We deduce a Novel Interferometric Tropospheric Error (NITE) formula for ground-based GNSS interferometric reflectometry (GNSS-IR). This formula contains two parts: a geometric displacement error that accounts for the reflection point change due to the atmosphere and the earth curvature, and a path delay derived following the definition of the mapping function (with the small curve path effect included). We validate the NITE formula together with two previously used approaches, the bending angle correction and the mapping function path delay (MPF delay) using raytracing and radiosonde data. The raytracing results show that the NITE formula is more accurate than the previous approaches. Numerically, the geometric displacement error is4 h) sea-level retrievals. Finally, we show that at low elevation angles, the bending angle correction can be reformulated as an MPF delay.

For the first time, rain effects on the polarimetric observations of the global navigation satellite system reflectometry (GNSS-R) are investigated. The physical feasibility of tracking the modifications in the surface roughness by rain splash and the surface salinity by the accumulation of freshwater is theoretically discussed. An empirical analysis is carried out using measurements of a coastal GNSS-R station with two side-looking antennas in right- and left-handed circular polarizations (RHCP and LHCP). Discernible drops in RHCP and LHCP powers are observed during rain over a calm sea. The power drop becomes larger at higher elevation angles. The average LHCP power drops by$\approx ~5$dB at an elevation angle of 45°. The amplitude of the correlation sum shows a dampening, responding to rain rate systematically. The LHCP observations show higher sensitivity to rainfall compared to RHCP observations. The retrieved standard deviation of surface heights shows a steady increase with the rain rate. The derived surface salinity shows a decrease at rains higher than 10 mm/h. This study confirms the potential under environmental conditions of the GNSS-R ground-based station, e.g., with salinity mostly lower than 30 psu, over a calm sea, being a starting point for future investigations.

Coastal sea level variation as an indicator of climate change is extremely important due to its large socioeconomic and environmental impacts. The ground-based global navigation satellite system (GNSS)-reflectometry (GNSS-R) is becoming a reliable alternative for sea surface altimetry. We investigate the impact of antenna polarization and orientation on GNSS-R altimetric performance at different carrier frequencies. A one-year dataset of ground-based observations at the Onsala Space Observatory using a dedicated reflectometry receiver is used. Interferometric patterns produced by the superposition of direct and reflected signals are analyzed using the least-squares harmonic estimation (LS-HE) method to retrieve sea surface height. The results suggest that the observations from global positioning system (GPS) L1 and L2 frequencies provide similar levels of accuracy. However, the overall performance of the height products from the GPS L1 shows slightly better performance due to more observations. The combination of L1 and L2 observations (L12) improves the accuracy up to 25% and 40% compared to the L1 and L2 heights. The impacts of antenna orientation and polarization are also evaluated. A sea-looking left-handed circular polarization (LHCP) antenna shows the best performance compared to both zenith- and sea-looking right-handed circular polarization (RHCP) antennas. The results are presented using different averaging windows ranging from 15 min to 6 h. Based on a 6-h window, the yearly root mean squared errors (RMSEs) between GNSS-R L12 sea surface heights with collocated tide gauge observations are 2.4, 3.1, and 4.1 cm with the correlation of 0.990, 0.982, and 0.969 for LHCP sea-looking, RHCP sea-looking, and RHCP up-looking antennas, respectively.

Monitoring coastal sea level has gained a large socioeconomic and environmental significance. Ground-based Global Navigation Satellite System Reflectometry (GNSS-R) offers various geophysical parameters including sea surface height. We investigate a one-year dataset from January to December 2016 to evaluate the performance of GNSS-R coastal sea levels during different sea states. Our experiment setup uses three types of antenna in terms of polarization and orientation. A zenith-looking antenna tracks Right-Handed Circular Polarization (RHCP) direct signals and two sea-looking antennas capture both Left-Handed Circular Polarization (LHCP) and RHCP reflections. The Singular Spectrum Analysis (SSA) is used for extracting interferometric frequency from the data and calculating the heights. The results indicate that the height estimates from the sea-looking antennas have better accuracy compared to the zenith-looking orientation. The LHCP antenna delivers the best performance. The yearly Root Mean Square Errors (RMSE) of 5-min GNSS-R L1 water levels compared to the nearest tide gauge are 2.8 and 3.9 cm for the sea-looking antennas and 4.7 cm for the zenith-looking antenna with correlations of 97.63, 95.02, 95.35 percent, respectively. Our analysis shows that the roughness can introduce a bias to the measurements.

