZTD. I propose an elevation-dependent
model by the data from a radiosonde station and observations at a surface weather station for modeling the seasonal amplitudes of ZTD at any arbitrary elevation. The results obtained from this model fit the vertical profile of the observed seasonal amplitude of ZTD in DInSAR data, increasing systematically from the elevation of the DInSAR reference point. I demonstrate that the proposed model could be used to estimate the seasonal amplitude of the differenced ZTD at each GPS station within a local network with high accuracy. The results of this study concluded that, employing this model in GPS processing applications eliminates the need for the meteorological observations at each GPS site.

Nowadays, the most central themes of Geodesy are linked to the provision of a
unique Global Reference System, to which can be tied of unique form and with
accurately the geometrical and physical global changes. In this sense, the bases of
the future Global Geodetic Reference Frame (GGRF) have been established by the
United Nations on February 26, 2015 with the Resolution (A/RES/69/266). The
GGRF aims at better structuring Earth Observation Systems currently with prospects
of the global changes determination at the level of one part per billion, considering
several geometric and physical parameters. In the Global Geodetic Observing
System (GGOS) of the International Association of Geodesy (IAG) the referred
accuracy presuppose is estimated that to be achieved by 2020. In July 2015 IAG
established the International Height Reference System (IHRS). In this context, it is
intended that the International Height Reference Frame (IHRF), realization of the
IHRS, has an overall consistency of at least one centimeter in its realization and
space/temporal control in the order of millimeter per year. The GRRF is, now,
understood as the association of the traditional International Terrestrial Reference
Frame with the IHRF. National Vertical Data worldwide must be linked to the IHRF.
Considering these aspects, it was analyzed the temporal evolution of the Imbituba
Brazilian Vertical Datum utilizing tide gauge data from the Sea Level of the
databases: Permanent Service for Mean Sea Level (1948 to 1968), University of
Hawaii Sea Level Center (2001 to 2007) and Permanent Tide Gauge Network for
Geodesy (2006 to 2016), as well as data from different altimetry missions from 1991
to 2015 obtained from the database of the Deutsches Geodätisches
Forschungsinstitut - Open Altimeter Database. Additionally, the temporal series
obtained from GNSS continuous positioning from the period 2007 to 2016 were used,
which were used to modeling the local movements of the crust. The velocity models
for South America indicated by SIRGAS were used, as well as geological and
geophysical models. These were used for validation of GNSS processing and for
comparison of the up component of Imbituba. The results allowed discriminating the
crust movements in relation to the sea level. To achieve it, the trend of sea level
variation evidenced by the tide gauge was used, as well as the variation of the
vertical component obtained with the GNSS processing and the Sea Surface Height
(SSH) obtained from the altimeter satellite data. After that the analyzing of the trend
for the estimation of the geocentric positioning of the Imbituba Brazilian Vertical
Datum, the following results were obtained: 5.26 mm/year the trend of the tide gauge;
-3.02 mm/year the subsidence of the up component; and 2.23 mm/year the trend of
the SSH. There is a trend of MSL elevation in the region of Imbituba Brazilian Vertical
Datum by the determination the resulting temporal variation approximately + 2.24
mm/year ± 0.4 mm / year.

Global Navigation Satellite Systems (GNSS) have revolutionised positioning, navigation, and timing, becoming a common part of our everyday life. Aside from these well-known civilian and commercial applications, GNSS is now an established atmospheric observing system, which can accurately sense water vapour, the most abundant greenhouse gas, accounting for 60–70 % of atmospheric warming. In Europe, the application of GNSS in meteorology started roughly two decades ago and today it is a well-established research field. This review covers the state-of-the-art in GNSS meteorology in Europe. Discussed are the advances in GNSS processing for derivation of tropospheric products, application of GNSS tropospheric products in operational weather prediction and application of GNSS tropospheric products for climate monitoring. Reviewed are the GNSS processing techniques and tropospheric products. Given is a summary of the use of the products for validation and impact studies with o...

Horizontal and vertical deformation of the Earth's crust is due to a variety of different geophysical processes that take place on various spatiotemporal scales. The quality of the observations from spaced-based geodesy instruments such as Global Positioning System (GPS) and differential interferometric synthetic aperture radar (DInSAR) data for monitoring these deformations are dependent on numerous error sources. Therefore, accurately identifying and eliminating the dominant sources of the error, such as troposphere error in GPS signals, is fundamental to obtain high quality, sub-centimeter accuracy levels in positioning results. In this work, I present the results of double-differenced processing of five years of GPS data, between 2008 and 2012, for sparsely distributed GPS stations in southeastern Ontario and western Québec. I employ Bernese GPS Software Version 5.0 (BSW5.0) and found two optimal sub-networks which can provide high accuracy estimation of the position changes. I demonstrate good agreement between the resulted coordinate time series and the estimates of the crustal motions obtained from a global solution. In addition, I analyzed the GPS position time series by using a complex noise model, a combination of white and power-law noises.

The time transfer technique based on Precise Point Positioning (PPP) has proved to be a very effective technique allowing the comparison of atomic clocks with a precision of a hundred picoseconds, and with latency of 2 days. Using satellite orbit and clock information from the IGS real-time products, it is now possible to compute very precise time transfer solutions based on PPP in near real-time, i.e., with a latency down to some minutes. We present PPP-based time transfer results obtained in near real time with the new version of the GNSS data processing software Atomium, and the satellite products mentioned above. We additionally analyze the results that can be obtained with low latency using the NRCan Ultra-Rapid products (EMU) available with a delay of 90–150 min. From the statistics of the results, it is concluded that the real-time IGS products allow detection of a clock jump larger than 1.5 ns after some minutes; the detection threshold falls down to 0.8 ns when using the EMU products about 2 h later. It is also shown that in near real time, a frequency change larger than 2e-14 can be detected when looking at the last 24 h data or larger than 2e-13 when looking at the last 2 h. As demonstrated, the quality of the monitoring depends on the distance between the two stations, so that distances shorter than about 3,000 km should be preferably used for a near real-time comparison of atomic clocks based on PPP.

Global Navigation Satellite Systems (GNSS) have revolutionised positioning, navigation, and timing, becoming a common part of our everyday life. Aside from these well-known civilian and commercial applications, GNSS is now an established atmospheric observing system, which can accurately sense water vapour, the most abundant greenhouse gas, accounting for 60–70 % of atmospheric warming. In Europe, the application of GNSS in meteorology started roughly two decades ago and today it is a well-established research field. This review covers the state-of-the-art in GNSS meteorology in Europe. Discussed are the advances in GNSS processing for derivation of tropospheric products, application of GNSS tropospheric products in operational weather prediction and application of GNSS tropospheric products for climate monitoring. Reviewed are the GNSS processing techniques and tropospheric products. Given is a summary of the use of the products for validation and impact studies with o...

The GPS system can play an important role in activities related to the monitoring of climate. Long time series, coherent strategy, and very high quality of tropospheric parameter Zenith Tropospheric Delay (ZTD) estimated on the basis of GPS data analysis allows to investigate its usefulness for climate research as a direct GPS product. This paper presents results of analysis of 16-year time series derived from EUREF Permanent Network (EPN) reprocessing performed by the Military University of Technology. For 58 stations Lomb-Scargle periodograms were performed in order to obtain information about the oscillations in ZTD time series. Seasonal components and linear trend were estimated using Least Square Estimation (LSE) and Mann-Kendall trend test was used to confirm the presence of a linear trend designated by LSE method. In order to verify the impact of the length of time series on trend value, comparison between 16 and 18 years were performed