Reflectometry of Global Navigation Satellite Systems (GNSS) signals from the ocean surface has provided a new source of observations to study the ocean-atmosphere interaction. We investigate the sensitivity and performance of GNSS-Reflectometry (GNSS-R) data to retrieve sea surface roughness (SSR) as an indicator of sea state. A data set of one-year observations in 2016 is acquired from a coastal GNSS-R experiment in Onsala, Sweden. The experiment exploits two sea-looking antennas with right- and left-hand circular polarizations (RHCP and LHCP). The interference of the direct and reflected signals captured by the antennas is used by a GNSS-R receiver to generate complex interferometric fringes. We process the interferometric observations to estimate the contributions of direct signals and reflections to the total power. The power estimates are inverted to the SSR using the state-of-the-art model. The roughness measurements from the RHCP and LHCP links are evaluated against match-up wind measurements obtained from the nearest meteorological station. The results report on successful roughness retrieval with overall correlations of 0.76 for both links. However, the roughness effect in LHCP observations is more pronounced. The influence of surrounding complex coastlines and the wind direction dependence are discussed. The analysis reveals that the winds blowing from land have minimal impact on the roughness due to limited fetch. A clear improvement of roughness estimates with an overall correlation of 0.82 is observed for combined polarimetric observations from the RHCP and LHCP links. The combined observations can also improve the sensitivity of GNSS-R measurements to the change of sea state.

Modern mobile phones and tablet computers can have the capacity to store raw Global Navigation Satellite System (GNSS) data for further processing. With a short proof-of-concept campaign, we show that such data, recorded with a tablet computer, can be used to measure the sea level using GNSS reflectometry (GNSS-R). The results suggest that the tablet computer performs on a similar level as more high-end, geodetic-quality equipment.

GNSS-R has emerged as an attractive way of using a signal of opportunity that is collected by GNSS stations all around the world to measure a wide variety of properties of the surroundings of the stations. Current state-of-the-art algorithms based on the inversion of SNR values rely on off-line processing, causing a significant delay before results are available. We present a new approach for ground-based GNSS-R that uses Kalman filtering with a realistic physical model that allows close to real-time inversion of SNR oscillations into sea-surface height with high precision. From the analysis of test measurements from the GTGU GNSS installation at the Onsala Space Observatory, Sweden, we conclude that the new method provides better estimates than single-arc retrievals from spectral analysis and that the final precision is close to that of post-processing inversion algorithms.

Inverse modeling of ground-based GNSS reflections has the potential to improve existing GNSS-R applications and lead to novel concepts for retrieving geophysical parameters around existing or deliberately built GNSS sites. As we will show in this paper, consistent, accurate and precise determination of sea-surface heights can be realized. Moreover, we demonstrate that it is possible to detect sea-ice freeze states at coastal GNSS sites. In addition, it will be shown how the inverse modeling approach can be used for self-calibration of troposphere delays, which would otherwise bias the target parameters and need to be corrected for by external measurements or data-sets.

Determination of sea ice extent is important both for climate modeling and transportation planning. Detection and monitoring of ice are often done by synthetic aperture radar imagery, but mostly without any ground truth. For the latter purpose, robust and continuously operating sensors are required. We demonstrate that signals recorded by ground-based Global Navigation Satellite System (GNSS) receivers can detect coastal ice coverage on nearby water surfaces. Beside a description of the retrieval approach, we discuss why GNSS reflectometry is sensitive to the presence of sea ice. It is shown that during winter seasons with freezing periods, the GNSS-R analysis of data recorded with a coastal GNSS installation clearly shows the occurrence of ice in the bay where this installation is located. Thus, coastal GNSS installations could be promising sources of ground truth for sea ice extent measurements.

The characterization of global mean sea level is important to predict floods and to quantify water resources for human use and irrigation, especially in coastal regions. Recently, the application of global navigation satellite system reflectometry (GNSS-R) for water level monitoring has been successfully demonstrated. This paper focuses on the retrieval of sea surface height within a field experiment that was conducted at the Onsala Space Observatory (OSO) using the phase-based altimetry method. A continuous phase tracking algorithm, which relies on the GNSS amplitude and phase observations is proposed and works even under rough sea conditions at OSO's coast. Factors impacting the phase-based altimetry model, i.e., atmospheric propagation effects of the GNSS signals and influence of the GNSS-R observation instrument, are discussed. The relationship between the yield of coherent GNSS-R compared to the overall recorded events and the wind speed is investigated in detail. Ground-based sea-level measurements from June 10 to July 3, 2015 demonstrate that altimetric information about the reflecting water surface can be obtained with a root mean square error of 4.37 cm with respect to a reference tide gauge (TG) data set. The sea surface changes, derived from our field experiment and the reference TG, are highly correlated with a correlation coefficient of 0.93. The altimetric information can be retrieved even when the sea surface is very rough, corresponding to wind speeds up to 13 m/s. Moreover, the use of inexpensive conventional GNSS antennas shows that the system is useful for future large-scale sea level monitoring applications including numerous low-cost coastal ground stations.

Usually ground-based GNSS-R installations are either existing geodetic GNSS stations or they are built with dedicated components that enable the deduction and monitoring of physical and geometrical properties of the reflecting area around that particular site. In both cases, hardware components usually enable real-time operation of such instruments. However, as software-defined radio (SDR) technology has advanced in the recent years it is now possible to carry out signal processing in real-time, which makes it an ideal candidate for the realization of a flexible GNSS-R system. In this paper it is shown how SDR helps to realize GNSS-R solutions for sea-level monitoring at the Onsala Space Observatory, Sweden. Moreover, such SDR solutions can be mounted on an unmanned aerial vehicle (UAV) in order to collect data from higher altitudes and even provide Delay-Doppler information for extended GNSS-R studies.

We present a new method to retrieve sea level from GNSS SNR data that relies upon inverse modelling of the detrended SNR. This method can simultaneously use data from both GPS and GLONASS, and both L1 and L2 frequencies, to improve the solution with respect to prior studies. Results from the GNSS-R installation at Onsala Space Observatory are presented and the retrieved sea level heights are compared with a co-located pressure mareograph. The method is found to give an RMS error of 1.8 cm. The results are also compared against previous implementations of GNSS tide gauges and found to have lower RMS than both the earlier SNR algorithm and also the dual receiver, phase delay method.

We present long term trends in the amount of atmospheric water vapor at the Swedish West Coast. These trends are derived from geodetic Very Long Baseline Interferometry (VLBI), ground based microwave radiometry, and radiosonde observations. The time span of observations covers 25 years and the data were collected at the Onsala Space Observatory (VLBI and microwave radiometry) and the Gothenburg-Landvetter Airport (radiosondes). The three techniques detect positive trends in the integrated precipitable water vapor (IPWV) on the order of 0.4 to 0.6 kg/m2per decade. The IPWV data derived from the three techniques have correlation coefficients on the order of 0.95 and better. However, there is no perfect agreement between the IPWV trends derived by the three techniques. This might partly be explained by different temporal sampling and data gaps.

We present first results from the analysis of high-rate observations with a GNSS-based tide gauge at the Onsala Space Observatory. The goal is to determine local sea level with high temporal resolution. The GNSS-based tide gauge makes use of right-hand circular polarized GNSS signals that are directly received and left-hand circular polarized GNSS signals that are reflected from the sea surface. An experimental setup of the GNSS-based tide gauge was operated in the spring of 2010 and data were recorded with a sampling rate of 20 Hz. We analyzed data decimated to 1 Hz using different temporal resolution between 5 and 240 seconds, and the resulting time series of local sea level were compared to each other and to results from two stilling well gauges. The comparison with the data from the stilling well gauges shows a common trend. The comparison of the results from analyses with different temporal resolution show consistent results. There is also an indication that the GNSS-based tide gauge might be able to give information on the sea surface state.